Digital Transition/Neural Capitalism of the Brain: What Can Art Bring?

For a Living and Moving History of Cognitive Capitalism

As I have pointed out in my book Cognitive Capitalism (2007), in the years 1975–1995 capitalism experienced its biggest change since the Industrial Revolution (1750–1820), much bigger than its transformation between the 1920s and its regime of Fordism and the welfarist state.¹ The industrial system made labor its primary commodity and was far more efficient at producing value than the mercantilist capitalism that preceded it. Its model was based on the labor power of workers who sold their labor, then restored it and sold it again the next day. This old pattern applied very well to physical force: the muscle is charged with energy and burns a given amount of sugar per hour, until it is discharged and becomes tetanized, preventing any further work. The operation of the exploitation of labor power was therefore very simple to understand because it was binary: activity/rest. It was also quite easy to contrive the body through corporal discipline (through thirst and hunger) enhanced by the machine.

The problem is that this classical analysis no longer applies to the current system based on intellectual work and immaterial labor. The specificity of cognitive capitalism is to incorporate more and more immaterial knowledge and services into its economic model. To function, it does not need muscle power, but brain activity. The body has, indeed, not disappeared. “The workers’ role in the shift from industrial capitalism to cognitive capitalism does not relinquish the body totally but rather refocuses the circuits of its embodiment according to an alternative logic.”² But the brain never stops working, even at night. Many people have experienced this with telecommuting or endless nights watching Netflix series. Unlike muscles, a brain is never at rest and a flat electroencephalogram is synonymous with death. Moreover, brain activity cannot be forced. You can physically force people to follow a particular cadence and coordinate on an assembly line, but you can’t force brains to cooperate. Attention (like trust, love, and all the feelings that govern interactions between people) cannot be fixed by a flow chart or a contract. This is the problem of the teacher who helplessly watches his or her students become disengaged: How to ensure that their attention does not wander? Only care can accomplish this.

In order for brains to produce continuously without rambling, cognitive capitalism has therefore developed ways of capturing and keeping attention (the importance of which has been stressed by Yves Citton³), and it has tools that are much more refined than contracts. Social networks, for example, use very insidious design elements to play on our gregarious nature, our cognitive biases, and our taste for randomness in order to make us stay on the application as long as possible. Cognitive capitalism is thus based on capturing positive externalities. This is exactly what is happening with bees: for a long time, we focused on the sale of honey or wax (the finished products) before realizing that their most productive activity was actually pollination, which has between 500 and 5.000 times more value than honey! So, our leisure time has become productive. The system is able to appropriate the many positive externalities generated by our most insignificant activities: our attention, our ingenuity, our interactions. Even our simple searches on Google or Firefox or Safari are ways to produce value. It is also thanks to this that we can access those ultra-sophisticated services for free.

This new capitalism considerably enlarges the mass of people who are active. The activity of individuals in networks (non-market and often free) produces extremely valuable data for companies, which is used to feed artificial intelligence capable of solving puzzles as complex as, for example, the “translation machine.” This is quite simply a revolution in science! True knowledge is being extracted from Big Data and this in a way that is infinitely faster and cheaper than the old methods. Many people have had their teeth knocked out on this translation machine, but it is collective intelligence that has made it possible.

Cognitive Capitalism: The Engagement of the Brain and Digital Networks

My definition of cognitive capitalism⁴ as the set of apparatuses and devices for capturing the positive externalities produced by the cooperation of brains in networks (or collective intelligence in networks) contained the two key elements of the New Great Transformation in progress: the digital revolution and the brain in a historically determined society. The digital revolution as a technological fact—for a moment contested in 1995 when my analysis was criticized for not taking into account the too small number of Internet and cellphone users—has since imposed itself. No one disputes this evidence anymore. On the second aspect, the importance of brains and their collective arrangements in order to produce intelligence, the rise of cognitive sciences since the beginning of the twenty-first century and the increasing role of artificial intelligence (both symbolic and connectionist) have consolidated a radical break with the world of before.

I must admit, however, that I was too preoccupied to make the double community of researchers and activists who pretend to be revolutionary aware of this new factual change (Hegel’s famous “c’est ainsi” in front of the Alps), to pay sufficient attention to the internal history full of new and old contradictions that has been the story of the last 30 years. The brain and new technologies have both become a true battlefield. If you want to capture positive externalities as an apparatus, you need to subsume both the technical dispositive and the brain.

