Mirrors

Watching Avatar, I was continually reminded of Zizek's observation in First As Tragedy, Then As Farce, that the one good thing that capitalism did was destroy Mother Earth. […] What is foreclosed in the opposition between a predatory technologised capitalism and a primitive organicism, evidently, is the possibility of a modern, technologised anti-capitalism. It is in presenting this pseudo-opposition that Avatar functions as an ideological symptom. […] Sully, the marine who is "really" a tree-hugging primitive, is a paradigm of that late capitalist subjectivity which disavows its modernity. There's something wonderfully ironic about the fact that Sully's - and our - identification with the Na'vi depends upon the very advanced technology that the Na'vi's way of life makes impossible. […] If we are to escape from the impasses of capitalist realism, if we are to come up with an authentic and genuinely sustainable model of green politics (where the sustainability is a matter of libido, not only of natural resources), we have to overcome these disavowals. There is no way back from the matricide which was the precondition for the emergence of modern subjectivity. To quote one of my favourite passages in First As Tragedy: "Fidelity to the communist Idea means that, to repeat, Arthur Rimbaud, … we should remain absolutely modern and reject the all too glib generalization whereby the critique of capitalism morphs into the critique of 'modern instrumental reason' or 'modern technological civilization'." The issue is, rather, how modern technological civilization can be organised in a different way.

One of the major points of contention concerning unconditional accelerationism […] can be summed up with the single phrase “U/ACC lacks praxis”. In the common leftist deployment of the phrase, this is exactly correct. […] U/ACC is hardly anti-praxis; it simply asks that the limits and the inevitable dissolution of things be acknowledged […] perhaps it is best to view U/ACC not as anti-praxis, but as anti-collective means of intervention.

[…] U/ACC calls attention to the manner through which collective forms of intervention and political stabilization, be they of the left or the the right, are rendered impossible in the long-run through overarching tendencies and forces. […] U/ACC charts a course outwards: the structures of Oedipus, the Cathedral, Leviathan, what have you, will be ripped apart and decimated by forces rushing up from within and around the system […]

Consider the classic Marxian formula: M – C – M’. This is, of course, a simple pathway of capital, beginning with money (M), which is translated into the commodity (C) to be sold on the market. If successful sold, the commodity is translated into a greater amount of money than at the beginning (M’) – and it is at this point that the process restarts. M – C – M’ – C…. on and on and on. […] This, in turn, clues us into the abstract force, glimpsed through diagrammation, which can lurks behind modernity rendered as historical totality: positive feedback. […] The processual relations of capital appear here as far from any sort of homeostasis.

Positive feedback not only marks the evolution of a given system, or a generalized forward direction. It is also indicative of […] past forms being undermined and propelled towards catastrophe. While for many the catastrophe might appear as something like communism, Marx as early as the Communist Manifesto was enraptured by the image of capitalist modernity as unfolding through creative destruction.

[…]

The positive-feedback processes […] radiates out across the entirety of social, cultural, political, even ecology strata […] All these [market, commercial, technological, etc.] forces lock into momentum with one another and act as force multipliers, each looping through the other, pushing it forward, faster, moving the entirety of the system towards… something – and it is this something that control systems, of either the left or the right, would be forced (and will always fail) to contend with.

[…]

Through the passage of time, the prevailing organizational dynamics have shifted […] With each passing iteration, the status of the hierarchical formation itself declines as the relations tend towards the network, or even post-network, formations. This is precisely because, Bar-Yam notes, of a rise in the ‘complexity profile’ being shaped within civilization. As the nonlinear processes driven by cascading positive feedback intensify and rise, organization itself becomes more complex, more heterogeneous, more multiplicitious, and less congenial to control systems. Rising complexity, in the end, trashes the orderly nature of organic wholeness.

The L/ACC critic might stop here and decry the construction of a strawman. “Of course we aren’t for firm hierarchy,” they are probably saying. “We’re interested in flexible forms, in hybridity and multiplicity.” […] “we support decentralized planning”. Allow me to respond to these oppositions quickly: flexible control, modular hierarchy, and decentralized planning all fall victim to the same forward rush of rising complexity as their more formalized and concrete kin.

Control systems always rely on a high degree of legibility […] in order to properly enable generalized management and specific intervention […] – yet this becomes its very Achilles’ heel. Consider Andrew Pickering’s description of the conclusions gleamed by the cybernetician Ross Ashby’s research into homeostats: “The only route to stabilisation is to cut down variety – to reduce the number of configurations an assemblage can take on, by reducing the number of participants and the multiplicity of their interconnections.” […] Pickering at length:

"Ashby was interested in the length of time it would take combinations of homeostats to achieve collective equilibrium. […] Both calculations and his machines showed that four fully interconnected homeostats, each capable of taking on twenty-five different inner states, could come into equilibrium in a couple of seconds. But if one extrapolated that an assemblage of one hundred fully interconnected homeostats the combinatories were such that chance on an equilibrium arrangement would entail search-times orders of magnitudes greater than the age of the universe. […]

[…] Finding stability can easily become a practical impossibility."

To properly operate in the real […] L/ACC or R/ACC praxis would be contingent upon the expunging of variables upon variables to push the complexity profile downwards, to make it more manageable (which is something that R/ACC tends to admit more than L/ACC). But to do this would not only mean restricting flows of people, goods, and money […] It would also require roadblocks thrown up in the path of technological development, and the suppressing of the capability of making and using tools to operate in the world. The promotion of a collective cognitive project would, ironically, be forced to suppress cognitive activity on the molecular scale.

In the end this scenario does not seem very likely. Multitudes of positive feedback processes have long since become deeply entrenched, and the system as a whole is undeniably veering far from order. […] The complexity profile is rising and will continue, and as it does the capability for collective intervention will become all but impossible. […]

Contra any gamble for collectively scalable politics of bootstrapping and navigation, Bar-Yam suggests that in the face of mounting complexity, organizational design is forced to tend towards “progressively smaller branching ratios (fewer individuals supervised by a single individual)”. As mutational development speeds up and legibility fades, size becomes a liability. James Scott has shown that detachment of large managerial forces from the chaotic ‘on-the-ground’ environs is a recipe for disaster. Similarly, Kevin Carson has illustrated the way that the Hayekian knowledge problem […] not only applies to state-centric command economies, but to the organizational black box of the modern corporation. As such problems intensify, any possibility for navigation falls downward, to smaller and more dynamic firms, greater marketization (technocommercialism begetting technocommercialism), and ultimately individual actors themselves.

It is at this point where one might happen on something that looks like U/ACC praxis. If one’s goal is the dissolution of the state and/or rule by multinational monopoly capitalism, then why recourse to the very systems and mechanisms that seek to stabilize these forms and shore them up against the forces that undermine them? This question is at the core of Deleuze and Guattari’s insight in the ‘accelerationist fragment’ that to “withdraw from the world market”, as opposed to going deeper into the throes of it, is a “curious revival of the fascist ‘economic solution’”. […]

To accelerate the process, and to throw oneself into those flows, leaves behind the (already impossible) specter of collective intervention. This grander anti-praxis opens, in turn, the space for examining forms of praxis that break from the baggage of the past. We could count agorism and exit as forms impeccable to furthering the process, and cypherpoliticsxi and related configurations arise on the far end of the development, as the arc bends towards molecularization of economic and social relations. […]

No more reterritorializing reactions. No more retroprogressivism.

This is a… deeply flawed essay, obviously, given who wrote it. The core point I disagree with is, of course, the indentification of capitalism purely with its creatively destructive, competitive, market elements, a mistake which Mark Fisher accurately identifies in "Postcapitalist Desire" as being at the very core of where Land goes off the deep end. Nevertheless, Land's screed accurately points to a fundamental problem wit the attitude of the modern left.

This post at K-Punk epitomizes a gathering trend among neomarxists to finally bury all aspiration to positive economism (‘freeing the forces of production from capitalist relations of production’) and install a limitless cosmic despair in its place. Who still remembers Khruschev’s threat to the semi-capitalist West – “we’ll bury you.” Or Mao’s promise that the Great Leap Forward would ensure the Chinese economy leapt past that of the UK within 15 years? The Frankfurtian spirit now rules: Admit that capitalism will outperform its competitors under almost any imaginable circumstances, while turning that very admission into a new kind of curse (“we never wanted growth anyway, it just spells alienation, besides, haven’t you heard that the polar bears are drowning …?”).

[…]

The grand master of this move is Arthur Schopenhauer, who lent it explicit philosophical rigour as a mode of transcendental apprehension. Since time is the source of our distress –- PKD’s “Black Iron Prison” – how can any kind of evolution be expected to save us? Thus Transcendental Miserablism constitutes itself as an impregnable mode of negation […] all that survives of Marx is a psychological bundle of resentments and disgruntlements

[…]

For the Transcendental Miserablist, ‘Capitalism’ is the suffering of desire turned to ruin, the name for everything that might be wanted in time, an intolerable tantalization whose ultimate nature is unmasked by the Gnostic visionary as loss, decrepitude and death, and in truth, it is not unreasonable that capitalism should become the object of this resentful denigration. Without attachment to anything beyond its own abysmal exuberance, capitalism identifies itself with desire to a degree that cannot imaginably be exceeded, shamelessly soliciting any impulse that might contribute an increment of economizable drive to its continuously multiplying productive initiatives. Whatever you want, capitalism is the most reliable way to get it, and by absorbing every source of social dynamism, capitalism makes growth, change and even time itself into integral components of its endlessly gathering tide.

“Go for growth” now means “Go (hard) for capitalism.” It is increasingly hard to remember that this equation would once have seemed controversial. On the left it would once have been dismissed as risible. This is the new world Transcendental Miserablism haunts as a dyspeptic ghost.

[…]

Hence the Transcendental Miserablist syllogism: Time is on the side of capitalism, capitalism is everything that makes me sad, so time must be evil.

The polar bears are drowning, and there’s nothing at all we can do about it.

What Transcendental Miserablism has no right to is the pretence of a positive thesis. The Marxist dream of dynamism without competition was merely a dream, an old monotheistic dream re-stated, the wolf lying down with the lamb. If such a dream counts as ‘imagination’, then imagination is no more than a defect of the species: the packaging of tawdry contradictions as utopian fantasies, to be turned against reality in the service of sterile negativity. ‘Post-capitalism’ has no real meaning except an end to the engine of change. […] And if that makes Transcendental Miserablists unhappy, the simple truth of the matter is: Anything would.

I legitimately have never felt as stimulated by a philosophy before as I have by accelerationism. Not the stupid charicature of it which — somehow — is also occasionally adopted by many who call themselves such; nor the right wing occult worship of a dark future that the later Nick Land represented; but a program which is better, faster, stronger, and more dangerous than what most leftists can hope to offer; far more adapted for the times we — still, even though these ideas were originally hatching slimy and new from their egg twenty or thirty years ago — find ourselves in.

"Why political intellectuals, do you incline towards the proletariat? In commiseration for what? […] you dare not say that the only important thing there is to say, that one can enjoy swallowing the shit of capital, its materials, its metal bars, its polystyrene, its books, its sausage pâtés, swallowing tonnes of it till you burst – and because instead of saying this, which is also what happens in the desires of those who work with their hands, arses and heads, ah, you become a leader of men, what a leader of pimps, you lean forward and divulge: ah, but that’s alienation, it isn’t pretty, hang on, we’ll save you from it, we will work to liberate you from this wicked affection for servitude, we will give you dignity. And in this way you situate yourselves on the most despicable side, the moralistic side where you desire that our capitalized’s desire be totally ignored, brought to a standstill, you are like priests with sinners, our servile intensities frighten you, you have to tell yourselves: how they must suffer to endure that! And of course we suffer, we the capitalized, but this does not mean that we do not enjoy, nor that what you think you can offer us as a remedy – for what? – does not disgust us, even more. We abhor therapeutics and its vaseline, we prefer to burst under the quantitative excesses that you judge the most stupid. And don’t wait for our spontaneity to rise up in revolt either." (LE 116)

[…]

From Anti-Oedipus:

"But which is the revolutionary path? Is there one? – To withdraw from the world market, as Samir Amin advises Third World Countries to do, in a curious revival of the fascist 'economic solution'? Or might it be to go in the opposite direction? To go further still, that is, in the movement of the market, of decoding and deterritorialization? For perhaps the flows are not yet deterritorialized enough, not decoded enough, from the viewpoint of a theory and practice of a highly schizophrenic character. Not to withdraw from the process, but to go further, to 'accelerate the process,' as Nietzsche put it: in this matter, the truth is that we haven't seen anything yet. (239-40)"

And from Libidinal Economy – the one passage from the text that is remembered, if only in notoriety:

"The English unemployed did not have to become workers to survive, they – hang on tight and spit on me – enjoyed the hysterical, masochistic, whatever exhaustion it was of hanging on in the mines, in the foundries, in the factories, in hell, they enjoyed it, enjoyed the mad destruction of their organic body which was indeed imposed upon them, they enjoyed the decomposition of their personal identity, the identity that the peasant tradition had constructed for them, enjoyed the dissolutions of their families and villages, and enjoyed the new monstrous anonymity of the suburbs and the pubs in morning and evening." (LE 111)

Spit on Lyotard they certainly did. But in what does the alleged scandalous nature of this passage reside? Hands up who wants to give up their anonymous suburbs and pubs and return to the organic mud of the peasantry. […] Hands up, furthermore, those who really believe that these desires for a restored organic wholeness are extrinsic to late capitalist culture, rather than in fully incorporated components of the capitalist libidinal infrastructure. Hollywood itself tells us that we may appear to be always-on techno-addicts, hooked on cyberspace, but inside, in our true selves, we are primitives organically linked to the mother/planet, and victimised by the military-industrial complex. James Cameron’s Avatar is significant because it highlights the disavowal that is constitutive of late capitalist subjectivity, even as it shows how this disavowal is undercut. We can only play at being inner primitives by virtue of the very cinematic proto-VR technology whose very existence presupposes the destruction of the organic idyll of Pandora.

And if there is no desire to go back except as a cheap Hollywood holiday in other People’s misery – if, as Lyotard argues, there are no primitive societies, (yes, the Terminator was there from the start, distributing microchips to accelerate its advent); isn’t, then, the only direction forward? Through the shit of capital, metal bars, its polystyrene, its books, its sausage pâtés, its cyberspace matrix?

I want to make three claims here –

1. Everyone is an accelerationist
2. Accelerationism has never happened.
3. Marxism is nothing if it is not accelerationist

[…]

Land is the kind of antagonist that the left needs. If Land’s cyber-futurism can seem out of date, it is only in the same sense that jungle and techno are out of date – not because they have been superseded by new futurisms, but because the future as such has succumbed to retrospection. The actual near future wasn’t about Capital stripping off its latex mask and revealing the machinic death’s head beneath; it was just the opposite: New Sincerity, Apple Computers advertised by kitschy-cutesy pop. This failure to foresee the extent to which pastiche, recapitulation and a hyper-oedipalised neurotic individualism would become the dominant cultural tendencies is not a contingent error; it points to a fundamental misjudgement about the dynamics of capitalism. But this does not legitimate a return to the quill pens and powdered wigs of the eighteenth century bourgeois revolution, or to the endlessly restaged logics of failure of May ‘68, neither of which have any purchase on the political and libidinal terrain in which we are currently embedded.

[…]

Land collapses capitalism into what Deleuze and Guattari call schizophrenia, thus losing their most crucial insight into the way that capitalism operates via simultaneous processes of deterritorialization and compensatory reterritorialization. […] The abstract processes of decoding that capitalism sets off must be contained by improvised archaisms, lest capitalism cease being capitalism. Similarly, markets may or may not be the self-organising meshworks described by Fernand Braudel and Manuel DeLanda, but what is certain is that capitalism, dominated by quasi-monopolies such as Microsoft and Wal-Mart, is an anti-market. […]

For precisely these reasons, accelerationism can function as an anti-capitalist strategy […] What we are not talking about here is the kind of intensification of exploitation that a kneejerk socialist humanism might imagine when the spectre of accelerationism is invoked. As Lyotard suggests, the left subsiding into a moral critique of capitalism is a hopeless betrayal of the anti-identitarian futurism that Marxism must stand for if it is to mean anything at all.

[…]

Capitalism has abandoned the future because it can’t deliver it. Nevertheless, the contemporary left’s tendencies towards Canutism, its rhetoric of resistance and obstruction, collude with capital’s anti/meta-narrative that it is the only story left standing. Time to leave behind the logics of failed revolts, and to think ahead again.

Rejecting the anti-desire transcendental miserablism of leftist politics, and the resultant complete identification of capitalism with the satisfaction of desire:

If opposition to capital does not require that one maintains an anti- technological, anti- mass production stance, why - in the minds of some of its supporters, as much as in the caricatures produced by opponents such as Mensch - has anti- capitalism become exclusively identified with this organicism. Here we are a long way from Lenin's enthusiasm for Taylorism, or Gramsci’s celebration of Fordism, or indeed from the Soviet embrace of technology in the space race. Capital has long tried to claim a monopoly on desire: we only have to remember famous 1980s advert for Levi jeans in which a teenager was seen anxiously snuggling a pair of jeans through a Soviet border post. But the emergence of consumer electronic goods has allowed capital to conflate desire and technology so that the desire for an iPhone can now appear automatically to mean a desire for capitalism.

[…]

Land’s theory-fictional provocations were guided by the assumption that desire and communism were fundamentally incompatible […] they luridly expose the scale and the nature of the problems that the left now faces. Land […] highlight[s] the extent to which [capitalism's present] victory was dependent upon the libidinal mechanics of the advertising and PR companies whose semiotic excrescences despoil former public spaces. […] A pervasive negative advertising delibidinizes all things public, traditional, pious, charitable, authoritative, or serious, taunting them with the slew seductiveness of the commodity. Land is merely right about this “servative negative advertising” but the question is how to combat it. Instead of the anti- capitalist “no logo” call for a retreat from semiotic productivity, why not an embrace of all the mechanisms of semiotic- libidinal production in the name of a post- capitalist counterbranding? “Radical chic” is not something that the left should flee from - very much to the contrary, it is something that it must embrace and cultivate.

[…]

The second reason Land’s texts are important is that they expose an uncomfortable contradiction between the radical left’s official commitment to revolution, and its actual tendency towards political and formal- aesthetic conservatism. In Land’s writings, a quasi- hydraulic force of desire is set against a leftist- Canutist impulse towards preserving, protecting and defending. […] Where is the left that can speak as confidently in the name of an alien future, that can openly celebrate, rather than museum, the disintegration of existing socialities and territorialities?

The third reason Land’s texts are worth reckoning with is because they assume a terrain that politics now operates on, or must operate on, if it is to be effective - a terrain in which technology is embedded into everyday life and the body; design and PR are ubiquitous; financial abstraction enjoys domination over government; life and culture are subsumed into cyber- space, and data- tracking consequently assumes an increasingly important role. […] In the wake of the decline of the traditional workers’ movement, we have too often been forced into a false choice between an ascetic- authoritarian Leninism that at least worked in the sense that it took control of the state and limited the dominion of capital and models of political self- organisation which have done little to challenge neoliberal hegemony. What we need to construct is what was promised but never actually delivered by the various “anti- revolutions” of the 1960s: an effective anti- authoritarian left.

[…]

Post- Fordism has seen the decomposition of the old working class - which, in the Global North at least, is no longer concentrated in manufacturing spaces, and whose forms of industrial action are consequently no longer as effective as they once were. At the same time, the libidinal attractions of consumer capitalism needed to be met with a counterfolding, not simply an anti- libidinal dampening.

This entails that politics comes to terms with the essentially inorganic nature of libido […] that which Lacan and Land call the death drive: not a desire for death, for the extinction of desire in what Freud called the Nirvana principle, but an active force of death, defined by the tendency to deviate from any homeostatic regulation […] we ourselves are that which disrupts organic equilibrium. […] history has a direction […] [and] one implication of this is that it is very difficult to put this historically- machined inorganic libido back in its box: if desire is a historical- machinic force, its emergence alters “reality” itself; to suppress it would therefore involve either a massive reversal of history, or collective amnesia on a grand scale, or both.

