Organology and Decision: On the Politics of the Brain

In their relentless pursuit of calculability, automatic systems work to disable decision-making. Our “Automatic Age,” as French philosopher Bernard Stiegler called it, therefore poses two political challenges. First, by overtaking the political and legal sphere of the administrative state, automatic systems weaken its capacity to respond to novel or emergency conditions. Second, for democratic republics—and, indeed, for all communities—digital infrastructures and the economy of the screen subject individuals to normative operations, to automatisms driven largely by the logic of economic interest or ideology. Here again, decision-making in moments of genuine crisis, now within the public sphere, is disabled because thinking itself has been disabled through the constant production and regeneration of artificial norms. Linking these two spheres—the political and the individual—is not a straightforward task. Unlike traditional political philosophy, which sought to bring politics and citizens into alignment, contemporary philosophy must first address what Stiegler calls organology. No individual mind operates autonomously; rather, it is constituted through a multiplicity of systems: psychic systems (that is, biologically driven systems), social organizations, and, of course, technical systems and their supports. What Stiegler termed the “political alternative” of the contemporary moment is the crucial struggle against those tendencies within digital technologies that accelerate entropy—a “struggle against entropy” that resists the “automation of decision-making.”¹ As he noted, “failing the development of therapies and therapeutics, proletarianization has the effect of eliminating the possibility of decision, that is, of neganthropogenesis.”²

The individual is understood here as a site for a plurality of operations that are neither simultaneous nor fully congruent with one another. Likewise, the political is no longer defined by an assumed ethnic or other fixed identity but rather by a plurality of differences. In both spheres, the possibility of decision is increasingly disabled by the technical advance of digitalization. What, then, constitutes a political decision within this double register—that of the state as an organ of the community and that of the individual as a participant in the public sphere?

Perhaps the first truly modern definition of the political was provided by German philosopher Carl Schmitt. For Schmitt, people form numerous associations, each characterized by different degrees of intensity and different boundaries of inclusion and exclusion. This conception is, of course, broadly consistent with a general organology. What organology cannot easily explain, however, is the formation of a particular political body—a bounded entity. As social systems develop, Schmitt argues, a point is reached at which one form of life (or, in contemporary terms, a socio-technical network) becomes primary, and people become willing to kill and die for its preservation. The state emerges as the organ of the decision concerning the friend and the enemy. The logic of the political is therefore not merely a projection of the logic of a socio-technical system but rather an existential logic of survival. Moreover, the threat is not a natural “fact” but is always defined by the groups involved. It is therefore always a matter of decision: a response to a potential rupture and an anticipation of dissolution.³

Schmitt also emphasized the significance of decision within the state, arguing that the genuine sovereign figure, regardless of the form of polity, is the one who can decide on the exception. When the norms internal to a political body begin to fail or when contestation becomes too intense, the sovereign decides in favor of unity by acknowledging the inadequacy of existing norms and the necessity of new political modes of being.⁴ For Schmitt, forms of liberalism that deny the primacy of decision threaten this critical dimension of sovereignty within the modern state.⁵ Today, however, the threat to the political can be understood differently. It lies in the destruction of the conditions necessary for genuine decision through the expansion of digital infrastructures and the automatisms they generate within an increasingly planetary-scale system of integration. In this sense, the political challenge is no longer simply the contestation of sovereignty but the progressive erosion of the capacity for decision itself.

The organological approach cannot avoid another key dimension of the political: the inevitable conflict among individuals, social formations, and their place within the organization of the state. As Sigmund Freud argued in Das Unbehagen in der Kultur (1930), the enforcement of norms at any level necessarily generates forms of resistance, insofar as fundamental psychic processes are constrained by social regulation.⁷ Which is to say, the brain both is and is not merely a physiological system. Thought requires a brain, but the brain is not the origin of thought. As Stiegler writes, “As a noetic organ, the brain is, precisely, not one, since it passes through an organological ‘third’ that lies outside it, as culture collectively transindividuated and supported by those tertiary retentions of all kinds that haunt it.”⁸ If politics is a function of organology, then an organological analysis of the brain becomes a necessary condition for any future concept of the political.

