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.

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.

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.

[…] 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?

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…

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.

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 […]

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 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.

This is a pretty good way to think about how LLMs work, IMO.

I don’t really think of them as artificial intelligence, partly because what does that term even mean these days?

It can mean we solved something by running an algorithm. It encourages people to think of science fiction. It’s kind of a distraction.

When discussing Large Language Models, I think a better term than “Artificial Intelligence” is “Imitation Intelligence”.

It turns out if you imitate what intelligence looks like closely enough, you can do really useful and interesting things.

It’s crucial to remember that these things, no matter how convincing they are when you interact with them, they are not planning and solving puzzles… and they are not intelligent entities. They’re just doing an imitation of what they’ve seen before.

All these things can do is predict the next word in a sentence. It’s statistical autocomplete.

But it turns out when that gets good enough, it gets really interesting—and kind of spooky in terms of what it can do.

A great example of why this is just an imitation is this tweet by Riley Goodside.

If you say to GPT-4o—currently the latest and greatest of OpenAI’s models:

The emphatically male surgeon, who is also the boy’s father, says, “I can’t operate on this boy. He’s my son!” How is this possible?

GPT-4o confidently replies:

The surgeon is the boy’s mother

This which makes no sense. Why did it do this?

Because this is normally a riddle that examines gender bias. It’s seen thousands and thousands of versions of this riddle, and it can’t get out of that lane. It goes based on what’s in that training data.

I like this example because it kind of punctures straight through the mystique around these things. They really are just imitating what they’ve seen before.

Dataset	Percentage	Size
CommonCrawl	67.0%	33 TB
C4	15.0%	783 GB
Github	4.5%	328 GB
Wikipedia	4.5%	83 GB
Books	4.5%	85 GB
ArXiv	2.5%	92 GB
StackExchange	2.0%	78 GB

And what they’ve seen before is a vast amount of training data.

The companies building these things are notoriously secretive about what training data goes into them. But here’s a notable exception: last year (February 24, 2023), Facebook/Meta released LLaMA, the first of their openly licensed models.

And they included a paper that told us exactly what it was trained on. We got to see that it’s mostly Common Crawl—a crawl of the web. There’s a bunch of GitHub, a bunch of Wikipedia, a thing called Books, which turned out to be about 200,000 pirated e-books—there have been some questions asked about those!—and ArXiv and StackExchange.

[…]

So that’s all these things are: you take a few terabytes of data, you spend a million dollars on electricity and GPUs, run compute for a few months, and you get one of these models. They’re not actually that difficult to build if you have the resources to build them.

That’s why we’re seeing lots of these things start to emerge.

They have all of these problems: They hallucinate. They make things up. There are all sorts of ethical problems with the training data. There’s bias baked in.

And yet, just because a tool is flawed doesn’t mean it’s not useful.

This is the one criticism of these models that I’ll push back on is when people say “they’re just toys, they’re not actually useful for anything”.

I’ve been using them on a daily basis for about two years at this point. If you understand their flaws and know how to work around them, there is so much interesting stuff you can do with them!

There are so many mistakes you can make along the way as well.

Every time I evaluate a new technology throughout my entire career I’ve had one question that I’ve wanted to answer: what can I build with this that I couldn’t have built before?

It’s worth learning a technology and adding it to my tool belt if it gives me new options, and expands that universe of things that I can now build.

The reason I’m so excited about LLMs is that they do this better than anything else I have ever seen. They open up so many new opportunities!

We can write software that understands human language—to a certain definition of “understanding”. That’s really exciting.

The talk then goes on to talk severel of the different really cool and brand new things you can do with LLMs, and also one of risks and problems you might run into as well and how to work around it (prompt injection). It then talks about Willison's personal ethics for using AI, which are similar to my own.

At the Brains, Minds, and Machines symposium held during MIT’s 150th birthday party in 2011, Technology Review reports that Prof. Noam Chomsky "derided researchers in machine learning who use purely statistical methods to produce behavior that mimics something in the world, but who don’t try to understand the meaning of that behavior."

[…]

I take Chomsky's points to be the following:

1. Statistical language models have had engineering success, but that is irrelevant to science.
2. Accurately modeling linguistic facts is just butterfly collecting; what matters in science (and specifically linguistics) is the underlying principles.
3. Statistical models are incomprehensible; they provide no insight.
4. Statistical models may provide an accurate simulation of some phenomena, but the simulation is done completely the wrong way; people don't decide what the third word of a sentence should be by consulting a probability table keyed on the previous words, rather they map from an internal semantic form to a syntactic tree-structure, which is then linearized into words. This is done without any probability or statistics.
5. Statistical models have been proven incapable of learning language; therefore language must be innate, so why are these statistical modelers wasting their time on the wrong enterprise?

Is he right? That's a long-standing debate. These are my short answers:

1. I agree that engineering success is not the sole goal or the measure of science. But I observe that science and engineering develop together, and that engineering success shows that something is working right, and so is evidence (but not proof) of a scientifically successful model.
2. Science is a combination of gathering facts and making theories; neither can progress on its own. In the history of science, the laborious accumulation of facts is the dominant mode, not a novelty. The science of understanding language is no different than other sciences in this respect.
3. I agree that it can be difficult to make sense of a model containing billions of parameters. Certainly a human can't understand such a model by inspecting the values of each parameter individually. But one can gain insight by examing the properties of the model—where it succeeds and fails, how well it learns as a function of data, etc.
4. I agree that a Markov model of word probabilities cannot model all of language. It is equally true that a concise tree-structure model without probabilities cannot model all of language. What is needed is a probabilistic model that covers words, syntax, semantics, context, discourse, etc. Chomsky dismisses all probabilistic models because of shortcomings of a particular 50-year old probabilistic model. […] Many phenomena in science are stochastic, and the simplest model of them is a probabilistic model; I believe language is such a phenomenon and therefore that probabilistic models are our best tool for representing facts about language, for algorithmically processing language, and for understanding how humans process language.
5. In 1967, Gold's Theorem showed some theoretical limitations of logical deduction on formal mathematical languages. But this result has nothing to do with the task faced by learners of natural language. In any event, by 1969 we knew that probabilistic inference (over probabilistic context-free grammars) is not subject to those limitations (Horning showed that learning of PCFGs is possible). I agree with Chomsky that it is undeniable that humans have some innate capability to learn natural language, but we don't know enough about that capability to say how it works; it certainly could use something like probabilistic language representations and statistical learning. And we don't know if the innate ability is specific to language, or is part of a more general ability that works for language and other things.

The rest of this essay consists of longer versions of each answer.

[…]

Chomsky said words to the effect that statistical language models have had some limited success in some application areas. Let's look at computer systems that deal with language, and at the notion of "success" defined by "making accurate predictions about the world." First, the major application areas […] Now let's look at some components that are of interest only to the computational linguist, not to the end user […]

Clearly, it is inaccurate to say that statistical models (and probabilistic models) have achieved limited success; rather they have achieved an overwhelmingly dominant (although not exclusive) position. […]

This section has shown that one reason why the vast majority of researchers in computational linguistics use statistical models is an engineering reason: statistical models have state-of-the-art performance, and in most cases non-statistical models perform worst. For the remainder of this essay we will concentrate on scientific reasons: that probabilistic models better represent linguistic facts, and statistical techniques make it easier for us to make sense of those facts.

