Author: boundary2

The Uses of Disorder: A Review of David Golumbia’s Cyberlibertarianism

Alexander R. Galloway

Does disorder have a politics? I suspect it must. It has a history, to be sure. Disorder is quite old, in fact, primeval even, the very precondition for the primeval, evident around the world in ancient notions of chaos, strife, or cosmic confusion. But does disorder have a politics as well? As an organizing principle, disorder achieved a certain coherence during the 1990s. In those years technology evangelists penned books with titles like Out of Control (the machines are in a state of disorder, but we like it), and The Cathedral and the Bazaar (disorderly souk good, well-ordered Canterbury bad).[1] The avant argument in those years focused on a radical deregulation of all things, a kind of full-stack libertarianism in which machines and organisms could, and should, self-organize without recourse to rule or law. Far from corroding political cohesion, as it did for Thomas Hobbes and any number of other political theorists, disorder began to be understood in a more positive sense, as the essential precondition for a liberated politics. Or as the late David Golumbia writes in Cyberlibertarianism, the computer society of the twentieth and early twenty-first centuries culminated in “the view that ‘centralized authority’ and ‘bureaucracy’ are somehow emblematic of concentrated power, whereas ‘distributed’ and ‘nonhierarchical’ systems oppose that power.”[2] And, further, Golumbia argues that much of the energy for these kinds of political judgements stemmed from a characteristically ring-wing impulse, namely a conservative reaction to the specter of central planning in socialist and communist societies and the concomitant endorsement of deregulation and the neutering of state power more generally. Isaiah Berlin’s notion of negative liberty had eclipsed all other conceptions of freedom; many prominent authors and technologists seemed to agree that positive liberty was only ever a path to destruction.[3] Or as Friedrich Hayek put it already in 1944, any form of positive, conscious imposition of order would inevitably follow “the road to serfdom.”[4] Liberty would thus thrive not from rational order, but from a carefully tended form of disorder.

Ceci tuera cela, wrote Victor Hugo. “This will kill that. Books will topple buildings … printing will kill architecture.”[5] As Golumbia discusses in his Chapter 4, cyberlibertarians frequently use the analogy of Gutenberg when speculating on the revolutionary politics of new digital technologies. The Internet will transform society, cyberlibertarians argue, by doing away with all the old hierarchies and gatekeepers, much as the printing press once weakened the clergy’s monopoly over the Good News. It’s a real historical transformation, perhaps, but the phrase is also meant to work as a metaphor. This will kill that. Computers will topple buildings. And it’s even more precise than this. Computers do away with the very concept of “building,” cyberlibertarians argue, because computers are inherently disruptive of hierarchies and institutions. Computers perform a kind of un-building, a deconstruction of all hitherto existing constructions. Or as Jacques Derrida once divulged with a refreshing candor, “[i]f there had been no computer, deconstruction could never have happened.”[6] The cyberlibertarians say something similar: behold the modern computer; in its wake are dissolved all the old hierarchies of Western culture.

Should we believe all this, this specific rhetoric of disorder? I, for one, don’t. And neither did Golumbia. I don’t believe Hayek. And if I were to believe Derrida, I doubt that he himself understood the consequences of such a pronouncement.[7] However I’m compelled to stay with the logic of disorder, at least for a while, given how disorder has colored so much of contemporary life. The disorder is real, I maintain, even if one should be skeptical about the rhetoric of liberation accompanying it. By the end I hope to convince you that disorder is not the general unraveling of order, but in fact an alternative system of order, and thus a clearly articulable form of political power.

In other words, what the tech evangelists got wrong, and what Golumbia got right, was that this new chaotic infrastructure, this new anarchy of flesh and ferrite, did not signal a generalized relaxation of order and organization, but in fact constituted a new system of management just as robust as any of the old hierarchies. (Tellingly, Gilles Deleuze once labeled the burgeoning computer epoch a “society of control”, not a society of liberty or justice.[8]) Particularly formative for me in arriving at this opinion were books like Branden Hookway’s Pandemonium, an unclassifiable text from 1999 devoted to the “environment of ‘all demons,’” understood through “chaotically activated surfaces, a swirl of constant motion, even brutal ubiquitous insurrection … a sort of diabolic friction between heaven and earth.”[9] What Hookway helped me understand was that the new pandemonium of the marketplace didn’t so much forestall the new serfdom as inaugurate a new type of subordination, even if the shape of that new subordination did not resemble Winston Smith kneeling underneath the supersized face of Big Brother. The new subordination was somehow “free” and self-driving, in that all participating agents within the system (each machine, each person) were obligated to induce their own subsidiary statuses within a swirl of contingent encounters. Forget about rugged individualism, everyone seemed content just being a beta. Capitalism had entered its cuck phase. There’s a permanent pecking order, and the market bull is always ahead of you.[10]

This logic of disorder is baked into computer networks. For example, computer protocols like Transmission Control Protocol (TCP) and Internet Protocol (IP) were designed to be open, free, and flexible, not rigid or tyrannical. And indeed they are! If there is a tyranny, it’s a tyranny stemming from the absence of tyranny. Today’s protocols claim to lack any kind of central authority. Of course this is a convenient myth, as new kinds of authorities emerge precisely from an environment bent on excluding authority. Network protocols have de jure authorities in the various international standards bodies such as the IEEE (Institute of Electrical and Electronics Engineers). Networks also have de facto authorities in the small number of behemoth nodes that claim an inordinate percentage of network throughput and computing power. Look up how much of the Internet runs on Amazon Web Services alone; you might be shocked at the result. But the argument goes further than that. Even at the point of breaking up all the monopolies and structurally removing all anti-markets, the control society would remain. Even if we managed to expropriate every billionaire, and got all markets to hum with zero friction, the beautiful disorder of control society would remain. It’s all just random variations of values in an enormous planetary spreadsheet; it’s all just arbitrage within a disorderly parade. Or to borrow the language of psychoanalysis, today’s cyberlibertarians are classic hysterics. They desperately strive to undermine order, while also propping up a new technical regime (if only for the purposes of further undermining it).

Is disorder the best word to describe this? Might disorganization work better? I am trying to put my finger on a specific phenomenon that is old but has accelerated over the last several decades. I see it as characteristically American, from my vantage at least, a phenomenon that combines different tendencies from disorganization and decentralization, to anti-authoritarianism and anti-foundationalism. What ties these tendencies together is a generalized skepticism toward institutions, fueled by a fundamental belief in the power of the individual paired with a skepticism toward others, a skepticism that frequently blossoms into outright contempt. In America, and the American West in particular, these tendencies are inextricable from racism and xenophobia within the political sphere. The wars against American Indians in the Black Hills or the Chiricahua Mountains are not so remote from today’s wars on the homeless in Grants Pass or the Tenderloin. In what Richard Barbrook and Andy Cameron termed “the Californian Ideology,” technology itself might embody these same kinds of carceral exclusions, taking advantage of technologies of disorder to promulgate a structure of mutual contempt, thereby furthering an institution that undermines all institutions.[11]

One of the winners out of all of this has been Ayn Rand, a mediocre novelist who left Soviet Russia for Hollywood America, and whose name is now permanently associated with cyberlibertarianism. During a revealing segment near the start of his BBC documentary All Watched Over by Machines of Loving Grace, filmmaker Adam Curtis chronicled how Silicon Valley has paid homage to Ayn Rand time and again, from the tech entrepreneurs who have christened their daughters Ayn and their sons Rand, to the various consultancies and finance companies with names like Fountainhead or the Galt Group. The profusion of Rands is dizzying: all those CEO sprouts named Rand, Ayn Rand herself, but also the libertarian Rand Paul, mixed together with white papers published by the RAND Corporation.[12]

Curiously, the 1960s counterculture both helped and hindered these developments. Mobilizing a kind of tactical ambiguity, the counterculture both proposed any number of tech-centric utopias, while also experimenting with versions of pastoral communalism that many of the new corporate magnates inherently despised. Golumbia has resolved the ambiguity by highlighting the many rightward tendencies while remaining unconvinced of their putative leftward potential.[13] Hence in Golumbia’s account, tech institutions like the WELL and Wired Magazine, along with figures like Steward Brand and John Perry Barlow, are all harbingers of a creeping conservatism, not innervating indicators of a liberated future.