The paleo-archaeological and historical record demonstrates that, at some point, human beings escaped natural determination and embarked upon a new mode of existence superimposed upon the biological: a political form of life that navigates the inevitable tensions between social modes of organization and the technical systems that enabled biological survival. An organological approach must therefore work against the dominant currents of contemporary cognitive neuroscience. It requires acknowledging that the human mind is never simply a product of the brain and its genetic inheritance. Rather, it is the site of the interaction of multiple systems—psychic, social, and technical—that often compete with one another even as they cooperate in maintaining the cohesion of social groups and the survival of biological individuals. As cognitive archaeologist Lambros Malafouris states, “The human mind as an interactive, embodied, and distributed autonoetic system is neither restricted to nor can it be identified with the temporal and spatial boundaries of the brain within.”⁹

What marks the human condition is, so to speak, the “invasion” of alien thought into our own minds: the thought of others, preserved in technical forms of memory—writing, for example, or technical artifacts themselves—and reanimated within our own brains. Equally significant is the alien logic of cultural norms, which shape behavior in ways that secure the survival of social formations. Alongside these influences, the biological demands of the body invade the mind in the form of drives. The crucial point is that no overarching set of norms governs the interaction of these multiple systems as they are instantiated within the individual human mind and brain. Put differently, what we call “the mind” is the ongoing—and inevitably incomplete—attempt to bring a degree of unity to the plurality of systems operating within the individual. The mind is therefore not itself a unified entity governed by a stable set of norms. Rather, it is an evolving effort to negotiate the competing logics of survival generated by our biological, socio-political, and technical forms of life. The mind is both defined by these systems and resolutely not these systems.

This is why the mind can become the true site of crisis, of the unexpected, of the event. The mind has no norms of operation of its own; rather, it is the site for the determination and configuration of alien norms. It is neither a purely biological entity conditioned by history nor a purely historical construction shaped by biological imperatives. Instead, the mind appears in human existence as a novel entity in which technical organization, social organization, and organismic organization—each governed by its own logic and demands—meet and become mutually constitutive. As one early twentieth-century commentator observed, “the individual nervous system is in this way taken over by society.”¹⁰ More recently, the computer visionary Douglas Engelbart wrote: “What really runs our society is the central nervous system of each of its individuals.”¹¹ Stiegler formulates this relation in organological terms; “the psychic apparatus, which undoubtedly takes root in the brain, is not reducible to the brain: it passes through a symbolic apparatus that is not situated only in the brain, but in society, that is, in those other brains with which this brain is in relation.”¹²

But what, precisely, is the organological brain? In his early work, Stiegler followed archaeologist and anthropologist André Leroi-Gourhan, who argued that the human brain emerged through the evolutionary consequences of bipedalism and the liberation of the hand. Once freed, the hand was no longer constrained by the gestural programming specific to its prior functions and thus became available for entirely new—that is, nonnecessary—uses. In this account, Leroi-Gourhan often makes use of the concept of plasticity. Yet plasticity alone is insufficient. As Stiegler noted, even the earliest accidental flint tool is “mirrored” in the brain through its inherent plasticity. However, plasticity—and even the more radical notion of destructive plasticity—captures only one side of the equation. It fails to account for the crucial turn in human evolution: the invention of new gestural programs, or a new organization of the hand, which was subsequently extended outward from this “internal” alien prosthetic instrument to nature as a whole. This capacity for organization—the capacity for technicity and, ultimately, the ground of human noetic thought—remains occluded within theories of plasticity that tend to overlook forms of thinking that not only incorporate memory but also project themselves toward a future yet to come. This temporal arc is well known within phenomenology and appears prominently in the work of both Leroi-Gourhan and Stiegler under the concept of anticipation. Yet can anticipation simply be assumed to arise from the interiorization of the organized tool? How does the plastic mirroring of the brain actually produce active organization? In other words, how does reflection become invention?

Much of modern brain science has emphasized the extent to which minds and bodies are governed by automatism arising both from biological (genetic) inheritance and from processes of “learning.” Thinkers working from a more explicitly organological perspective have supplemented this account by emphasizing the incorporation of social and technical imperatives within the nervous system itself. As neuroscientist Bruce E. Wexler states, “human beings alter their environment that shapes their brain to a degree without precedent among animals. These human alterations in the shared social environment include physical structures, laws and other codes of behaviors, food and clothes, spoken and written language, and music and other arts.”¹³ This is the point that Stiegler emphasized throughout his work: the brain is literally cultivated by culture through the medium of technical artifacts,¹⁴ while those artifacts, in turn, shape the brain through processes of grammatization.¹⁵ For this reason, the brain cannot be understood as merely neuronal. Participation in a form of life presupposes a brain that has been, in a certain sense, “written” for this possibility of cooperation—that is, inscribed with capacities for the sharing of memory and experience. In general, what we call education can be understood as a process of “inscription” upon the brain through which particular automatisms are formed—patterns of behavior that enable both the survival of the group and the transmission of knowledge, most notably through language.