[…]

When Chomsky said “That’s a notion of [scientific] success that’s very novel. I don’t know of anything like it in the history of science” he apparently meant that the notion of success of “accurately modeling the world” is novel, and that the only true measure of success in the history of science is “providing insight” — of answering why things are the way they are, not just describing how they are.

[…] it seems to me that both notions have always coexisted as part of doing science. To test that, […] I then looked at all the titles and abstracts from the current issue of Science […] and did the same for the current issue of Cell […] and for the 2010 Nobel Prizes in science.

My conclusion is that 100% of these articles and awards are more about “accurately modeling the world” than they are about “providing insight,” although they all have some theoretical insight component as well.

[…]

Every probabilistic model is a superset of a deterministic model (because the deterministic model could be seen as a probabilistic model where the probabilities are restricted to be 0 or 1), so any valid criticism of probabilistic models would have to be because they are too expressive, not because they are not expressive enough.

[…]

In Syntactic Structures, Chomsky introduces a now-famous example that is another criticism of finite-state probabilistic models:

"Neither (a) ‘colorless green ideas sleep furiously’ nor (b) ‘furiously sleep ideas green colorless’, nor any of their parts, has ever occurred in the past linguistic experience of an English speaker. But (a) is grammatical, while (b) is not."

[…] a statistically-trained finite-state model can in fact distinguish between these two sentences. Pereira (2001) showed that such a model, augmented with word categories and trained by expectation maximization on newspaper text, computes that (a) is 200,000 times more probable than (b). To prove that this was not the result of Chomsky’s sentence itself sneaking into newspaper text, I repeated the experiment […] trained over the Google Book corpus from 1800 to 1954 […]

Furthermore, the statistical models are capable of delivering the judgment that both sentences are extremely improbable, when compared to, say, “Effective green products sell well.” Chomsky’s theory, being categorical, cannot make this distinction; all it can distinguish is grammatical/ungrammatical.

Another part of Chomsky’s objection is “we cannot seriously propose that a child learns the values of 109 parameters in a childhood lasting only 108 seconds.” (Note that modern models are much larger than the 109 parameters that were contemplated in the 1960s.) But of course nobody is proposing that these parameters are learned one-by-one; the right way to do learning is to set large swaths of near-zero parameters simultaneously with a smoothing or regularization procedure, and update the high-probability parameters continuously as observations comes in. Nobody is suggesting that Markov models by themselves are a serious model of human language performance. But I (and others) suggest that probabilistic, trained models are a better model of human language performance than are categorical, untrained models. And yes, it seems clear that an adult speaker of English does know billions of language facts (a speaker knows many facts about the appropriate uses of words in different contexts, such as that one says “the big game” rather than “the large game” when talking about an important football game). These facts must somehow be encoded in the brain.

It seems clear that probabilistic models are better for judging the likelihood of a sentence, or its degree of sensibility. But even if you are not interested in these factors and are only interested in the grammaticality of sentences, it still seems that probabilistic models do a better job at describing the linguistic facts. The mathematical theory of formal languages defines a language as a set of sentences. That is, every sentence is either grammatical or ungrammatical; there is no need for probability in this framework. But natural languages are not like that. A scientific theory of natural languages must account for the many phrases and sentences which leave a native speaker uncertain about their grammaticality (see Chris Manning’s article and its discussion of the phrase “as least as”), and there are phrases which some speakers find perfectly grammatical, others perfectly ungrammatical, and still others will flip-flop from one occasion to the next. Finally, there are usages which are rare in a language, but cannot be dismissed if one is concerned with actual data.

[…]

Thus it seems that grammaticality is not a categorical, deterministic judgment but rather an inherently probabilistic one. This becomes clear to anyone who spends time making observations of a corpus of actual sentences, but can remain unknown to those who think that the object of study is their own set of intuitions about grammaticality. Both observation and intuition have been used in the history of science, so neither is “novel,” but it is observation, not intuition that is the dominant model for science.

[…]

[…] I think the most relevant contribution to the current discussion is the 2001 paper by Leo Breiman (statistician, 1928–2005), Statistical Modeling: The Two Cultures. In this paper Breiman, alluding to C. P. Snow, describes two cultures:

First the data modeling culture (to which, Breiman estimates, 98% of statisticians subscribe) holds that nature can be described as a black box that has a relatively simple underlying model which maps from input variables to output variables (with perhaps some random noise thrown in). It is the job of the statistician to wisely choose an underlying model that reflects the reality of nature, and then use statistical data to estimate the parameters of the model.

Second the algorithmic modeling culture (subscribed to by 2% of statisticians and many researchers in biology, artificial intelligence, and other fields that deal with complex phenomena), which holds that nature’s black box cannot necessarily be described by a simple model. Complex algorithmic approaches (such as support vector machines or boosted decision trees or deep belief networks) are used to estimate the function that maps from input to output variables, but we have no expectation that the form of the function that emerges from this complex algorithm reflects the true underlying nature.

It seems that the algorithmic modeling culture is what Chomsky is objecting to most vigorously [because] […] algorithmic modeling describes what does happen, but it doesn’t answer the question of why.

Breiman’s article explains his objections to the first culture, data modeling. Basically, the conclusions made by data modeling are about the model, not about nature. […] The problem is, if the model does not emulate nature well, then the conclusions may be wrong. For example, linear regression is one of the most powerful tools in the statistician’s toolbox. Therefore, many analyses start out with “Assume the data are generated by a linear model…” and lack sufficient analysis of what happens if the data are not in fact generated that way. In addition, for complex problems there are usually many alternative good models, each with very similar measures of goodness of fit. How is the data modeler to choose between them? Something has to give. Breiman is inviting us to give up on the idea that we can uniquely model the true underlying form of nature’s function from inputs to outputs. Instead he asks us to be satisfied with a function that accounts for the observed data well, and generalizes to new, previously unseen data well, but may be expressed in a complex mathematical form that may bear no relation to the “true” function’s form (if such a true function even exists).

[…]

Finally, one more reason why Chomsky dislikes statistical models is that they tend to make linguistics an empirical science (a science about how people actually use language) rather than a mathematical science (an investigation of the mathematical properties of models of formal language, not of language itself). Chomsky prefers the later, as evidenced by his statement in Aspects of the Theory of Syntax (1965):

"Linguistic theory is mentalistic, since it is concerned with discovering a mental reality underlying actual behavior. Observed use of language … may provide evidence … but surely cannot constitute the subject-matter of linguistics, if this is to be a serious discipline."

I can’t imagine Laplace saying that observations of the planets cannot constitute the subject-matter of orbital mechanics, or Maxwell saying that observations of electrical charge cannot constitute the subject-matter of electromagnetism. […] So how could Chomsky say that observations of language cannot be the subject-matter of linguistics? It seems to come from his viewpoint as a Platonist and a Rationalist and perhaps a bit of a Mystic. […] But Chomsky, like Plato, has to answer where these ideal forms come from. Chomsky (1991) shows that he is happy with a Mystical answer, although he shifts vocabulary from “soul” to “biological endowment.”