At a second and more crucial level, you also need to subsume human cerebral activities played and displayed together in common. You need to be able to subsume groups and sometimes a multitude of people. This has always been the rule of the game when the subject of the working process was an ensemble of bodies and muscles. Subsuming the workers as a collective was precisely what transformed money into machines, hence into capital, and gave the capitalist the possibility to discipline the working class. Now that what is to be subsumed is the free activity of the collective continuous brain, discipline is not enough. This is why the famous distinction Gilles Deleuze draws between a society of discipline and a society of control fits so well with the period of 1980 to 1995. This is the point where the Foucaldian concept of the disciplinary apparatus of bodies so well described in Surveiller et punir (Discipline and Punish, 1975) misses something of the control of the mind. The computer and the network is an unwritten chapter of Le Souci de soi (The Care of the Self, 1984). This is not a critique, since Foucault’s interest in monitoring processes on the one hand and for neoliberalism on the other shows how close he was to a theory of the subject and apparatus of control of the self through a technic—even if he did not pay attention to digital technics as such.

A Short History of Capitalist Colonization of the Brain

Returning to our problem of how to put together, in the same theoretical basket, the problem of the subsumption of brains in collective interaction and neural control of the mind, we must revisit the short history of cognitive capitalism. The past experiences of working class struggles under industrial capitalism have taught us that the escape from the condition of subordinate and dependent workers, the refusal of work, and sabotage in the workplace have been powerful factors of automation, socialization, and the exploitation and diffusion of capitalism as a general regime of human activity. Mario Tronti,⁵ one of the fathers of Italian operaismo, posed as a methodological axiom that the real history of capital is entirely contained in that of the reaction of capitalism to working class responses to conditions of laboring, especially its material composition (and not simply to its ideological and institutional aspects). Such responses as the refusal of work and sabotage in the workplace elicited reactions from capitalism like automation, socialization, exploitation, and diffusion of capitalism as a general regime reigning over human activity.

Nowadays, the history of cognitive capitalism (this third age of capitalism) is too often reduced to mono- and hagiographies, somewhat similar to the biographies of saints, Big Tech giants, ​​and glorious entrepreneurs like Elon Musk. But this is only one side of the coin. The analysis of power is not enough to understand it, effectively criticize it, and eventually replace it. It is necessary to look for its roots and articulations in the strength of what it faces and what it must contain. Power and productive force are the secret of the power of capital. These are the true terms of the historical equation of the real subsumption of labor into capital. Under cognitive capitalism, the same rule applies, ​​but with a shifted focus from muscular to neural activity. The refusal of work becomes the disentanglement of the cognitariat from online platforms, their refusal of guided attention, the sabotage of the control of life, and alternative uses of the power of the digital. In turn, all of these behaviors serve as powerful stimuli to capitalist recuperation resulting in an extension of the sphere of commodification and in a more subtle automation. The question of the automation of brain operations (feelings, emotions, knowledge, judgement, choices) is decisive to better understand the rapid evolution of cognitive capitalism in its late stage.

Industrial mechanization was first a form of substitution in the performance of the muscular work of the animal as well as the human (the steam horse). The second phase (1965 to 1980) begins with the transfer of machines that had already incorporated the first wheels of informatics. In post-Fordism, cybernetic regimes of feedback and feed-forward loops were incorporated in the workplace environment. The third phase begins with the digital revolution (digitalization of information, calculation, memory and information circulation), which replaces simple cerebral operations involving language, especially the analytical capacities of symbol processing (algebras), by programs. These faculties depend on the left brain.⁶ This mechanization instigates not just the abstract categorization of information, but the value of intelligence as the ability to respond in creative ways to questions whose solutions have not been previously formulated. It points in the direction of the immaterial (complex and not complicated) and therefore what cannot be decomposed or codified and executed by a program or, in other words, easily commoditized.

As with industrial capitalism, from the economic point of view, operations in cognitive capitalism (even the most complicated ones) performed by humans are devalued by de-skilling most of the necessary tasks still performed by humans and by an over-qualification of a much smaller number of workers. This is the purpose of abstracting labor into incremental and fractionated components. Thus, the price of these jobs falls and we see the share of capital (machines, but also general equipment and organization, including finance) increase at the expense of the share of wages. On the other hand, complex tasks (those in which the whole is different from the sum of its parts, there is simultaneous multidimensionality, or a very large number of variables) where the right hemisphere of the brain is at the helm or in leadership, have become more valuable (see the creative class and traders).