Yet the noetic brain is not merely a site for the inscription of automatisms. Precisely because of the plurality of inscriptions—and the plurality of modes of inscription—the brain is also a site of différance. First, the noetic brain is always a living brain, activated by drives while simultaneously constituted through its relation to dead memory—that is, to technology. For Stiegler, noesis is a “circuit” between the living and the dead.¹⁶ This circuit ensures that the brain is never simply “one.” It is continually in motion, being written and rewritten while simultaneously subjected to new forms of writing as technologies evolve. The result is an ongoing process of disorganization and reorganization. As Stiegler writes, “the cerebral organic matter of the human brain has the precise characteristic of being constantly disorganized and reorganized by the practice of artificial organs composed of the organization of inorganic matter.”¹⁷ Second, the living brain remains capable of decision precisely because it is perpetually written and rewritten. The brain is an organ that functions only in relation to other organs, whether living or dead. As Stiegler puts it, the brain is “traversed, divided, thrown into movement and turmoil by opposing tendencies that may want to respond in opposing ways, and therefore to pose questions.”¹⁸ It is through this process of differentiation that decision becomes possible, because the system remains fundamentally open.¹⁹ As Stiegler argues:

The passage from psycho-biological automatic selection to its disautomatization as decision is possible only when organic organs combine with, and form a system with, the organological organs that are tertiary retentions, that is, with the epiphylogenetic supports of collective memory, opening up an interpretive play (différance) through which criteria of selection become criteria of decision, that is, of psychosocial individuation, and not just vital individuation.²⁰

For Stiegler, however, the industrialization of memory gives rise to what he calls the Automatic Society. By short-circuiting processes of individuation, which always unfold through states of différance, industrialized automatisms act directly upon the brain and nervous system on a massive scale, producing what he once described as a “monoculture of brains.”²¹ The effect is the production of closed systems that work against the radically open nature of the plastic brain, a brain capable of invention through disorganization.

It is therefore not surprising that contemporary neuroscience frequently emphasizes the construction of automatisms rather than the possibilities of decision. Indeed, one increasingly influential model of cognition in neuroscience illustrates this tendency clearly. In research inspired by machine learning—and especially by the generative architectures associated with so-called deep learning systems—the brain has been fundamentally refigured. No longer understood merely as plastic and capable of transformation, the brain is increasingly conceived as a continuously active Bayesian prediction machine. According to this model, the brain constructs mini-hypotheses at different layers and across multiple networks on the basis of accumulated experience in order to predict the world. Present experience is therefore not simply received but actively constructed by the brain itself. Rather than processing the vast quantity of incoming sensory information directly, the brain predicts based on memory and attends only to prediction errors. These errors are then back-propagated through the system, allowing new predictions to be revised in a continuous feedback loop. This model of the brain has, in turn, inspired a corresponding cognitive theory of mind. The school of thought known as Predictive Processing argues that cognition is simply the projection of memory and the continual correction of prediction errors: “For PP, imagination is the architecture by which generative models ‘generate’ and produce predictive perceptions. This means that imagination is in some ways required for perception.”²²

Despite its flexibility and adaptability, the Bayesian brain–mind model associated with the deep learning paradigm remains incapable of decision. First, it is difficult to see how such a system could ever recognize what it means to be in a state of “crisis,” as opposed to merely encountering an “error,” and thus attempt to break free from the norms that have guided all of its prior activity. In this sense, the machine—even a relatively open and complex information-processing machine such as a digital computer—is not genuinely open to internal conflict. Unlike the human mind, the computer is always what it is; its operations remain consistent with its own determinations. There is no genuine temporality in the computer, insofar as the “clock” that marks time functions only as the regulation of a predictable sequence in which each moment is entirely determined by the program. One might imagine a computer programmed with conflicting norms or competing operations. Yet there would be no comprehensive unity within which such conflict could be recognized as a moment requiring genuine decision. To decide a conflict in this stronger sense would require taking seriously the possibility of an undetermined future. Decision, in other words, presupposes the capacity to imagine a future that exceeds past experience. This is what remains incalculable.

The human mind is capable of this kind of decision in moments of crisis. It can determine that a crisis exists and can commit itself to a future that might resolve that crisis, even when doing so requires abandoning established norms of existence and the automatisms that sustain them. Decision, in this sense, is inseparable from the possibility of transformation. It is important to note that both the machine learning paradigm and earlier computational models are grounded in what can be described as an erasure of temporality. The “new”—whether understood as the present or the future to come—remains fundamentally homogeneous with the past that governs the normative operation of the machine system. Present inputs and future predictions are constituted as knowable only and entirely within the normative network that is the system’s configuration. What makes today’s machine learning systems so powerful, of course, is that they are continually transforming this configuration on the basis of new data.