"Plato’s answer was that the knowledge is ‘remembered’ from an earlier existence. The answer calls for a mechanism: perhaps the immortal soul … rephrasing Plato’s answer in terms more congenial to us today, we will say that the basic properties of cognitive systems are innate to the mind, part of human biological endowment."

[…] languages are complex, random, contingent biological processes that are subject to the whims of evolution and cultural change. What constitutes a language is not an eternal ideal form, represented by the settings of a small number of parameters, but rather is the contingent outcome of complex processes. Since they are contingent, it seems they can only be analyzed with probabilistic models. Since people have to continually understand the uncertain, ambiguous, noisy speech of others, it seems they must be using something like probabilistic reasoning. Chomsky for some reason wants to avoid this, and therefore he must declare the actual facts of language use out of bounds and declare that true linguistics only exists in the mathematical realm, where he can impose the formalism he wants. Then, to get language from this abstract, eternal, mathematical realm into the heads of people, he must fabricate a mystical facility that is exactly tuned to the eternal realm. This may be very interesting from a mathematical point of view, but it misses the point about what language is, and how it works.

I have a deep running soft spot for symbolic AI for many reasons:

1. I love symbols, words, logic, and algebraic reasoning
2. I love programming computers to do those things, with databases, backtracking, heuristics, symbolic programming, parsing, tree traversal, everything and anything else. It's just so fun and cool!
3. I love systems that you can watch work and really understand.
4. Symbolic AI plays to the strengths of computers — deterministic, reliable, controlled.
5. I love the culture and history of that particular side of the field, stemming as it does from the Lisp hackers and the MIT AI Lab.
6. I love the traditional tools and technologies of the field, like Prolog and Lisp.

Sadly, time and again symbolic AI has proven to be fundamentally the wrong approach. This famous essay outlines the empirical and technological reasons why, citing several historical precidents, that have only been confirmed even more in the intervening years. It is, truly, a bitter lesson.

The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. […] We have to learn the bitter lesson that building in how we think we think does not work in the long run. The bitter lesson is based on the historical observations that

1. AI researchers have often tried to build knowledge into their agents,
2. this always helps in the short term, and is personally satisfying to the researcher, but
3. in the long run it plateaus and even inhibits further progress, and
4. breakthrough progress eventually arrives by an opposing approach based on scaling computation by search and learning.

The eventual success is tinged with bitterness, and often incompletely digested, because it is success over a favored, human-centric approach.

[…]

The second general point to be learned from the bitter lesson is that the actual contents of minds are tremendously, irredeemably complex; we should stop trying to find simple ways to think about the contents of minds […] as their complexity is endless; instead we should build in only the meta-methods that can find and capture this arbitrary complexity. Essential to these methods is that they can find good approximations, but the search for them should be by our methods, not by us. We want AI agents that can discover like we can, not which contain what we have discovered. Building in our discoveries only makes it harder to see how the discovering process can be done.

See also my own thoughts on symbolism vs connectionism.

This is a great followup to the original essay, specifically the section on how the invention of reinforcement learning only amplifies the benefits of connectionist approaches and scaling over and above symbolism and explicit rule-encoding by allowing us to still train models for specific tasks and steer them towards and away from specific behaviors using expert human knowledge, without needing to encode the specific ways to get there:

In 2025, this pattern becomes even more evident with Reinforcement Learning agents. While many companies are focused on building wrappers around generic models, essentially constraining the model to follow specific workflow paths, the real breakthrough would come from companies investing in post-training RL compute. These RL-enhanced models wouldn’t just follow predefined patterns; they are discovering entirely new ways to solve problems. […] It’s not that the wrappers are wrong; they just know one way to solve the problem. RL agents, with their freedom to explore and massive compute resources, found better ways we hadn’t even considered.

The beauty of RL agents lies in how naturally they learn. Imagine teaching someone to ride a bike - you wouldn’t give them a 50-page manual on the physics of cycling. Instead, they try, fall, adjust, and eventually master it. RL agents work similarly but at massive scale. They attempt thousands of approaches to solve a problem, receiving feedback on what worked and what didn’t. Each success strengthens certain neural pathways, each failure helps avoid dead ends.

[…]

What makes this approach powerful is that the agent isn’t limited by our preconceptions. While wrapper solutions essentially codify our current best practices, RL agents can discover entirely new best practices. They might find that combining seemingly unrelated approaches works better than our logical, step-by-step solutions. This is the bitter lesson in action - given enough compute power, learning through exploration beats hand-crafted rules every time.

If you don't have time to read this post, these five graphs give most of the argument. Each includes both the energy/water cost of using ChatGPT in the moment and the amortized cost of training GPT-4:

graph 1

Source for original graph, I added the ChatGPT number. Each bar here represents 1 year of the activity, so the live car-free bar represents living without a car for just 1 year etc. The ChatGPT number assumes 3 Wh per search multiplied by average emissions per Wh in the US. Including the cost of training would raise the energy used per search by about 33% to 4 Wh. Some new data implies ChatGPT's energy might be 10x lower than this.

graph 2

I got these numbers by multiplying the average rate of water used per kWh used in data centers + the average rate of water used generating the energy times the energy used in data centers by different tasks. The water cost of training GPT-4 is amortized into the cost of each search. This is the same method used to originally estimate the water used by a ChatGPT search. Note that water being “used” by data centers is ambiguous in general, read more in this section

graph 3

Statistic for a ChatGPT search, burger, and leaking pipes.

graph 4

I got these numbers from back of the envelope calculations using publicly available data about each service. If you think they're wrong I'd be excited to update them! Because this is based on the total energy used by a service that's rapidly growing it's going to become outdated fast.

graph 5

Back of the envelope calculation here

And it's crucial to note that, for instance, if you're using Google's AIs, which are both mixture of experts models (so inference is much cheaper) and run on Google's much more power efficient Tensor chips, it's probably less than this! Running a small AI locally is probably less efficient than running that same small AI in a data center, as well, but the AIs you can run locally are so much smaller than the ones you'd run in a data center that that counts as an optimization too, not to mention it decreases the power density and distortion that datacenters impose on the power grid.

This is a really excellent and relatively accessible — especially with the excellent workable toy examples and illustrations which slowly build up to the full thing piece by piece — not just of how generative pretrained transformers and large language models work, but all of the concepts that build up to them, that are necessary to understand them. It also contains a sober analysis of why these models are so cool — and they are cool!! — and their very real limitations, and endorses a neurosymbolic approach similar to the one I like.

I think embeddings are one of the coolest parts of all this.

Cyc: Obituary for the greatest monument to logical AGI

After 40 years, 30 million rules, 200 million dollars, 2000 person-years, and many promises, Cyc has failed to reach intellectual maturity, and may never will. Exacerbated by the secrecy and insularity of Cycorp, there remains no evidence of its general intelligence.