What are the technical conditions of such an automation: the passage from Web 1.0. to 2.0? Taking into account human interaction and its digital tracing through networks, above all, the technical conditions include the existence of platforms that aim to collect not only the results, but also the soft immaterials (or immaterial of second-grade), that is to say, the halo of logical operations, which symbolically includes the properly linguistic (structural connectivity of language, the capacity to create  words and new categories by metaphor and metonymy, the production of one or more figurative meanings). What will these traces allow? To look for patterns of behavior, to mint automatisms, and to encourage the use of such automatisms.

However, I would like to insist here on another aspect: the traces of human interaction analyzed by the power of the digital do not allow us to explain (causal reasoning) but to correlate (the effectual reasoning of Saras D. Sarasvathy). This correlation creates a link between the performance of cerebral tasks with the complex operation of the right brain, the individual-collective intelligence. Artificial intelligence should be called simulated intelligence because it derives from the imitation of human behaviors in society, which are captured and statistically processed. This interactivity produces positive results that are not necessarily accounted for and that I have elsewhere named human pollination.⁷

In the 2021 edition of The Glossary of Cognitive Activism, Warren Neidich has proposed to distinguish two phases of cognitive capitalism:

Today, cognitive capitalism can be separated into two distinct periods, an early and late phase. The early phase is defined by the following characteristics: precarity, valorization, financialization of capital, immaterial labor, real subsumption, and communicative capitalism. . . . Late cognitive capitalism—also known as the “cognitive turn” in cognitive capitalism—commenced around the turn of this century. In a world in which the predominant forms of labor are intellectual and service-oriented, the machinery of the brain takes on added importance as a locus of capitalistic adventurism and speculation. Various interdisciplinary approaches have been engaged to understand its logic, including cognitive neuroscience, behavioral economics, and epigenetics. As I describe in my book, The Psychopathologies of Cognitive Capitalism, Part 1 (2013), late cognitive capitalism is defined by three conditions. First, biopower is supplanted by neuropower, in which populations of brains and the nervous systems to which they are connected are the new focus of sovereignty and governmentalization. (The term “brain,” as described here, is understood as an entity existing inside and outside the skull and includes not only the intracranial substance, but its extensions into the body, especially its somatic and autonomic nervous system, as well as the evolving external semiotic, social and cultural relations to which it is tethered.) . . . Instead of the body’s movements, especially those utilized during physical labor, being the focus of scientific research, with its desire to improve surplus value, the new focus of  this research is the optimization of the efficiencies of networks in the material brain with those of the new computational apparatuses with which it is linked. Here, surplus value concerns augmenting, intensifying, and enhancing cognitive laboring on the networks of virtual platforms in the process of searching information, crowdsourcing, or prosuming.⁸

If the first phase of cognitive capitalism (1975 to 1995) essentially aims at what in the cognitariat represents the power of the living, capitalism discovers life as a matrix of productivity infinitely superior to the mechanics of body physics (see, for example, René Passet⁹). The second phase (2000 to 2020) enters into the brain through neurosciences and an analogy of neurons with digital networks. It is neuro-power—provided that we understand the bio-power of the living being (be it animal or human) as reproduction through time of complex organisms governed by the brain and nervous system. Therefore, the passage from the exploitation of bio-power to that of neuro-power is marked by the conquest and attempted colonization of the brain by artificial intelligence in its successive and future versions (weak or strong).

The mechanization at work in the Industrial Revolution and the two mechanizations at work thanks to the digital revolution have many points in common: reduction of labor is always too expensive for capitalism; the refinement of the exploitation is not simply labor power but also cognitive capacity (learning and creativity)—the invention force. In the digital age, intelligence can be defined as the possibility of providing a new solution to a problem that does not have to be pre-programmed. Of particular relevance is what I call immaterials of a second grade or level, that is to say, those that cannot be reduced to a digitalized algorithm or codified in Intellectual Property Rights (IPR).

This leads to the mechanization or colonization of the two cerebral hemispheres, the most spectacular being that of the right brain and interactive human complexity.

1. In the second digital revolution, the deluge of data and learning machines intervenes on generations highly accustomed to the mechanization of left-brain work.
2. In a new knowledge society, value has shifted to the value of learning rather than the value of knowledge already acquired and incorporated into fixed capital—and soon it will shift to intelligent learning rather than AI-mechanized learning

Why and How Did This Evolution Occur?