In resolving the ambiguity, Golumbia assembles a mountain of evidence. Going person by person, he shows that a sizable number of figures from the computer revolution were either proud right-wingers, or ought to be labelled as such by virtue of their affection for Atlas-Shrugged-style libertarianism. By contrast, to enumerate all of the bona fide socialists or communists among the raft of hackers and computer scientists driving cyberculture would produce a very short list indeed. Beyond individual personalities, Golumbia also shows that many of the cherished organizations within cyberculture (such as Wikipedia or the Electronic Frontier Foundation), along with many of the Internet-oriented campaigns of recent years (such as the 2012 campaign against SOPA and PIPA legislation), typically act in the service of new-economy titans in Silicon Valley at the expense of old economy dinosaurs like Hollywood. Whoever wins, we lose.

Many readers will blanch at the details; I even did in certain places, given my interest in open-source software, the hacker community, and other aspects of cyberculture targeted by Golumbia as inherently right-leaning. I fear some readers will simply discard his argument out of hand, not wishing to have their base assumptions tested, as happened with Golumbia’s previous work on the right-wing politics behind cryptocurrencies.[14] In listening to some of the lectures and podcast appearances he gave before his death, Golumbia was actively concerned about the mismatch between the evidence offered and its reception by both his supporters and critics. With patience and composure, but clearly exasperated, Golumbia would frequently note how the Internet elicits a disproportionate amount of goodwill, despite all of its negative and even reactionary tendencies. I just don’t know how much more evidence you need, Golumbia has lamented in different ways on different occasions. In fact, Golumbia was clever enough to scrutinize his own rhetorical disadvantage, ultimately adducing this disadvantage as a piece of the argument itself. According to him, cyberculture entails an inversion between evidence and belief. Hence it is entirely possible for Golumbia’s readers to accept his evidence on rational terms, while also stubbornly believing the opposite. Yes, Golumbia is correct about bitcoin, but I still want to get rich off crypto…. Yes, he’s correct about Google, but I still love my Gmail account. This mechanism of disavowal — yes, but still — allows cyberculture to appear progressive on the surface, while also promulgating reactionary politics at its core.[15] It is a classic instance of ideological inversion. The very thing that users desire is also the thing that undermines them. Or as Golumbia reminds his readers on page after page: beware of geeks bearing gifts!

Indeed, the question of gifts sits at the heart of many of these debates. Economists and legal theorists frequently talk about the advent of the so-called gift economy rooted in the wide circulation of free content online. And one of the founding principles of the open-source movement turns on a claim about gifts, or the lack thereof. Since the 1990s, computer scientist Richard Stallman has been one of the most visible figures in the free and open-source software movement. A technical genius, Stallman is notable for his ability to write compellingly about the topic, while also evangelizing through lectures and other public appearances. Perhaps the most widely quoted passage from Stallman has to do with distinguishing between two senses of the word “free.” “‘[F]ree software’ is a matter of liberty, not price,” Stallman has insisted. “To understand the concept, you should think of ‘free’ as in ‘free speech,’ not as in ‘free beer.’”[16] I recall hearing this line many times during the first Internet boom of the late 1990s. Free speech, yes; free beer no — that was the essence of liberated software according to Stallman and his ilk. It always struck me as misguided. But I guess the ebullience of those years made it feel too petty to debate the point. So at the risk of exposing myself to ridicule, let me be crystal clear today: If we are stuck with Stallman’s perhaps artificial binary, the truly progressive position would obviously be the second option, free beer! One must insist on this. Stallman was devilishly clever to constrain our choices to only these two terms, given how such a framing inherently mocks the progressive position as outrageous and frivolous, like those old conservative tabloids that would satirize the workers’ movement as wanting to make the streets flow with champagne. A sense of liberty is paramount within any healthy society. But the left has always understood freedom through the prism of justice, hence not freedom for freedom’s sake, but rather free social services, free public commons, free health care, free education, and, above all, freedom from the tyranny of private property. Or as Golumbia explains in plain terms: “The roots of open source do not emerge from Marx. Instead, they are more in line with anarcho-capitalists like Murray Rothbard and David Friedman.”[17] (I often wonder whether left tech even exists at all. Has humanity yet invented a communist computer?) To repeat, Richard Stallman made the wrong choice regarding freedom, and the success of his error has negatively influenced the history of software and computing for the last three decades. Or, to cede the thread back to Golumbia, Stallman was wrong, but, more importantly, his being wrong was evidence of his right-wing tendencies.

On this point Golumbia benefits from a certain slippage between political monikers. While many of the antagonists in his book are libertarians, in fact a good portion of them would better be described as mainline liberals, and indeed label themselves as such. The key for Golumbia is to insist on defining liberal in the traditional Lockean sense of individual liberty, private property, and market capitalism, rather than how the label tends to be used in the contemporary vernacular (as a loose synonym for NPR, Volvos, and Elizabeth Warren). Golumbia does this effectively in the book. Yet I sometimes found myself having to rehearse every step of the argument in order for the point to land. Many of Golumbia’s readers will readily agree that Elon Musk and Peter Thiel are political reactionaries; but the proposal is more labored when it comes to Cory Doctorow or danah boyd.

That Musk has described himself as an anarcho-capitalist complicates the discussion a great deal.[18] If Musk is an anarchist too, then, yuck, I will decline association. And yet, while conspiratorial thinking is no doubt enjoyable, particularly when it means putting capitalism in the sights, there’s no anarchist conspiracy taking place in corporate boardrooms, alas. The “anarcho” in anarcho-capitalism is a misnomer of the highest order; Musk & Co. are not anarchists in any real sense of the term. As Golumbia explains with more patience than I could ever muster, anarcho-capitalists do not adopt any of the various principles of political anarchism such as radical equality via the removal of social hierarchy, a rejection of representation in favor of local decision making and communization, Peter Kropotkin’s mutual aid contra Charles Darwin’s survival of the fittest. (Enumerating the principles of anarchism is absurd of course, at least superficially; those made nervous by the listing of principles might prefer to think in terms of tendencies or practices, identified merely to facilitate the very contingency of anarchism, its essential disorder.) And yet so many tech entrepreneurs want to fly the black flag. Do these titans of industry know more than they let on? Do they admit to themselves that capitalism is a corrosive force in society? Is “anarchism” just a sexier word for “disruption” (which itself was a sexy word for all the daily depravities of capitalism)? I already know Marx and Engels’s lamentations on the disruptive forces of bourgeois society, “[a]ll that is solid melts into air, all that is holy is profaned,” and yet I have to hear it again from a bunch of cheery entrepreneurs?[19]

Here’s a guiding principle to help stay mentally balanced: less Tim May and more Todd May. I screw up the names myself sometimes. Todd, the leftist philosopher who first made his mark thirty years ago with a lean and punchy book about political anarchism[20]; Tim, the cypherpunk engineer and low-skill author of the “Crypto Anarchist Manifesto” about techno anarchism. (“A specter is haunting the modern world, the specter of crypto anarchy. … Arise, you have nothing to lose but your barbed wire fences!”[21]) Is it even worth complaining about Tim’s amateurish allusions when the ideas driving them are so repulsive? As Golumbia diligently documents in his book, Tim was virulently bigoted against Blacks, Jews, and Latinos. Golumbia reproduces some of the offending passages in his book — I won’t cite them myself; the quotations are not worth your eyes — but Golumbia’s true task was to show readers exactly why Tim’s bigotry paired so easily with his libertarianism.