The legendary Cyc project, Douglas Lenat’s 40-year quest to build artificial general intelligence by scaling symbolic logic, has failed. Based on extensive archival research, this essay brings to light its secret history so that it may be widely known.

Let this be a bitter lesson to you.

As even Gary Marcus admits in his biggest recent paper:

Symbol-manipulation allows for the representation of abstract knowledge, but the classical approach to accumulating and representing abstract knowledge, a field known as knowledge representation, has been brutally hard work, and far from satisfactory. In the history of AI, the single largest effort to create commonsense knowledge in a machine- interpretable form, launched in 1984 by Doug Lenat, is the system known as CYC […] Thus far, the payoff has not been compelling. Relatively little has been published about CYC […] and the commercial applications seem modest, rather than overwhelming. Most people, if they know CYC at all, regard it as a failure, and few current researchers make extensive use of it. Even fewer seem inclined to try to build competing systems of comparable breadth. (Large- scale databases like Google Knowledge Graph, Freebase and YAGO focus primarily on facts rather than commonsense.)

Given how much effort CYC required, and how little impact it has had on the field as a whole, it’s hard not to be excited by Transformers like GPT- 2. When they work well, they seem almost magical, as if they automatically and almost effortlessly absorbed large swaths of common- sense knowledge of the world. For good measure,

"Transformers give the appearance of seamlessly integrating whatever knowledge they absorb with a seemingly sophisticated understanding of human language."

The contrast is striking. Whereas the knowledge representation community has struggled for decades with precise ways of stating things like the relationship between containers and their contents, and the natural language understanding community has struggled for decades with semantic parsing, Transformers like GPT2 seem as if they cut the Gordian knot—without recourse to any explicit knowledge engineering (or semantic parsing)—whatsoever.

There are, for example, no knowledge- engineered rules within GPT- 2, no specification of liquids relative to containers, nor any specification that water even is a liquid. In the examples we saw earlier

If you break a glass bottle of water, the water will probably flow out if it’s full, it will make a splashing noise.

there is no mapping from the concept H2O to the word water, nor any explicit representations of the semantics of a verb, such as break and flow.

To take another example, GPT- 2 appears to encode something about fire, as well:

a good way to light a fire is to use a lighter.

a good way to light a fire is to use a match.

Compared to Lenat’s decades-long project to hand encode human knowledge in machine interpretable form, this appears at first glance to represent both an overnight success and an astonishing savings in labor.

An excellent short guide to the different architectures that can be used to structure neuro-symbolic AI, with successful recent examples from the field's literature.

Perhaps the best general encapsulation of Gary Marcus's standpoint, and well worth reading even if to be taken with a small pinch of salt and more than a little of whatever beverage you prefer to get through the mild crankiness of it.

Two conjectures I would make are these

• We cannot construct rich cognitive models in an adequate, automated way without the triumvirate of hybrid architecture [for abstractive capabilities], rich prior knowledge [to be able to understand the world by default enough to model it], and sophisticated techniques for reasoning [to reliably be able to apply knowledge to the world without having to memorize literally everything in the world]. […]
• We cannot achieve robust intelligence without the capacity to induce and represent rich cognitive models. Reading, for example, can in part be thought a function that takes sentences as input and produces as its output (internal) cognitive models. […]

Pure co- occurrence statistics have not reliably gotten to any of this. Cyc has the capacity to represent rich cognitive models, but falls down on the job of inducing models from data, because it has no perceptual component and lacks an adequate natural language front end. Transformers, to the extent that they succeed, skip the steps of inducing and representing rich cognitive models, but do so at their peril, since the reasoning they are able to do is consequently quite limited.

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.

A response to the famous organizationalist essay "The Tyranny of Structurelessness." I was going to write my own, but this one phrases my complains just as well and completely as I would, so I decided to save myself some time and merely mirror this for later reference instead.

All I would add is that a synthesis of the critiques present in the original essay, as flawed as they are, and the responses found in this one is possible, and I think that's to be found in creating explicit "governance documents" even for informal, fluid, affinity based anarchist associations, if they're going to have more than a couple members and stick around for more than a few weeks (which is sometimes necessary, especially when centered around managing material resources), as a way to have a common touchstone for everyone to understand the values, intentions, goals, and processes of the group, to help avoid miscommuncations. The caveats being that such documents need to be:

• collaboratively edited (preferably using something like CryptPad),
• living (open to be changed at any time as norms and needs and context shift, and things are learned from experience),
• designed to be interpreted as a loose statement of common feeling, not legalistically and procedurally interpreted and adhered-to like some sort of Law,
• and the content of which should be explicitly based on things like consensus decision making, direct action, non-hierarchical organization and conflict resolution, drawing lots for different roles, separation, limitation, and enumeration of powers, etc.

I am not spiritual in the traditional sense. I do not believe in the supernatural, or gods, or goddesses, or enjoy spiritual traditions, practices, or ceremonies, or go on drug trips. I don't adhere to a religion. Insofar as I have a religion (in the broad sense some mystics use it to mean, as in "any set of life practices inspired by a historical tradition that touches on the moral and axiological dimensions of life") then, as this essay says, anarchism is my religion. This essay is a really well-written piece exploring what that means, with some help from philosophical Taoism, which I'm also very sympathetic to.

Some modern anarchists seem to worship democracy. Most liberals do. This is a collection of criticisms of it from most major anarchists.

A great short little article walking through all the ways people have protected themselves in each other without the state historically in England. While none of these ways are close to perfect, they show that there are alternatives to the state that have worked in the past.

An eloquent, concise statement of the idea that anarchism means a rejection of any imposed authority, and nothing more. It is "the hammer that smashes the chains" but it does not dictate what we should do after, in the space created by that smashing, except that it should not impose authority. Everything else is up to us. And any ideology that dictates one specific way of organizing "after anarchy has come" (whatever that means) is simply not really anarchism, but something else, like communism.

Despite my many disagreements with Rothbard, my revulsion with his paleoconservative turn, and my even greater disagreements with his intellectual heirs such as Hoppe, some of his writings are quite good. This is one of them. There are, of course, areas where I'd refocus his analysis, listed below, but in general it's very good, and I recommend reading it, just taken with a good-size grain of salt.

Some areas where I'd change what he said if I was writing it include (but aren't limited to):

• his belief that the greatest evil and aggression of the state is the invasion of private property is laughable,
• his confusion of capitalism with simply free(d) market cooperation such that he thinks states are "anti-capitalist" is fucking hilarious,
• he cites John C. Calhoun pointing out that a constitution and bill of rights means nothing if those governed by a state so "bound" cannot directly enforce those rights against that state somehow, or nullify violating state laws, and if the state is "a judge in its own case" regarding whether it's adhering to them, and then points out quite astutely that Calhoun's solution to this only protects individuals from federal, but not state, encroachment. He doesn't bother to realize why that is the case – that it's very convenient for a racist slaver "philosopher" to suggest a system where the federal government's laws can be blocked, but the states can do whatever they like

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

A very thorough, in depth, and well-reasoned argument against moralist anarchists from the perspective of a Stirnerite – both that morality is not inevitable from a sort of enlightened egoism, and that it is not necessary to be anarchist.