The machine, however, never institutes new norms on its own. Rather, it identifies patterns with normative potential. Prediction serves as a test of the success of this process of discovery. A failed prediction is never encountered as the appearance of something genuinely new. For machine learning systems, failure is always treated as error—which is literally digested by the system through back-propagation, always erasing its potential as a sign of more radical failure. What phenomenology taught us is that the human experience of time is not homogeneous. The historicity of the past lingers within the present, while the present is simultaneously shaped by anticipations of the future, themselves organized through memories of the past. Yet, as Martin Heidegger demonstrated, our experience of temporality reveals something more profound about human thought. For Heidegger, the experience of failure is critical. When an anticipated future does not arrive, the mind does not simply reorganize memory in order to account for an error. Rather, the human mind becomes exposed to the fracture between past, present, and future—to the radical gap or slippage that separates these temporal dimensions. The anticipated future is therefore not simply a prediction based on past experience, nor an automatic inference generated by existing norms. It is anticipated insofar as it is imagined as a possibility among many possible futures. The human mind is therefore defined by its dis-articulation of time, one that reveals every anticipation to be a decision rather than merely a prediction that either succeeds or fails.²³ Because anticipation of the future is a decision—a cut with respect to the past—the norms of past experience are never given in the decision. In moments of crisis especially, the mind confronts its own creative responsibility. It is constituted by experience, by the concrete reality of memory and habit, yet it is also not what it is, insofar as the normative organization of experience can never generate future anticipation automatically. As philosopher and physician Georges Canguilhem understood, the human mind, unlike the computer, confronts a logical void: a space in which new possibilities may be imagined and genuine errancy—not merely “mistakes”—may occur.²⁴ One decides only after passing through a condition of undecidability, as Jacques Derrida famously argued.²⁵ Yet, following Stiegler, we can go further. The decision is not itself determined by some prior norm; rather, it constitutes the foundation or institution of a new norm. Decision is therefore not merely a response to an existing order but arguably a creative act through which a new order becomes possible.

The crucial political question today emerges in the context of machine intelligence: how are we to conceptualize this condition of undecidability, this gap that reveals a future that is always possible yet never necessary?

One promising area of neuroscientific research offers potential resources for thinking of the organological brain as a site not only of normative automatization but also of what Stiegler calls disautomatization and disorganization—that is, decision. Recent work in cognitive neuroscience has identified a large-scale neural system known as the Default Mode Network (DMN).²⁶ Anatomically, the DMN encompasses several distinct brain regions, including both localized neural populations and the functional connections that link them. Although many aspects of this research remain hypothetical, neuroimaging studies suggest that the DMN is associated with forms of cognition related to selfhood, narrative construction, and imagination. What is particularly significant is that the DMN often operates, so to speak, in the shadows of the normative brain. Evidence suggests that it remains continuously active but is neurologically inhibited during task-oriented cognition and other forms of more generally routine automatized activity.

The DMN comes most clearly to the fore when the brain is not working, that is, engaged in externally directed tasks. Left alone in a dark room, an animal will typically remain at rest while awaiting the next stimulus. Human beings, by contrast, often begin to mind-wander, daydream, construct elaborate plans, and imagine futures.²⁷ Research on the DMN has also contributed to contemporary accounts of dreaming, including attempts to understand the possible cognitive functions of dreams in relation to memory, imagination, and complex reasoning. As cognitive research scientist Jessica R. Andrews-Hanna states, “An intriguing possibility is that engaging in spontaneous thought may allow individuals to construct and simulate alternative scenarios, mentally organize their plans, and prepare for what may lie ahead . . . humans have the unique ability to disengage from the external world and turn our thoughts inwards.”²⁸

This phenomenon is difficult to account for within a strictly Bayesian framework because the Default Mode Network operates independently from any particular inputs into the system. In a literal sense, when released from the demands of normative prediction, the brain enters a distinctly creative mode in which concepts, memories, and anticipations can become detached from the pragmatic requirements of routine action and instrumental cognition. It is therefore not implausible to imagine the brain as a complex system that combines Bayesian prediction—particularly within perceptual systems—with capacities for creative reorganization, which could help explain how the brain itself generates moments of disautomatization. More provocatively, we might speculate that when the brain is literally arrested—by wonder, by violence, by the breakdown and failure of established norms—this network surfaces, capable of filling the gap of de-cision with a newly imagined future logically distinct from the existing organological configuration of its psychic, social, and technical being through a radical reorganization of tertiary retentions and the discretized processes of higher cognition.