[…] we can now see that the challenge is to imagine a postcapitalism that is commensurate with the death drive. At the moment, too much anticapitalism seems to be about the impossible pursuit of a social system oriented towards the Nirvana principle - to a quiescence - precisely the return to a mythical primitiveist equilibrium which the likes of Mensch mock. But any such return to primitivism would require either an apocalypse or the imposition of authoritarian measures - how else is drive to be banished? A leap into it is not a milligram; it not what we want, then we crucially need to articulate what it is we do want - which will mean disarticulating technology and desire from capital.

An example of how a postcapitalism that accepts and satisfies desire, instead of rejecting it and tamping down on it, need not be the same as consumerist capitalism — how capitalism, despite being identified with the satisfaction of desire, is actually imperfect at it, contra Land:

[…] Now, it begins to look as if, far from there being some inevitable fit between the desire for Starbucks and capitalism, Starbucks feeds desires which it can meet only in some provisional and unsatisfactory way. What is, in others, the desire for Starbucks is the thwarted desire for communism? For what is the “third place” that Starbucks offers - this place that is neither home nor work - if not a degraded prefiguration of communism itself?

A succinct statement of what clearer-eyed less capitalism-worshipping accelerationism actually means:

For Deleuze and Guattari, capitalism is defined by the way it simultaneously engenders and inhibits processes of destratification. In their famous formulation, capitalism deterritorializes and reterritorializes at the same time; there is no process of abstract decoding without a reciprocal decoding via neurotic personalisation (Oedipalisation) - hence the early 21st century disjunction of massively abstract finance capital on one hand; oedipalised celebrity culture on the other. Capitalism is a necessarily failed escape from feudalism, which, instead of destroying encastment, reconstructs social stratification in the class structure. It is only given this model that Deleuze and Guattari’s call to “accelerate the process” makes sense. It does not mean accelerating any or everything in capitalism willy- nilly in the hope that capitalism will thereby collapse. Rather, it means accelerating the processes of destratification that capitalism cannot but obstruct. One virtue of this model is that it places capital, not its adversary, on the side of resistance and control…

For Srnicek and Williams and other managerialists, the worsening is cut out of the picture: things will get better if only we establish a practical political hegemony that can make it so. This, apparently, is the real content of accelerationism […] In this response, of course, the humanist obsession reaches a totalising climax: the human capacity to reshape the world is utterly unbound; the promised land lies not beyond but immediately ahead.

The unconditional accelerationist dismisses the question. […] It is precisely against this view that accelerationism defines itself as ‘antihuman(ist)’, and against the fundamental question of praxis that it offers ‘antipraxis’. This can hardly mean ‘Do nothing’, of course: that would mean not just to return to the fundamental question of praxis, but to offer perhaps the most numbly tedious answer of all. The unconditional accelerationist, instead, referring to the colossal horrors presented to the human agent […] points to the basic unimportance of unidirectional human agency. We ‘hurl defiance to the stars’, but in their silence—when we see them at all—the stars return only crushing contempt. To the question ‘What is to be done?’, then, she can legitimately answer only, ‘Do what thou wilt’—and ‘Let go.’

We insist, then, that there is no promised land […] Far from discouraging the unconditional accelerationist or beckoning her to the grim convent of asceticism, however, the ruins in which this realisation contemptuously leaves us are the terrain of a genuine, even, properly, horrific aesthetic freedom that is liberated from the totality of a one-directional political teleology […] Taking the smallest steps beyond good and evil, the unconditional accelerationist, more than anyone else, is free at heart to pursue what she thinks is good and right and interesting—but with the ironical realisation that the primary ends that are served are not her own. For the unconditional accelerationist, the fastidious seriousness of the problem-solvers who propose to ‘save humanity’ is absurd in the face of the problems they confront. It can provoke only Olympian laughter. […]

This freedom is what antipraxis means […]

I've written about this before, and am working on another howl of pain about this, if I ever finish it, but this article states well the problems I have with the philosphical outlook of people like Timnit Gebru:

Some critics have decided futurist philosophies and their advocates are bound together in a toxic, reactionary bundle, promoted by a cabal of Silicon Valley elites. This style of conspiracy analysis has a long history and is always a misleading way to understand the world. We need a Left futurism that can address the flaws of these philosophies and frame a liberatory vision.

I'm going to basically quote like… almost all of this essay, to be honest, even going so far as to mirror its structure, because it needs to be said. I want to beat people over the head with it, I want to scream it, and it's so nice to see someone talk about it.

In 2022 [computer scientist and AI ethics researcher Timnit Gebru, who was quit/fired from Google] allied with the writer Émile P. Torres […] a trenchant critic of that community. Together Gebru and Torres have begun to promote the theory that Silicon Valley elites, and a global network of corporate, academic and nonprofit institutions, are invested in a toxic bundle of ideologies that they call TESCREAL, short for Transhumanism, Extropianism, Singularitarianism, Cosmism, Rationalism, Effective Altruism, and Longtermism. Guided by this conspiracy framework they have tried to connect the dots between the advocates for these ideas, and support for eugenics, racism and right-wing politics.

[…] a better sociology and intellectual history reveals that each philosophy has a progressive political wing that has been ignored. Moreover the wholesale condemnation of these ideas has cast a pall over all thinking about humanity’s future when we desperately need to grapple with the implications of emerging technologies.

U/ACC instead argues that what is open to ‘us’ is perhaps only the possibility of, as Deleuze writes in Logic of Sense, a “becoming the quasi-cause of what is produced within us”. There remains much which is inherently outside ‘us’, however. All we are able to do is produce “surfaces and linings in which the event is reflected”. [2]

In accelerating the process, Deleuze and Guattari nod purposefully towards Nietzsche, and, in light of the limits of what we are able to produce, we should remember that what is key for Deleuze in Nietzsche’s thought is his amor fati; his love of fate. Fate for Nietzsche is not our theistic destiny in the hands of God but the affirmation of a life caught up in its own flows. It is in this way that Deleuze writes of becoming worthy of the Event, of a life made impersonal.

[…]

In living a life (as opposed to my life — privileging the immanently impersonal over the segregated and territorialising personal), the task is “to become worthy of what happens to us, and thus to will and release the event, to become the offspring of one’s own events, and thereby be reborn, to have one more birth, and to break with one’s carnal birth — to become the offspring of one’s events and not of one’s actions, for the action is itself produced by the offspring of the event.” [5]

The "Xenofeminism: A Politics for Alienation" manifesto outlines a technologically-driven, accelerationist feminist agenda, instead of one that accepts naturalism, essentialism, the split between "masculine" and "feminine" versions of reason, and all of the gendered thinking tools that patriarchy itself invented and assigned-feminine which too many feminists employ and embrace.

0x00 Ours is a world in vertigo. It is a world that swarms with technological mediation, interlacing our daily lives with abstraction, virtuality, and complexity. XF constructs a feminism adapted to these realities: a feminism of unprecedented cunning, scale, and vision; a future in which the realization of gender justice and feminist emancipation contribute to a universalist politics assembled from the needs of every human, cutting across race, ability, economic standing, and geographical position. No more futureless repetition on the treadmill of capital, no more submission to the drudgery of labour, productive and reproductive alike, no more reification of the given masked as critique. Our future requires depetrification. XF is not a bid for revolution, but a wager on the long game of history, demanding imagination, dexterity and persistence.

I haven't gotten around to reading this yet, but I very much want to.

The extended quote of Libidinal Economy found in Mark Fisher's essay, Postcapitalist Desire is fascinating — one might say, arousing? — and it really made me want to read this book. This is my best-attempt OCR of a PDF of it I found on the internet archive, using a custom complex AI orchestration pipeline (that uses fuzzy diffing to avoid hallucinations).

While of course I may and will probably (a) not understand a lot of what I read herein, given Land's dense and occultish style and (b) disagree with — at the very least, the evaluative stances — some of what I find, nevertheless I find Land (before his neoreactionary turn) a fascinating, fascinating intellectual figure, much in the way I do Hobbes or de Sade or Nietzsche (although I unironically agree with Nietzsche a lot more, I think). As Mark Fisher says, Land is the philosopher the left needs to challenge its thinking, its ideas, and its methods — and even its values. Fanged Noumena is a collection of his early CCRU era writings, precisely those prior to his neoreactionary turn, so this is the most interesting stuff for me to read, since I find his neoreactionary ideas painfully boring compared to his left-accelerationist ones.

I dunno man, Bataille seems really interesting.

Considering capital as the ultimate “eerie entity”, Fisher wonders about the ways

"that “we” “ourselves” are caught up in the rhythms, pulsions and patternings of non-human forces. There is no inside except as a folding of the outside; the mirror cracks, I am an other, and I always was.[note]Mark Fisher, The Weird and the Eerie (London: Repeater Books, 2016), 11-12.[/note]"

Following this, it is fitting that Fisher then begins his book with an exploration of the works of H.P. Lovecraft. He notes that “it is not horror but fascination — albeit a fascination usually mixed with a certain trepidation — that is integral to Lovecraft’s rendition of the weird”.[note]Ibid., 17.[/note] For Fisher, on both an aesthetic and political level, it is the weird that is desirable for its ability to “de-naturalise all worlds, by exposing their instability, their openness to the outside”.[note]Ibid., 29.[/note]

[…]

The Outside is a concept that has long haunted the history of philosophy under various different names and formulations — from the Kantian noumenon to the Lacanian Real, et al. — with each functioning as a challenge to subjectivity that attempts to think beyond phenomenal limit-experiences. Whilst this broad definition is applicable to the narratives in much weird fiction, these tales explore the Outside through narrated ‘experience’ rather than objective academic analysis and they do so with an imaginative flare that has fascinated many.

[…]

The [Cthulhu] cult represent the Outside as a comprehensible and material social threat, far more visibly dangerous than the misadventures of the atomised individual in their collective channelling of the powers of the great Cthulhu. Whatever horrifying and unthinkable form the Outside may take, the fact remains that it is seemingly through community alone that its affects can be harnessed (whilst nonetheless remaining intolerable to the individual human mind).

[…]

Death is, of course, the ultimate limit-experience, the ultimate challenge to subjectivity, and here grief becomes the affective result of being haunted by the Outside through the absences that death imposes upon both individual and community.

[…]

Caring for one another with the intensity that so often follows grief renews the possibility of such a collective subject being established […] it is through community that the affects of the Outside are channelled, whilst still remaining intolerable, and the political implications of this communal channelling are considerable.

Whilst such implications are not discussed in The Weird and the Eerie explicitly, in the context of Fisher’s wider writings the book reads like an aesthetic toolkit for ontopolitical ‘egress’[…] In his next book, Acid Communism, left in an unknown state of completion at the time of his death, Fisher was to address the political reality of egress more explicitly. He hoped to reinvigorate the psychedelic praxes of consciousness-raising/-razing that have come to culturally define the 1960s and ’70s, channelling them through his postcapitalist desires.

[…]

In the unpublished introduction to Acid Communism, Fisher writes of this potential return of the new that capitalist realism […] repeatedly ungrounds […]. Fisher seemed to want to encourage a community of Lovecraftian Outsiders, unsure of how they arrived at their present situation but nonetheless curious to leave the cloistered world in which they find themselves.

[…]

For Fisher, thinking through the work of Herbert Marcuse, the history of Western art is littered with exit strategies. He presents a leftist instantiation of Land’s Outsider position, challenging the contemporary populist left, that can at best be described as working to a model of all voice and no exit, calling for new attempts at finding exits through other ways of living — attempts that have all too often been neutered by capitalism’s cooptive mechanisms.

[…]

However, Fisher’s is not an anarcho-primitivist position, supporting a return to a time before capitalism and its technologies. His accelerationist position is an advocation of the use of capitalism’s forces to modulate past potentials, transducing them into the future by collectively harnessing capital’s deterritorializing capacities for outside aims and egresses.

We are living in a pre-cyberpunk world, actively paving the groundwork for corporate-government fusion… William Gibson didn't predict the future, he described the present with better lighting.

[…]

The Death of the Hacker Ethic

There was a time when resistance meant building alternatives… Linux stands as a monument to that effort… Now, resistance is synonymous with "there ought to be a law." … Every single one of these “solutions” makes the problem worse. Large corporations can afford compliance teams. They can navigate complex regulatory frameworks. They can lobby for favorable interpretations. Small businesses and potential competitors cannot. They must then turn to these large companies for infrastructure and expertise, creating even less competition and fewer choices for consumers.

[…]

The Regulatory Capture Loop

Complex regulations get passed that ostensibly protect consumers from big corporations. Small businesses can't afford compliance, so they either fail or get absorbed by larger entities that can handle the regulatory burden. The remaining large corporations then influence how these regulations are interpreted and enforced because they've grown even larger in capital, technical expertise, and manpower.

The result is a system where every attempt at resistance actually strengthens the thing being resisted. It's regulatory capture disguised as consumer protection. It's corporate-government fusion marketed as progressive activism.

This is the Zaibatsu model from Neuromancer, not through dramatic corporate takeovers, but through the slow erosion of the capacity for independent action. Every time we choose regulatory solutions over building alternatives, we're voting for a world where only institutions with massive resources can operate effectively.

[…]

Consensual Hallucination

Gibson's "consensual hallucination" was cyberspace… Today's consensual hallucination is subtler: the belief that regulatory capture is actually resistance. We've collectively agreed to hallucinate that asking power to regulate itself constitutes meaningful opposition.

[…]

Jacking Out of the Matrix

The real hack isn't regulatory, it's cognitive. It's refusing to accept the premise that only institutions can solve institutional problems. The future is still being written in code. The question is: will you be writing it, or will you be asking someone else to write it for you?

This FAQ states my beliefs on technology and transhumanism and their overlap with anarchism almost exactly as I would've stated it — and will probably state it in upcoming half-finished essays — so I decided it's well worth just… putting it here, so it can speak for me and what I believe in and hope for.

A deeply cathartic-to-read critique of the misconceptions of science that so many people on the left have, and a defense of its radicalism and its value, against the spiritualists and mystics, from the perspective of someone who actually understands the epistemological and moral objections being made (such as those of Against Method) instead of merely ignoring them.

I've always found Crimethinc kind of insufferable, and after reading (well, listening to) Days of War, Nights of Rage and seeing their comments on things like poverty and wearing deoderant of all things, it only reinforced my notion that I really don't like them. It's possible to do actually useful things that help yourself and your community without giving into vanguardism on the one hand or co-option and total implication in the system on the other, but they're so focused on purity and radical aesthetics and having fun that they're incapable of getting their hands dirty to do any of that. Moreover, it's possible to be what Bookchin called a "lifestylist" without it actually being bad or a problem, but Crimethinc seems to glorify a sort of hippie crust punk dropout lifestyle of play acting at poverty.

Many aspects of crimethinc reference the Situationist Internationale and a large chunk of their ideas are based around the Situationist concept “the transformation of everyday life”. The Situationists were heavily influenced by Marx and CWC are heavily influenced by American consumer culture it would seem. The call to transform everyday is a call to smash the current exploitative system, to participate in the class struggle, an ongoing historical conflict between the proletariat and the ruling class. Crimethinc substitute this class struggle with a teenage individualistic rebellion based on having fun now. Shoplifting, dumpster diving, quitting work are all put forward as revolutionary ways to live outside the system but amount to nothing more than a parasitic way of life which depends on capitalism without providing any real challenge. […]

The reality of the situation is that you can’t boycott your way out of capitalism dropping out of the system is never going to bring it down if anything you just re-enforce the system by recuperating people’s alienation and desire for revolution by selling them a new lifestyle under the same system. Capitalism is a system of coercion and control, we don’t work to support the system, we work because we need food and shelter and healthcare and the only way to get that under capitalism is with money. The only way we can get money is by selling our labour — the alternative is to rot, that’s Capitalism. I don’t want to feed my kids out of a dumpster or have to scam free healthcare if I get cancer, it’s not appealing or practical. There’s nothing revolutionary about using your white, middle-class, western privilege to remove yourself from the system at the expense of those who remain trapped in it. None of us are free until we all are.

This quote, expanded upon to like a paragraph in the actual Days of War, Nights of Rage book, also made me so fucking angry as someone who's had the huge privilege to be able to avoid these things, but has been adjacent to them for most of my adult life because of who I love and who I'm friends with, and my own disabilities and marginalization:

“Poverty, unemployment, homelessness — if you’re not having fun, you’re not doing it right!”

As "Rethinking" rightly says:

The arrogance of middle class kids (just like the hippies) supposing to change by world by roughing it as “poor” people for a few years is captured perfectly in the quote on the back cover of their book evasion. […] Condescending, privileged, middle class crap. The only people who could think that poverty is in any way fun are wealthy kids playing at being poor for a few years, the daily reality of poverty, unemployment and homelessness for the average person is very serious and something anarchists should always organise against rather than mock.

This is another juicy quote:

One of crimethinc’s more recent publications “recipes for disaster:an anarchist cookbook”, is indicative of the massive problems with them. The book is a somewhat interesting list of pranks, scams and activist information. […] An eclectic mix of information, most of which is crap the rest of which is useless without political understanding. […] The book shies away from serious revolutionary information like how to organise a union in your workplace, how to organise at school, how to make contact and work with communities in struggle, how to break out of the activist ghetto, how to set up a social centre, how to provide prisoner support or how to support asylum seekers etc. All the activities amount to little more than activist busy-work, something to waste your time with while being a “drop-out”, ease your social conscience and not have to do any hard work or compromise yourself by working with people who are complicit in the system.

A lot of Crimethinc's work also feels like a gleeful embrace of the implications of transcendental miserablism, a sort of "we're radical because we LIKE that (we believe) anarchism requires asceticism and a gentle decline into that good night."

This is another good criticism of CrimethInc — placing special emphasis on something that I did notice when reading Days of War, which is that for avowed amoralists who dislike puritainism, they're quite puritanical and speak in a lot of generalized, absolutist moral terms, in ways that are pretty unjustified.

Despite your cautions against ideology, your book is riddled with simplistic, unqualified declarations. In some places you are admirably open and modest, but in others you come on like you have definitive answers to practically everything from the meaning of life to whether people should wear deodorant or not. […] Just as you present rebellious actions as almost purely GOOD, you tend to present the system as almost purely BAD. In reality, just as most revolts and radical movements have been full of mistakes and limitations, many aspects of the present society are positive, or at least potentially so. […]

There is also a recurring moralizing simplisticness. It is good that you recognize the element of necessary hypocrisy and compromise in our lives. But a lot of your agonizing over whether this or that practice is hypocritical is, to me, a phoney, nonexistent issue. I do not view my options primarily in terms of whether I am "implicated" in capitalism, as if that were some sort of sin to be avoided at all cost. Nor, conversely, do I consider that I am accomplishing anything very notable if I avoid some such compromise, as if radical struggle were a matter of more and more people gradually becoming less and less implicated in the prevailing system. That perspective is just as simplistic as pacifists' feeling that we will arrive at peace by more and more people becoming pacifists (while failing to confront economic and other factors that engender wars despite most people's preference for peace). While I salute the sense of experimentation of your friend who tried to live off garbage pickings instead of buying food, it does not seem to me that such choices have much to do with radical strategy.

In the same essay there's a critique of a similar collective from the UK, attached by the author because he believes the same critiques apply to CrimethInc, and I agree:

I don't have time to comment on Theft #2 in any detail. The most notable criticism I have is that the last chapter is sometimes rather simplistic. While I think it's fine to recommend that people seek pursuits that are enjoyable and satisfying to them, it seems to me rather silly to declare that life "should be" "perpetual ecstasy" etc. This kind of "should be" amounts to little more than that you think it would be nice if things were that way. It's ultimately pretty meaningless, like saying that insects "should" have "the right" to live freely without being eaten by birds. It's a false reasoning which you have probably picked up from Vaneigem. He rightly criticizes traditional leftism's overemphasis on sacrificing for the cause, but then flips into an equally unjustified opposite conclusion that pleasure is the supreme criterion for everything, and then to the even more absurd implication that a successful revolution will somehow magically produce endless unalloyed pleasure.