I suspect that the fatal flaw of cyberlibertarianism has been to value formal determinations over political ones. By formal determinations I mean the adoption of tools and techniques selected for their specific shape and arrangement rather than due to the political realities they engender. Hence the cyberlibertarian values of openness over closedness, distribution contra centralization, the horizontal instead of the vertical, flows rather than fetters, and rhizomes not trees. Yet the disparaged second terms in this list of pairs are often politically valuable, even necessary. For example, closedness is necessary for privacy, and centralization helps with economies of scale.

Here we may also definitively untangle the unfortunately intimate relationship forged between libertarianism and anarchism in recent decades. Anarchists want a different shape, that’s true, but a shape that directly informs a series of political desires such as mutual aid, anti-racism, collapsing the hierarchy of representation, and so on. Whereas libertarians use a superficial form of anarchism as camouflage to hide what amounts to cynical egoism: I’m an anti-foundationalist because I just don’t want to pay taxes.[22]

What gets overlooked by cyberlibertarians, and frankly by many others including some proper anarchists, is that these arrangements (horizontality, openness, free flows) constitute a system of order like any other. Fickle and free liquidity furnishes no exemption from organization. My dear anarchist comrades—at least some of them–ought to be admonished on this point and this point alone, namely for continuing to believe that anti-foundationalism doesn’t entail its own autonomous form of power and organization. In the end, anarchism is not so much the absence of government or the annihilation of a foundation — arkhe plus the alpha privative — as it is the adoption of a specific set of formal and political virtues (virtues which just so happen to resist established domination and undermine centralized authority). This is part of why disorder has a politics, precisely because it has no inherent political valence, and thus can and should become a site of struggle.

If Golumbia overlooked anything in this long and thorough book it was no doubt the domain of artificial intelligence. I imagine he omitted any serious discussion of AI due to practical concerns; it’s a massive topic and would have compounded the book’s scope and length significantly. Yet AI fits the book’s primary thesis. Current generation AI is inherently cyberlibertarian because it requires enormous stockpiles of putatively free data, unfettered by regulations around copyright or restrictions over ownership. The fair use doctrine has been mobilized as a new form of corporate theft of common resources, so that “free speech” will now alchemically transform into a glass of “free beer,” but only for those culling the data and gulping its value. Marx wrote about “primitive accumulation” at the end of Capital, vol. 1; AI is just the latest wave of this type of accumulation by dispossession.[23] (In fact the theft of value from unpaid micro labor is only the most egregious violation in a long list that should also include the squandering of vast amounts of energy and natural resources. If the overdeveloped nations of the world weren’t hastening climate catastrophe fast enough, we’ve also invented robots to burn additional fossil fuels on our behalf. Suicide by proxy.)

Here too we see a new order forged from disorder. I mean that very literally. Certain types of AI, diffusion models in particular, explicitly use randomness and other entropic phenomena during the process of image generation. Discrete rationality is sterile and deterministic, alas; it may only transcend itself via excursions into more fertile lands, what information scientists call latent space and what Deleuze called the virtual. Computers have long served as a special tool to leverage the distinction between the orderly and the disorderly, to form a bridge between these two domains. And the richest source of disorder is us, the users.

Hannes Bajohr has brilliantly described AI image generation in terms of an “operative ekphrasis,” that is, the use of textual description to summon an image into existence, as Homer did with the shield of Achilles.[24] Everything inside a computer is text, after all, or at least a series of alphanumeric tokens (represented primarily as integers and ultimately as discrete changes in electrical voltage). There are no images inside the beige box, even when it outputs a synthetic picture. And yet the machine accepts commands (i.e. textual prompts) that actualize a single image from out of the near infinity of possible alternatives.

Disorder in technical systems was first defined by one Ludwig Boltzmann. However, “no Boltzmann without Shannon,” as Friedrich Kittler once insisted.[25] The historical causality appears to be reversed. But is it? I imagine Kittler to have meant that the existence of Ludwig Boltzmann in 1877 lead naturally to the existence of Claude Shannon in 1948. And this is no doubt true. The mathematical definition of entropy found in Boltzmann was directly deployed, mimicked even, by Shannon in his definition of information.[26] In other words, disorder has a history, and it has a politics, but it also has a technology. And this disorder technology, this entropy technology, has been central to cyberlibertarianism from the outset. Encryption technology, the killer app of cyberlibertarianism, is simply unthinkable without technologies of disorder, specifically the ability to fabricate high-quality random numbers and the (practical) inability to calculate the factors of large integers. So AI synchronizes with Golumbia’s theme due to the rhetorics of liberation surrounding the extraction of value. But also through the more proximate connection of AI diffusion models that map between low entropy images and high entropy images.

This is what I will retain most from Golumbia’s final work, that while the bobbles and trinkets invented by cyberlibertarians in Silicon Valley, Bangalore, or Shenzhen are touted for their ability to disorder the order of things, such disorder is ultimately a distraction. So here at the exit, let’s exit the concept entirely. Instead I prefer to insist that the apparent disorder at the heart of cyberlibertarianism, along with the apparent anarchy at the heart of anarcho-capitalism, are merely new forms of order. And this new order is also a clearly articulable form of power.

Alexander R. Galloway is a writer and computer programmer working on issues in philosophy, technology, and theories of mediation.  

[1]    See Kevin Kelly, Out of Control: The New Biology of Machines, Social Systems and the Economic World (New York: Basic Books, 1994) and Eric S. Raymond, The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary (Sebastopol, CA: O’Reilly Media, 1999). Interestingly, “cathedral,” as a proper name for the structure of power, has also been mobilized by neo-reactionary authors like Curtis Yarvin.

[2]    David Golumbia, Cyberlibertarianism: The Right-Wing Politics of Digital Technology (Minneapolis: University of Minnesota Press, 2024), 62. Golumbia credits Langdon Winner for coining the term cyberlibertarianism in his essay “Cyberlibertarian Myths and the Prospects for Community,” ACM SIGCAS Computers and Society 27, no. 3 (September, 1997): 14-19.

[3]    On negative liberty (the removal of freedom’s fetters) and positive liberty (the assertion of free conditions), see Berlin’s 1958 lecture “Two Concepts of Liberty” in Isaiah Berlin, Liberty (London: Oxford University Press, 2002), 166-217.

[4]    Friedrich Hayek, The Road to Serfdom (Chicago: University of Chicago Press, 1944).

[5]    Victor Hugo, Notre-Dame de Paris (Paris: Gallimard, 1973), 244-245.

[6]    As Friedrich Kittler reported in an interview: “I was very pleased that Jacques Derrida, during a recent visit to the university in Siegen, actually uttered the sentence (after some questioning): ‘If there had been no computer, deconstruction could never have happened.’” See Friedrich Kittler, “Spooky Electricity: Laurence Rickels Talks with Friedrich Kittler,” Artforum 31, no. 4 (December 1992): 67-70, p. 68.

[7]    Despite being a devoted user of Macintosh computers, Derrida had no real intellectual engagement with computation during this lifetime. Some notable exceptions exist including Béatrice and Louis Seguin’s interview with Derrida, first published in La Quinzaine Littéraire (August 1996) and later included as chapter three, “The Word Processor,” in Jacques Derrida, Paper Machine, trans. Rachel Bowlby (Stanford: Stanford University Press, 2005), 19-32. I engage the relationship between Derrida and computing at greater length in a forthcoming essay titled “What are the Media that Determine Philosophy?”

[8]    See Gilles Deleuze, “Postscript on Control Societies” in Negotiations, Martin Joughin, trans. (New York: Columbia University Press, 1990), 177-182.