Practically speaking, disautomatization at different scales would require expanding the zones in which interruption, crisis, error, and failure can occur, while preserving the genuine benefits of normative organization. Following Stiegler, we might therefore imagine the creation of artificial spaces for dreaming—spaces for noetic mind-wandering within the currents of our political and legal orders inscribed upon our individual nervous systems.

This essay first appeared as “Organologie et décision: Sur la politique du cerveau,” Le Portique 48–49 (2024): 117–130.

1. Bernard Stiegler, “The Writing Screen,” in The Neganthropocene, ed. and trans. Daniel Ross (London: Open Humanities Press, 2018), 175.
2. Bernard Stiegler, “Organology of Limits and the Function of Reason,” in Nanjing Lectures, 2016–2019, ed. and trans. Daniel Ross (London: Open Humanities Press, 2020), 63.
3. Carl Schmitt, La notion du politique; Théorie du partisan, trans. Marie-Louise Steinhauser (Paris: Flammarion, 1992), 64–65, 75–76, 79.
4. Carl Schmitt, Théologie politique, 1922–1969, ed. and trans. Jean-Louis Schlegel (Paris: Gallimard, 1988).
5. Carl Schmitt, Parlementarisme et démocratie, ed. and trans. Jean-Louis Schlegel (Paris: Seuil, 1988).
7. Sigmund Freud, Das Unbehagen in der Kultur (Vienna: Internationaler Psychoanalytischer Verlag, 1930).[/enote] Today, however, it is necessary to reconsider this condition through the lens of organology, for the human individual possesses no radical foundational identity. Rather, as a thinking, social, and technical being, the individual is constituted by a plurality of norms and forms of memory. Instead of returning to psychoanalysis and its now-dated categories, we must confront contemporary neuroscience—although without succumbing to what Bernard Stiegler called cognitivism. In other words, we must recognize that organology depends upon one singular organ: “we must adopt an organological approach to the brain.”⁶Bernard Stiegler, “From Psychopower to Neuropower,” in Nanjing Lectures, 182.
8. Stiegler, “Neuroscience, Neuroeconomics, Neuromarketing,” in Nanjing Lectures, 221.
9. Lambros Malafouris, “Metaplasticity and the Human Becoming: Principles of Neuroarchaeology,” Journal of Anthropological Sciences 88 (2010): 55.
10. Charles Hubbard Judd, The Psychology of Social Institutions (New York: Macmillan, 1926), 328.
11. Douglas C. Engelbart, Augmented Human Intellect Study (prepared for the Headquarters of the Air Force Office of Scientific Research, Washington, DC, 1961), 4.
12. Stiegler, “From Writing to Digital Writing,” in Nanjing Lectures, 197.
13. Bruce E. Wexler, Brain and Culture: Neurobiology, Ideology, and Social Change (Cambridge, MA: MIT Press, 2006), 3.
14. See Stiegler, “From Psychopower to Neuropower,” 182.
15. Bernard Stiegler, “Désir et connaissance: Le mort saisi par le vif: Éléments pour une organologie de la libido,” La Deleuziana 6 (2017): 74.
16. Stiegler, “The Pharmacology of Technological Memory,” in Nanjing Lectures, 213.
17. Stiegler, “First Lecture: Introduction,” in Nanjing Lectures, 270.
18. Stiegler, “Neuroscience,” 221.
19. Bernard Stiegler, “The New Conflict of the Faculties and Functions: Quasi-Causality and Serendipity in the Anthropocene,” Qui Parle 26, no. 1 (2017): 88, 90.
20. Stiegler, “Organology of Limits,” 54.
21. Stiegler, “From Psychopower to Neuropower,” 187.
22. L. R. Swanson, “The Predictive Processing Paradigm Has Roots in Kant,” Frontiers in Systems Neuroscience 10 (2016): 10.
23. See Martin Heidegger, Apports à la philosophie: De l’avenance, trans. François Fédier (Paris: Gallimard, 2013).
24. Georges Canguilhem, “Le cerveau et la pensée,” in Georges Canguilhem: Philosophe, historien des sciences (Paris: Albin Michel, 1993), 21.
25. Jacques Derrida, ‘‘Force of Law,’’ trans. Mary Quaintance, Cardozo Law Review 921 (1989–90): 116.
26. See Marcus E. Raichle, “The Brain’s Default Mode Network,” Annual Review of Neuroscience 38 (2015): 433–47.
27. Johannes Bruder, “Infrastructural Intelligence: Contemporary Entanglements between Neuroscience and AI,” Progress in Brain Research 233 (2017): 113–14.
28. Jessica R. Andrews-Hanna, “The Brain’s Default Network and Its Adaptive Role in Internal Mentation,” The Neuroscientist 18, no. 3 (2012): 12.