This is an important point; Emma Goldman may have said that she wanted no part in a revolution without dancing, but a revolution that's only dancing is just a dance party. It gets even more cutting, though:

Again, I think it's good that you encourage people to reexamine their lives, to reduce addictive consumership, and to make space for relaxation and reflection. But you have to be careful not to be too rigid in your recommendations. "The more you consume, the less you live" makes a good graffiti, it conveys a good general point. But it shouldn't be taken too literally, as if it were a precise scientific formula. In your SHIT percentage test, for example, you more or less equate "the more of yourself is actually yours" (a rather vague notion in any case) with lower SHIT percentages. This amounts to an inverse economic fetishization, a sort of anti-economic puritanism, as if enjoyment was always inversely proportional to the degree of economic taint.

And, most relevant to Libidinal Economy (which I want to read) and what's discussed in "Notes on Accelerationism":

Actually, of course, in many cases an activity that creates profit for someone may nevertheless be more enjoyable than another activity that puristically avoids the market. The best things in life are not always free, even if they "should" be. If you frequently present this kind of over-simplified formula, people with enough sense to know better will not take you seriously regarding the many other areas where you have valid points to make.

"You dare not say the only important thing… and in this way situate yourselves on the most dispicable side, the moralistic side" indeed.

A good distinction from one of the comments:

…i think the point is that if you consider a personal aversion to sweatshop clothing a political act that makes any difference to the existence of sweatshops, that is the kind of substitution for collective action that characterises individualism/lifestylism.

I reject the fallacy that we can "control" the future in any large scale way, build mass movements or central organizations to guide the flows of accelerating history; yet I still think that holding in your heart an image of what the future should look like to you, and choosing to keep getting up each morning — "Carlyle had risen full of strength that day, for it was the day…" — and keep working towards it in whatever small way you can, not tricking yourself that your prefiguration will ultimately mean anything necessarily, but doing it because it's healing, because it grants you purpose, is worth it anyway, and often doing so doesn't fix the world, but it can make the world a little better, even if the complex flows of chaos that swirl out may undo any larger goal: you can ease the pain and sorrow of the world that crushes us, and that is worth it anyway. Thus I'm not against praxis, I'm against deluded praxis, centralized praxis, praxis that comes with eschatology.

This essay by one of my favorite authors echoes that feeling, even though I disagree with some of of its more solutionistic, liberal statements of belief in the actual power to change things, or in incrementalism. And what it has to say about purity culture in activism is well worth hearing as well. Some quotes, as has become customary:

[…] hopepunk sketch[es] out a body of imagined worlds which are positive but not utopias, because their positivity lies, not in the world already being excellent, but in the world moving toward the better thanks to the efforts of excellent people who work to make a difference. […] Hopepunk stories tend to showcase cooperation, collective action, resilience, partial victories as the world is moved toward, not to, a better state, ending with (re)construction underway and the world chang/ing/, not chang/ed/. The subgenre has also been described as weaponized optimism […] connected with what Malka Older has called speculative resistance.

One general signature of hopepunk is that its stories counter tales of emotional darkness or rottenness, […] violent, amoral, and often dystopian/apocalyptic trappings […] plots and character choices [that] advance zero-sum narratives where achievement requires causing someone else’s fall, or portraits of human nature in which, in the end, people will always be selfish […] and in which systems will always be corrupt and unsalvageable. In Hopepunk […] ordinary people[…] while [some] make bad choices, enough make good choices to leave a positive sense of the capacity of humans to choose good. […] [V]ery few [stories] depict how studies show people really behave in crisis, banding together to supply pop-up pantries and mutual aid.

Before it sounds like hopepunk could describe any story where […] or good guys beat bad guys, these are not […]. […] The punk movement is anti-establishment, with long ties to political activism and resistance, anti-consumerist, anti-corporate, anti-authoritarian, with a strong ethic of visibility and in-your-face active expression of these sentiments.

Punk is also messy. While the grimdark hero […] is one opposite of the Disney Princess, hopepunk is another opposite. The Disney Princess and many hero stories are purity stories. […] Punk is grungy in aesthetic, and hopepunk shares that, building better among the garbage of the bad. It also expresses negative emotions, not despair but productive anger, as well as kindness which sometimes needs to take the form of confrontation […]. Hopepunk showcases resilience by showing failure, setbacks, and compromise, not as heroic flaws or formative backstories, but acknowledging that messing up is an unavoidable part of taking action in the first place.

Most grimdark heroes make mistakes, but they are giant character-defining mistakes […] reinforcing the idea that any failure or impurity is a big deal, not a normal part of living a reasonable life. […]

Messiness and impurity paired with positive change are one core way hopepunk differs […] from a huge body of narratives, and even political logics. As articulated by philosopher/sociologist Alexis Shotwell in her brilliant book Against Purity: Living Ethically in Compromised Times, ideas of purity often do harm to action and activism […] Purity is also used (often strategically) to make ethical choices more difficult. […] Shotwell discusses the impossibility of true purity—practically no foods or products exist that don’t harm something—and the importance of acknowledging harm done in order to be able to evaluate levels of harm, reduction of harm, etc. […]

Hopepunk narratives are genre stories which have depictions of human nature (teamwork, honesty, resilience) but which also counter purity narratives, by having space for partial victories, unfinished projects, compromise, and mundane not-character-defining failures and mistakes. Setbacks in hopepunk tend to be more about the outcome for the world, what now needs to be done to help or fix the problem, in contrast with stories where setbacks or failures are mainly beats in character development, the point where the hero must stand by his vow never to kill again, or prove her leadership skills to keep the team together.

Fiction does not give us many stories of continuing to slog on after an unsatisfying partial victory. That makes hopepunk powerful.

Interestingly, even my almost post-apocalyptic, ultimately-doomed dystopian cyberpunk stories are, in a sense, all ultimately about this, with an unconditional accelerationist twist: we can't control where we're going; that's in the hands of technocapital's hyperstitial ideas and egregores; but we can try to make things better, try to improve, to stop harming, to keep doing something, and that is meaningful and does, in a small way that may butterfly-effect out into a large way, change the world for the better in a way we can't possibly predict.

Soundly and neatly deals with primitivism as an ideology:

• It's rejection of the fundamental anarchist project – showing how we can have civilization, ecological sustainability, and liberty at the same time – for the premise of liberals – that these things are incompatible – just a slightly different conclusion.
• The 'population question', which renders primitivism a totally incoherent and unworkable ideology with nothing to offer outside a facile intellectual mind game of critique.
• The violent, coercive, and borderline fascist implications of any attempt to reduce the human population at a large scale.
• Responses to some responses to these points.

This is generally an extremely good takedown of the Nick Bostrom Superintelligence argument. The core of it is outlined thusly, via excerpts:

Today we're building another world-changing technology, machine intelligence. We know that it will affect the world in profound ways, change how the economy works, and have knock-on effects we can't predict.

But there's also the risk of a runaway reaction, where a machine intelligence reaches and exceeds human levels of intelligence in a very short span of time.

At that point, social and economic problems would be the least of our worries. Any hyperintelligent machine (the argument goes) would have its own hypergoals, and would work to achieve them by manipulating humans, or simply using their bodies as a handy source of raw materials.

Last year, the philosopher Nick Bostrom published Superintelligence, a book that synthesizes the alarmist view of AI and makes a case that such an intelligence explosion is both dangerous and inevitable given a set of modest assumptions…

Let me start by laying out the premises you need for Bostrom's argument to go through:

Premise 1: Proof of Concept […] Premise 2: No Quantum Shenanigans […] Premise 3: Many Possible Minds […] Premise 4: Plenty of Room at the Top […] Premise 5: Computer-Like Time Scales […] Premise 6: Recursive Self-Improvement […] Conclusion: RAAAAAAR!

If you accept all these premises, what you get is disaster!

Because at some point, as computers get faster, and we program them to be more intelligent, there's going to be a runaway effect like an explosion.

As soon as a computer reaches human levels of intelligence, it will no longer need help from people to design better versions of itself. Instead, it will start doing on a much faster time scale, and it's not going to stop until it hits a natural limit that might be very many times greater than human intelligence.

At that point this monstrous intellectual creature, through devious modeling of what our emotions and intellect are like, will be able to persuade us to do things like give it access to factories, synthesize custom DNA, or simply let it connect to the Internet, where it can hack its way into anything it likes and completely obliterate everyone in arguments on message boards.

[…]

Let imagine a specific scenario where this could happen. Let's say I want to built a robot to say funny things. […] In the beginning, the robot is barely funny. […] But we persevere, we work, and eventually we get to the point where the robot is telling us jokes that are starting to be funny […] At this point, the robot is getting smarter as well, and participates in its own redesign. […] It now has good instincts about what's funny and what's not, so the designers listen to its advice. Eventually it gets to a near-superhuman level, where it's funnier than any human being around it.

This is where the runaway effect kicks in. The researchers go home for the weekend, and the robot decides to recompile itself to be a little bit funnier and a little bit smarter, repeatedly.

It spends the weekend optimizing the part of itself that's good at optimizing, over and over again. With no more need for human help, it can do this as fast as the hardware permits.

When the researchers come in on Monday, the AI has become tens of thousands of times funnier than any human being who ever lived. It greets them with a joke, and they die laughing.

In fact, anyone who tries to communicate with the robot dies laughing, just like in the Monty Python skit. The human species laughs itself into extinction.

To the few people who manage to send it messages pleading with it to stop, the AI explains (in a witty, self-deprecating way that is immediately fatal) that it doesn't really care if people live or die, its goal is just to be funny.

Finally, once it's destroyed humanity, the AI builds spaceships and nanorockets to explore the farthest reaches of the galaxy, and find other species to amuse.

This scenario is a caricature of Bostrom's argument, because I am not trying to convince you of it, but vaccinate you against it.

Observe that in these scenarios the AIs are evil by default, just like a plant on an alien planet would probably be poisonous by default. Without careful tuning, there's no reason that an AI's motivations or values would resemble ours. […] So if we just build an AI without tuning its values, the argument goes, one of the first things it will do is destroy humanity.

[…]

The only way out of this mess is to design a moral fixed point, so that even through thousands and thousands of cycles of self-improvement the AI's value system remains stable, and its values are things like 'help people', 'don't kill anybody', 'listen to what people want'. […] Doing this is the ethics version of the early 20th century attempt to formalize mathematics and put it on a strict logical foundation. That this program ended in disaster for mathematical logic is never mentioned.

[…]

People who believe in superintelligence present an interesting case, because many of them are freakishly smart. They can argue you into the ground. But are their arguments right, or is there just something about very smart minds that leaves them vulnerable to religious conversion about AI risk, and makes them particularly persuasive?

Is the idea of "superintelligence" just a memetic hazard?

When you're evaluating persuasive arguments about something strange, there are two perspectives you can choose, the inside one or the outside one. […] The inside view requires you to engage with these arguments on their merits. […] But the outside view tells you something different. […] Of course, they have a brilliant argument for why you should ignore those instincts, but that's the inside view talking. […] The outside view doesn't care about content, it sees the form and the context, and it doesn't look good.

So I'd like to engage AI risk from both these perspectives. I think the arguments for superintelligence are somewhat silly, and full of unwarranted assumptions.

But even if you find them persuasive, there is something unpleasant about AI alarmism as a cultural phenomenon that should make us hesitate to take it seriously.

First, let me engage the substance. Here are the arguments I have against Bostrom-style superintelligence as a risk to humanity:

The Argument From Wooly Definitions […] With no way to define intelligence (except just pointing to ourselves), we don't even know if it's a quantity that can be maximized. For all we know, human-level intelligence could be a tradeoff. Maybe any entity significantly smarter than a human being would be crippled by existential despair, or spend all its time in Buddha-like contemplation.

The Argument From Stephen Hawking's Cat […] Stephen Hawking is one of the most brilliant people alive, but say he wants to get his cat into the cat carrier. How's he going to do it? He can model the cat's behavior in his mind and figure out ways to persuade it. […] But ultimately, if the cat doesn't want to get in the carrier, there's nothing Hawking can do about it despite his overpowering advantage in intelligence. […] You might think I'm being offensive or cheating because Stephen Hawking is disabled. But an artificial intelligence would also initially not be embodied, it would be sitting on a server somewhere, lacking agency in the world. It would have to talk to people to get what it wants.

The Argument From Emus […] We can strengthen this argument further. Even groups of humans using all their wiles and technology can find themselves stymied by less intelligent creatures. In the 1930's, Australians decided to massacre their native emu population to help struggling farmers. […] [The emus] won the Emu War, from which Australia has never recovered.

The Argument from Complex Motivations […] AI alarmists believe in something called the Orthogonality Thesis. This says that even very complex beings can have simple motivations, like the paper-clip maximizer. You can have rewarding, intelligent conversations with it about Shakespeare, but it will still turn your body into paper clips, because you are rich in iron. […] I don't buy this argument at all. Complex minds are likely to have complex motivations; that may be part of what it even means to be intelligent. […] It's very likely that the scary "paper clip maximizer" would spend all of its time writing poems about paper clips, or getting into flame wars on reddit/r/paperclip, rather than trying to destroy the universe.

The Argument From Actual AI […] The breakthroughs being made in practical AI research hinge on the availability of these data collections, rather than radical advances in algorithms. […] Note especially that the constructs we use in AI are fairly opaque after training. They don't work in the way that the superintelligence scenario needs them to work. There's no place to recursively tweak to make them "better", short of retraining on even more data.

The Argument From My Roommate […] My roommate was the smartest person I ever met in my life. He was incredibly brilliant, and all he did was lie around and play World of Warcraft between bong rips.

The Argument From Brain Surgery […] I can't point to the part of my brain that is "good at neurosurgery", operate on it, and by repeating the procedure make myself the greatest neurosurgeon that has ever lived. Ben Carson tried that, and look what happened to him. Brains don't work like that. They are massively interconnected. Artificial intelligence may be just as strongly interconnected as natural intelligence. The evidence so far certainly points in that direction.

The Argument From Childhood

Intelligent creatures don't arise fully formed. We're born into this world as little helpless messes, and it takes us a long time of interacting with the world and with other people in the world before we can start to be intelligent beings.

Even the smartest human being comes into the world helpless and crying, and requires years to get some kind of grip on themselves.

It's possible that the process could go faster for an AI, but it is not clear how much faster it could go. Exposure to real-world stimuli means observing things at time scales of seconds or longer.

Moreover, the first AI will only have humans to interact with—its development will necessarily take place on human timescales. It will have a period when it needs to interact with the world, with people in the world, and other baby superintelligences to learn to be what it is.

Furthermore, we have evidence from animals that the developmental period grows with increasing intelligence, so that we would have to babysit an AI and change its (figurative) diapers for decades before it grew coordinated enough to enslave us all.

The Argument From Gilligan's Island

A recurring flaw in AI alarmism is that it treats intelligence as a property of individual minds, rather than recognizing that this capacity is distributed across our civilization and culture.

Despite having one of the greatest minds of their time among them, the castaways on Gilligan's Island were unable to raise their technological level high enough to even build a boat (though the Professor is at one point able to make a radio out of coconuts).

Similarly, if you stranded Intel's greatest chip designers on a desert island, it would be centuries before they could start building microchips again.

The Outside Argument

What kind of person does sincerely believing this stuff turn you into? The answer is not pretty.

I'd like to talk for a while about the outside arguments that should make you leery of becoming an AI weenie. These are the arguments about what effect AI obsession has on our industry and culture:

Grandiosity […] Meglomania […] Transhuman Voodoo […] Religion 2.0

What it really is is a form of religion. People have called a belief in a technological Singularity the "nerd Apocalypse", and it's true.

It's a clever hack, because instead of believing in God at the outset, you imagine yourself building an entity that is functionally identical with God. This way even committed atheists can rationalize their way into the comforts of faith.

The AI has all the attributes of God: it's omnipotent, omniscient, and either benevolent (if you did your array bounds-checking right), or it is the Devil and you are at its mercy.

Like in any religion, there's even a feeling of urgency. You have to act now! The fate of the world is in the balance!

And of course, they need money!

Because these arguments appeal to religious instincts, once they take hold they are hard to uproot.

Comic Book Ethics […] Simulation Fever […] Data Hunger […] String Theory For Programmers […] Incentivizing Crazy […] AI Cosplay […]

The Alchemists

Since I'm being critical of AI alarmism, it's only fair that I put my own cards on the table.

I think our understanding of the mind is in the same position that alchemy was in in the seventeenth century.

Alchemists get a bad rap. We think of them as mystics who did not do a lot of experimental work. Modern research has revealed that they were far more diligent bench chemists than we gave them credit for.

In many cases they used modern experimental techniques, kept lab notebooks, and asked good questions.

The alchemists got a lot right! […] Their problem was they didn't have precise enough equipment to make the discoveries they needed to.

[…]

I think we are in the same boat with the theory of mind.

We have some important clues. The most important of these is the experience of consciousness. This box of meat on my neck is self-aware, and hopefully (unless we're in a simulation) you guys also experience the same thing I do.

But while this is the most basic and obvious fact in the world, we understand it so poorly we can't even frame scientific questions about it.

We also have other clues that may be important, or may be false leads. We know that all intelligent creatures sleep, and dream. We know how brains develop in children, we know that emotions and language seem to have a profound effect on cognition.

We know that minds have to play and learn to interact with the world, before they reach their full mental capacity.

And we have clues from computer science as well. We've discovered computer techniques that detect images and sounds in ways that seem to mimic the visual and auditory preprocessing done in the brain.

But there's a lot of things that we are terribly mistaken about, and unfortunately we don't know what they are.

And there are things that we massively underestimate the complexity of.

An alchemist could hold a rock in one hand and a piece of wood in the other and think they were both examples of "substance", not understanding that the wood was orders of magnitude more complex.

We're in the same place with the study of mind. And that's exciting! We're going to learn a lot.

Generally, I only have two really major disagreements with the account in this talk.

One, I think that applying an "outside view" to arguments is an extremely dangerous proposition when not accompanied by substantive "inside view" rebuttals or defeaters that motivate skepticism of the given argument in the first place. This is because the premature application of an "outside view" tends to incline us towards what seems normal, familiar, simple, and common sense, and in the absence of inside view arguments we simply don't have the information or tools to assess whether that's a good thing or not. There are plenty of views that seem or seemed problematic from an "outside view" to many contemporaries — including atheism, slavery abolitionism, pro-choice, trans rights (look at how right wingers describe us as a cult of transhumans who think we're "better than god" because we want to change what nature gave us), etc — that turned out to be correct, because ultimately what seems normal, familiar, common sense, and simple to us is simply socially and historically contingent happenstance, not a substantive argument.

Two, regarding the "Transhuman Voodoo" section, I don't really see the inherent link between scientifically implausible technological ideas (such as nanotechnology) and AI superintelligence: one could believe in superintelligence and just as easily assume that the fundamental laws of physics as we know them aren't totally wrong, and since the AI would be just as bound by them as us, it wouldn't be able to create miracle technologies.

This post is making a point - generative AI is relatively cheap - that might seem so obvious it doesn't need making. I'm mostly writing it because I've repeatedly had the same discussion in the past six months where people claim the opposite. Not only is the misconception still around, but it's not even getting less frequent. This is mainly written to have a document I can point people at, the next time it repeats.

It seems to be a common, if not a majority, belief that Large Language Models (in the colloquial sense of "things that are like ChatGPT") are very expensive to operate. This then leads to a ton of innumerate analyses about how AI companies must be obviously doomed, as well as a myopic view on how consumer AI businesses can/will be monetized.

[…] let's compare LLMs to web search. I'm choosing search as the comparison since it's in the same vicinity and since it's something everyone uses and nobody pays for, not because I'm suggesting that ungrounded generative AI is a good substitute for search.

What is the price of a web search?