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.

A highly entertaining, very egoist critique of Marxism that shares many of the issues I have with it. Take it with a grain of salt of course, since it isn't the most rigerous out there, but definitely worth at least poking around and reading sections of!

One of the few essays by Rothbard that, even after my move away from anarcho-capitalism, I still really like, probably because its from the time when he was courting the New Left, instead of trying to create a paleoconservative form of "libertarianism," and so its ideals and projects are more compatible with mutualist ideas. In this case, he advocates for the giving of public propery, and any property gained through state violence, expropriation, or funding, to the people that actually occupy, use, and maintain it!

"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.

In this essay Roderick Long argues, successfully in my opinion, that corporate power is actually antithetical to an actually freed market, both because corporations naturally fear constant competition and shifting market demands, which will naturally break their power, and so will need to use state power to protect their position, and because corporate power is actually, historically, bought and protected (from competition, but also externalities, diseconomies of scale, etc) by means of substantial explicit, incidental, and implicit subsidies for big business on the part of the government. Thus, he argues, we should stop conflating advocacy for a free(d) market with advocacy for corporate capitalism.

These essays show clearly and concretely why, if the Austrians were consistent in their critiques of the information, incentive, calculation, and ethical problems of centralization, authoritarianism, and surveillance, they would also have to be anticapitalist. These critiques are excellent and unique in providing excellent efficiency arguments against capitalism that don't rely on ideas about "rational planning."

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.

An account of how mutualist property titles might arise from anarchist conditions and concerns, as a defense of market anarchism from communist anarchists.

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

This is an excellent article about how Hayeks ideas about science and epistemology and information are essentially a post-structualist critique of the idea that we can analyze and understand society scientifically, but argued clearly and in an analytic way. This is essentially a twin of the essay I eventually intend to write showing how late Wittgenstein aligns closely with the anti-essentialism of the post-structuralist philosophers, but in a way that lends a new perspective and argumentative comprehensibility to them.

A defense of public commons against more propertiarian arguments (based on the tragedy of the commoons) against it, and a gesture at why public commons are a very necessary corrective against the ways in which everything being private space could curtail autonomy. Useful as a critique of Hoppeans.

Benjamin Tucker was one of the very first and most influential individualist anarchists, and many of his essays – which this book collects – are excellent and well worth reading, as well as being immensely influential on me. Obviously he has his rough spots (I haven't read most of Instead of a Book yet), and I'm sure personally he probably had many reprehensible beliefs as a man of his time, but the man is not what's important to me.

My favorite essays in here are:

• State Socialism and Anarchism
• Socialism: What It Is
• The Relation of the State to the Individual
• Armies That Overlap

An explanation of how, in a free(d) market world, workers are powerful and have many options for collectively fighting back against exploitation, but these days they have been castrated by government regulation much more than they have been superficially "helped." Useful for those worried about worker's rights in a market anarchist society.

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 very fun egoist anarchist/moral nihilist takedown of the inane logic of natural law. I tried to get natural law to "work" for like four years before I realized no matter what I did it was always totally arbitrary, or collapsed back into egoism, so it's cathartic to read something like this!

So many anarchists seem to want an end-state world much like Anarres from The Dispossessed – living gray, ascetic lives with the bare minimum of necessities meted out to us by centrally planned and centrally controlled storehouses. They seem to want to reach equality by making nearly everyone worse off, instead of trying to lift everyone up as high as possible – and yes, that will probably require the relinquishing of many luxuries on the part of first world inhabitants, especially middle class suburbanites and above, but the goal isn't that relinquishment, the goal is the enrichment of as many as possible as much as possible. This very short essay is a statement of rejection of that ideology.

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).

Leftism has a continual history of failure – failure to achieve anything, or failure to achieve anything good – and recuperation by capital. Anarchism must reject leftism, even though it was born alongside leftism and shares many of the same ends, and embrace a uniquely anarchist critique of everything leftism stands for: organization, ideology, and morality among them.

The woke left fears the individualist/egoist post-left, because it offers something so much stonger, more vital, more free, than it ever could. This is a takedown of many of the ways in which it tries to smear egoists to protect its precious "correct" church of anarchism or leftism.

Proudhon is a massively underrated, deeply interesting thinker elucidating a form of anarchy that has been lost, but that I think is worth exploring, since it comes from outside the pure social anarchy and Marxist anarchy traditions found today. This reader compiles the most important parts of his otherwise often long and difficult works, including some brand new translations. I haven't read much of his yet, but I really intend to go through this.

An excellent and enlightening exposition of why markets and market pricing are extremely helpful in resolving resource allocation problems – even when you care about equity! – in comparison even to just face to face communication.

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.

An exposition of how the government takes away options that poor people would have otherwise had for supporting themselves and caring for each other, or criminalizes them, making poverty much more terrifying and dangerous and difficult than it would otherwise have to be. None of these options the government takes away are ideal, of course – some are dirty, or fire-prone, and so on, which is the guise under which the government steals them away – but they are better than jail, constant repossession of your belongings and destruction of your shelter, starvation, beatings, or death, and often better than helpless reliance on a centralized bureaucratic state organization that doesn't have to care about you and uses the money of other people who themselves don't personally care about you (and is thus incentivized to skimp on helping you).

This is another one I haven't read, but the ideas about the impossibility of top down planning and modernist totalizing systems from which have percolated already deeply into my head from other things I've read. I look forward to reading it.

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.

A pretty good summary of all of the core problems that anarchists have with Leninism as an ideology:

1. A tendency toward cult of personality and denial of Lenin's historical mistakes
2. Vanguardism as an authoritarian, substitutionist, secrative system.
3. Marxist and Leninist critiques of the state are never about fundamental problems with it as an institution, with plice, courts, prisons, and the military, but only who is weilding the power (good if it's them, bad if it's anyone else!)
4. Socialism is just a form of bureaucratic state capitalism and reformism (see State Socialism and Anarchism by Benjamin Tucker)

A treatment of various issues in software design and production (including programming tools) from the perspective of an egoist anarchist influenced by Bookchins ideas around social ecology and liberatory technology. This is definitely an interesting piece, although there are specific things I disagree with, such as:

• That a static type system is inherently bad or limiting of the programmer. To make this critique, the authors seem to be conflating static type systems with static programming languages, but you could easily have a language as dynamic as Common Lisp or Smalltalk with a static type system (see Coalton), as well as pointing at the anti-human consequences of non-gradual type systems without realizing that gradual type systems are possible! If those two points are addressed, then, static type systems can be had without them being inherently anti-liberatory, and can provide benefits, by helping you remember and deal with details that'd otherwise be easy to forget or get wrong – an important thing for someone like me who has a memory-related disability!
• The idea that it's a good idea to use a license for your works that is copyleft but also explicitly denies commerical use to all except worker co-operatives, or in peer-production where trade is direct sharing instead of monetary compensation. While at first I found this idea intriguing, because I see licenses not as things that we need to worry about the enforcability of, since the copyright system ultimately always serves corporate interests, and therefore it doesn't matter whether they could theoretically be enforced or not, but instead as statements of intentions and preferences with respect to how your contributions to the Commons should be understood and treated by others, and this seemed like a clear statement of values in support of things I like (peer production and worker ownership), I quickly grew uncomfortable with it upon further thought. Namely because:
  1. While licenses are in my opinon mostly to be viewed as statements of values and preferences, they also do inherently involve the, at least rhetorical, invocation of state violence. Using the state's legal system to undo copyright itself, to return things to the commons where they should be, if they benefitted in any way from the commons, as copyleft does, doesn't seem like a problem to me, because it's less a positive application of state violence (rhetorically) then a nullification of it. However, this license seems to want to use state violence to militate against certain forms of organization.
  2. This is especially bad, in my opinion, because I don't think peer production is inherently better than trade for forms of monetary compensation, and I don't think all worker cooperatives are good, or all forms of corporations or wage labor are bad. Especially in the second case, the former is more likely to be less exploitative than the latter, but not necessarily. There are situations in which I can imagine wage labor is just fine, and a small business isn't exploitative, and situations I can imagine in which a worker cooperative is a cesspit of backstabbing, infighting, power politics, and exploitation of people with less voice in the process, and externalities on the community. So I don't see why I should make such an absolute statement.

However overall I agree with and am interested in the conclusions of this paper!

The creative nothing is one of the most interesting, and overtly Taoist, ideas that Stirner has – but it is only explicitly discussed in two places in The Unique and Its Property. More can be inferred about it from applying the rest of Stirner's philosophical attitude to the idea, however, and this article takes up that worthwhile endeavor well, as a useful elaboration on that crucial idea.

Stirner (in the third person) responds to some criticisms of his philosophical magnum opus. Provides a clearer, shorter, and more accessible elucidation of some of his ideas, and responds preemptively to some critiques one might have. This was my introduction to him, and could well by yours as well!

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.

An interesting intellectual play, coming from property rights from another angle.

Although I'm not a fan of natural law arguments, this is an interesting article making the case that the corporate form is ultimately a child of the state, and I think the argument might possibly offer components that can be applied outside a natural law framework, by just thinking about how we might constitute economic and social norms that make the corporate form impossible in the ways he proposes natural laws do.

• 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.

This is a short parody of anti-market anarchists which operates by replacing "market" (a network of trade) with just the abstract concept of networks of individual actors, to show how absurd their arguments truly are.

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 critique of the dominant Marxist culture (outside acadamia) of being a stagnant, nearly religious exigetical exercise, instead of a dynamic, developing intellectual discipline, from a Marxist (or as he would prefer to be called, a "scientific socialist"). What's funny about this essay is that despite a correct assesment of the problem, there's no analysis of why the problem came to be our really how to solve it – the fundamental ideological, philosophical, and cultural issues that made Marxism the way it is today – and, ironically, it falls into the exact same problems that caused the issue it's pointing out, such as the blinkered monomania with ideological terms (notice how often "dialectical" is prepended to terms unnecessarily in order to make them more Marxist, to the point where the word almost means nothing?), the claiming of "scientificness" for the ideology despite admitting there's very little empiricism, falsificationism, and a very large normative element, and a re-affirmation that any modification or development of core principles or ideas put forward by Marx would be "revisionist" and thus inherently bad and wrong. Thus it is an accurate critique that ultimately demonstrates the problem it's trying to get out of.

This is a great takedown of the idea of copyright from an anarchist egoist perspective. Written in a slightly oldtimey manner and not dealing with any "new developments," but it's funny as hell and the arguments are still sound all these years later.

A vision for how medical care could be made radically more decentralized and accessible, without falling into the trap of single payer healthcare:

Finally: I object strenuously to those who see a single-payer system, or a government-controlled delivery system like the UK’s National Health, as the solution. I’d like to give those who talk about healthcare being a “right” the benefit of the doubt, and assume they just don’t understand the implications of what they’re saying. But when you talk about education, healthcare, or anything else being a “right,” what that means in practice is that you get it in the (rationed) amount and form the State wants you to have, and buying it in the form you want becomes much more difficult (if not criminalized). It means the providers of the service will be cartelized, and that the provision of the service will be regulated according to the professional culture and institutional mindset of the cartels. As with “public” education, “public” healthcare means that the existing “professional” institutional culture is locked into place, but that you get their services at taxpayer expense.

Making something a “right” that requires labor to produce also carries another implication: slavery. You can’t have a “right” to any good or service unless somebody else has a corresponding obligation to provide it. And if you’re obligated to provide a good or service at a cost determined by somebody else, you’re a slave. Nobody is born with a “right” to somebody else’s labor-product: as Lilburne said, nobody is born with a saddle on his back, and nobody is born booted and spurred to ride him.

An in-depth description of and elaboration of a secondary, but extremely useful, concept from Stirner's work, as above, but this time regarding the idea of the "union of egoists." This essay deeply shapes my ideas about how social life and organization should work, or at least how I wish it could.

The best translation of Stirner's work to date. I wouldn't necessarily say this book has shaped my ideas, so much as it provides an interesting exploration of ideas that I had already come to by myself (moral nihilism, perspectivism, anti-dogma in all forms) as well as a more consistent and very challenging working-out of them, although I find his arguments, when viewed analytically, as somewhat wanting – hence the essays I intend to write arguing for his positions in a more analytic philosophy way.

Although Hayek's knowledge problem argument is often put to use by conservatives and libertarians, that doesn't mean it isn't correct – and in more consistent hands, it militates strongly against any form of hierarchy or centralization at all, not just the much-feared socialist bureaucracy.

Stirner is often accused of being somehow antithetical in principles, values, and tendencies to anarchism. This is bullshit. This will show you why.

A passionate manifesto that I have only felt more as time has gone on speaking out against LGBTQ assimilationism, against the urge to become legible, and speaking to all the ways in which the Queer is at odds inherently with the system we live under. It has deeply influenced how I see what the goals and approaches of queer life and organizing should be.

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.

This essay has aged poorly in one, narrow sense — in that the particular figure Fisher chose to defend, Russell Brand, has shown himself to be an asshole in a multilayered, ongoing way since the time of writing. But Fisher was not Brand, and for every person like Brand whom the left accurately identifies as a problem, there are an equal number whom they slander for no reason; and that isn't even what's important about this essay. Many of the core ideas behind this essay are evergreen, and truer now than when it was written.