[9]    Branden Hookway, Pandemonium: The Rise of Predatory Locales in the Postwar World (New York: Princeton Architectural Press, 1999), 23. Like Golumbia, Hookway also passed away far too young.

[10]   The urge to rank users into a specific set of hierarchical tiers based on captured data is expertly investigated in two recent works of social science: Marion Fourcade and Kieran Healy, The Ordinal Society (Cambridge: Harvard University Press, 2024); and Cédric Durand, How Silicon Valley Unleashed Techno-feudalism: The Making of the Digital Economy, trans. David Broder (London: Verso, 2024).

[11]   For more on what he calls carceral systems, by way of Anthony Wilden’s important early text on digital theory, System and Structure, see Seb Franklin’s essay “The Pattern and the Police: Carceral Systems and Structures” in Parapraxis 4 (August, 2024): 109-128.

[12]   Based in Santa Monica, California, the RAND Corporation was in fact not named after Ayn Rand, but rather as an acronym of “research and development.”

[13]   Golumbia’s own leftist politics hinged on “the political, the social, and the human,” as he puts it in the book’s epilogue (Cyberlibertarianism, 401). Buy this he means fostering a robust democratic state, supported by strong public institutions and an educated citizenry. Golumbia was anti-fascist because fascism threatens that Whiggish ideal; he was anti-capitalist for the same reason.

[14]   David Golumbia, The Politics of Bitcoin: Software as Right-Wing Extremism (Minneapolis: University of Minnesota Press, 2016).

[15]   For more on disavowal as a psychic mechanism see Alenka Zupančič, Disavowal (Cambridge: Polity, 2024). The inverse relation between evidence and belief has also been a part of Slavoj Žižek’s intellectual project for many years. See, inter alia, Slavoj Žižek, The Sublime Object of Ideology (London: Verso, 2009).

[16]   Richard M. Stallman, Free Software, Free Society: Selected Essays of Richard M. Stallman (Boston: GNU Press, 2002), 43.

[17]   Golumbia, Cyberlibertarianism, 24.

[18]   The world’s most visible suck-up, Musk called himself a “utopian anarchist” in a tweet from June 16, 2018, while more recently favoring the descriptors “dark, gothic MAGA” at a Donald Trump rally held on October 27, 2024 at Madison Square Garden. Musk may be MAGA, but, dear reader, he is most certainly not dark, gothic, utopian, or anarchist.

[19]   Karl Marx and Friedrich Engels, The Communist Manifesto, trans. Samuel Moore (London: Penguin, 2002), 223.

[20]   Todd May, The Political Philosophy of Poststructuralist Anarchism (University Park: Pennsylvania State University Press, 2021). May’s argument remains relevant for a number of reasons. I will merely highlight one central feature of the book, how May explicitly characterized French poststructuralism as anarchist. As he put it unambiguously in the final sentence of the book, anarchism is the “most lasting … legacy of poststructuralist political thought” (155). Some will quibble over the deals, and a lot depends on how one defines the boundary of French poststructuralism; May’s references are predominantly Michel Foucault, Gilles Deleuze, and Jean-François Lyotard. But there’s no doubt in my mind that French theory, broadly conceived, illustrates the general migration, evident within leftist intellectual circles overall during the last fifty years, away from Leninism and toward anarchism, away from the red and toward the black. In a recent work, Catherine Malabou has also traced the peculiar relationship between philosophy and anarchism, with reference to both France (Emmanuel Levinas, Jacques Derrida, Michel Foucault, and Jacques Rancière) and elsewhere (Aristotle, Reiner Schürmann, and Giorgio Agamben). See Catherine Malabou, Stop Thief!: Anarchism and Philosophy, trans. Carolyn Shread (Cambridge: Polity, 2023), along with an even more recent book on the question of property in the work of anarchist Pierre-Joseph Proudhon, Il n’y a pas eu de Révolution: Réflexions sur la propriété privée, le pouvoir et la condition servile en France (Paris: Rivages, 2024). Golumbia was disappointed by Malabou’s June 14, 2018 statement in Le Monde titled “Cryptomonnaie, stade anarchiste du capitalisme” [“Cryptocurrency–The Anarchist Stage of Capitalism”], where she explained her interest in cryptocurrencies, and specifically her rationale for endorsing John McAfee’s “Declaration of Currency Independence,” a cyberlibertarian document. In fact a number of prominent leftist theorists have expressed an interest in crypto. See, for instance, Brian Massumi, who in his book 99 Theses on the Revaluation of Value: A Postcapitalist Manifesto (Minneapolis: University of Minnesota Press, 2018) proposed a “maximally non-compromising, postblockchain speculative alter-economy” (20).

[21]   These being the first and last lines of Tim May’s “Crypto Anarchist Manifesto” from 1992 (https://groups.csail.mit.edu/mac/classes/6.805/articles/crypto/cypherpunks/may-crypto-manifesto.html). A whole study could be done on how engineers and entrepreneurs have adopted the literary genre of the political tract, while almost completely inverting the political impulses of the old avant-garde manifestos or revolutionary cahiers de doléances. Another such representative, also discussed by Golumbia, is the “Magna Carta for the Knowledge Age” co-authored by Esther Dyson, George Gilder, George Keyworth, and Alvin Toffler. This new Great Charter of Liberty opened by asserting that “[t]he powers of mind are everywhere ascendant over the brute force of things,” before lapsing into a fairly predictable form of pro-market libertarianism. See Esther Dyson, et al., “Cyberspace and the American Dream: A Magna Carta for the Knowledge Age” (http://www.pff.org/issues-pubs/futureinsights/fi1.2magnacarta.html).

[22]   Which prompts the necessary inversion: I’m an anarchist, and I do want to pay taxes. In other words, the best kinds of anti-foundationalism revolve around an invigorated sense of responsibility and commitment, not the general dissolving of social bonds. See, for instance, Kristin Ross, The Commune Form: The Transformation of Everyday Life (London: Verso, 2024).

[23]   In the first new English translation in fifty years, Paul Reitter has opted instead for the phrase “original accumulation,” arguing that it is closer to the original German while also avoiding unnecessary connotations suggested by the word “primitive.” See Karl Marx, Capital: Critique of Political Economy, vol. 1, trans. Paul Reitter (Princeton: Princeton University Press, 2024), 650 and note i on 836-838.

[24]   See Hannes Bajohr, “Operative Ekphrasis: The Collapse of the Text/Image Distinction in Multimodal AI,” Word and Image 40, no. 2 (2024): 77-90. According to Antonio Somaini, this kind of operative ekphrasis “does not describe pre-existing images but rather generates images by pre-describing them” (Antonio Somaini, “A Questionnaire on Art and Machine Learning,” October 189 [Summer 2024]: 112-120, p. 115).

[25]   Friedrich Kittler, The Truth of the Technological World: Essays on the Genealogy of Presence, trans. Erik Butler (Stanford: Stanford University Press, 2013), 183.

[26]   Indeed Kittler was less ambiguous elsewhere: “[Boltzmann’s] entropy formula is mathematically identical to Shannon’s later information formula” (see Friedrich Kittler, Optical Media: Berlin Lectures 1999, trans. Anthony Enns [Cambridge: Polity, 2010], 125). Although “mathematically identical” is imprecise even if Kittler’s sentiment was correct overall: Shannon’s formulation omits the Boltzmann constant, it uses log base two rather than the natural log (in base e), and it entails a summation of probabilities.

The Last Manager (Review of Craig Gent’s Cyberboss: The Rise of Algorithmic Management and the New Struggle for Control at Work)

Marc Kohlbry

The common man wasn’t nearly as grateful as he should be

for what the engineers and managers had given him.