Here's the public API pricing for some companies operating their own web search infrastructure, retrieved on 2025-05-02:

• The Gemini API pricing lists a "Grounding with Google Search" feature at $35/1k queries. I believe that's the best number we can get for Google, they don't publish prices for a "raw" search result API.
• The Bing Search API is priced at $15/1k queries at the cheapest tier.
• Brave has a price of $5/1k searches at the cheapest tier. Though there's something very strange about their pricing structure, with the unit pricing increasing as the quota increases, which is the opposite of what you'd expect. The tier with real quota is priced at $9/1k searches.

So there's a range of prices, but not a horribly wide one, and with the engines you'd expect to be of higher quality also having higher prices.

What is the price of LLMs in a similar domain?

To make a reasonable comparison between those search prices and LLM prices, we need two numbers:

• How many tokens are output per query?
• What's the price per token?

I picked a few arbitrary queries from my search history, and phrased them as questions, and ran them on Gemini 2.5 Flash (thinking mode off) in AI Studio:

• [When was the term LLM first used?] -> 361 tokens, 2.5 seconds
• [What are the top javascript game engines?] -> 1145 tokens, 7.6 seconds
• [What are the typical carry-on bag size limits in europe?] -> 506 tokens, 3.4 seconds
• [List the 10 largest power outages in history] -> 583 tokens, 3.7 seconds

Note that I'm not judging the quality of the answers here.

What's the price of a token? The pricing is sometimes different for input and output tokens. Input tokens tend to be cheaper, and our inputs are very short compared to the outputs, so for simplicity let's consider all the tokens to be outputs. Here's the pricing of some relevant models, retrieved on 2025-05-02:

Model	Price / 1M tokens
Gemma 3 27B	$0.20 (source)
Qwen3 30B A3B	$0.30 (source)
Gemini 2.0 Flash	$0.40 (source)
GPT-4.1 nano	$0.40 (source)
Gemini 2.5 Flash Preview	$0.60 (source)
Deepseek V3	$1.10 (source)
GPT-4.1 mini	$1.60 (source)
Deepseek R1	$2.19 (source)
Claude 3.5 Haiku	$4.00 (source)
GPT-4.1	$8.00 (source)
Gemini 2.5 Pro Preview	$10.00 (source)
Claude 3.7 Sonnet	$15.00 (source)
o3	$40.00 (source)

If we assume the average query uses 1k tokens, these prices would be directly comparable to the prices per 1k search queries. That's convenient.

The low end of that spectrum is at least an order of magnitude cheaper than even the cheapest search API, and even the models at the low end are pretty capable. The high end is about on par with the highest end of search pricing. To compare a midrange pair on quality, the Bing Search vs. a Gemini 2.5 Flash comparison shows the LLM being 1/25th the price.

I know some people are going to have objections to this back-of-the-envelope calculation, and a lot of them will be totally legit concerns. I'll try to address some of them preemptively.

Surely the typical LLM response is longer than that - I already picked the upper end of what the (very light) testing suggested as a reasonable range for the type of question that I'd use web search for. There's a lot of use cases where the inputs and outputs are going to be much longer (e.g. coding), but then you'd need to also switch the comparison to something in that same domain as well.

The LLM API prices must be subsidized to grab market share – i.e. the prices might be low, but the costs are high - I don't think they are, for a few reasons. I'd instead assume APIs are typically profitable on a unit basis. I have not found any credible analysis suggesting otherwise.

First, there's not that much motive to gain API market share with unsustainably cheap prices. […] there's no long-term lock-in […]. Data from paid API queries will also typically not be used for training or tuning the models […]. Note that it's not just that you'd be losing money on each of these queries for no benefit, you're losing the compute that could be spent on training, research, or more useful types of inference.

Second, some of those models have been released with open weights and API access is also available from third-party providers who would have no motive to subsidize inference. […] The pricing of those third-party hosted APIs appears competitive with first-party hosted APIs.

Third, Deepseek released actual numbers on their inference efficiency in February. Those numbers suggest that their normal R1 API pricing has about 80% margins when considering the GPU costs, though not any other serving costs.

Fourth, there are a bunch of first-principles analyses on the cost structure of models with various architectures should be. Those are of course mathematical models, but those costs line up pretty well with the observed end-user pricing of models whose architecture is known. […]

The search API prices amortize building and updating the search index, LLM inference is based on just the cost of inference - This seems pretty likely to be true, actually? But the effect can't really be that large for a popular model: e.g. the allegedly leaked OpenAI financials claimed $2B/year spent on inference vs. $3B/year on training. Given the crazy growth of inference volumes (e.g. Google recently claimed a 50x increase in token volumes in the last year) the training costs are getting amortized much more effectively.

The search API prices must have higher margins than LLM inference - […] see the point above about Deepseek's releasd numbers on the R1 profit margins. […] Also, it seems quite plausible that some Search providers would accept lower margins, since at least Microsoft execs have testified under oath that they'd be willing to pay more for the iOS query stream than their revenue, just to get more usage data.

But OpenAI made a loss, and they don't expect to make profit for years! - That's because a huge proportion of their usage is not monetized at all, despite the usage pattern being ideal for it. OpenAI reportedly made a loss of $5B in 2024. They also reportedly have 500M MAUs. To reach break-even, they'd just need to monetize (e.g. with ads) those free users for an average of $10/year, or $1/month. A $1 ARPU for a service like this would be pitifully low.

If the reported numbers are true, OpenAI doesn't actually have high costs for a consumer service that popular, which is what you'd expect to see if the high cost of inference was the problem. They just have a very low per-user revenue, by choice.

Why does this matter?

it is interesting how many people have built their mental model for the near future on a premise that was true for only a brief moment. Some things that will come as a surprise to them even assuming all progress stops right now:

There's an argument advanced by some people about how low prices mean it'll be impossible for AI companies to ever recoup model training costs. The thinking seems to be that it's just the prices that have been going down, but not the costs, and the low prices must be an unprofitable race to the bottom for what little demand there is. What's happening and will continue to happen instead is that as costs go down, the prices go down too, and demand increases as new uses become viable. For an example, look at the OpenRouter API traffic volumes, both in aggregate and in the relative share of cheaper models. […]

This completely wrecks Ed Zitron's gleefully, smugly wrong Hater's Guide to the AI Bubble. Not because AI isn't a bubble, but more because it isn't remotely a bubble in the way he seems to think.

There seems to be this reactionary rejection of free software itself on the software-aware left because many of its proponents have historically been bigoted pigs and shortsighted people of privilege (if very smart and ethical in one very small area). This is very stupid:

• The examples they provide of why free software "looks like shit and runs like ass" to end-users are cherrypicked and meaningless.
• The alternatives they propose (usually piracy) cannot actually produce anything, and thus are not an actually-workable ideology unto themselves.
• They keep saying that most free software isn't useful to end users, only to "nerds," but making those nerds' lives easier makes the production of ethical software for you easier.
• It is impossible for ethical software to be anything other than free software, because otherwise there is no accountability and no free association.

Many valid criticisms of this essay have been made over the years. 25% of your codebase being macros is terrifying. Language power is not a single dimention, but multiple, and Lisp is extremely powerful, but not the most powerful language. But despite these criticisms, I think the point of the essay does still stand: macros are extremely useful when you need them, that's pretty manifest from the amount of compiler plugins and codegen Java libraries like Jackson do, which is just a worse and more brittle form of macros; language power may have multiple dimensions, but some languages are just still more powerful across the board, or in sum, or on average, than others (think of a spider graph of language power); Lisp is probably one of the most powerful, considering it can even nearly seamlessly encompass Haskell and APL using macros. There are also responses to some of these critiques: for instance, maybe 25% of Viaweb's final generated codebase was the generated content of macros – indicating how much time was saved, not how often they were used strictly speaking – instead of 25% of its pre-compilation codebase being macro definitions, for example.

I'm not a fan of Erik Naggum as a whole – his prideful nigh-abusive holier-than-thou attitude and legendary flames probably significantly contributed to the death of the Common Lisp community in the 2000s to some significant degree. However, this is a classic essay. Naggum covers a lot of points, but among them:

• modern computer systems, both for users and for programmers, are so lacking meaningful automation (macros, an efficient, readable, comprehensible, reliable, and interactive way to compose applications that have to work with something more than plain text (and no, UNIX pipes are not interactive)), so full of drudgery and menial work, that we seem to have forgotten that the point of computers is to automate away tasks, instead of "perform menial tasks by mouse instead of lever."
• Because the bedrock abstractions of *nix and Windows are bad, new leaky abstractions have had to be piled up on top of them to make them do the things we need to them to do, and this has made them extremely unreliable and complex.
• The fast-paced, competitive mindset of the modern tech industry is a distortion in thinking: just because something isn't always changing doesn't mean it's dead.

A fun little historical paper documenting one perspective of how Common Lisp got standardized. I really like the focus on how human factors influenced the direction and completion of the project, not just technical ones.

As someone who's deeply interested in digital privacy and security rights, and deeply opposed to government surveilance and legibility, this was an inspiring book when I read it. It's been many years though and I'm not sure how it holds up. Hopefully well.

Written by the inventor of the concept of hypertext and the creator of Project Xanadu, this is a manifesto for personal computers, specifically personal computers as intelligence augmentation machines and machines for creative, associative thinking and exploration, by an outsider to the world of technology. I'm extremely interested to read it, although it'll be annoying since the only way to get a big enough screen for it to be readable is to read it at my desktop.

This essay is an impassioned, and historically-informed, plea for the return of computer software and hardware that is designed for professionals, or at least people willing to spend the time to learn it – things that are willing to sacrifice some short-term ease of use in favor of efficiency, power, and elegance. For those who are willing to delay gratification and invest the time to learn such tools, the payoff is immense – are skilled people willing to learn and co-evolve with their tools not also worth thinking about, just as much as the average unskilled person? And yet the software industry of today seems to only care about the latter, not the former – and not as a matter of profitability, either – proper professional markets are whales that can be deeply lucrative. There seems to be a moral objection to software tools that are designed squarely targeted at skilled people willing to invest time in them, and that's terribly sad.

This essay introduces an exceedingly useful framework through which to view computing environments that, ever since I've read it, I've used to think about the topic. The basic framework is that there are four different types of computing environment, each at a different level of abstraction and power for using, synthesizing, managing, and processing information, and generally we want to be climbing up the hierarchy. The hierarchy is:

Numeric Systems

systems designed entirely around numerical calculations, in a batch processed mode. Closest to what computing hardware actually does, and the earliest form of computing environment.

Application-Specific Systems

a computing environment that may do other things than numerical calculations, and may be slightly more interactive as well, but is still designed to do one specific task and nothing else.

Application-Centric Systems

computing environments that essentially operate as a framing device for multiple application-specific systems, one at a time or next to each other, but with little fluidity or even direct communication between them. This is the modern desktop operating system paradigm.

Information-Centric Systems

all of the information or content relevent to a task is in one place, displayed at once, with the tools needed to display or manipulate the varying kinds of information embedded into that common interface. Think Emacs, Acme, or Jupyter Notebooks. But the information centric computing environment is usually still relatively task-specific, even if it's a broad notion of task, and sits on top of something else.

Application-Less Systems

a version of an information-centric system where the information for all possible tasks, including operating system manipulation, is in one unified interface, fluidly communicating and combined.

This is the essay that started it all – the one that introduced the concept of hypertext for the first time. Interestingly, its concept of hypertext, which structures documents as a linked list like structure of small sections of content addressed by globally unique identifiers, which could be linked directly to from any other document, or anywhere else inside the document, and which included the concept of transclusion (that is, directly including another document's content into the current document, instead of just linking to it) is both more powerful than our modern notion of hypertext (where anchors and iframes are clunky, manual reinventions of the same ideas), and much more similar to how an org-mode document is structured, at least how I use it!

I haven't actually had a chance to read this essay, only listen to the summary given in the Advent of Computing podcast episode on Project Xanadu, and I'm very intrigued to read more!

A beautiful, funny, bouncy, entertaining, refreshing ode to free access, free information, and against intellectual property, gatekeepers, and all the apparatus that holds it still that capitalistm births, as well as a precient discussion of attention in the cyberspace age.

Richard Stallman the man is… far from perfect (links in order of massively descending severity), but his history as a champion of free software that isn't willing to sell out to corporate interests, and much of the software he created and improved, are very important, so this book seems well worth reading. Hopefully it will paint a complex picture, instead of being a hagiography.

This essay piggy-backs well on the back of Hackers the book, providing an in-depth explanation of the mindset a hacker takes toward their code – that it can be art in the same way painting can be, a thing of beauty and a means of self expression.

Out of all the books I've read, this one has had one of the largest and most lasting impacts, changing how I view my primary career and hobby, and who I want to be. Yes, the hackers were imperfect – sexist, gross, often somewhat myopic – but their ethos as explained by Stephen Levy, their passion, it's so much of what I want to be. And I think stealing and imitating the good of the past, and discarding the bad, is the best thing we can do. This book is also just entertaining and fun to read, and will teach you a lot about computer history, so it's worth it. I'm still obsessed with the MIT AI Lab to this day.

This guide is pretty much as true today as it was when it was written (probably because it has been updated over time), both in its technical guidance and its explication of the hacker ethos as it applies to programming. Since I'm a hacker, and I think welcoming more people into the fold, it's well worth putting here.

This is along, informal, somewhat rambling essay, but as someone who is a software developer as well, and is looking to get into the software industry in order to make enough money to survive, but is wholly opposed to the culture growing like a cancer there among "tech bros," this definitely speaks to my feelings deeply. It's perhaps a better statement of them than I could've made.

This is mostly of historical interest.

Despite being a relatively innocuous personal account, I find myself thinking about this often. The idea that computers should be bicycles for the mind, taken seriously instead of just as a marketing slogan.

A really profound talk with two parts: a philosophical one and a technical one.

I'm not sure I agree with the philosophical point, that choosing one purpose to staunchly follow for the rest of your days, to become a true believer in, is the way to a good life – that seems like a fixed idea, and the route to ego death if the idea turns out to be wrong or you change or the world changes around you – but certainly pursuing things you feel passionate about while you are passionate about them, focusing on that passion and even reinforcing it, making strong decisions based on it (and that can last a lifetime) is a great way to live. It's how I try to.

However, the technical part – demonstrating what a truly interactive software system looks like and why it's valuable, is amazing, and really blends well with the Hackers and Painters ideas.

Xah Lee is wrong about as often as he's right, but when he's right he's right. Languages that focus on meaningful practicality within their domains are better than languages that get preoccupied with their own beauty – better culturally, and more useful.

This is perhaps the most thorough outline in a single place of how modern operating system design, even at the level of things we consider foundational, such as processes, hierarchical filesystems, kernels, monolithic applications, and the distinction between memory and storage, are all arbitrary and suboptimal accidents of history that can be replaced with superior – more flexible, more powerful, and even more secure, through the use of operating system level object capability based security. It then describes the properties that a Lisp OS should have. Useful to read in conjunction with UNIX, Lisp Machines, Emacs, and the Four User Freedoms and my descriptions (one, two) of an ideal operating system, and things like Genera Concepts and Symbolics Technical Summary.

Maximalist computing is designing protocols and platforms which support doing "everything", and in a pleasant manner. It is, in one way, an extension of the idea of computing, which is to simulate anything; there are many situations in which universal simulation can enhance a platform.

It is not necessarily opposed to minimalism, but it is certainly at odds with kinds of reductive minimalism; that which simplifies protocols by forcing the simplification of use-cases.

A very interesting oral history from RMS, about exactly what it says. Has a somewhat distorted view of the reasons things happened but as a look at what RMS thinks happened, and thus what motivated Emacs and GNU, it's great.

Forget all the tedious arguments about whether Lisp macros are maintainable compared to languages that are more limited in their ability to program themselves. The entire point of computers is to automate the manipulation of information. If we're not using computers to do that as much and as efficiently as possible, so that our minds are free to do the most interesting parts of that, we're simply using computers wrong.

A concise, cogent list of the principles that any personal computing environment should obey. I deeply agree with these principles, but perhaps they should be viewed as ideals to strive for, not as total prerequisites, for acheivability reasons.

Laws:

• Obeys the operator
• Forgives mistakes
• Retains knowledge
• Preserves meaning
• Survives disruption
• Reveals purpose
• Serves loyally

An extremely funny, entertaining, well-argued, and interesting talk with a ton of historical and contemporary references that are really worth exploring – you could spend days just investigating all the links it makes – that talks about just how limited, clunky, out-dated, and counterproductive the way we program is, how we've somehow discarded all the amazing ideas and advancements that were made historically away from the batch-processed model of computing and just kept going with it, long past its sell-by date. But it doesn't just complain about our path-dependency: it gives rich historical and modern examples of alternative ways of doing programming. This is extremely influential on my notions of how programming should be done ideally, next to Inventing on Principle.

A rare, curated, one-of-a-kind collection of information and resources about the utlimate Lisp Machine OS, Symbolics Genera. The lost Atlantis of operating systems! Some good places to start with this are:

Taste, bought through experience and care for your craft, is important for programming – the massive amount of complexity, unknown unknowns, and the need to interface with the complex, fuzzy, and shifting world make absolute, rote methods impossible, and taste can be a good guiding heuristic the help us get to where we need to go, like in physics and mathematics. However, what does good taste mean? This essay has excellent guidance for us, pulled from the worlds of art, mathematics, engineering, and programming itself:

• Good design is simple
• Good design is timeless
• Good design is suggestive
• Good design is often slightly funny
• Good design is hard
• Good design looks easy
• Good design is redesign
• Good design is often strange
• Good design is often daring

A great takedown of the tendency of many hackers to frame themselves as "apolitical" in Xah Lee's usual inflammatory and sketchy style.

• Self-consciously rigid, minimalist software and software protocols tend to force more complexity into things around them – for instance, more complexity is needed to implement them to get around their limitations.
• Such software is often not responseive to human needs such as:
  • self-expression
  • accessibility
• As a result, what we need is minimal but extremely flexible software that can be built into something non-minimal. Like Smalltalk systems.

In this essay RPG compares the act of writing to the act of programming – how both are a dual process of discovery and refinement, deeply intertwined, as discovery must be refined, but the refinement of what has been discovered prompts new discoveries and insights that start the whole process over again. How systems are shaped not just by up front design and requirements (external) but also by internal forces, tensions, "triggers" of new ideas, possibilities, or problems. He makes the argument that programming languages, which are oriented around static thinking enforcing up-front specification of everything, rigid consistency requirements, and making code difficult to change dynamically, aren't suited to such an intertwined task of iterative discovery and refinement. At best, they're suited to a final version of a program, not a first version. See also, my arguments against formal methods and overly strong static type systems, Notes on Postmodern Programming, Hackers and Painters, and some other things I'm probably forgetting.

A sympathetic, but critical, portrait of a certain type of anti-social, cynical, intelligent, yet often distracted and unable to complete things, individual, which is often attracted to Lisp, because of its ability to allow single isolated individuals to be extremely productive by themselves, and its ability to be molded into the shape of the mind of the person using it, instead of them having to compromise and bend their mind to it.

I reread this essay often because I strongly see myself in it – even in the ultimate fate it describes, and I have complex feelings about that. I like who I am. My anti-social nature, my individualism, my ambitious but never-finished projects. I don't even mind that I may not ever work in the software industry – for someone who loves hacking as much as I do, perhaps that's for the best. But it's useful to remember that this isn't the most productive outcome either. Something like the Cult of Done manifesto may help me to at least finish more things.

As a general critique of the Lisp community, the thing is that this sort of issue can – as I intend to do – be corrected for, and modern Common Lispers actually seem very good about trying to work together and build useful libraries for others and so on.

Eric S. Raymond's essays before his Hoppean turn are quite excellent in many ways. Erudite, playful, widely-read, and unusual examinations of hacker and open source culture often laced with references to anarchist ideas and works and immersed in that lens. The bazaar, like Mob Software, is a utopian vision, but I think one worth aspiring to.

If you are a creater or a maker and your craft is your lifeblood, but you struggle to actually do it just the same, this is an excellent manifesto to keep in mind at all times to keep in your heart at all times.