Insights:

1. "The petit bourgeoisie which dominates the academy and the culture industry has all kinds of subtle deflections and pre-emptions which prevent [class] even coming up, and then, if it does come up, they make one think it is a terrible impertinence…"
2. "[T]he features of the discourses and the desires which have led us to this grim and demoralising pass, where class has disappeared, but moralism is everywhere, where solidarity is impossible, but guilt and fear are omnipresent" are "we have allowed bourgeois modes of subjectivity to contaminate our movement". Namely:
   1. The Vampire Castle:
      1. "The Vampires’ Castle specialises in propagating guilt. It is driven by a priest’s desire to excommunicate and condemn, an academic-pedant’s desire to be the first to be seen to spot a mistake, and a hipster’s desire to be one of the in-crowd."
      2. "The danger in attacking the Vampires’ Castle is that it can look as if – and it will do everything it can to reinforce this thought – that one is also attacking the struggles against racism, sexism, heterosexism. But, far from being the only legitimate expression of such struggles, the Vampires’ Castle is best understood as a bourgeois-liberal perversion and appropriation of the energy of these movements"
      3. "rather than seeking a world in which everyone achieves freedom from identitarian classification, the Vampires’ Castle seeks to corral people back into identi-camps, where they are forever defined in the terms set by dominant power, crippled by self-consciousness and isolated by a logic of solipsism which insists that we cannot understand one another unless we belong to the same identity group."
      4. "I’ve noticed a fascinating magical inversion projection-disavowal mechanism whereby the sheer mention of class is now automatically treated as if that means one is trying to downgrade the importance of race and gender. In fact, the exact opposite is the case, as the Vampires’ Castle uses an ultimately liberal understanding of race and gender to obfuscate class. […] it [is] noticeable that the discussion of class privilege [is] entirely absent."
      5. "The problem that the Vampires’ Castle was set up to solve is this: how do you hold immense wealth and power while also appearing as a victim, marginal and oppositional? The solution was already there – in the Christian Church. So the VC has recourse to all the infernal strategies, dark pathologies and psychological torture instruments Christianity invented, and which Nietzsche described in The Genealogy of Morals. This priesthood of bad conscience, this nest of pious guilt-mongers, is exactly what Nietzsche predicted when he said that something worse than Christianity was already on the way. Now, here it is …"
      6. "The Vampires’ Castle feeds on the energy and anxieties and vulnerabilities of young students, but most of all it lives by converting the suffering of particular groups – the more ‘marginal’ the better – into academic capital. The most lauded figures in the Vampires’ Castle are those who have spotted a new market in suffering […]"
      7. "The first law of the Vampires’ Castle is: individualise and privatise everything. While in theory it claims to be in favour of structural critique, in practice it never focuses on anything except individual behaviour."
      8. "Because they are petit-bourgeois to the core, the members of the Vampires’ Castle are intensely competitive, but this is repressed in the passive aggressive manner typical of the bourgeoisie. What holds them together is not solidarity, but mutual fear – the fear that they will be the next one to be outed, exposed, condemned."
      9. "The third law of the Vampires’ Castle is: propagate as much guilt as you can. The more guilt the better. People must feel bad: it is a sign that they understand the gravity of things. It’s OK to be class-privileged if you feel guilty about privilege and make others in a subordinate class position to you feel guilty too. You do some good works for the poor, too, right?"
      10. "The fourth law of the Vampires’ Castle is: essentialize. While fluidity of identity, pluraity and multiplicity are always claimed on behalf of the VC members […] the enemy is always to be essentialized. Since the desires animating the VC are in large part priests’ desires to excommunicate and condemn, there has to be a strong distinction between Good and Evil, with the latter essentialized. Notice the tactics. X has made a remark/ has behaved in a particular way – these remarks/ this behaviour might be construed as transphobic/ sexist etc. So far, OK. But it’s the next move which is the kicker. X then becomes defined as a transphobe/ sexist etc. Their whole identity becomes defined by one ill-judged remark or behavioural slip."
      11. "The fifth law of the Vampires’ Castle: think like a liberal (because you are one). The VC’s work of constantly stoking up reactive outrage consists of endlessly pointing out the screamingly obvious: capital behaves like capital (it’s not very nice!), repressive state apparatuses are repressive. We must protest!"
   2. Neo-Anarachism (this is the one I most fall afoul of, although I'm neither bourgoise nor educated technically, that is the culture I was raised in/am closest to; and although I think I have good reasons for my lack of action — namely, being very disabled — that doesn't change the effects): "By neo-anarchists I definitely do not mean anarchists or syndicalists involved in actual workplace organisation, such as the Solidarity Federation. I mean, rather, those who identify as anarchists but whose involvement in politics extends little beyond student protests and occupations, and commenting on Twitter. Like the denizens of the Vampires’ Castle, neo-anarchists usually come from a petit-bourgeois background, if not from somewhere even more class-privileged […] They are also overwhelmingly young: in their twenties or at most their early thirties, and what informs the neo-anarchist position is a narrow historical horizon."
      1. "Neo-anarchists have experienced nothing but capitalist realism. […] But the problem with neo-anarchism is that it unthinkingly reflects this historical moment rather than offering any escape from it. It forgets, or perhaps is genuinely unaware of, the Labour Party’s role in nationalising major industries and utilities or founding the National Health Service. Neo-anarchists will assert that ‘parliamentary politics never changed anything’, or the ‘Labour Party was always useless’ while attending protests about the NHS, or retweeting complaints about the dismantling of what remains of the welfare state. media to attempt to engineer change from there. […] Purism shades into fatalism; better not to be in any way tainted by the corruption of the mainstream, better to uselessly ‘resist’ than to risk getting your hands dirty."
      2. "It’s not surprising, then, that so many neo-anarchists come across as depressed. This depression is no doubt reinforced by the anxieties of postgraduate life, since, like the Vampires’ Castle, neo-anarchism has its natural home in universities, and is usually propagated by those studying for postgraduate qualifications, or those who have recently graduated from such study."
   3. "Why have these two configurations come to the fore?"
      1. "they have been allowed to prosper by capital because they serve its interests. […] why would capital be concerned about a ‘left’ that replaces class politics with a moralising individualism, and that, far from building solidarity, spreads fear and insecurity?"
      2. "It might have been possible to ignore the Vampires’ Castle and the neo-anarchists if it weren’t for capitalist cyberspace. The VC’s pious moralising has been a feature of a certain ‘left’ for many years – but, if one wasn’t a member of this particular church, its sermons could be avoided. Social media means that this is no longer the case, and there is little protection from the psychic pathologies propagated by these discourses."
   4. "The bourgeois-identitarian left knows how to propagate guilt and conduct a witch hunt, but it doesn’t know how to make converts. But that, after all, is not the point. The aim is not to popularise a leftist position, or to win people over to it, but to remain in a position of elite superiority, but now with class superiority redoubled by moral superiority too. ‘How dare you talk – it’s we who speak for those who suffer!’"
3. "What is to be done?"
   1. "So what can we do now? First of all, it is imperative to reject identitarianism, and to recognise that there are no identities, only desires, interests and identifications. […] Sadly, the right act on this insight more effectively than the left does."
   2. "But the rejection of identitarianism can only be achieved by the re-assertion of class. A left that does not have class at its core can only be a liberal pressure group. Class consciousness is always double: it involves a simultaneous knowledge of the way in which class frames and shapes all experience, and a knowledge of the particular position that we occupy in the class structure."
   3. "It must be remembered that the aim of our struggle is not recognition by the bourgeoisie, nor even the destruction of the bourgeoisie itself. It is the class structure – a structure that wounds everyone, even those who materially profit from it – that must be destroyed."
   4. "The interests of the working class are the interests of all; the interests of the bourgeoisie are the interests of capital, which are the interests of no-one. Our struggle must be towards the construction of a new and surprising world, not the preservation of identities shaped and distorted by capital."