—Vonnegut (1952, 220)

In early 2024, Bill Anderson, CEO of the pharmaceutical giant Bayer, took to the pages of Fortune to announce the end of management. Citing the difficulties posed to sustainable growth by cumbersome workplace bureaucracy and hierarchies, the op-ed details his company’s plan to fundamentally restructure 100,000 positions across its various business units. Under the banner of “Dynamic Shared Ownership,” Bayer will do away with 99% of its 1,362-page corporate handbook in hopes of becoming “as agile and bold as a startup” (Anderson). In its absence, employees will “self-manage,” forming “self-directed teams” endowed with the freedom to select new projects every 90 days and to sign off on one another’s ideas along the way—all “without a manager in sight” (Royle). This “radical reinvention,” he promises, will “liberate our people” and save the company upwards of $2.15 billion, notably by first liberating thousands of middle managers from their employment contracts.[1]

While Anderson’s op-ed stops short of clarifying exactly how these self-directed teams will cooperate to achieve Bayer’s corporate goals (an equation typically solved by managerial personnel), a more recent New York Times article, “If A.I. Can Do Your Job, Maybe It Can Also Replace Your C.E.O.,” indicates what the means to such ends might be. There, journalist David Streitfeld suggests that emerging technologies, namely those driven by generative AI, stand poised to take over executive decision making by analyzing new markets, discerning trends, and communicating with colleagues. “Dark factories, which are entirely automated,” he ventures, “may soon have a counterpart at the top of the corporation: dark suites” (Streitfeld 2024).

The rationale behind these structural shifts is simple enough: because middle- and upper-management positions are highly compensated, eliminating them can result in considerable savings for employers. Faced with a growing market bubble[2], companies like OpenAI might see in this an opportunity to deliver shareholder value by developing products capable of carrying out supervisory tasks and of supporting (that baleful corporate euphemism) workers’ efforts to manage themselves. As one former IBM consultant notes, the change delivered by AI in corporations could accordingly be “as great or greater at the higher strategic levels of management as [in] the lower ranks” (Streitfeld 2024). Indeed, for some, replacing managers with algorithms or LLMs appears as common sense: “[s]omeone who is already quite advanced in their career and is already fairly self-motivated may not need a human boss anymore,” intimates Phoebe V. Moore, a professor of management and author of The Quantified Self in Precarity: Work, Technology and What Counts (Routledge, 2017). “In that case, software for self-management can even enhance worker agency” (Streitfeld 2024).

*

But what might such changes actually mean for work and those who carry it out? Put otherwise, in taking up the managerial function, are information technologies truly capable of enhancing worker agency? Craig Gent’s Cyberboss: The Rise of Algorithmic Management and the New Struggle for Control at Work—an adaptation of his 2018 doctoral dissertation—responds by offering readers a powerful and timely excavation of how new workplace technologies are in fact making workers of all stripes less free—“not by chance but by design” (Gent 2024, 3). This “design,” Gent conveys across the text’s six chapters, is propped up by “algorithmic management,” “a way of organizing work in which workers are directed, monitored, tracked and assessed—all at once, in real time—by a computer system that doesn’t rely on a human manager to control it” (3-4). In an observation that recalls the motivations behind Bayer’s $2.15 billion experiment in self-management, Gent notes that, “for most practical work, human workers are simply cheaper, more reliable and easier to replace than robots” (4). Managers, it turns out, are not.

Building on this logic, Cyberboss takes stock of the true consequences of work under algorithmic management, where “poor employment protections, high workloads and advanced technology conspire to create high-turnover jobs that come with a harsh toll of mental and physical exhaustion” (3). By concentrating his attention on these dynamics in the (UK) logistics sector (while acknowledging that they define the gig-economy as a whole), Gent identifies that the core goal of Cyberboss is to—as its epigraph from Mark Fisher would have it—“destroy the appearance of a natural order” held together by algorithmic power.

In Chapter 1, “The Stakes,” Gent outlines three analytical strokes for fulfilling this goal. In the first, his study seeks to demystify the aforementioned natural order by tracking how contract workers are compelled to work in accordance with “objective” standards set by seemingly infallible calculations and analytics (3). Second, Cyberboss looks to illuminate a crippling blind spot of the contemporary labor movement, whose myopic focus on contract recognition and related concession that a company’s “right to manage” is “its business alone” both foster the unchecked exploitation of “flex” workers that is itself operated by management and workplace technologies (13). Finally, Gent endeavors to counter extant scholarship on algorithmic management in particular and gig-work more generally by identifying the limitations of calls for such technologies to be made more “transparent,” “explainable,” and “human-centered”; emanating from academics and trade unions alike, these demands, he will later insist, fall short by proposing a “technical solution to a political problem” (23).[3]

According to Gent, what is needed instead is a “political understanding of algorithmic management on its own terms” (8). Yet, “it is important not to disappear into the abstract,” he cautions (23). Instead, “[b]ecause the politics of algorithmic management is so intimately entwined with the organisation of work, it is necessary to show how such workplaces function in practice” (23). To do so, Cyberboss concerns itself “more with discipline and management” than with wages or the effects of material precarity outside of the workplace (11). In sum, Gent explains, “I want to question what the stakes are for workers and work, and what it means for technologies of control and communication to be sites of struggle and contestation” (12). This line of inquiry ultimately permits Cyberboss to generatively account for how “workers are being managed by computers rather than replaced by them” “on the basis of cybernetic feedback loops” (6), then to reveal how workers are fighting back outside of the traditional organizational structures of the labor movement.

To fully grasp how Gent arrives at these conclusions, it is instructive to read ahead to Cyberboss’s fourth chapter, “Technological Politics.” In this somewhat belated methodological introduction, Gent surveys several dominant views of technology’s relationship to sociopolitical dynamics. Judging “technological determinism,” “social determination” (109), and the “economic view of capitalist innovation” (113) as insufficient, he instead privileges a “theory of technological politics” aimed at accounting for the “political dynamics—in other words, class relations—that are immanent to technology” (114). In lieu of “saying technology is determined by political dynamics,” this perspective focuses on how “the scale, design or organisation of certain technical arrangements can engender technological imperatives that command particular social responses” (115).

Rather than target capital’s conceptual abstractions, structural dynamics, or technical artifacts, Gent leans on the theory of technological politics to construct a markedly ethnographic methodology (119). “Uncovering the conflictual political interests that have been concealed, circumvented or naturalized,” he argues, “requires empirical investigation with the aim of showing that labour is never completely subordinated to capital” (132). The point, he continues, is not simply to understand relations of power, but to empower workers by unconcealing the “ongoing contingency of class struggle from within work, quite aside from any sweeping structural principles or managerial ideals we might identify” (133). Taking as a point of departure the so-called Trontian inversion—or, the insistence on “the primacy of working-class struggle within the development of capitalism”—Gent grounds Cyberboss in autonomist Marxism’s insights about how “the working class has political agency regardless of the conditions imposed upon it by either capital, the state, or traditional political vehicles such as trade unions or workers’ parties,” all while emphasizing workers’ ability to contest the dominative power of capital (117, 120). Indeed, he maintains, “the indeterminacy of technology […] leaves open the possibility that workers will contest managerial techniques as implemented through specific technologies” (123). With his sights set on the “indeterminacy” of algorithmic management, Gent finds in autonomism not only a political framework that registers how “technology is always subject to ongoing class struggle,” but a set of concepts and tools with which to effectively “develop an account of technology at work” (120).

Among these, Gent singles out the workers’ inquiry (as developed by Romano Alquati in 1975’s Sulla FIAT) for its ability to trace “class composition,” a move that turns back the clock on post-operaismo by framing ethnography as a means of explicating particular sites of class struggle rather than zooming further out in an attempt to assess the composition of the working class as a whole (137). By centering pickers in UK distribution centers as well as couriers working for similar facilities or on lean platforms, Gent skillfully explicates how “capital and the working class are specific but relational” (130) by analyzing algorithmic management technologies as both “a prism through which to understand contemporary class struggle and an under-studied component of regimes of ‘control’ in contemporary workplaces” (137). Workers’ inquiries form the core of these analyses; however, they also serve as dynamic supplements to Gent’s assessments of the intellectual histories, media objects, and conceptual abstractions that gave rise to and continue to fuel algorithmic management. Woven together, these threads forcefully clarify the concrete fallout of this managerial mode as well as the forms of worker resistance that have risen to counter it.