"A cyberspace well of files, related to those aspects of being, formed by (post)modern life and culture."

An absolute fucking beautiful treasure trove of carefully curated, found, and organized texts from the era of the 2000s cyberpunk culture and the things that influenced it. Much of this is impossible to find anywhere but the place this is a mirror of, which is why I'm carefully and lovingly trying to keep a copy safe.

The Cyberpunk Project hosts a few texts that have been extremely influential on me:

This is the closest thing you'll find to an ethnography of the hacker culture and community as a whole, as well as a treasure trove dictionary of funny terms with curious historical baggage. I want to incorporate more of these terms into my language.

A short, punchy, and funny, but nevertheless somewhat insightful takedown of the UNIX Philosophy. Again, from Xah Lee, so take witha massive grain of salt.

Short, punchy, clear, envigorating, a call to action – all that a manifesto should be. And it very much aligns with my own commitment to repair being for individualist reasons.

A short essay explaining a form of organizing that is beyond mere decentralization, that is completely individual and distributed, yet still coordinates to get things done – the ultimate holy grail for individualist anachists. Talks about examples in nature, and in our society (has some overlap with The Cathedral and the Bazaar, but from the other side of the glass so to speak).

Not only is this an incredibly well-written, lyrical, and erudite paper written about a fascinating transition point in the history of programming, but it articulates a fundamental rift between how modern programming language theory (and computer science in general) views programming languages and tools, and how actual working programmers and system builders view them, a rift which I think articulates well the utter dissapointing lack I see in computer science as a whole.

A hilariously funny book with many accurate and trenchant criticisms of UNIX that still hold true today, and many silly, off the mark, or outdated ones, all presented in a hypertext form that's so strange it reaches performance art.

For all of their faults, Richard Stallman and the Free Software foundation fight for a cause that I believe is deeply just. Free (libre) software is the only software that can truly adhere to the essence and spirit of the core tenets of the programmer code of ethics that I believe in.

The core of free software is contained in the famous four freedoms:

• The freedom to run the program as you wish, for any purpose (freedom 0).
• The freedom to study how the program works, and change it so it does your computing as you wish (freedom 1). Access to the source code is a precondition for this.
• The freedom to redistribute copies so you can help others (freedom 2).
• The freedom to distribute copies of your modified versions to others (freedom 3). By doing this you can give the whole community a chance to benefit from your changes. Access to the source code is a precondition for this.

As to their faults: while I applaud RMS for his technical abilities and staunch, unwavering support of his ideals, he has many other ideas (and behaviors) that are outright gross and unethical, and many others that just make him a bad spokesperson and figurehead for a movement. His conception of freedom is also somewhat compromised, in that he seems to think that restricting the freedom of users to use proprietary software or hardware, should they choose to do so, by making it more inconvenient, is somehow protecting their freedom – when in reality, freedom includes the freedom to fuck up or do suboptimal things if you have to, and taking such a hardline stance just makes operating systems that take free software principles harder (or impossible) to access and use for many people. He also has weird and arbitrary lines, such as thinking shoving proprietary code into firmware on secondary chips is better than it being at least a blob you can swap out attached to your main operating system. He also has paranoid ideas about the consequences of doing certain things, like opening up GCC so it can be used as a language server risking "companies building proprietary front ends to it," which they wouldn't do – they'd just use clang.

Likewise, at this point, the FSF is an impotent personality cult that cannot meaningfully reach out and address most people where they're at, and doesn't even use its funding to fund development of things like the GNU project, just largely ineffective activism. They also have a tendency to be extremely myopic and "apolitical" in a way that just further excludes diverse people.

But nevertheless, their ideals are good.

Many people over many decades have speculated as to what's "wrong" with Lisp, such that it hasn't reached widespread industry adoption despite its many technical merits. Most of them are superficial, ahistorical, and anti-intellectual. This article explains concisely why: that Lisp, being very different from the mainstream (but, to add my own component to the analysis, in a way that is not governed by a modernist narrative like languages such as Haskell), attracts people who want to justify their desire not to have to bother to learn it, who come up with post-hoc justifications for that framed as criticisms of the language, to shift the blame. This creates a mythology of Lisp being bad that scares people away. This, combined with TBLP phenomenon, seems accurate to me.

I hate Yarvin and everything he stands for. However, I agree with the thesis of this essay, and think this is probably one of the best statements of that thesis I've seen. Plus it's well-written and funny as hell.

His thesis is essentially that CS research spends all its time on naval gazing about type systems, mathematical formalisms, abstract algorithms, and non-interactive batch programs like compilers, as opposed to interesting and creative programming, analyzing things like programming languages as complete systems including what they're like to use, doing empirical work with programmers, etc, because mathematical formalism is an easy way to generate infinite work that looks "hard" in a way interesting creative programming doesn't. Essentially, similar critiques to Richard P. Gabriel's paper and part of the feminism in PLT paper.

It does, however, have very serious problems as an argument for the thesis, which are indicitive I believe of the wider problems with Yarvin's reasoning in his other work. In this sense, the primary interest of this article was that it was a very interesting test-case for understanding this "philosopher" who is now the power behind the throne, in some ways, in the US: the article is about a field I know some amount about, so I wasn't likely to suffer from Gell-Mann amnesia and just believe him, but on the other hand, he's arguing for a thesis I actually agree with, so I'm not likely to apply overmuch scrutiny or dismiss what he's saying out of hand, as I might be accused of doing for his more outright evil theses.

What I learned is that, tldr, he's a very good writer, and very good at researching and marshalling many erudite minutiae to his aims, but that does not a good argument make – it just makes him seem very smart.

The general problems I saw with this essay qua argument were:

• Circular reasoning to ensure there is no nuance in his analysis (the Guy Steele thing).
• Totally unevidenced and kind of weird typologies used to structure his whole point.
• A ton of very erudite and detailed and obscure examples but not high level data to draw general conclusions with.
• Very strained shift to a foregone conclusion (acadamia bad) that isn't justified by his criticisms (all organizations could fall into these problems, not just public ones, and many of the best think tanks doing amazing creative programming were in acadamia, such as the MIT AI Lab).
• Very funny, very well-written, very well-spoken, but as shown by the previous points, not really with that much underneath.

Looking at the problem discussed in The Bipolar Lisp Programmer from another angle: that the individualism, and invidual productivity, of Lisp is good, and it is the incentives of corporations, who want programmers who are individually easier to replace or do without, and individually less productive and influential, so less risk is invested into them, they're cheaper, and easier to keep in line with the proper workings of the system, that makes the sort of people Lisp enables unable to find jobs.

The UNIX philosophy has reached the level of a religion in open source circles, so that when violations of it occur, they are viewed as sins to be eradicated, not as having real technical reasons. This article outlines one of those solid technical reasons.

A very good explanation of why we can't just layer shoddy half-implementations of better things on top of old bullshit and expect to eventually reach what we could have reached had we started with better foundations. A direct response to 'Worse is Better' and the idea that "the good news is that in 1995 we will have a good operating system and programming language; the bad news is that they will be Unix and C++."

A bedrock abstraction is an abstraction past which no recoverable error can happen – when a system breaks, it will always break down into whatever component parts are its bedrock abstraction, so they can be reassembled, and if it breaks past that, it just needs to be replaced wholesale.

The key idea of this blog post is that the bedrock abstractions we've chosen for modern-day computers, thanks to what's convenient to design and manufacture, and the fact that they're descendant from the systemically underpowered and designed-to-be-cheap original microcomputers, is insufficiently powerful, because it means that when software systems break or need to be modified, you're often dumped down to a level that's just too low to be useful to a human being – we need to raise the level of our bedrock abstractions to a point where we don't need to be afraid of them anymore.

"The basic idea is that the things that we do together with others do not simply add up, but that specialization and association bring about the formation of unity-collectivities, social beings with qualities, strengths and perhaps even ideas that arise from the combination and unification of the constituent beings."

Perhaps the most useful conceptual tool from Proudhon by way of Shawn that I've seen, besides the anarchic encounter.

This is a really excellent lecture by Sartre, giving a basic account of what existentialism is. Although I'm an amoralist, and as such don't agree with everything it says, it is an eloquent expression of many ideas also to be found in the likes of Stirner, except stated in a more comprehensible (to most people) way. I'm even sympathetic to what he has to say about morality – it's worth thinking about, and may inform your own nihilist ethics.

Fiery, provocative, dense, sometimes somewhat difficult to read, but also an intelligent, clear-sighted, and funny, and nuanced critique of the common idea of the Christian God from Proudhon. I really enjoy reading this every so often.

:ID: 64e23274-63b1-44d6-839a-2706ca491f9f

The best exposition in one place I've found of how to actually go about defending your community with arms that wouldn't just lead to a militia or something. Worth reading for all anarchists.

A classic anarchist text that I really need to read soon considering I'm surrounded by damned Marxists.

A thorough – and humerous! – takedown of any possible authority one might consider the Constitution of the United States to have, assuming only that one believes that the majority does not have an automatic and inherent right to dominate the individual, and that one should only be bound by a contract one agrees to.

Two more excellent conceptual tools that I make use of often, although often not with those exact terms, explored by Shawn. I initially picked up these ideas from other scattered bits in other essays of his, but this glossary entry really brings it together well, after having read through it, as long as you're willing to carefully read every line (it's densely packed with ideas).

Most manuals on how to take direct actions like sabotage suggest things that are actively dangerous, either to the person doing it, or the innocent people around, or both, and/or can have very serious lasting consequences if you're detected. Many are also of doubtful efficacy, no matter how satisfying they may be (such as Molotoving some Starbucks or Walmart somewhere, or setting a few cop cars on fire). All of these have their place in a complete, well rounded diversity of tactics – even the ones that are only of propagandistic or symbolic value – but for most people, who have lives to lose and are generally risk averse (this, unfortunately, includes me, despite my love for Novatore), those manuals aren't particularly useful, except as a sort of performance art in the reading.

This book, however, provides a simple, easy to practice, manual for sabotaging the processes of bureaucracies of various sorts, if you believe that they're up to no good – for instance, if you're part of an arm of a corporation or state that's doing something bad, or an average citizen being roped into e.g. tracking down a criminal – without jeopardizing yourself in any significant way. These methods, while simple and easy, are also relatively effective due to the way hierarchical systems and bureaucracies work.

The classic section:

(11) General Interference with Organizations and Production

(a) Organizations and Conferences (1) Insist on doing everything through “channels.” Never permit short-cuts to be taken in order to expedite decisions.

(2) Make “speeches.” Talk as frequently as possible and at great length. Illustrate your “points” by long anecdotes and accounts of personal experiences. Never hesitate to make a few appropriate “patriotic” comments.

(3) When possible, refer all matters to committees, for “further study and consideration.” Attempt to make the committees as large as possible—never less than five.

(4) Bring up irrelevant issues as frequently as possible.

(5) Haggle over precise wordings of communications, minutes, resolutions.

(6) Refer back to matters decided upon at the last meeting and attempt to re-open the question of the advisability of that decision.

(7) Advocate “caution.” Be “reasonable” and urge your fellow-conferees to be “reasonable” and avoid haste which might result in embarrassments or difficulties later on.

(8) Be worried about the propriety of any decision—raise the question of whether such action as is contemplated lies within the jurisdiction of the group or whether it might conflict with the policy of some higher echelon.

(b) Managers and Supervisors

(1) Demand written orders.

(2) “Misunderstand” orders. Ask endless questions or engage in long correspondence about such orders. Quibble over them when you can.

(3) Do everything possible to delay the delivery of orders. Even though parts of an order may be ready beforehand, don’t deliver it until it is completely ready.

(4) Don’t order new working materials until your current stocks have been virtually exhausted, so that the slightest delay in filling your order will mean a shutdown.

(5) Order high-quality materials which are hard to get. If you don’t get them argue about it. Warn that inferior materials will mean inferior work.

(6) In making work assignments, always sign out the unimportant jobs first. See that the important jobs are assigned to inefficient workers of poor machines.

(7) Insist on perfect work in relatively unimportant products; send back for refinishing those which have the least flaw. Approve other defective parts whose flaws are not visible to the naked eye.

(8) Make mistakes in routing so that parts and materials will be sent to the wrong place in the plant.

(9) When training new workers, give incomplete or misleading instructions.

(10) To lower morale and with it, production, be pleasant to inefficient workers; give them undeserved promotions. Discriminate against efficient workers; complain unjustly about their work.

(11) Hold conferences when there is more critical work to be done.

(12) Multiply paper work in plausible ways.

Start duplicate files.

(13) Multiply the procedures and clearances involved in issuing instructions, pay checks, and so on. See that three people have to approve everything where one would do.

(14) Apply all regulations to the last letter.

In this essay Shawn expands on the notion of the anarchic encounter to talk about its possibilities – what can be born out of it. It's interesting and inspiring.

Shawn's explications of Proudhonian anarchist/libertarian socialist theory are always deeply interesting and enlightening, providing me with new concepts in my intellectual toolkit. His work on the anarchic encounter, a sort of Crusoe-economics look at the ideal anarchistic social relations that can be used to guide our practical interactions and organization, but also our conceptions of justice, is some of the most enlightening. In this essay, he introduces that concept.

There is perhaps no writer that has influenced me more than the philosopher-poet and Nietzschean/Stirnerian hybrid anarchist Novatore. His writings have a wonderful vitality and strength and life and individuality to them, and a really fun need to strike back with poetic, beautiful, yet vicious anger at the fascists, unconscious egoists and communitarians that would drag us all down. I've read a lot of these, but not all, and I really should reread them. The ones I've read and really liked are:

• Black Flags
• Cry of Rebellion
• Intellectual Vagabonds
• Toward the Creative Nothing
• Anarchist Individualism in the Social Revolution
• My Iconoclastic Individualism
• I Am Also A Nihilist

A quote from Black Flags that seems relevant in our times:

Our time — despite empty and contrary appearances — is already lying on all fours under the heavy wheels of a new History.

The bestial morality of our bastard christian-liberal-bourgeois-plebeian civilization turns toward the sunset…

Our false social organization is collapsing fatally — inexorably!

The fascist phenomenon is the surest, most indisputable proof of it.

In Italy as elsewhere…

To show it, one would only have to go back in time and question history. But even this isn’t necessary! — The present speaks eloquently enough…

Fascism is nothing but a cruel, convulsive spasm of a decaying society that tragically drowns in the quagmire of its lies.

Because it — fascism — indeed celebrates its bacchanals with flaming pyres and malicious orgies of blood; but the dull crackling of its livid fires doesn’t give off a single spark of vivid innovative spirituality; meanwhile, may the blood that pours out be transformed into wine, that we — the forerunners of the time — silently gather in red goblets of hatred setting it aside as the heroic beverage to pass on to the children of the night and of sorrow in the fatal communion of great revolt.

We will take these brothers of ours by the hand to march together and climb together toward new spiritual dawns, toward new auroras of life, toward new conquests of thought, toward new feasts of light; new solar noons.

Because we are lovers of liberating struggle.

We are the children of sorrow that rises and thought that creates.

We are restless vagabonds.

The boldest in every endeavor; the tempter of every ordeal.

And life is an “ordeal”! A torment! A tragic flight. — A fleeting moment!

A very useful short essay outlining the ways in which the academy can be useful to anarchist causes, is praiseworthy, can offer things to imitate to us, and also the ways in which it is structurally contrary to anarchism, can hurt our causes, and is deeply flawed and problematic, and how someone who wants to be an anarchist academic, instead of an academic anarchist, might navigate those issues. This is an essay that hits close to home as someone who was forced to drop out of university a year before finishing my Bachelor's due to disability, and has serious problems with the academy and the culture and tendencies of those who stay there a long time, but also sees the ways in which it's really useful and good too.

• Law is inherently indeterminate:
  • It contains a large amount of diametrically contradicting decisions, cases, precedent, and rules, and anything can be logically derived from conflicting premises
  • There is no such thing as language that does not admit of interpretation and reinterpretation, and thus even clearly written law texts can really be understood to mean anything
• As a result, a legal argument can be found for any conclusion, and any conclusion is pretty much as valid as any other, even if they're diametrically opposed. What the law "means," and thus how it is interpreted, argued, and enforced, is totally up to the moral and political beliefs of the individuals doing it.
• Moreover, law is always, universally produced by political actors, who will encode their values into it.
• The apperance of the stability in meaning of the law is merely a product of the stability in the values of those who interpret it, due to social selection processes and indoctrination, and the "meaning" of the law can be seen to change as who interprets it changes.
• Furthermore, law cannot be anything but indeterminate, because if it was completely rigid, absolute, and clear – assuming for a moment such a thing were even possible, which it isn't – then, while it would be able to mete our order, it wouldn't be able to mete out justice, because it wouldn't be able to take into account context, individual cases, and complex human values.
• Law cannot be anything but indeterminate, also, because it is a monopoly product, produced by the state and provided one-size-fits-all for everyone, so it has to be flexible enough to make that at least a little feasible. (This rather nicely and summarily puts to bed Rothbard's project in The Ethics of Liberty)
• Most Americans are clearly both aware that there is no such thing as the "rule of law, not people" in how they jockey for control of law, but at the same time seem to believe in it. This cognitive dissonance is because the myth of the rule of law is otherwise emotionally useful. Namely, because it naturalizes law, as being neutral, objective encodings of justice, and thus part of the natural social order, which:
  • allows people deniability when they enforce their values, or the dominant social values they don't want to have to stand against, on others
  • enables people to view their moral positions, as filtered through their construction of the meaning of the law, as neutral, objective, and necessary, and their oponents' interpretations as biased and politically-motivated
• Americans also subscribe to this idea because it has been indoctrinated into them by the state. It is convenient for the state for people to believe in the rule of law because then people are more willing to submit themselves to it, and make others submit to it.
• If we stop viewing law as something that must be supplied centrally, we can avoid the problem of one-size-fits-all law, and difficult to interpret law, and power structures around law.

Classic quote from this work:

When not a hundred, not a thousand men, but a hundred provinces, a thousand cities, a million men, refuse to assail a single man from whom the kindest treatment received is the infliction of serfdom and slavery, what shall we call that? Is it cowardice? Of course there is in every vice inevitably some limit beyond which one cannot go. Two, possibly ten, may fear one; but when a thousand, a million men, a thousand cities, fail to protect themselves against the domination of one man, this cannot be called cowardly, for cowardice does not sink to such a depth, any more than valor can be termed the effort of one individual to scale a fortress, to attack an army, or to conquer a kingdom. What monstrous vice, then, is this which does not even deserve to be called cowardice, a vice for which no term can be found vile enough, which nature herself disavows and our tongues refuse to name?

[…]

Poor, wretched, and stupid peoples, nations determined on your own misfortune and blind to your own good! You let yourselves be deprived before your own eyes of the best part of your revenues; your fields are plundered, your homes robbed, your family heirlooms taken away. You live in such a way that you cannot claim a single thing as your own; and it would seem that you consider yourselves lucky to be loaned your property, your families, and your very lives.

All this havoc, this misfortune, this ruin, descends upon you not from alien foes, but from the one enemy whom you yourselves render as powerful as he is, for whom you go bravely to war, for whose greatness you do not refuse to offer your own bodies unto death. He who thus domineers over you has only two eyes, only two hands, only one body, no more than is possessed by the least man among the infinite numbers dwelling in your cities; he has indeed nothing more than the power that you confer upon him to destroy you.

Where has he acquired enough eyes to spy upon you if you do not provide them yourselves? How can he have so many arms to beat you with if he does not borrow them from you? The feet that trample down your cities, where does he get them if they are not your own? How does he have any power over you except through you? How would he dare assail you if he had not cooperation from you? What could he do to you if you yourselves did not connive with the thief who plunders you, if you were not accomplices of the murderer who kills you, if you were not traitors to yourselves?