Beyond the reflex arc implemented in the disciplining of bodies by mechanization and the consumption of muscular energy, what first resists in the cognitive worker whose brain is required to be used (for their autonomy, their ability to adapt, to innovate, and no longer to follow protocols, see Alain Supiot¹⁰) is their logic, their rationality. This phenomenon already existed to a lesser extent with industrial work. The collective resistance (and quest for spaces of autonomy) of the worker on the assembly line—traced and spied on by the timekeeper and reordered by the adjuster who sets the new cadences—becomes a stimulus of productivity for the factory itself. Marx already wrote that the introduction of new machines occurs after the strikes. Furthermore, without counter-planning, the management and scientific organization of work that is actually implemented (in other words, the employer’s planning) does not even work. The same ferments of antagonism can be found in immaterial or mental work situations. Two elements have sought to bypass the resistance of the cognitive worker: (1) to compete with the socialization of the workers by a just in time incorporation into the digital networks and logistics—a point that has been correctly underlined; but also (2) to penetrate the brain by seeking to automate, with the help of algorithms, the logical operations carried out by the left part of the brain (analytical language, instructions, logical sequences). Here again, the rule that the automation of rational procedures used to implement intellectual tasks (design, logistics, personal services, and interactions between people) is directly proportional to the intensity of subjective resistance to standardization is verified. The same can be seen with the scalability of tasks and even the phenomena of idiosyncratic exchanges by which individuals try to make themselves individually indispensable (for example, with the digital networking of the address book and the mission reports carried out by sales representatives, then their direct execution via the internet). Digital networking is to service operations and immaterial work what the timekeeper and the setter are to the assembly line.

By penetrating the cerebral functioning of the living, cognitive capitalism has begun to better understand its own making, its place of manufacturing, and the nature of the subsumption that it had to realize in order to reign. In the past, industrial capitalism had been slow to understand the nature and the possibilities of the great factory. This point is remarkably documented by Jeremy Bentham’s brother, Samuel Bentham, in the Russian and English shipyards. The theft of wood (a third of the logs) by the shipyard workers to make an additional income (the famous moonlighting of the employee using the machines of his boss) led him to imagine fencing off the enterprise with a continuous wall and therefore creating a special place for manufacturing with internal regulations.

If cognitive capitalism in its first period had managed to make living brains work together either on professional digital platforms or even without their knowledge as data producers through free services like search engines, nothing guaranteed that salaried employees, freelancers, or geeky consumers would not use the power of digital technology to build autonomous spaces to escape from a pre-constrained attention. The automation of logical functions through artificial intelligence programs was the first stage of response. Mechanization and assembly lines stripped the skilled worker, as well as the craftsperson, of their irreplaceable character. Artificial intelligence (whether symbolic or connectionist) made it possible to establish a reference system of collective choices that was not optimal but sufficient (Herbert Simon) for complex situations—just as the human brain does with its limited possibilities of information, calculation, and memory. It could provide the professional hierarchy with an instrument to calculate and prevent deviation by the Millennial generation.

The government of emotions, moods, and the state of mind in general constitutes a higher degree of complexity to master as human behavior is not only made of rational decision-making, but is largely composed of emotions, reflexes, habits, and body-folds. Language, for example, far from being only a code that can be transcribed into logical and mathematical signs, contains an ambivalence toward sensations and emotions. The complexity of reality is irreducible to a simple formalization. A communicating network is not merely a series of logical propositions introduced in a database but a sharing of emotions, resonances, and correspondences—a history and a memory of interpretations that is sometimes contradictory. AI (artificial intelligence) has set out to colonize these domains. This all the more so as these areas of complexity became a refuge of attention, of subversive ingeniosity, of autonomy vis-à-vis the rule of dependent work.