A pivotal moment in this approach comes in the third chapter of Cyberboss, “Management,” which details how algorithmic management “combines three key traditions in management thought: the scientific, the humanistic and the cybernetic” (65). Beginning with the observation that management is, “in its essence, a political project” representing “a formal and intentional division of power, information, communication and control in the workplace” (64), Gent momentarily brackets out the question of digital technology to trace the means and ends of the managerial function both historically and in the present. He begins by surveying the tradition of scientific management promoted by Frederick Winslow Taylor at the turn of the twentieth century. Understanding labor power to be a commodity that, when purchased, merely offers the potential for labor, Taylor identified the goal of management as the actualization of that labor power (68). The defining feature of this approach—or Taylorism—would ultimately be its deskilling of manual labor and subsequent separation of the conception and execution of work. This design made managers responsible for “applying detailed measurement to each element of work” (67). Under Taylorism, then, the managerial conception of labor consists of “the knowledge and planning of the labour process, the development of strategy” (76), while its execution is the eventual cooperative labor of workers themselves. Critically, the “knowledge put into the process by managers is initially gleaned” from the workers, which enables supervisors to “generate [the] general rules and targets that will govern the work process” (76-77).

Gent continues his survey of capitalist management by registering an important corrective made to Taylor’s thinking by Frank Bunker Gilbreth, Lillian Moller Gilbreth, and Elton Mayo. In Gent’s retelling, this shift represents the “humanistic tradition,” which belies the realization that scientific management need indulge “the human factors of the labour process” (73). Together, these thinkers urged managers to concentrate on developing affable, personal relationships with workers in order to create “social units” in the workplace; Mayo, in particular, would identify sociality as workers’ primary motivation (73). This tradition would reach its apogee in the years following World War II, largely thanks to management innovations in Japan led by Yoichi Ueno and later by Taiichi Ohno, the father of Toyotism, lean manufacturing, and “total quality control.” These markedly humanistic upgrades to Taylorism, Gent explains, would break with the idea of a perfectible system by instead insisting on the continuous refinement of the labor process over time, or kaizen in Japanese (81).

To these interrelated approaches, Gent adds an important third: the “cybernetic tradition,” whose principal feature is “the use of feedback loops to control or steer a complex system (in this case, a workplace)” (6). This name—from which Cyberboss draws its titular prefix—points to both total quality control’s roughly cybernetic nature as well as to the management theories that grew from the seeds sown by Norbert Wiener’s foundational 1948 text, Cybernetics: Or Control and Communication in the Animal and the Machine. “As an adaptive, continuous system,” Gent clarifies, “total quality control retains ideas from scientific management about the reformulation of knowledge to produce targets, but adopts a more holistic, and arguably cybernetic, form: beyond work rates, [it] is concerned with managing work relations through communication and delivering wide control to management through attention to intra- and inter-departmental dynamics” (82). “Cybernetic” management thus creates a company-wide circuitry of feedback-based control (called a “quality-control circle”) through which “management can control various aspects of the work process by communicating with workers and encouraging their cooperation” on the basis of the information gathered from those workers as they carry out their tasks (83-84).

Further on, Gent turns to certain core thinkers of “cybernetic management” (namely Stafford Beer) to detail how, in viewing the firm as a cybernetic feedback system, this third tradition shirks purely hierarchical control and total knowledge of the work process to instead “exercise control […] by virtue of [managers’] position within communicative flows” (96). To illustrate how this approach underpins “algorithmic” management, Gent observes that the scanning guns used by Amazon pickers mediate a process of informatic feedback. While “the separation of conception and execution persists” and management was “still present [there] in a number of ways,” these Motorola WT4000 scanners would dictate to workers the next item to be picked all while displaying a real-time evaluation of their performance (88-91). Behind the scenes, the interface was tracking and collecting performance data and in turn using that information to adjust the labor process in keeping with established productivity targets. Yet even though (or because) “[n]o one could say how the […] targets were set” (101), each data-driven adjustment appeared as neutral, objective, rational, and, above all, “beyond question” (99-100). Further, while these workers at times would intermittently interact with a human manager, they were more often in communication with “the system,” another name for “a computer database (or databases) that manages stock or order progress, tracks the work of employees, time-stamps activity, calculates performance and assigns new tasks where necessary” (101).

These ethnographic observations lead Gent to a series of sweeping theoretical conclusions about algorithmic management. In addition to drawing on “the separation of conception and execution advocated by Taylor and the continuous improvement impulse of kaizen,” digital tools such as the scanner mediate “performance-orientated feedback loops” all while introducing “new dimensions to the workplace that force us to rethink what communication and mediation mean at work” (105-106). In the logistics sector, these “new dimensions” weigh on managers and workers alike. For the former, technologies like the scanner maximize worker efficiency by leaving the calculative aspects of conception to algorithms, which frees them up to smooth out any kinks in the labor process through direct communication with workers. For these workers, the execution of labor comes to resemble what Jamie Woodcock calls the “algorithmic panopticon,” or a form of workplace governance without a physical managerial presence wherein interaction with digital interfaces and platforms contributes to a “feeling of being constantly tracked or watched” (107).

Nevertheless, Gent insists that the control posited by this “algorithmic panopticon” is illusory, a position that he defends across the chapters “Algorithmic Work” and “Algorithmic Management.” In a way, these chapters take up the division of labor proposed by Taylorism, but in reverse: the first focuses more on descriptions and analyses of the execution of labor in the logistics sector, whereas the second concentrates on the means and ends of its conception (though, given Cyberboss’s privileging of workers’ perspectives, there is considerable overlap between the two). These examinations support Gent’s reasoning that “the principal idea governing contemporary logistics is to minimise ‘waste’” by (in part) ensuring that workers are as “productive as humanly possible” (16-17). This is where algorithmic management steps in: by assigning, administrating, measuring, and assessing this work in real time, its technologies

cover the allocation of work, the direction of the employee towards particular items, the employee’s performance against a pick rate (itself set by the algorithm according to online order traffic), and the direction of supervisors towards workers who fail to meet targets. In such cases, algorithmic tracking and decision-making are either augmenting or replacing the traditional managerial or supervisory function. (26-27)

Such an approach reduces logistics workers to a series of data points, or information, which is then measured on the basis of productivity targets and surveillance before being “fed back” into the system to maximize efficiency (and discipline workers who underperform) (28).

To demonstrate how this takes place in the logistics sector, Gent elaborates specific forms of media that render workers as “tools of the algorithmic system” (40). Hardly dead media, the scanner, the barcode (41-42), digitally-augmented goggles (42), and even VR headsets (44) enable management to control individual workers by “transforming each […] into an embodied real-time data tracker” (42). The information gathered by such devices facilitates this determination in two movements. First, it allows “the system” to determine which workers will work and when; “[l]ike the goods in the warehouse, [these] workers are forever just-in-time” (152). Second, once workers are on-site, this same data is used to subject them to circular work patterns (a more concrete feedback loop), the instructions for which are set computationally and displayed on the digital devices themselves (147). “Much of the skill involved in successfully carrying out the work,” Gent goes on to highlight, “boils down to successfully acting on the basis of a digital interface” (149). This has the upshot of focusing workers’ attention on hardware and thus of minimizing communication between them (157). To prevent a total breakdown in sociality, then, the role of actual managers shifts toward “humanistic intervention” capable of ensuring that work (and its improvement) remains a “continuous process” rather than a “goal-oriented sequence” (169, 160). In sum, while “algorithmic management operates within a Taylorist paradigm, it signals a key development in terms of its ability to decentralise the managerial endevour by distributing power across the workforce in a more democratic way, but by way of a digital media infrastructure within which real-time cybernetic feedback loops produce a more generative form of control” (171).