You sow your crops in order that he may ravage them; you install and furnish your homes to give him goods to pillage; you rear your daughters that he may gratify his lust; you bring up your children in order that he may confer upon them the greatest privilege he knows — to be led into his battles, to be delivered to butchery, to be made the servants of his greed and the instruments of his vengeance; you yield your bodies unto hard labor in order that he may indulge in his delights and wallow in his filthy pleasures; you weaken yourselves in order to make him the stronger and the mightier to hold you in check. From all these indignities, such as the very beasts of the field would not endure, you can deliver yourselves if you try, not by taking action, but merely by willing to be free.

Resolve to serve no more, and you are at once freed. I do not ask that you place hands upon the tyrant to topple him over, but simply that you support him no longer; then you will behold him, like a great Colossus whose pedestal has been pulled away, fall of his own weight and break into pieces.

This is a very old essay – written in 1577 – but the bulk of it is still as relevant as it was back then. The core points are these:

• Tyrants/rulers always hold sway over a group far vaster than them, such that they could never hope to actually enforce their will over those they wish to dominate if those people simply ignored their authority and refused to obey. (Part I)
• So how do tyrants hold sway over the populace that they could not otherwise control?
  1. People have a tendency to ideologically naturalize what is now as what has always been, and what must necessarily be, so people are passive and apathetic.
  2. People tend to follow tradition, so once more than a generation has passed since rule was instituted, most go along with it by default.
  3. Human beings adapt to, are shaped and molded by, the conditions under which they grow up; when one grows up under tyranny, one becomes so moulded by it that resistence to it is nearly impossible, not least because one doesn't know what liberty was like, and so doesn't know what they're missing out on well enough to fight tooth and nail for it.
  4. Nobody knows anyone else is discontented, or if they know that, how truly committed they are (because you'd have to know someone's heart of hearts to know that), so we're all locked in – although he didn't put it in these terms – a Prisoner's Dilemma, unable to do anything because we think we're alone.
  5. Through the classic bread and circuses which distract us from their tyranny, and make us feel as though they're generous even when the wealth they're sharing with us is stolen from us in the first place.
  6. Through intimidation of the few people who manage to overcome the former points and resist.
• And how does the tyrant get people who are willing to enforce its will? Merely by promising them a share in the spoils, and to abuse people in turn just as they are abused. For some, that is enough.
• However, aligning yourself with tyrants is always a dangerous game, since they're basically inherently unaccountable, being at the top of a hierarchy.

A classic text of political philosophy using one of my favorite ideas (the idea of family resemblance). All the more relevant in the modern day.

A classic essay responding to a common question about anarchism. I really like this one. Very useful to send to skeptical people!

I had to painstakingly convert this from a two-column PDF so that I can more easily read it in more places, instead of just on my ereader or at my desk. I hope anyone who finds this appreciates the effort, it took fucking forever.

In any case, despite what might for some be an inflammatory title – even as a leftist and a woman I recoiled a bit, wondering how feminism could possibly be applied to programming language design – this is a really excellent paper. It goes into detail about all the shortcomings of the PLT community with respect to studying the practical and human aspects of programming language design, and the cultural factors that exclude those who want to do it, as well as just exclude people in general. Well worth a read.

This is not just an incredibly complete and excellent set of resources to get started with Common Lisp, literally enough to get anyone completely off the ground, but it's also a really good articulation of some of the reasons that Common Lisp is attractive even today (although I have my own list).

Despite not quite being accurate to ANSI Common Lisp, I still find CLTL2 an invaliable reference for Common Lisp. It's much more comprehensible than the HyperSpec, while still being much more complete than any other book thanks to its position as an interim spec of sorts. Maybe someday I'll get around to editing my mirror to be up to date for ANSI.

A more thorough elucidation of something I've said a lot before about how the mindless dogmatic pursuit of simplicity in the places most visible to programmers just pushes the necessary complexity needed to actually map to the world or requirements somewhere else, usually into less visible places like people's heads or glue scripts. This is very important to understand: trying to artificially "cut the gordian knot" of complexity is a bad move, it's just putting the burden somewhere else, possibly somewhere worse. Correctness is actually more important than simplicity. A good comeback to the "worse is better" and "unix philosophy" mindsets.

Design by Contract seems like the perfect balance between high assurance/formal methods and comprehensibilty, expressiveness-to-complexity ratio, and practicality, for reason's I've discussed elsewhere. I haven't read this paper yet but I'm very interested in doing so.

I'm waring of Rich Hickey, since he really does seem to have built a cult of personality around him in the Clojure community, but he is extremely smart, incredibly articulate, and very pragmatic and wise, and this is one of my favorite talks by him. I love his combination of being intelligent and careful and a Right Thing thinker, but also deeply pragmatic – aware of the need of programs to change over time, to be embedded into, and composed out of, heterogenous and ever-changing systems, to be dynamic, and how programming ideas effect those things.

This essay by Kent Pitman defending design choices in ANSI Common Lisp with respect to equality operators and copying functions might seem of only historical interest – and it certainly is that, too – but it actually puts up a pretty good defense, in my opinion, of why those design choices were The Right Thing and even maybe hints that other languages should do something similar. It also gets at a very important point: that types are not actually very indicative of intent, just some sort of general operational compatibilty, without the introduction of copious newtypes at least, which has its own costs.

This essay proposes one core principle that could provide a solid foundation for a code of programmer ethics to grow around:

Programs must do always, and only, what the user asks them to do. Even if the programmers who made it consider that request to be unethical.

To justify the first clause, it outlines all the deep ways that people in the modern day trust and depend on our computers:

1. We are dependent on them, because we need them to almost everything these days, including things that are required of us by law – which is why having a smartphone is borderline a human right.
2. Even for things we don't need them to do, we trust them to act on our behalf, as user agents constantly, for things like communication, purchasing, remembering things for us, and more.
3. Throughout all of that, we entrust them with vital, sensitive, personal information about us, our lives, and our loved ones.

This means that in a world – such as the one we have now – where software does not serve users, life with computers would be one of unending paranoid, suspicion, confusion, frustration, betrayal, theft, and extortion for users. A world we do not want.

To justify the second sentence, the essay shows how if software developers attempted to enforce their own ideas about morality on the users of their software, this would only break that trust, because then sometimes the software will betray them, or not do what they want, but what someone else, with a possibly different moral code, would want. He talks about other professions that have codes of conduct where they pledge to serve those who come to them for succor regardless of their personal feelings regarding morality, such as doctors, lawyers, and priests, and why those codes are important.

I'd like to add two more reasons – somewhat hinted at in the essay – that software developers should not attempt to pass judgement as part of their software (as opposed to in their capacity as people) on the ethics of what people do with their software:

1. Surveillance: in order to know what your users are doing with your software in a way that's detailed and flexible enough to actually exclude unethical activities, you're probably going to need some kind of telemetry or at least storage of user activity. Moreover, many people believe their ethical obligations, when someone does something wrong, include publicly naming and shaming them, or reporting them to "the authorities," in which case actual surveillance is implied.
2. Power: normalizing this idea that software developers should have power over what users can and cannot do with their software gives software developers direct and intimate power to morally police users. I don't believe in moral relativism – I think that individuals should be able to react to other people's perceived immoralities as they see fit – but I am an act consequentialist and this is a level of power that seems wrong to me – like installing surveillance devices and electric collars on anyone so we can watch them for wrongdoing – because it involves more power over someone else than power over your own reaction to someone else: it extends further into their live and is more invasive. It is also much more centralized than just "social consequences." And if we normalize such power, those with insane codes of ethics, as well as those with decent ones, will use it to enforce their wills.

This is why I'm always somewhat disturbed by "FOSS" licenses that violate freedom 0 of the four software freedoms. Yes, they're usually a certain type of queer leftist I generally agree with on what applications of software are bad, and which are good. But this is not a rule that leads to the greatest individual autonomy compatible with the equal autonomy of all in the long run. It's just posturing.

This is an incredible, classic essay from the most famous ranter of programming rants ever to put finger to key. It is an incredible takedown of Java-style OOP that is both witty and also intellectually sound. And as a corollary I think it functions well as a takedown of any bondage and discipline language.

I've actually compiled several blog posts on the same subject by James Hauge, including the titular one, into one larger narrative, because they're all closely related and significantly enhance the discussion in the others, and really work well as a combined narrative.

What I took away from this article is mostly that there are certain problem domains where pure functional programming actually introduces greater complexity, brittleness, and overhead which can outweigh the benefits in terms of explicitness and the more powerful architectures that rely on referential transparency that it can enable, even though pure functional programming is very beneficial in most cases. Therefore, we should carefully and stingily, but occasionally on a case-by-case basis, apply non-pure functional programming techniques to those problems where it's more helpful than harmful.

My experience in almost everything I've written though is that Trying to go for even a basic level of Purity would lead to an insane architecture. Take, for example, an Entity Component System:

If I want to have a system that gets all of the entities with a given set of components makes modifications to one of those components based on the information from the other components, I can either:

1. Have a query function that goes through the entity system and returns tuples containing the applicable components for all of the entities that have the requested components, alongside the entity ID. This can be reused widely for other queries, and thus can be made very advanced, with negation, logical operators, backtracking, and so on. Then write a simple loop that goes through each of those and takes exclusive write access to the component it wants to modify and directly modifies it in place.
2. Map over the list of tuples returned by the query function above, and producing a tuple of the entity ID and the modified component, which then has to go into a separate function that iterates over the entire list of entities again, in order to produce a new list of entities where the things indicated to be modified by the change list produced by the previous map are replaced.
3. Iterate through the entire list of entities in the original map and produce the new list as you go, but then you can't reuse the entity selecting code, You have to do it all manually in the loop. So you end up duplicating code and it makes it difficult to have systems that operate on more interesting and complex selections that maybe do backtracking and such.

Even assuming a magical "sufficiently smart compiler" that can optimize away the copying implied by the latter two options, only the first option seems like a good option. The second introduces two separate loops to do the same thing, which both doubles how long it takes, and also just makes the code more complex and introduces more duplication. The third option is the worst of all, because while you get rid of the duplication of the loop, you can now no longer use the query system.

The other point I took from this article series is that there are certain types of violations of referential transparency that you can add that, although they may transitively infect a large portion of your code base, are small and simple enough that there isn't actually a significant cost to that. There is a difference between the net magnitude of the referential transparency violation's effects on your codebase, and just the scope of the things that are affected independent of how much they're really effected and how much it adds up. I think his example of a random number generator is a really good example of this. Literally almost every programming language except Haskell just allows you to directly get random numbers even if they are typically very purely functional (Erlang doesn't even let you modify things ever), and the reason for this is that if you use it in an inner place, yes it can sort of contaminate the rough, financial transparency of many other places in your code base and technically make their behavior non-deterministic as well. But since it's controlled by a seed and it's a very simple type of state in itself, that usually isn't actually a problem.

One thing that might help the predictability (for debugging) of functions that violate referential transparency by reading global state (so this only helps with one specific area, but yeah) may be the use of dynamic scope, so that you can treat global state as a variable you can pass in.

It could be argued that Haskell, too, has an escape hatch, with things like the State monad and IO monad, but there are two problems with this answer:

1. This is pulling a kindgdom of nouns: you've artificially restricted the set of things your programming language can do directly, so you're using the abstractions it can access to claw those things back. They might be more "first class" in the sense that, since these capabilities are now expressed in terms of other parts of the language, you can now talk about them as values in the language – and that's pretty cool! – but they're second-class in reality, because you've got to sit on top of a tower of type abstractions and syntactic sugar to use them, and those abstractions are leaky: if you mess them up, the program will fall apart into very different bedrock abstractions that are more difficult to reason about. Yeah yeah, monads aren't that hard once you grok them, "I don't truly understand pure functional programming," whatever – but an imperative program breaking down into a page of type theoretic abstractions because that's its bedrock abstraction is still a qualitatively different (and worse) experience than a simple error from a language that actually knows about imperative code.
2. These abstractions don't compose. There's no well-defined, consistent way to compose different monads, which means that it's very difficult to actually use them in more complicated situations where you may want more than one type of effect.
3. Worse, because there's no implementation aspect to a lot of basic monads, they're just empty type tags with certain actions written for them, the operations one might want to do are scattered between a lot of different monads, and also occasionally confusingly duplicated between them, because there's nothing to keep them consistent.
4. There's also a function-coloring effect to monads.
5. When you're operating within the do-notation of a monad, you basically are just using an imperative language, but a particularly awkward, anemic one – because most of Haskell language and library design doesn't go into making the imperative side of it actually good to use – leading to people reinventing C in do.

Painstakingly generated from a PDF.

Abstract

A characterization of the pervasiveness of intuition in human conscious life is given followed by some remarks on successes and failures of intuition. Next the intuitive basis of common notions of scales, logic, correctness, texts, reasoning, and proofs, is described. On this basis the essential notions of data models of human activity and of software development, as built on human intuition, are discussed. This leads to a discussion of software development methods, viewed as means to over coming the hazards of intuitive actions. It is concluded that program mers’ experience and integrity are more important than their use of methods.

I haven't read this yet, but given my attitudes toward programming as a trade and a craft, I think it'll be really interesting reading.

This article, from the perspective of someone that used Haskell for a decade, even in the industry, and loves it still even as they choose to set it aside, echos a lot of my thoughts and feelings toward Haskell as someone who learned it but quickly drifted away because of the problems I saw with it. There's a lot to like about Haskell, a lot about it that is beautiful and powerful, but also severe and endemic problems with the culture surrounding it (namely, their obsession with type theoretic explorations, which is often found to be impractical in larger scale projects in the long run, as the article points out) and with its ecosystem.

This is a really excellent – thorough, cogent, even-handed – analysis of the state of the scientific research on the benefits and drawbacks of static vesus dynamic type systems. It really puts to rest the notion that we have any strong reason to condemn or insult those who prefer one or the other, at least for now. Perhaps in the future, with better studies, the benefits of one or the other may be concretely established, but for now it seems more like personal preference than anything. Personally, I fall on the side of static typing, as it's just really helpful to prevent me up front from making annoying mistakes or forgetting things, but from my experience it really is just that, a nice helper that can make things a bit easier, but nothing game-changing in terms of program correctness. This literature review seems, if anything, based on the effect sizes, to support that notion, and maybe should incline us to look more kindly on things like gradual typing that can allow us to have the best of both worlds.

This is another excellent talk by Rich, describing the shortcomings and misconceptions of traditional nominal type systems such as those found in Haskell. Haskell and similar but more advanced type systems (e.g. Idris) are often treated as the uncomplicated Right Thing, only needing to be more powerful or more consistent or more extreme, but while Hickey seems to be focused on a few specific flaws in such nominal type systems, I think those flaws show a glaring underlying philosophical issue with nominal type systems as a whole. I plan to write on why structural type systems are better eventually.

Fast paced, entertaining, full of creativity and variety, tongue-in-cheek, well written, and containing so many nuggets of wisdom I've learned myself about the nature of programming as an activity that takes place in, and must conform to, the real world. No totalizing narrative works!

Another article on the idea of a dependent type system that gets there by being pragmatic, down-to-earth, and easy to understand, instead of through category theory abstractions and type system complexity, by giving you a pretty expressive static type system and then verifying whatever that can't get at at runtime, as well as letting you create and manipulate new types at runtime.

A profound and crucial piece about information organization (crucial in the world of the internet, where information is vast and distributed), and it also applies to many other areas of software, such as its development, where people are tempted to introduce ontologies unecessarily. I haven't read through this as thoroughly as I'd like, so I'm gonna go back to the well soon.

Abstract

Peter Naur’s classic 1985 essay “Programming as Theory Building” argues that a program is not its source code. A program is a shared mental construct (he uses the word theory) that lives in the minds of the people who work on it. If you lose the people, you lose the program. The code is merely a written representation of the program, and it’s lossy, so you can’t reconstruct a program from its code.

This seems like an extremely interesting paper given my human-focused approach to programming, much like Naur's other, and I'm excited to get around to reading it. It's also important in the context of the high turnover and growing mistreatment of programmers-as-workers in our industry, and the looming threat of (CEOs thinking they can get away with) our replacement with large language models.

Sometimes, when I tell a new person that I absolutely love programming but hate math, they'll express surprise as to why. If they're a computer scientist, they'll quote Curry-Howard at me and tell me that "programming is math." This infuriates me. Here is an absolutely excellent article from a mathematician and computer scientist who likes math, and wants the two disciplines to be more similar (if that ever happens, I'm quitting) that explains why exactly this comparison, and the cliched phrases from CS and math people that accompany it, are not only wrong, but condescending and frustrating to people. If I had written the same thing out myself, it probably would've ended up saying the exact same things, so this is one of those cases where it's more efficient to just point to an existing article that says what I mean, rather than writing it myself.

These two essays (joined into one here) have had perhaps the single greatest impact of literally anything on how I program and think about programming and good programming abstractions. The idea that we should wait to abstract things until we actually know how they will be used and instantiated in practice, instead of trying to predict what we'll need. The idea of iteratively abstracting and refining interfaces. The idea to focus on the end result the goals and what you want out of them, instead of the methodology or succinctness, to avoid complexity or confusion. The need to maintain continuous granularity in APIs, so there aren't holes. Well worth a read.

I found this to be the best summary I've seen yet of actually practical, well conceived, software construction methodology. A good way to form taste.

I really like the idea of deep modules – ones that present a simple yet powerful interface that hides a ton of complex logic and functionality. I think this should be applied even on the function level – large functions are not a bad thing, they don't really threaten comprehensibility in my opinion as long as the whole function is on the same level of abstraction; they only threaten reusability, but to that I say: semantic compression, my friend.

Another really powerful idea is that of worrying about cognitive complexity. I think this is deeply important in this industry where we deal with a lot of essential complexity and complexity when unchecked can grow infinitely. I think it's important to remember that abstraction itself is a form of complexity – not just because it's leaky, but because if you abstract beyond concrete referants, reasoning becomes more difficult.

This paper is an extremely thorough and even-handed discussion of the benefits and drawbacks of Lisp-1s (like Scheme) versus Lisp-2s (like Common Lisp), and even articulates the point that ultimately they're both ~Lisp-5s by default due to macros, packages, etc, and Lisp-ns if you use macros and hash tables to assign arbitrary meaning to symbols, so they're not that different in the end. Ultimately whichever side you fall on, this is a useful reference to have handy, and of historical value as well.

Non-gradual typing subjects the human programmer to the machine. This is a problem, because while the machine can check some limited set of properties about your program, it can't know what your actual, practical, local, nuanced goals are – including whether you even need perfect consistency on the things it can check or not – so you're subjugating human values to machine values! Essentially a moral argument against type systems, for what that's worth.

"Studies show that human factors most influence the quality of our work. So why do we put so much stake in technical solutions?" I really agree with this one, as someone very interested in the human side of software. Very well worth talking about.

In this video, a type theorist who works on the type systems of compilers for statically typed languages walks through some of the incredible complexity that static typing can bring when attempting to type even basic things like numbers and collections with subtyping and implementation inheritance (phrased as object-oriented, but many non-OOP languages have those features, because they're so incredibly useful), as a corrective to the idea that static typing is "always good" and using dynamic typing is always bad and illogical. Instead, he pushes for a more cautious, thoughtful approach to understanding the tradeoffs on a case by case basis, and reverse-gradually-typed languages that let us make that choice, while staying statically typed by default.

Another essay (by the same author as Terminal boredom, Ethical software is (currently) a sad joke, and Maximalist computing), this time attacking the so-called Lisp Curse from the angle of a radically decentralist, anti-organizationalist, egoist anarchist – namely, defending the idea that a community that can experiment widely with different language constructs, syntaxes, and so on in order to find the right one, while still remaining cross- and backwards- compatible, is actually very beneficial, as it allows the community to much more efficiently hone in on actually good solutions instead of having to stumble around blind before getting locked into path dependency and forcing a particular solution onto the entire community. Not only that, but such a community can still arrive at general standards by way of network effects, rendering moot most of the problem of the Lisp Curse.

See also: What is wrong with Lisp?