The exploration and colonization of the brain by cognitive capitalism then turned to the seat of emotional and practical motor intelligence, the intelligence that governs the coordination of movements, the emotions linked to the five senses and the vital reflexes (fear, flight). ​​Here again the aim was to monetize these domains and build a reference system of behavior and emotion. We should mention here the work carried out since the end of the 1990s by Eva Illouz, who demonstrates how effectively digital capitalism has intervened in the manufacture of simple emotions, as well as complex ones such as love. Since this “information” could be coded differently than by formal logic, in particular with emotions (smiley faces, emojis) on social networks, and because, at the same time, translation machines were no longer based on linguistics but on a generalization of data available in a very large numbers (Big Data) close to infinity, it became possible to produce content mimicking human behaviors and inventiveness during problem-solving. Thus, connectionist AI was able to predict (without knowing how to account for it in a hypothetical-deductive and therefore scientific way, but through transduction in a black box) complex human conducts, to account for them and to dialogue in an artificial way with real creatures (chatbots). Even if, according to its father Yann LeCun, the AI of Facebook (neural networks) has the mimetic intelligence of a six-year-old child and “less common sense than a rat,” it doesn’t need more to pretend to govern a considerable number of collective behaviors including not only passions, animal spirits, and small perceptions of public opinion, but also the phenomena of addiction to social networks.

An interesting debate has progressively taken place with the rapid development of the automation of the operations requiring the various cerebral functions discovered by the neurosciences. The research program of cybernetics (Norbert Wiener) hypothesized that the brain worked like a computer through a complex combination of networked algorithms. The research on artificial intelligence finally led to an inverse program: it was necessary to use the power of computers to imitate the functioning of a living brain. Marc Julia in his book L’intelligence artificielle n’existe pas (2019) proposes to speak rather of “intelligence augmented” by the power of digital technologies. Underlining the phantasmatic character of strong artificial intelligence, he proposes a redefinition of intelligence as the capacity to break rules, to innovate, to be interested in what is different (and for reasons we do not know yet). Paradoxically, the development of programming and digital technologies underlines the importance and value of non-programmed responses and thus elucidates intelligence as a source of innovation and adaptation to complex environments that are contingent, in a state of becoming, and never totally mastered. The evolution of living beings in their environment is one of the most striking examples.

In the prolongation of this movement of diversification of artificial (or augmented) intelligences by the power of digital technologies, a third human cognitive and behavioral function has appeared which draws the challenge of a third digitally augmented intelligence: the one linked to the awareness of the relationship with a complex environment which includes common values (norms) and controls the inhibiting forces of instinctive and sensory-motor reactions (first intelligence) as well as the logical quality of behavior (second intelligence). According to Olivier Houdé, besides the short circuit of intuitions belonging to sensorimotor display, and a longer circuit of algorithms fed by Jean Piaget’s rational intelligence, a third intelligence is required to achieve a complete and complex human conduct.¹¹ This third intelligence has something to do with the capacity to inhibit both the first and the second intelligence through norms and values in the decision-making process. According to this theory, the acquisition of this last faculty intervenes more tardily and is only complete around age 19. This is contrary to the formation of the first intelligence, which takes place during early childhood until age 6, as well as the second intelligence (studied by Piaget), which occurs between the ages of 7 and 12. The famous ethical dilemmas posed by the automation of driving, or those of medical diagnoses aided by medical AI, have highlighted the irreducible nature of this most accomplished form of human intelligence and of corrective and just decision-making in a complex environment.

On the other hand, the requirements of traceability, robustness, and analytical understanding of the automatic decisions made by algorithms appear each time the third intelligence is involved. The same requirement to understand the construction of algorithms generated by deep learning becomes decisive in order to avoid biases linked to the characteristics of Big Data that is feeding machine learning as shown by the examples of chatbots that very quickly became racist, as well as posts on social networks that maximize the time the internet user spends on applications designed essentially for advertising reasons.

The frontier of brain colonization via AI shows that the use of algorithms gives spectacular but dangerous results in the case of neural networks (connectionist AI). It automates reactions and sensory-motor learning, which makes it possible to better know “what a body can do” but also to manipulate behaviors and excite fear and attraction reflexes. The symbolic AI, less able to mimic sensations and states of mind, obtains unquestionable results that have contributed powerfully to the industrialization of services and the tertiarization of industry (industry 4.0).

What About Its Ability to Colonize and Automate the Inhibiting and Creative Third Intelligence?

Non-statistical predictive models based on fuzzy logic as implemented by Zyed Zalila (Intellitech) (using principles of the excluded third intelligence) present very significant advantages in the direction of a strong intelligence: (1) They are built in a transparent and traceable way at all stages; (2) They are extracted and learned automatically from massive data; (3) During this extraction the Extractis robot learns to learn, looks for models, but also returns to the data and is able to use its expertise to ascertain the robustness (not only the accuracy) of the model and detect the quality of the data that fed the learning machine. ​​This leads to applications such as automatic detection of tax evasion schemes occurring in money laundering integrated into real estate deals.