This new reality, Gent warns in “Guile Against Adversity,” “poses significant issues for how we think about the capacity of workers to exercise agency within the work process” (173): increasingly faced with a system able to “fill gaps in labour” and “redirect work processes to other locations in real time,” “we can no longer rely on forms of political mobilisation that have become our common sense” (176-177). Rather than lay plans for a future political strategy (predicated on unions, strikes, and so forth), this final chapter focuses on contingent employees’ resistance to algorithmic management in “actually existing workplaces” (203). Reframing instances of “everyday resistance” and “organisational misbehavior” (178) as “metic resistance” (201), or “workers’ guile,” Gent highlights “the use of situated wisdom and experiential cunning to seize or subvert, even momentarily, the current of managerial control” (203). But while such acts[4] are capable of “reappropriating personal dignity,” Cyberboss’s author also acknowledges that it remains an open question whether metic resistance—as well as the new forms of worker sociality and “chains of discovery” that make them possible (which he terms “metic commonality”)—can be “scaled up or generealised across a workforce as part of a collective endeavour” (198, 205). Still, “[b]y thinking about resistance in terms of metis,” Gent maintains, “we are forced to consider the situatedness of political action away from ideal types, such as those found in the organiser’s repertoire” (205).

Beyond its contributions to our understanding of the gig economy and provocative assessments of the emancipatory possibilities available to workers under algorithmic management, Cyberboss also makes crucial interventions in pressing social-scientific conversations at the nexus of political economy and digital culture. Importantly, the text grounds scholarly interest in the logistics sector (as both a site of exploitation and a possible choke point for resistance) in what one might call a social history of algorithmic management—that is, a theorization of technology’s relationship to the capitalist division of labor rooted in actually existing workplaces rather than in idealism, however cogent its political leanings. This perspective informs Gent’s skepticism of “[a] growing number on the left [who] wish to see social movements emerge around the logistics sector” (60), which later leads him to conclude that locating the strategy of “fault lines and weak points” in logistics “falters against the scale of [algorithmic] managerial control” (202). One could certainly be persuaded by this point in taking seriously Cyberboss’s arguments; however, Gent’s account is also a complementary rejoinder to work on this subject by Aaron Benanav, Jasper Bernes, or Søren Mau, who have made incisive points about how, under capitalism, “mobility is power, and means of transportation and communication are weapons.” (Mau 2023, 273). To these more structural positions, Gent lends the voices of workers to reorient conversation toward, in the context of logistical power, what it is that’s to be done—though stops short of leveraging this essential move into an affirmative elaboration of the kinds of broader, coalition-based strategy that will be necessary to effectively fight back.

Elsewhere, Cyberboss generatively nuances certain of Mau’s arguments about “economic power,” or that which is “not immediately visible or audible as such, but just as brutal, unremitting, and ruthless as violence; an impersonal, abstract, and anonymous form of power immediately embedded in the economic processes themselves rather than tacked onto them in an external manner” (Mau 2023, 4). Importantly for the present purposes, Mau postulates that management, or“[t]he authority of the capitalist within the workplace,” is the mere “form of appearance of the impersonal power of capital”; formulated otherwise, “[t]he despotism of the workplace is nothing but the metamorphosis of the impersonal and abstract compulsion resulting from the intersection of the double separation constitutive of capitalist relations of production” (233, italics in original). By this token, Cyberboss brings Mau’s cursory insights about how the managerial function directs economic power to bear on the question of algorithmic power, in turn pointing the way to a fuller understanding of how technology might mediate “mute compulsion” in the digitized workplace along “multifarious points of communication” (Gent 2024, 170). If “management at work is the primary means by which most people experience the phenomenon of capitalism in daily life” (65), Gent’s arguments suggest that, by replacing managers with technologies aimed primarily at the production of surplus value, algorithmic management presents workers with an experience of the value form that is paradoxically more abstract and concrete than that animated by previous managerial modes—more abstract because it is immaterial and non-human, more concrete because it offers a less mediated experience of the abstracting movements of capital. Here, more concentrated study of the place of technology in capital’s abstract domination of the concrete—particularly in the context of managerial practice—appears as particularly urgent.

Gent’s study also vitally reasserts the centrality of management for cybernetics (and vice-versa), a point of convergence that is among the most enduring afterlives of the science; indeed, before migrating into anthropology, linguistics, or “French theory,” this model for communications engineering was motivating managerial thought and practice.[5] Read in this context, Cyberboss’s focus on “actually existing workplaces” provides a materialist explanation for the cybernetic underpinnings of contemporary capitalism, a welcome supplement to more recent studies of the ideological impact of the science of communication and control on neoliberal economics.[6] On this basis, Gent’s discussion of cybernetics underscores the need for research into how the science’s successive historical stages—i.e., first-order, second-order, or, later and by extension, systems theory—respectively modified the coordinates of the “scientific” and “humanistic” managerial traditions to which Cyberboss so urgently draws our attention.

Further afield, Cyberboss should provoke similar (if perhaps uncomfortable) questions for scholars in the humanities. There, it is no secret that “cybernetic” thought has served as inspiration for a range of fields from posthumanism to poststructuralism thanks to the “ontology of unknowability” (Pickering 2010, 23) typically associated with cybernetics’ more reflexive second wave. With this in mind—and following Gent’s lead in registering that this same ontology has enabled capital to actualize labor power since the mid-twentieth century—one wonders about the extent to which some strains of humanities research have been unknowingly trafficking in managerial discourse for what would now amount to decades. Such a line of inquiry is only complicated by the fact that management scientists themselves have long-since realized the use value (and not simply the exchange value) contained in the thought of Michel Foucault (McKinlay and Starkey 1998), Gilles Deleuze (Linstead and Thanem 2007), or Judith Butler (Tyler 2019), as well as in certain fields often assumed to be the exclusive province of humanistic inquiry (de Vaujany et al. 2024).

*

Without undercutting its arguments or diluting its many contributions, Cyberboss ends abruptly. A three-page epilogue briefly addresses the topic of artificial intelligence by glossing the 2023 Writers Guild of America (WGA) strike and the demands made therein for the curtailment of AI use across the film industry. “The WGA,” Gent suggests in closing, seems to have understood what “other unions ought to”: “the infeasibility of leaving technology within the realm of corporate decision making” (Gent 2024, 211). Rather than content ourselves with this nod to generative AI, however, we should push Gent’s study further to illuminate the futures of work and component forms of exploitation that these technologies may make possible—some of which are already upon us.

In early 2024, I received an unexpected job offer. The position—for which I had not applied—was that of an AI model evaluator with a company that I’ll call “Mute.” This was an opportunity, I read with some confusion, to “shape the next generation of AI with [my] expertise” while “enjoying the flexibility to work where and when” I wanted. Puzzled yet intrigued by how I might do so with a background in comparative literature, I accepted.

It was not long before I discovered that the management of this work (which Mute refers to as “tasking”) was entirely algorithmic. Once I had created an account on the company’s platform and completed the necessary “enablement” modules, the system assigned me to a project, the two pay rates for which (one for “project” tasks and another for “assessment” tasks, themselves indistinguishable in all but name) were both conspicuously lower than the promises of Mute’s initial proposition. Undeterred, I clicked the “Start Tasking” button and a new interface appeared: at the top of this window sits a timer (typically longer than the maximum amount of time a user can be paid for—a detail buried elsewhere in a project description footnote) alongside a reveal of the task type at hand.