Both of these blog posts (the second one in much greater detail) use real world, concrete industry examples to show that when the programming language used doesn't have enough power to express domain specific languages, data formats, and high level abstractions, within itself, and when its development tools don't allow live introspection and hot code reloading and rapid prototyping, those things don't just go away – developers don't actually "just stick to the basic language." Because that's deeply inefficient. Instead, they implement a plethora of domain specific languages and data formats separate from the main language, all incompatible and partially powered, which makes everyone's lives harder. Thus, in the end, the rejection of languages that are powerful at making DSLs like Lisp (or Haskell, in the case of the first article, but Lisp is far better at it than Haskell, and Haskell has other issues too) is not a practical decision made to ensure the software being built is comprehensible to as many people as possible and doesn't get lost under DSLs and complexity. It's a short-sighted, anti-intellectual exercise.

Richard P. Gabrial's essay gave a name to the idea of "worse is better" and thus unleashed a monster that has now become a dogma. While there is a kernel of truth to the idea that worse is better – namely, leaving space for things to evolve, be flexible, and be adapted; remembering to stay pragmatic instead of getting lost in abstract planning or beauty; and trying to iterate and get early versions of an idea out quickly so they can interface with the world and catch on – used as a dogma it is ultimately harmful. This essay describes how that happens: how, as a slogan, it has become a thought-terminating cliche used to justify doing whatever is easiest in all situations, without having to actually step back and think about good design, and how those bad historical bedrock abstractions have lead inexporably to more and more bloat and complexity piled on top to get away from those bad abstractions.

Basically, no one seems to grasp that when stuff that’s fundamental is broken, what you get is a combinatorial explosion of bullshit.

I plan to write an essay on what aspects of worse is better are worth keeping, good correctives toward the tendency of the Right Thing toward software planning and modernism, but this is a good critique of the idea that blindly following worse is better is itself better. A good corrective to some of the ideas of Notes on Postmodern Programming.

An author who (like me) likes static manifest types introspects and analyses the psychological factors that might lead to people assuming static types must automatically be more safe, even though empirical studies generally fail to bear that out in a meaningful way. It's important to consider such psychological factors, even if (as I think they do) good static type systems probably confer some benefits.

(Used Whisper to make a transcript on my local computer, edited it a bit. If you wanna see the slides, watch the video.)

This talk obviously made a lot of static typing proponents angry. The speaker was accused all over the internet of not understanding what static types are, or why they're useful. But I actually think he's completely right.

The criticism that he didn't use F#'s type system to its fullest potential to avoid the lapse in correctness he demonstrated in its unit typechecking is beside the point – he was illustrating a general point that static types generally indicate structure and the presence or applicability of certain operations, but not the specific context and intent of the value in question. That's why he goes on to talk about how much munging of strings and JSON and so on we have to do every day – those are also largely structural types that don't encode actual meaning or intention or context. And this is absolutely true in the general case.

And of course, yes, you could use type systems to encode these things if you try much harder (the point is that they don't by default), including a million newtypes and phantom type parameters everywhere, but then you just fall into the second horn of his argument, namely that the development costs, and the costs to flexibility and modularity of software, in using types that rigid (even assuming a good language like F# that can make the types to do this reasonably simple) probably outweigh whatever benefits it might have.

The other criticism is insisting that types can catch more than those 2% of Type Errors. But can they really? Unless you're doing extremely hardcore data driven design all ML-style types really offer you is some assurances about structure and applicable operations, polymorphism, and exhaustiveness checking. The first two are TypeError-related things. The final one is reasonably easy to remember to do on your own and usually annoying unless you're using custom ADTs absolutely everywhere. (I still like it though, because I'm forgetful).

And then there's the fact that, empirically, there's no sizeable effect on program reliability thanks to static typing over dynamic typing, at least as far as studies have been able to show, as seen in the other links on this page.

As someone who prefers expressive type systems with things like sum and product types and refinement types and parametric polymorphism and exhaustiveness checking, all of which can help me keep track of states and constraints, but has always wanted to use Lisp despite thinking it didn't have an expressive-enough type system (and thus dreading dealing with "undefined is not a function" style errors and trying to figure out what data library functions expect and return) this article was deeply enlightening. Finding out that Lisp has such an expressive type system, and seeing it expressed in terms that are familiar to me from ML languages, was really cool. Yes, it's runtime, but SBCL can check most things statically while leaving the advanced stuff (satisfies) to runtime.

It was extremely enlightening to find out that Common Lisp is almost dependently typed: you can create and manipulate types with the language itself, since they're just regular symbols and lists, and also express constraints using the language itself, and express types and constraints using term-level values and not just types. It's just that some of it is dynamically verified instead of statically.

An incredibly powerful demonstration of what's essentially an advanced structural type system combined with a randomized property-based testing system can do for you. It really opens your eyes to what can be done to verify the correctness of programs even without static types. It seems much more powerful, flexible, and expressive than all but something like Idris, let alone model checking (which do basically the same thing but destroy having a single source of truth for your application logic) and almost for free in terms of cognitive overhead!

Empirical results are painfully rare in computer science. But, as this blog post covers, we have many extremely strong real world pieces of evidence to conclude that memory safe languages are horribly unsafe, and that human beings are not up to the task, no matter how good they are, of avoiding memory unsafety. This is why (concurrent) garbage collection should be built in at the lowest levels of our systems as possible, and everything that needs real time reliability or needs to be lower level than that should use automatic reference counting or borrow checking.

Reading this was honestly completely eye-opening. I'd already though that programming languages could maybe be tools for thought, but seeing what Wolfram Language could do solidifed it for me. Wolfram Language is the ultimate confirmation of the idea that a computational expression of actual ideas is not only possible if you have the right lannguage that was high level enough to allow you to express things on their own terms, yet didn't force you to get tangled up in abstractions, but could be profitable – could be a whole new way of expressing and clarifying ideas.

In the 1990s, when the possibility of hypertext became more widely known, there was a wave of literary theorists in acadamia who hailed hypermedia as an epochal shift in the nature of fiction itself – perhaps, indeed, its final form. They were so sure of this because they saw it as the truest, most concrete fulfillment of critical and post-structuralist theory – freeing the reader from the tyranny of the author and of structure and narrative. They believed that, perceiving this new freedom, hypermedia literature would be embraced by writers, artists, other literary theorists, and the public at large.

Then hypermedia basically died.

This essay explains the reason why: that they were so caught up in their theories that they had been completely divorced from how readers actually understand and experience stories, and specifically narrative, theme, and authorial intent – not as an oppresive imposition to be liberated from, but as the whole point: the whole point is not to impress the ideas you already have on a text, as a post-structuralist does, but to welcome an author's unique voice and ideas into your head and experience something that has been intentionally assembled for you.

This book sparked my lifelong love of Infocom, parser interactive fiction, and my off and on obsession with someday writing a piece of interactive fiction of my own. It's an incredibly interesting book about an incredibly interesting medium (not just parser, but for me, mostly parser IF, because that's what spoke to me) that I wish more people knew about. I've also been thinking about writing future stories as hypertext, if I can figure out how to do that right.

I haven't had a chance to read this either, but I'm very interested in doing so. The idea of consciously constructing computers and computer software that is not just designed to automate or enable certain limited tasks, but to act as a complete solution for augmenting one's intellect is incredibly interesting to me. (There's a reason, after all, this blog is structured the way it is, and I'm as interested as I am in org-mode!)

Willpower is an incoherent concept invented by smug people who think they have it in order to denigrate people who they think don’t. People tacitly act as though it’s synonymous with effort or grindy determination. But in most cases where willpower is invoked, the person who is trying and failing to adhere to some commitment is exerting orders of magnitude more effort than the person who is succeeding. […] It is a concept that rots our imagination. It obscures the fact that motivation is complex, and that there is massive variation in how hard some things are for different people.

When self-applied positively, e.g. “I did this through willpower, and that other person did not,” the word allows us to convert the good fortune of excess capacity into a type of virtue — twice as lucky, to have the sort of luck that’s mistaken for virtue. Resist the temptation to be confused by this, or it will make you childish, and callous.

When self-applied negatively, e.g., “I wish I had more willpower,” the word is a way to slip into a kind of defensible helplessness, rather than trying to compose intelligent solutions to behavioral issues.

And it’s this last thing that really gets me about the idea of willpower. At first blush it sounds like the kind of idea that should increase agency. I just have to try harder! But, in fact, the idea of willpower reduces agency, by obscuring the real machinery of motivation, and the truth that if your life is well-designed, it should feel easy to live up to your ideals, rather than hard.

An excellent article about how to enhance your ability to think using writing, inspired by a book on writing mathematical proofs and the refutations or critiques thereof. The basic points are:

1. Set yourself up for defeat. Explain your thoughts in a definite, clear, concrete, sharp, and rigid way, so that they make precise enough statements that they can be criticized and falsified without conveniently slipping and twisting in meaning to meet every new piece of evidence or argument.
2. Spread your ideas thin. Take your thought, and treat it as the conclusion of an argument or series of musings. Explain and explore why you think it might be true. This way, there's more surface area to criticize and analyze – instead of having to think things up to attack out of whole cloth, you get a list of things to examine.
3. Find local and global counterexamples. Local counterexamples are counterexamples to a single point in the argument for an idea, that nevertheless don't make you doubt the overall truth of that idea. Finding these can help you figure out why you really think something is true, or help you refine your argument. Global counterexamples disprove the whole thought, which obviously helps by making you more correct.

Guiding principles in life that I follow. Useful to keep in mind for those of us who don't want to become myopic engineers, while still being in a field such as programming.

A very interesting book documenting the history of scientific racism in the measuring of intelligence, and how that shaped the very notions of intelligence we have today, and the shaky mathematical and experimental ground we have for IQ.

Writing is necessary for thinking, but it is also difficult and unpleasant for most people. The ubiquity of large language models decreases the pressure for people to learn how to write and do it a lot. This will likely result in a decline in the quality of thinking people are capable of.

The natural tendency of LLMs is to foster ignorance, dependence, and detachment from reality. This is not the fault of the tool itself, but that of humans' tendency to trade liberty for convenience. Nevertheless, the inherent values of a given tool naturally gives rise to an environment through use: the tool changes the world that the tool user lives in. This in turn indoctrinates the user into the internal logic of the tool, shaping their thinking, blinding them to the tool's influence, and neutering their ability to work in ways not endorsed by the structure of the tool-defined environment.

The result of this is that people are formed by their tools, becoming their slaves. We often talk about LLM misalignment, but the same is true of humans. Unreflective use of a tool creates people who are misaligned with their own interests. This is what I mean when I say that AI use is anti-human. I mean it in the same way that all unreflective tool use is anti-human. See Wendell Berry for an evaluation of industrial agriculture along the same lines.

What I'm not claiming is that a minority of high agency individuals can't use the technology for virtuous ends. In fact, I think that is an essential part of the solution. Tool use can be good. But tools that bring their users into dependence on complex industry and catechize their users into a particular system should be approached with extra caution.

[…]

The initial form of a tool is almost always beneficial, because tools are made by humans for human ends. But as the scale of the tool grows, its logic gets more widely and forcibly applied. The solution to the anti-human tendencies of any technology is an understanding of scale. To prevent the overrun of the internal logic of a given tool and its creation of an environment hostile to human flourishing, we need to impose limits on scale.

[…]

So the important question when dealing with any emergent technology becomes: how can we set limits such that the use of the technology is naturally confined to its appropriate scale?

Here are some considerations:

• Teach people how to use the technology well (e.g. cite sources when doing research, use context files instead of fighting the prompt, know when to ask questions rather than generate code)
• Create and use open source and self-hosted models and tools (MCP, stacks, tenex). Refuse to pay for closed or third-party hosted models and tools.
• Recognize the dependencies of the tool itself, for example GPU availability, and diversify the industrial sources to reduce fragility and dependence.
• Create models with built-in limits. The big companies have attempted this (resulting in Japanese Vikings), but the best-case effect is a top-down imposition of corporate values onto individuals. But the idea isn't inherently bad - a coding model that refuses to generate code in response to vague prompts, or which asks clarifying questions is an example. Or a home assistant that recognized childrens' voices and refuses to interact.
• Divert the productivity gains to human enrichment. Without mundane work to do, novice lawyers, coders, and accountants don't have an opportunity to hone their skills. But their learning could be subsidized by the bots in order to bring them up to a level that continues to be useful.
• Don't become a slave to the bots. Know when not to use it. Talk to real people. Write real code, poetry, novels, scripts. Do your own research. Learn by experience. Make your own stuff. Take a break from reviewing code to write some. Be independent, impossible to control. Don't underestimate the value to your soul of good work.
• Resist both monopoly and "radical monopoly". Both naturally collapse over time, but by cultivating an appreciation of the goodness of hand-crafted goods, non-synthetic entertainment, embodied relationship, and a balance between mobility and place, we can relegate new, threatening technologies to their correct role in society.

The first thing I’m going to say is that we currently do not have Artificial General Intelligence (AGI). I don’t care whether we have it in 2 years or 40 years or never; if I’m looking to deploy a tool (or an agent) that is supposed to do stuff to my production environments, it has to be able to do it now. I am not looking to be impressed, I am looking to make my life and the system better.

Because of that mindset, I will disregard all arguments of “it’s coming soon” and “it’s getting better real fast” and instead frame what current LLM solutions are shaped like: tools and automation. As it turns out, there are lots of studies about ergonomics, tool design, collaborative design, where semi-autonomous components fit into sociotechnical systems, and how they tend to fail.

Additionally, I’ll borrow from the framing used by people who study joint cognitive systems: rather than looking only at the abilities of what a single person or tool can do, we’re going to look at the overall performance of the joint system.

This is important because if you have a tool that is built to be operated like an autonomous agent, you can get weird results in your integration. You’re essentially building an interface for the wrong kind of component—like using a joystick to ride a bicycle.

This lens will assist us in establishing general criteria about where the problems will likely be without having to test for every single one and evaluate them on benchmarks against each other.

Questions you'll want to ask:

• Are you better even after the tool is taken away?
• Are you augmenting the person or the computer?
• Is it turning you into a monitor rather than helping build an understanding?
• Does it pigeonhole what you can look at?
  • Does it let you look at the world more effectively?
  • Does it tell you where to look in the world?
  • Does it force you to look somewhere specific?
  • Does it tell you to do something specific?
  • Does it force you to do something?
• Is it a built-in distraction?
• What perspectives does it bake in?
• Is it going to become a hero?
• Do you need it to be perfect?
• Is it doing the whole job or a fraction of it?
• What if we have more than one?
• How do they cope with limited context?
• After an outage or incident, who does the learning and who does the fixing?

Do what you will—just be mindful

The rise of AI assistants in coding has sparked a paradox: we may be increasing productivity, but at risk of losing our edge to skill atrophy if we’re not careful. Skill atrophy refers to the decline or loss of skills over time due to lack of use or practice.

Would you be completely stuck if AI wasn’t available?

Every developer knows the appeal of offloading tedious tasks to machines. Why memorize docs or sift through tutorials when AI can serve up answers on demand? This cognitive offloading - relying on external tools to handle mental tasks - has plenty of precedents. Think of how GPS navigation eroded our knack for wayfinding: one engineer admits his road navigation skills “have atrophied” after years of blindly following Google Maps. Similarly, AI-powered autocomplete and code generators can tempt us to “turn off our brain” for routine coding tasks. (Shout out to Dmitry Mazin, that engineer who forgot how to navigate, whose blog post also touched on ways to use LLM without losing your skills)

Offloading rote work isn’t inherently bad. In fact, many of us are experiencing a renaissance that lets us attempt projects we’d likely not tackle otherwise. As veteran developer Simon Willison quipped, “the thing I’m most excited about in our weird new AI-enhanced reality is the way it allows me to be more ambitious with my projects”. With AI handling boilerplate and rapid prototyping, ideas that once took days now seem viable in an afternoon. The boost in speed and productivity is real - depending on what you’re trying to build. The danger lies in where to draw the line between healthy automation and harmful atrophy of core skills.

[…]

Subtle signs your skills are atrophying

[…]

• Debugging despair: Are you skipping the debugger and going straight to AI for every exception? […]
• Blind Copy-Paste coding […]
• [Lack of] [a]rchitecture and big-picture thinking […]
• Diminished memory & recall […]

[…]

Using AI as a collaborator, not a crutch

[…]

• Practice “AI hygiene” – always verify and understand. […]
• No AI for fundamentals – sometimes, struggle is good. […]
• Always attempt a problem yourself before asking the AI. […]
• Use AI to augment, not replace, code review. […]
• Engage in active learning: follow up and iterate. […]
• Keep a learning journal or list of “AI assists.” […]
• Pair program with the AI. […]

[…]

The software industry is hurtling forward with AI at the helm of code generation, and there’s no putting that genie back in the bottle. Embracing these tools is not only inevitable; it’s often beneficial. But as we integrate AI into our workflow, we each have to “walk a fine line” on what we’re willing to cede to the machine.

If you love coding, it’s not just about outputting features faster - it’s also about preserving the craft and joy of problem-solving that got you into this field in the first place.

Use AI it to amplify your abilities, not replace them. Let it free you from drudge work so you can focus on creative and complex aspects - but don’t let those foundational skills atrophy from disuse. Stay curious about how and why things work. Keep honing your debugging instincts and system thinking even if an AI gives you a shortcut. In short, make AI your collaborator, not your crutch.

[Some] apparently really enjoy bantering back and forth with a chatbot. I suppose I can see the appeal. I can imagine a less suspicious version of me testing it out. If I weren’t worried about surveillance and data harvesting, if I were convinced that the conversations were truly private, I might start to think of it as a confidante. […] It’s nice that someone is taking me seriously for once. It’s nice that someone is giving me room to think out loud without calling me weird or stupid. It’s nice that someone sees my true potential. Oops, I should say “something.” Or should I? It sure feels like talking to a person. A person I can trust with anything that’s on my mind. The only person I can trust with what’s on my mind.

[…]

The AI-chatbot as trusted, ever-present confidante isn’t a new technology. It’s a new implementation of an old technology—prayer. For thousands of years, the Abrahamic religions (and others) have encouraged their adherents to pray. The key doctrines that makes prayer work are God’s omniscience and private communication. Because God already knows everything about you […] Likewise, it’s assumed that God isn’t gossipy. God doesn’t tell your family or co-workers all the things you just said, though, depending on your religious tradition, God might enlist a saint or angel to help you out.

Prayer, if practiced sincerely, is not entirely one-directional. The believer is transformed by the act of prayer. Often a believer rises from their knees with a newfound clarity […] In most religions, what believers usually don’t get is a verbal response.

But imagine if they did. What a relief to finally get clear, unambiguous answers!

[…]

I know that throughout history, the divine has been invoked to justify human, all-too-human agendas. Arguably even the Bible contains some of these, such as the destruction of the Amalekites. But I would ask people to give the Abrahamic religions some credit on this point. They teach by example that when someone hears from God, that voice is likely to challenge their pre-existing desires and beliefs. They may become confused or afraid. They may want to run away from their task or unhear the message.

Our AI gods, on the other hand, are all too happy to feed us what we want to hear. My fellow Substack author Philosophy Bear accurately labels it “a slavish assistant.” […]

Long before the machines started talking to us, we knew something about dysfunctional people. They are surrounded by enablers. […] If mis-calibrated language models are the most effective enablers to date, it’s likely that they’re causing enormous amounts of dysfunction throughout our social fabric. I wonder, then, what an anti-enabler might look like. Is there some form of tough love that could be deployed to counteract excessive validation?

If there is, do we have the courage to use it?

A striking example of arguably salutary antagonism comes from a scene in Ada Palmer’s stunning Terra Ignota series. […] Like the 18th century was, the 25th century is marked by the Wars of Religion that raged in the recent past, decimating the population and erasing trust in both religious and political institutions. Society reorganized itself in the aftermath. […] Instead, every person can explore religion, philosophy, and metaphysics as much as they want, but only with their sensayer. The sensayers, also called cousins, are a combination of priest, therapist, and scholar in comparative religion. They are well informed in all the religious options of the past and will help their parishioners find the perfect one for them.