However, the automation of the third intelligence using programmable algorithms comes up against a considerable obstacle, which is delineated as two essential characteristics that distinguish human language from logical coded instructions: its ambiguity and its plasticity. These are expressed by two figures, metaphor and metonymy, which are characterized by complexity in which the whole is different from the sum of its parts. Metonymy is defined by the use of the container to designate its contents, or that of the part to express the whole. The permanent plasticity of language is illustrated in the production of new metaphors (which means moving next to or beyond).

In the translating of two different languages into one another, no better solution has been found than to collate as many occurrences of similar usage as possible and then to try them until it seems to fit the problem. But here we encounter the difficulty that we still find in intelligence: the faculty of being aware of the complex environment (the textual context, but also the relational one) and of arbitrating possible solutions (including by bringing into play inhibition mechanisms). Second degree intelligence—derision, invention of catchwords, in short, singularity of style—are still for the moment out of reach for automatic programming.

Let us now take a look at the role of digital technologies in shaping the functionality of cerebral activity concerning intelligence, especially those capacities concerning the capture of attention, the desire of autonomy and cerebral independence of subjects, and behaviors of detour or blocking. The colonization by AI of the first two forms of human intelligence has given rise to new forms of legal combat and conceptual frameworks for understanding a new form of ethics. We used to talk about company law and labor law, but in the future we are going to talk more and more about cerebral rights or the rights of the brain—the dream of neural liberation from governmentalization by digital tools, the detoxification from digital addictions, the deregulation of digital networks and digital public authorities. These meta-tools, conditions of digital work and of the entanglement of brains inside computer networks, constitute the new territories of jurisprudence of the cognitariat, as well as of the internet consumer (prosumer). The definition and protection of the new digital commons will result from an often conflicting co-construction. The third intelligence, the only one able to make ethical requirements prevail (guarantee of freedom, equality, and fraternity in the access to digital technologies as well as in their uses and consequences) constitutes the horizon of a third decolonized phase of cognitive capitalism. This possibility exists. Digital servitude is neither a constraining fatality nor a voluntary servitude consented in exchange of rent (a few crumbs fallen from the table of Big Tech) or privileges reserved for those included in the digital culture.

What Can Art and Artistic Activism Deliver in the Age of the Triumph of Cognitive and Neuro-Capitalism and Its Colonization of the Brain?

Let us remember, as we briefly exposed above, that the more serialization, industrialization, and progress by the automation of the products of cerebral work, the more the value of emotions, of behaviors, of exercises of logic, of knowledge reducible to the production of algorithms decreases, and the more soft and fuzzy immaterials of degree two (not codifiable) intelligence provide new sources of wealth and value. This happens for two reasons: (1) They are much rarer and more sought after because they are more original, more singular; but also (2) because they are the places par excellence of the resistance and the construction of antagonistic subjects (what were formerly the trade unions under industrial capitalism). The more a curious, indocile, intelligent digital subject emerges that likes to break routines, to widen the focus, to deconstruct and reconstruct the complex framework of its environment, the more the need for neuro-capitalism to control “its” workers (as well as the whole society) pushes it to colonize all forms of cerebral intelligence.

The brain could be defined as a machine to apprehend and process the complex in that this complex¹² concerns the corporal coordination (sensory-motor), the mathematical and logical decomposition that is essentially analytical (left brain), or the global and synthetic intuition of the whole distinct from the parts (right brain) and the ethical imperatives. Art is a form of knowledge of oneself and of others that comes from the maturation of the third intelligence. It is in this sense that it is necessary to understand how a complete human intelligence could not exist without literary and artistic culture. All political regimes that seek legitimacy—that is, acquiescence to their power—seek to exercise their authority over artistic and literary productions and to legitimize themselves through and thanks to them. In the case of cognitive capitalism, it is no longer a question of an external necessity. Cognitive capitalism is compelled to automate cerebral intelligence in order to subdue it, and it is, therefore, an endogenous tendency consubstantial with its deployment. Let us understand: it is in the art of language (its creative production) and the visual, plastic, and musical arts that the conquest and the colonization of the third intelligence is played out. Music does not simply soften morals, it is also one of the forms of mental activity that mobilizes the whole brain (along with sexual orgasm). Art under all its forms is thus a stake for the future. When the digital Big Brother manages to domesticate many of our reflexes and movements, our most frustrated feelings and our instrumental rationality, the importance of the third intelligence, the one that crystallizes the ethical refusals, the inhibiting faculty, as well as the will, becomes more crucial than ever.