For this first “Rewrite” project, Mute’s system instructed me to evaluate and improve single- and multi-turn LLM (large language model) responses according to the assessment categories of “instruction following,” “concision,” “truthfulness,” “harmfulness,” and the vaguer “satisfaction” (a catch-all for any issues that fail to fit neatly into another category). To move from one stage of a task to the next, I was required to “Verify” my recommendations by fixing any issues flagged by a series of inscrutable, AI-powered plug-ins.[7] Once my suggestions had been approved by these digital managers, I could “Submit” the task for evaluation by an anonymous “Reviewer”—a role, I learned following a later algorithmic reassignment, whose own tasks are evaluated by still other taskers using an identical 1-5 Likert scale. Regardless of one’s project or role, these scores contribute to an “Average Task Score,” which the system then uses to compute pay rates and assign future tasks, projects, and, if one is lucky, “bonus missions.”

The managerial function animating this division of labor operates horizontally: thanks to the system’s opaque algorithms for allocating and evaluating tasks, each tasker is unknowingly managing the work of another. But this same process is also circular: because their communication occurs textually and is mediated by standardized assessment categories, Likert scores, and other veiled parameters, taskers are transformed into algorithmic managers; cloaked in code, they become indistinguishable from the LLMs they are training (who are training them in turn). This is evident as soon as one completes a first unpaid “enablement” program, at which point they are asked to assign it a rating between 1 and 5. Within this circuit, the question of whether tasks are being evaluated by a human or an AI (or, if they are being used to evaluate the work of one or the other) is thus irrelevant.

While tasking on Mute is a solitary endeavor, it is still possible to communicate with fellow workers by clicking on a tab labelled “Community.” Doing so will launch an embedded Discourse forum featuring locked threads with updates and reminders about the project(s) to which one is assigned as well as open threads seemingly meant for more casual exchange. Among these is the “Watercooler Thread,” a name that cruelly parodies the social relations that have been dissolved by the machinations of algorithmic management. Indeed, every move on this platform is destined for capture and optimization; in Mute’s “Community,” for instance, taskers’ scrolling and keystrokes are tracked and calculated into a “Trust” level that will determine the threads and features (including personal messaging or the ability to post links) to which they have access.

This brief window into Mute’s algorithmic management highlights the explanatory power of Cyberboss—even while revealing certain of its limitations. Though not pickers or couriers, for example, Mute’s workers are similarly directed, monitored, tracked, and assessed by non-human agents in real time. And, much as Gent describes of Amazon or Deliveroo, this company’s “system” facilitates the resulting flows of data through feedback loops intended to actualize labor power. In the absence of any discernible human supervisor, however, here AI stands in as the tasker’s last manager, creating an algorithmic panopticon wherein each is the source and subject of an automated mode of control. Alarming, too, is that the sociality shaped by Mute’s platform limits workers’ ability to fight back more comprehensively than a logistics facility might with its scanners and barcodes; for instance, even if taskers dream of staging a slowdown or mass log-off to improve their working conditions, every channel (and water cooler) for metic commonality is already subsumed by the system’s gaze. In difference to the logistical distribution of material goods that Gent analyzes, then, the algorithmic power governing Mute’s immaterial labor is hardly an illusion; rather, it is totalizing, a “quality-control circle” wherein each worker is compelled to (self-)manage.

On a more speculative level, the possible ends of this self-management complicate Gent’s conclusions about the impossibility of automating the managerial function altogether. In sum, Mute’s evaluators are carrying out the microwork that maintains LLMs’ veneer of “intelligence,”[8] including editing responses for grammar and syntax, identifying and correcting hallucinations, and generating datasets through which such tools might be trained to better respond to contextual and affective cues. The technical name given to this more general form of labor—which, as one of my Mute training modules clarified, draws on taskers’ “human knowledge and expertise” to craft products “far superior to an AI like ChatGPT”—is unmistakably cybernetic: “reinforcement learning from human feedback,” or RLHF.

But what of the products that these efforts might generate, and to whom could they be sold? After first being contacted by Mute, I quickly gleaned that the company is the labor-supplying subsidiary of a much larger B2B firm who counts OpenAI, Meta, Microsoft, and Nvidia among its clients. To prevent the most recent tech boom from becoming a bust, organizations like these have begun searching for ways to deliver AI solutions to businesses that will ensure model accuracy, secure company and customer data, minimize response bias, and, above all, feel irrefutably human. One path to this is the increasingly popular “retrieval-augmented generation” (RAG) approach, which allows the LLMs that it powers to retrieve information that is external to the datasets upon which they’ve been trained. In theory, AI infrastructures grounded in RAG can provide accurate and secure LLMs tailored to companies’ “enterprise resource planning” (ERP), “customer relationships management” (CRM), and “human capital management” (HCM) systems and needs. Conceivably, then, Bayer could hire Mute’s parent company (or one of its marquee clients) to build a RAG-powered LLM based on customized HCM datasets and the protocols laid out in their 1,362-page corporate handbook. By actualizing the necessary labor power correctly and at scale (e.g., by way of RLHF)[9], Mute’s algorithmic management could present IG Farben’s heir with its own algorithmic means of hiring, onboarding, and directing workers—or, of taking up the role of “humanistic intervention” to communicatively support self-management, much as AI is already doing for those of us on Mute’s lean platform.

Nevertheless, it would be a mistake to hastily conclude that the algorithms fueling generative AI models and other digital technologies will soon (or ever) be capable of fully automating the role of management. This natural order Gent only partially decodes: because such objects will always require a self-organizing subject[10], we must summon whatever guile we can—together with the lessons of Cyberboss and the future work it should inspire—to collectively resist becoming our own last manager.

Marc Kohlbry received his PhD in comparative literature from Cornell University in 2022. His research centers on the intersections of literature and media, digital culture, and political economy and has been published or is forthcoming in such journals as Social Text, New Literary History, and Cultural Critique.

Thanks to Sam Carter for his incisive reading of a previous draft of this essay.

[1] Shoring up stock valuations by cutting managerial positions is hardly novel, let alone “radical.” In 2023, for instance, middle managers—i.e., nonexecutives who oversee other employees—accounted for almost a third of global layoffs, with notable cost-saving measures being implemented at Meta, Google, Citi, and FedEx (Olivia 2024).

[2] See Cahn 2024.

[3] Relevant examples can be found in Rosenblat 2018, Aloisi and de Stefano 2022, and Ajunwa 2024.

[4] These include “the exploitation of menu options to bring about breaks; the stealing and sharing of supervisors’ codes or computer log-in details; use of the knowledge of what supervisors can and can’t know, and how busy they will be at a given moment, to amuse oneself and create problems for the stock database; defiance of the narrow forms of communication demanded by interfaces; the shared experience invoked in slowing down to 70% of productivity, reasserting workers’ autonomy over performance; [and] the ingenuity of testing new equipment in order to find new ways to subvert it” (Gent 2024, 207).

[5] For evidence of this, one might look to Norbert Wiener’s comments on industrial management (briefly discussed by Gent 2024, 12) as well as to Beer 1959.

[6] For examples, see Hancock 2024, Oliva 2016, or Haplern 2022.

[7] Frequently, these algorithmic management tools claimed that “AI [had been] detected” in an entry, an issue that I could “Agree and Fix” or “Decline”—there is no third option for informing the LLM that it was, in fact, mistaken.

[8] See also Altenried 2020, Crawford 2021, 53-87.

[9] At the time of this writing, these efforts—and any resulting profits—still seem out of reach. See Sam Blum’s recent reporting on the subject for Inc.

[10] Still, the automation of management strikes me as somewhat more feasible than the “proletarianization” of artificial general intelligence (AGI) (Dyer-Whitheford et al. 2019, 135-138). For my thinking on the means by which digital interfaces might facilitate the former process, see Kohlbry 2024.

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