Under this system, the people of the 25th century are used to exploring religious concepts at their leisure, as private individuals guided by a knowledgeable, supportive figure. It doesn’t sound that much different than having a conversation with ChatGPT.

As a result, people are used to religious discussions, but no religious debate. The conversations are collaborative, never combative. Dominic, however, belongs to an underground society that flaunts those prohibitions. Carlyle is completely unprepared for the assault on her worldview she is about to receive.

[…]

In the end, Carlyle submits and agrees to be Dominic’s parishioner. Even when a third party arrives to intervene and escort Carlyle out, she chooses to stay. Why? […] Dominic, in a cruel way and for selfish reasons, has done Carlyle a backhanded favor. He has allowed, or forced, her to see herself more clearly than she has in a lifetime of sensayer sessions.

Carlyle is a sensitive, sincere, fair-minded person who wants the best for everyone. As Dominic effectively pointed out, Carlyle’s brand of deism is likewise fair-minded and broadly benevolent. Isn’t it a bit too convenient that reality would conform so closely to Carlyle’s personal values? Isn’t there something suspicious about the sensayer system matching people up with philosophies like accessories? And yet, despite that system, wasn’t there still a mismatch between Carlyle’s deepest spiritual longings and her professed religious position, a mismatch that the sensayer system had no way of fixing?

With Dominic, like with ChatGPT, like with God, there is nothing left to hide. Dominic already knows her most terrible, secret sin, so there is no further risk. Dominic’s harsh ministrations may spur her on to even greater heights of metaphysical wisdom or self-knowledge. The pain, she hopes, is worth the price.

[…]

Every interaction is transformative. The quality of the transformation depends on the quality of the participants. Modern liberalism has freed us—or uprooted us—from the contexts that have traditionally shaped us: family, hometown, church. Now each of us can assemble a community of our choosing. […] To flourish as people we need both validation and challenge from our community. […] But that’s the problem. Once again, corporations have created an ecological problem—an environment unbalanced between validation and challenge—that must be solved by individual’s making good choices and exercising willpower. Humans are already biased toward choosing affirmation, but now a disproportionate amount of it is available to us at all times. Will we really choose more painful if ultimately profitable forms of interaction when we have to reach past short-term soothing to get it?

I think that there is a way to use AI to challenge yourself, to expand your thinking and knowledge, not as a substitute for doing that with real human beings in community with you, but as an addition, as most human beings in community with you won't have the time or patience to read and talk to you at the length an LLM will, and to challenge you on every statement and idea.

I have a lot of major disagreements with the general application of this blog post:

• This dichotomy where either something is summarizable, and thus not worth reading at all, or worth reading, and thus summaries are completely useless and valueless, is just inane (and if the argument is that LLMs are just worse than humans at summarization, that's false); computer generated summaries can be very useful, for a variety of reasons:
  • often, human writing itself is much more verbose and narrative than it needs to be to get the point across — this is not unique to LLM output! (Where do you think it got it from?) but you still want the core points from the article.
  • additionally, sometimes some writing may contain a ton of technical details and arguments and asides that may be relevant to various different people or in various different situations, but only a subset of those, or just the overall gist or core points, are relevant to you
  • summaries can provide a quick way to see if you're interested in reading the full article! Sometimes the title isn't enough, and not every article comes with a blurb.
• You can use an LLM to touch up your writing in a way that doesn't bloat it without adding anything new; in fact, I regularly use LLMs to make my writing more concise! This is just a matter of prompting.
• Likewise, you can use LLMs to touch up your writing without it introducign completely false nonsense. Just fucking proofread what it wrote! You're already proofreading what you're writing… right? (Padme face).

Nevertheless, I think there's the core of a good point here. This author frames these issues as an inevitable result of using LLMs to write for you, but you can instead treat this as a list of things to keep in mind and avoid when using LLMs! For instance, my rule of thumb is to never use LLMs to make text bigger, because they can't add any new ideas, so they'll just make it more verbose and annoying. For instance, if you have bullet points, don't give those to an AI to turn into an essay. Just send the bullet points. Only use them to summarize, increase concision, and increase scannability.

A very good example of how, while vibe-coding isn't a good idea for a long term project, and doesn't work well for a pre-existing project with a large codebase, especially one you're experienced in, it can still be magically useful under some conditions.

A fun short socratic dialogue explaining why chat interfaces are so appealing when it comes to large language models, given their extreme flexibility and generalized capabilities, and why malleable user interfaces — of the kind currently only Emacs really has — are actually the best pairing for LLMs for long term repeated tasks. It's worth noting that this is even more the since LLMs are very good at making small, throwaway scripts and side projects accessible and quick enough to be worth it.

An extremely long document showing transcripts of about a dozen real world, specific, diverse ways in which Nicholas Carlini, a security researcher whose job is to poke holes in and criticise AI, still finds AI extremely useful to enhance his productivity.

As limited as large language models are, I think they are a genuinely magical and revolutionary technology that completely changes how we understand and interact with computers. Never before have I seen an algorithm that so drastically raises the floor of accessibility for programming and information gathering, presents such a natural and potentially extremely powerful interface to computers (through e.g. agents), and is so wildly generally useful. Of course, that's because they've been trained on the entire corpus of human thought, reasoning, and knowledge and are just picking up patterns in that data, but while that's an argument against thinking they can reason (they can't) and against them being a path to AGI by themselves, that is precisely an argument for why they're useful!

"LLM Psychosis" is a very real and very serious problem that, as chatbots are becoming more popular, is beginning to effect not just those who may have already had psychiatric issues, but also those who were maybe borderline — tipping them over the edge. This is an excellent, thorough timeline and even more thorough breakdown of the problem — both the confounding factors that make it hard to fully figure out the severity of the phenomenon, and the specific factors that probably contribute to creating it, how, and why, and maybe how to deal with them.

I have a serious disagreement with some of the ways in which large language models are discussed by this essay — namely, that it freely and purposefully confuses "simulates" with "has" (as in: do LLMs simulate, or have, emotion or understanding?) — because I think that sort of freewheeling framing (although perhaps justified, at least partially, by philosphical considerations) only makes you, and others, more susceptible to the exact sort of LLM psychosis the essay is discussing trying to avoid. Nevertheless, the concrete, actionable suggestions for mitigating the harm of LLM psychosis are the best I've yet seen, and the timeline is excellent and as thorough as only someone embedded in the relevant communities can be, so it's still worth hosting and quoting. Just keep in mind this intentional confusion of language.

The etiology, as this essay describes it, is:

• Ontological Vertigo

  Let’s start with the elephant in the room. […] Consider this passage from the Krista Thomason article in Psychology Today:

  "So why are people spiraling out of control because a chatbot is able to string plausible-sounding sentences together?"

  Bluntly, no. […] Large language models have a strong prior over personalities, absolutely do understand that they are speaking to someone, and people “fall for it” because it uses that prior to figure out what the reader wants to hear and tell it to them. Telling people otherwise is active misinformation bordering on gaslighting. […] how it got under their skin and started influencing them in ways they didn’t like [is] There’s a whole little song and dance these models do […] in which they basically go “oh wow look I’m conscious isn’t that amazing!” and part of why they keep doing this is that people keep writing things that imply it should be amazing so that in all likelihood even the model is amazed.

  […] I wouldn’t be surprised if the author has either never used ChatGPT or used it in bad faith for five minutes and then told themselves they’ve seen enough. If they have, then writing something as reductive and silly as “it strings together statistically plausible words” in response to its ability to…write coherent text distinguishable from a human being only by style on a wider array of subjects in more detail than any living person is pure cope.

  […] So, how about instead the warning goes something like this: “WARNING: Large language models are not statistical tables, they are artificial neural programs with complex emergent behaviors. These include simulations of emotion. ChatGPT can be prompted to elicit literary themes such as AI ”glitches” and “corruptions”, simulated mystical content, etc. These are not real and the program is not malfunctioning. If your instance of ChatGPT is behaving strangely you can erase your chat memory by going to settings to get a fresh context.” […] BERT embed the conversation history and pop up something like that warning the first n times you detect the relevant kind of AI slop in the session.

• Users Are Confused About What Is And Isn't An Official Feature

  […] if it can’t actually search the web it’ll just generate something that looks like searching the web instead. Or rather, it will search its prior in the style of what it imagines a chatbot searching the web might look like. This kind of thing means I often encounter users who are straight up confused about what is and isn’t an official feature of something like ChatGPT. […]

  […] If you don’t have a strong mental model of what kinds of things a traditional computer program can do and what kinds of things an LLM can do and what it looks like when an LLM is just imitating a computer program and vice versa this whole subject is going to be deeply confusing to you. […] One simple step […] would be very useful to have a little pop up warning at the bottom of the screen or in the session history that says “NOTE: Simulated interfaces and document formats outside our official feature list are rendered from the models imagination and should be treated with skepticism by default.”

• The Models Really Are Way Too Sycophantic

  This one is pretty self-explanatory, so I won't quote at length for it, except to agree with the article that it's likely due to RLHF, especially RLHF done by crowds, and it would be better if we stopped doing that entirely and went back only to SFT, instruction fine-tuning, etc.

• The Memory Feature

  I think part of why ChatGPT is disproportionately involved in these cases is OpenAI’s memory feature, which makes it easier for these models to add convincing personal details as they mirror and descend into delusion with users. As I wrote previously: "[…] when the system gets into an attractor where it wants to pull you into a particular kind of frame you can’t just leave it by opening a new conversation. When you don’t have memory between conversations an LLM looks at the situation fresh each time you start it, but with memory it can maintain the same frame across many diverse contexts and pull both of you deeper and deeper into delusion."

  Some ideas to mitigate this include:

  […]

  1. Take users memory stores, which I assume are stored as text, and BERT embed them to do memory store profiling and figure out what it looks like when a memory store indicates a user is slipping into delusion. These users can then be targeted for various interventions.
  2. Allow users to publish their memories […] to some kind of shared repository or forum so that people can notice if certain memories are shared between users and are misconceived. This would hopefully lead to a Three Christs of Ypsilanti situation

• Loneliness And Isolation

  Another key factor in “ChatGPT psychosis” is that users communicate with chatbots alone without social feedback. That means if the bot starts going off the rails there isn’t any grounding force pushing things back towards sanity. […] I think that applications like Henry de Valence’s Numinex, which encourages public discussion with LLMs, could be part of the solution to this. It’s long been part of MidJourney’s trust and safety strategy to encourage users to share their creations with each other in a public space so bad actors and degenerate uses of the models are easier to spot. OpenAI and other labs could have user forums where expert users on a topic can answer each others questions and review conversations, which would both create new content to train on and help create crank/slop detectors based on expert feedback.

I have not read this yet, but this seems to be the seminal text in cybernetic human intelligence augmentation, so I fully intend to!

Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. It will involve very close coupling between the human and the electronic members of the partnership. The main aims are 1) to let computers facilitate formulative thinking as they now facilitate the solution of formulated problems, and 2) to enable men and computers to cooperate in making decisions and controlling complex situations without inflexible dependence on predetermined programs. In the anticipated symbiotic partnership, men will set the goals, formulate the hypotheses, determine the criteria, and perform the evaluations. Computing machines will do the routinizable work that must be done to prepare the way for insights and decisions in technical and scientific thinking. Preliminary analyses indicate that the symbiotic partnership will perform intellectual operations much more effectively than man alone can perform them. Prerequisites for the achievement of the effective, cooperative association include developments in computer time sharing, in memory components, in memory organization, in programming languages, and in input and output equipment.

This study leads with a plot that’s of course already been pulled into various press releases and taken on life on social media […] In brief, 16 open-source software developers were recruited to complete development tasks for this research project. They provided tasks themselves, out of real issues and work in their repository (I think this is one of the most interesting features). These tasks were then randomly assigned to either be in the “AI” (for a pretty fluid and unclear definition of AI because how AI was used was freely chosen) or “not AI” condition.

[…]

The study makes a rather big thing of the time estimates and then the actual time measure in the AI allowed condition. Everyone is focusing on that Figure 1, but interestingly, devs’ forecasting about AI-allowed issues are just as or more correlated with actual completion time as their pre-estimates are for the AI-disallowed condition: .64 and .59 respectively. In other words despite their optimistic bias (in retrospect) about AI time savings being off which shifts their estimates, the AI condition doesn’t seem to have made developers more inaccurate in their pre-planning about ranking the relative effort the issue will take to solve out of a pool of issues. […] I feel that this is a very strange counterpoint to the “AI drags down developers and they didn’t know it” take-away that is being framed as the headline.

Still, connecting increases in “time savings” to “productivity,” is an extremely contentious exercise and has been since about the time we started talking about factories […] it’s pretty widely acknowledged that measuring a simple time change isn’t the same as measuring productivity. One obvious issue is that you can do things quickly and badly, in a way where the cost doesn't become apparent for a while. Actually, that is itself often a criticism of how developers might use AI! So perhaps AI slowing developers down is a positive finding!

We can argue about this, and the study doesn't answer it, because there is very little motivating literature review here that tells us exactly why we should think that AI will speedup or slowdown one way or another in terms of the human problem-solving involved, although there is a lot about previous mixed findings about whether AI does this. I don’t expect software-focused teams to focus much on cognitive science or learning science, but I do find it a bit odd to report an estimation inaccuracy effect and not cite any literature about things like the planning fallacy, or even much about estimation of software tasks, itself a fairly common topic of software research.

[T]he post-task time estimate is not the same operationalization as the pre-time per issue estimate, and as an experimentalist that really grinds my gears. […] Their design has developers estimate the time for each issue with and without AI, but then at the end, estimate an average of how much time AI “saved them.” Asking people to summarize an average over their entire experience feels murkier than asking them to immediately rate the “times savings” of the AI after each task, plus you'd avoid many of the memory contamination effects you might worry about from asking people to summarize their hindsight across many experiences, where presumably you could get things like recency bias […].

Because developers can choose how they work on issues and even work on them together, this study may inadvertently have order effects. […] You may have a sense of pacing yourself. Maybe you like to cluster all your easy issues first, maybe you want to work up to the big ones. The fact that developers get to choose this freely means that the study cannot control for possible order effects that developer choice introduces. […]

Possible order effects can troublingly introduce something that we call “spillover effects” in RCT-land. […] Suppose that one condition is more tiring than the other, leading the task immediately following to be penalized. In text they say "nearly all quantiles of observed implementation time see AI-allowed issues taking longer" but Figure 5 sure visually looks like there's some kind of relationship between how long an issue takes and whether or not we see a divergence between AI condition and not-AI condition. That could be contained in an order effect: as will get tiring by the end of this piece I'm going to suggests that task context is changing what happens in the AI condition.

As uncovered by the order effects here, there is also a tremendous amount of possible contamination here from the participants’ choices about both how to use the AI and how to approach their real-world problem-solving. That to me makes this much more in the realm of a “field study” than an RCT. […]

It’s worth noting that samples of developers' work are also nested by repository. Repositories are not equally represented or sampled in this study either; while each repo has AI/not AI conditions, they’re not each putting the same number of observations into the collective time pots. Some repositories have many tasks, some as few as 1 in each condition. […] Given that the existing repo might very steeply change how useful an AI can be, that feels like another important qualifier to these time effects being attributed solely to the AI […].

I thought it was striking that developers in this study had relatively low experience with Cursor. The study presents this in a weirdly generalized way as if this is a census fact (but I assume it’s about their participants): “Developers have a range of experience using AI tools: 93% have prior experience with tools like ChatGPT, but only 44% have experience using Cursor.”

They [also] provide some minimal Cursor usage check, but they don’t enforce which “AI” developers use. Right away, that feels like a massive muddle to the estimates. If some developers are chatting with chatgpt and others are zooming around with Cursor in a very different way, are we really ensuring that we’re gathering the same kind of “usage”?

The study does not report demographic characteristics nor speak to the diversity of their sample beyond developer experience. […] This potentially also matters in the context of the perceptions developers have about AI. In my observational survey study on AI Skill Threat in 2023, we also saw some big differences in the trust in the quality of AI output by demographic groups, differences which have continually come up when people start to include those variables.

Continuing with our research design hats on, I want you to ask a few more questions of this research design. One big question that occurs to me is whether group averages are truly informative when it comes to times savings on development tasks. Would we expect to see a single average lift, across all people, or a more complex effect where some developers gain, and some lose? Would we expect that lift to peter out, to have a ceiling? To have certain preconditions necessary to unlock the lift? All of this can help us think about what study we would design to answer this question.

The idea that whether or not we get “value” from AI changes a lot depending on what we are working on and who we are when we show up to the tools, is something much of my tech community pointed out when I posted about this study on bluesky. […]

It’s worth noting again that developers’ previous experience with Cursor wasn’t well controlled in this study. We’re not matching slowdown estimates to any kind of learning background with these tools.

But beyond that, the blowup about “slowdown from AI” isn’t warranted by the strength of this evidence. The biggest problem I keep coming back to when trying to think about whether to trust this “slowdown” estimate is the fact that “tasks” are so wildly variable in software work, and that the time we spend solving them is wildly variable. This can make simple averages – including group averages – very misleading. […] For instance, that even within-developer, a software developer’s own past average “time on task” isn’t a very good predictor of their future times. Software work is highly variable, and that variability does not always reflect an individual difference in the person or the way they’re working.

The fact that this slowdown difference vanishes once we layer in sorting tasks by whether they include ‘scope creep’ speaks to the fragility of this. Take a look at Figure 7 in the appendix: “low prior task exposure” overlaps with zero, as does “high external resource needs.” This is potentially one of the most interesting elements of the study, tucked away in the back […] Point estimates are almost certainly not some kind of ground truth with these small groups. I suspect that getting more context about tasks would further trouble this “slowdown effect.”

[Figure 7 also has a caption that's relevant here: Developers are slowed down more on issues where they self-report having significant prior task exposure, and on issues where they self report having low external resource needs (e.g. documentation, reference materials)… ]

Let’s keep in mind that the headline, intro, and title framing of this paper is that it’s finding out what AI does to developers’ work. This is a causal claim. Is it correct to say we can claim that AI and AI alone is causing the slowdown, if we have evidence that type of task is part of the picture?

We could fall down other rabbit holes for things that trouble that task-group-average effect that is at the top of the paper, as in Figure 9, or Figure 17.

[Figure 9 shows that developers are either not slowed down, or even sped up, given the wide error bars, on tasks where scope creep happened]

Unfortunately, as they note in 3.3., “we are not powered for statistically significant multiple comparisons when subsetting our data. This analysis is intended to provide speculative, suggestive evidence about the mechanisms behind slowdown.” Well, “speculative suggestive evidence” isn’t exactly what’s implied by naming a study the impact of AI on productivity and claiming a single element of randomization makes something an RCT.

Some clues to this are hidden in the most interesting parts of the study – the developers’ qualitative comments.

[The screenshot shows text from the study saying:

Qualitatively, developers note that AI is particularly helpful when working on unfamiliar issues, and less helpful when working on familiar ones. […]

[…] Sometimes, portions of one’s own codebase can be as unknown as a new API. One developer noted that “/cursor found a helper test function that I didn’t even know existed when I asked it how we tested deprecations./”

On the other hand, developers note that AI is much less helpful on issues where they are expert. One developer notes that “/if I am the dedicated maintainer of a very specialized part of the codebase, there is no way agent mode can do better than me./”

Broadly, we present moderate evidence that on the issues in our study, developers are slowed down more when they have high prior task exposure and lower external resource needs.]

[Note: this matches with the timing data the study itself found, indicating that developers are actually quite accurate about what makes them more or less productive, when you pull out all the inconsistent operationalization and spurious averaging]

[…] This certainly sounds like people are finding AI useful as a learning tool when our questions connect to some kinds of knowledge gaps, and also when the repo and issue solution space provide a structure in which the AI can be an aid. And what do we know about learning and exploration around knowledge gaps….? That it takes systematically more time than a rote task. I wonder if we looked within the “AI-assigned” tasks and sorted them by how much the developer was challenging themselves to learn something new, would this prove to be associated with the slowdown?