Artistic neuro-activism can, then, find a much more precise and programmatic concrete sense to fight against the colonization by the cognitive capitalism of the three intelligences. Following the example of the new political economy, which exposes the value of the positive externalities of the pollination and thus of the production of the living by means of the living, the contemporary art of neuro-capitalism makes visible the forces of dissensus and resistance at the heart of the colonization and the decolonization of the three intelligences. It makes this apparent by the recourse to the very same means of the numerical technologies through which it creates codes that operate to produce different (radical) others.

One possible fruitful direction is to counterbalance the superiority that has been conferred to the second mathematical-logical intelligence, the a-temporal and not very spatial (left brain), through an elevation and thus equalization of the capacities of the right brain. (See, for example, the historical rejection of the left brain’s dependence upon a model of Cartesian perspectivalism found in Renaissance painting and the Baconian empiricism of the grid-like isomorphic succession of space found in early Dutch landscape painting.) The binary character of computer science and digital technologies (true/false, on/off, white/black) always brings us back to the side of the left brain, but produces results in domains of the first and third intelligence that have more to do with short circuits, inertness, or absurdities than with nuance, colors, and life.

Neurosciences helped by digital technologies and vice versa allow us to revisit the sensitive and emotional learning of child intelligence (in its limits, notably those of the reflexes that the second intelligence will learn to overcome, but also in its mysterious link with speech, intuition, and creative power). The learning of logic and rationality “à la Piaget” allows one to experience the coherence and consistency of a written symbolic system—and paradoxically, it allows us to touch the madness of rationality without limit, without space and without body. Artistic practice inhibits our reflexes and frees us from being a new cerebral monad navigating through cyberspace pre-chewed by algorithms. It lifts us out of our taboos and the routines of the second intelligence consolidated by the colonization of the permanently connected brain. It builds our reference points for new common paths. The neuro-activist is a becoming-right-brain subject in a world of brutes activated by the logic and algorithmic colonization of a left brain that is obstinately binary. Art has already used the becoming-child (or the figure of the primitive) to free itself from the boring world of adults and identical repetition. The artist has already invented painting outside the walls of the studio. Artists can now install their palettes in the cerebral wastelands of our intelligences.

Many thanks to Laurence Coutrot for revising my first version and to Bonnie Begusch, Sarrita Hunn, and Warren Neidich for their suggestions to improve the essay.

1. English edition: Yann Moulier Boutang, Cognitive Capitalism, trans. Ed Emery (Cambridge, UK: Polity Press, 2012).
2. Warren Neidich, The Glossary of Cognitive Activism (Berlin: Archive Books, 2019).
3. Yves Citton, L’économie de l’attention: Nouvel horizon du capitalisme (Paris: La Découverte, 2014). 
4. It would be foolish and presumptuous to claim some kind of copyright on this terminology and especially on what it covers. The reality that this term describes was the product of a collective elaboration within the Matisse team at the University of Paris 1 between 1995 and 2005. Bernard Paulré, Carlo Vercellone, Patrick Dieuaide, Antonella Corsani, Maurizio Lazzarato, Pascal Jollivet, and myself have all contributed to it. Starting from the regulationist, institutionalist, and evolutionist currents, we coined this expression, which has since become widely accepted even if it has met with strong resistance.
5. Mario Tronti, Ouvriers et Capital (Paris: Christian Bourgois, 1977), https://www.multitudes.net/category/archives-revues-futur-anterieur-et/bibliotheque-diffuse/operaisme-autonomie/tronti-ouvriers-et-capital/.
6. Lucien Israël, Cerveau droit, cerveau gauche (Paris: Plon, 1994).
7. Yann Moulier Boutange, L’abeille et l’économiste (The bee and the economist) (Paris: Carnets Nord, 2010).
8. Warren Neidich, The Glossary of Cognitive Activism (Berlin: Archive Books, 2021), 80–82.
9. René Passet, L’économique et le vivant (Paris: Payot, 1979).
10. Alain Supiot, Le travail n’est pas une marchandise: Contenu et sens du travail au xxie siècle (Paris: Collège de France, 2019), 72.
11. Olivier Houdé, L’intelligence n’est pas un algorithme (Paris: Odile Jacob, 2019).
12. Alain Berthoz, La simplexité (Paris: Odile Jacob, 2009).