This is a good brief, high level explanation by Kevin Carson as to why a freed market, absent the various monopolies that the state enforces on behalf of capitalists, would not necessarily result in the same distortions, inequalities, and exploitations we find under capitalism. To those, I'd add a few of my own:

• There is no such thing as a free market simpliciter; the nature of the market is always defined by particular property (and other) norms, and mutualist property norms of occupacy and use for personal possessions, and usufruct for things like land, substantially change the possibilities and incentives of a market. For instance:
  • It would be impossible to have large economic organizations with direct control over or ownership of branches in different locations, because, if occupancy and use constitute ownership, the local people working at a branch would automatically be considered to be the ones that actually own any capital there, and since intellectual property can't be occupied, it couldn't be used to still keep such local branches in line. This means you wouldn't get big corporations (or even co-ops) steamrolling local businesses, because if they tried that, whatever local branch they created would be automatically converted into a local business! The only way to have large organizations like that with multiple locations would be to have fundamentally independent entities coordinate via federation.
  • While global trade would still be possible (and necessary), it would be impossible for any kind of economic organization to fire all its local workers and ship all of its jobs overseas while keeping its management structure well paid and in tact, not only because there would be no third world to exploit, but also because the workers would be the management structure, and they would be unlikely to push for the obliteration of their own livelihoods.
  • Extraction of natural resources bypassing local communities would be impossible.
  • In a capitalist society, you can turn simply owning some piece of wealth into a way to generate more wealth for you without you having to do any more work through rent-seeking behavior like paying wage laborers to work it, renting it out, loaning it, etc. This means that all wealth that you own can generate more wealth for you at some conversion ratio, and then that wealth can generate more wealth, and so you can reach geometric wealth growth. Whereas, in a mutualist economy where you can only own what you personally occupy and use, then that strategy is not open to you. The only way that gaining more wealth can make more wealth for you is if it makes your, personal, labor-hours more productive – and there are significant diminishing returns there, as well as significant limits, since there are only so many things you can regularly use or occupy, and only so many hours a day you can work. Thus, what was once geometric is converted to logorithmic. There will be inequalities, yes, but since they won't come as a result of exploitation, there's no reason to worry about that, and they'll never be able to become so great as to threaten to create a significant power structure or centralization of wealth.

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.

Another horrifically poignant and accurate personal account, from a trans woman on Tumblr, of what it is like to exist in "queer feminist" spaces as someone who's femininity – and thus right to belong, and moral goodness – is constantly fragile and in question.

A painfully personal exposition of a life of gender dysphoria as a closeted trans woman, and using that position as a window into how truly, horribly and damaging the misandry of cis (and some transfem) feminists is. Not just to trans women, but also to cis men, too, but how it also forms a convenient echo chamber through thought-terminating cliches and dismissing messages based on who says them, to insulate feminists from possible criticism and the impacts of their words.

A trans women's experiences being abused at the hands of queer feminist spaces – transmisogyny, the inherent evil of callout culture and whisper networks, and so on. Just go fucking read it, it's an incredibly powerfully and poignantly written essay that, if you're on the left in the US, will probably deeply challenge your views.

The story of how Twitter cancel culture essentially killed a trans woman, convincing her that she couldn't truly be a woman, that the newfound identity she'd just been stepping into was invalid and needed to die, and that she should detransition, all because they couldn't handle a provocative title, and didn't read further than that title before banding up into a mob to punish her.

The story repeatedly goes to great lengths to try to say that it somehow wasn't cancel culture, but that's purely an exercise in doublethink. It absolutely is, it bears all the hallmarks of it:

• A preference for paranoid over reparative readings – looking for what's wrong with a work and trying to be angry at that, instead of looking at what's good about a work, possibly even what's good about it that others might appreciate even if you don't.
• Non-marginalized people trying to be social justice warriors on marginalized people's behalf without asking them, for virtue points.
• Thw dynamics of a mob, where nuance is erased and stopping the momentum is impossible.
• Paranoid assumptions about intention.
• The idea that only marginalized people can possibly write about marginalized experiences
• The idea that if someone writes about a marginalized experience differently than you would have, that means they "aren't really X."
• etc.

Some particularly egregious quotes are:

“There were several reporters that reached out to me right after the story came down. I remember having a conversation with one of them and saying, ‘Is [writing about] this really what you want to do? I’m not going to participate. I think that this is just going to make it worse,’” Clarke says. “And they ran with it. It brought in the whole cancel culture thing. Isabel needed that story down for her, not for them, and not for anybody else. But for her. And that’s why it came down. I tried to make that clear [in the editor’s note on the story’s removal]. But people still wanted that cancel narrative.”

Why did Isabel Fall need the story taken down for her own sake, hmm?

And:

"If anybody canceled Isabel Fall, it was Isabel Fall. She remains the subject of her own sentences."

Who made her "cancel herself" – check into the hospital and take down her story and ultimately kill the new version of herself she was stepping into? This is almost victim blaming to protect cancel culture.

Despite being framed as specific to the furry community – and one particular kind of social harassment – this is actually a really good general guide, if interpreted more broadly, for spotting many (although not all) kinds of social harassment that aims to take advantage of our desire to be "good," "moral," "protect people," "weed out creeps," and other such instincts. The crux of it is this:

As I mentioned previously, this “Google Doc expose” pattern has been employed in the past by actual victims desperate for their community to stop supporting their abuser.

Sometimes, when you see a Google Doc floating around accusing a furry of being abusive, that’s what you’re seeing.

Other times, you’re being handed a specially crafted piece of rhetoric that cherry-picks and lies by omission to make innocent people seem guilty of being terrible.

Here are a few things to watch out for to distinguish legitimate grievances from targeted harassment.

• Scope creep.
  • Is the doc focused on a specific, focused group of people, or does it read like a hit piece on as many popular furries as possible?
• Actions, not affiliations.
  • A legitimate call-out will focus on what harmful actions a person did, their victims’ stories, and the harms caused as a result of said actions.
  • Harassment docs focus on weak ties (“they were in the same Telegram group as ____”) or a person’s interests.
• Past remediation efforts.
  • Did the person in question immediately jump to the Google Doc outcome without trying anything else first?
• What are the incentives involved?
  • Speaking out about a horrible experience is terrifying, especially if it was perpetrated by someone with a lot of wealth or social capital in your community.
  • Conversely, trying to guilt the offending party or their audience into donating money to buy silence is simply blackmail.
• Is this part of a larger pattern?
  • Is this the only callout a person has ever made?
  • Is this the tenth callout this person has made this year?
  • What other metadata can you use to judge the validity of the information you’re presented with?

This short list of things to look out for isn’t foolproof, but it should help most people reduce their error rate for assessing a callout on social media.

A story of how purity culture took over online spaces.

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.