MMCA Studies x Stedelijk Studies Fellowship

On the Human Mode of Operation

by Lee Sooyon

Image: Mathematician Norbert Wiener, whose publication Cybernetics: Or Control and Communication in the Animal and the Machine (1948) laid the theoretical foundation for a.o. artificial intelligence, 6 February 1964. Courtesy of M.I.T. archives.

November 13, 2025

To read James Joyce’s Ulysses (1922) properly requires an abundance of annotations. Set over the course of a single day—June 16, 1904—in Dublin, the novel traces the everyday lives of ordinary people through a stream-of-consciousness narrative mapped onto the epic structure of Homer’s The Odyssey (c. 8th century BCE). Embedded within this structure lies a datafied narrative: Between the fragmented lines of prose that scatter scenes and characters, one senses the elision of mythological and religious allusions, the geography and history of Dublin, literary references—as well as half-concealed traces of personal sentiment. To engage with this text in all its richness, often regarded as the pinnacle of twentieth-century literature, ironically demands an aid that surpasses the ordinary capacity of the human mind. With the help of a subscription-based language model such as ChatGPT-5, for instance, a reader might explore overlooked contexts of Greco-Roman philosophy or consult contemporaneous maps of Dublin alongside the text. Nevertheless, Ulysses remains decidedly human—unsuited to AI’s understanding.

Consider, for example, the information about Leopold Bloom’s weight, how it was measured, and on what date. Such details contribute nothing to understanding the novel as a whole. References to dominical letters or the Julian calendar are factual details that, prior to the advent of AI, most readers could not easily verify; most readers would simply have read past them.^[1] Whether the lunation is twelve or thirteen, whether the Roman hour is recorded as two or three, or whether the Julian year is 6617 or 6618— none of this has any consequence on the act of reading. These passages function less as insights into Bloom himself than as ostentatious displays of historical knowledge: that Christian, Jewish, and Islamic systems of timekeeping differ; that dominical letters and Roman numerals were once in use; and that solar reckoning emerged alongside advances in natural science. In other words, such sentences are—regardless of the character Bloom—also an aggregation of historical information. Nevertheless, with the aid of an AI capable of retrieving etymologies and verifying historical facts, meanings emerge between the lines that would otherwise exceed human cognitive limits. These include religious and social contexts such as the relationship between the Julian calendar and the solar cycle or its role as a crucial metric in the medieval Christian calculation of Easter. For the uninformed reader, AI thus enables the act of reading literature in its most humanistic mode.

Can Human Thought and Patterns of Action Be Scientifically Explained?

Whenever new technologies are introduced, people often respond with excitement, as if welcoming an entirely new world. Since the invention of electricity and the telegraph in the nineteenth century, countless technologies have come and gone. At times perceived as extensions of the human body (recorder, phonograph, camera), they have in other instances broadened the horizons of spatial perception (telephone, engine, metaverse) or generated wholly new modes of communication (the internet, social media). More recently, technologies have moved beyond extending and inventing the external world to enabling imagination of cognitive expansion in ways humanity has never experienced before (AI). In this sense, it is not surprising that people often interpret new technologies as the gateways to an entirely different realm. Yet the question remains: Is this truly the case? Do the worlds conjured by technology represent genuine entries into previously nonexistent domains or encounters with an altogether new cosmos?

The exhilaration and anxiety provoked by the “new worlds” of technology have recurred throughout human history. This phenomenon is evident even in the comparatively brief history of AI. In 1997, when IBM’s Deep Blue—with only one year of upgrades and tweaks—defeated world chess champion Garry Kasparov; in 2016, when Google DeepMind’s AlphaGo won against Lee Sedol by four games to one; and in 2024, when Ai-Da, an AI robot, produced a portrait of Alan Turing titled AI God, which sold at auction for $1,084,800: Each of these events was greeted with fervor, as though a new era had dawned and a previously unseen world had been unveiled before humanity. However, the possibility of new worlds has always existed. Technology merely provides a pathway to such possibilities, which ultimately originate in the operating system of the human brain.

Throughout history, diverse explanations have been offered concerning intelligence and the workings of the brain, the very foundations of human cognition. The Latin term intelligentia, denoting the “faculty of understanding,” has been interpreted in various ways. Nicolas Malebranche, for instance, when discussing the intelligence of the truths of faith understood the term as the “capacity for intuitive comprehension.”^[2] His conception of human intelligence, which enables the perception and understanding of the world, was closely aligned with Aurelius Augustine’s notion of illuminatio divina (divine illumination): the belief that true knowledge only becomes possible through the light bestowed by God.

Malebranche’s claim that the brain can comprehend the world through intuition was not confined to theology. His predecessor Rene Descartes had already asserted, in the maxim cogito, ergo sum (“I think, therefore I am”), that human reason grounds clear and distinct ideas—and certainty itself—not in external inference but in the internal intuition of the mind. Likewise, Immanuel Kant located the conditions of cognition within the a priori forms of the human subject: time, space, and categories.^[3] For Kant, human beings do not perceive external objects as they are in themselves but instead construct and comprehend them within the framework of cognition. In a similar vein, historical studies of sudden enlightenment (頓悟), a central concept in Zen Buddhism, reveal a comparable philosophical insight: the idea that awakening to one’s true nature is not the product of accumulated knowledge or logical deduction, but of a sudden, profound self-realization achieved through direct intuition of the mind.^[4] In this way, the philosophical tradition of situating human intelligence in the realms of intuition and enlightenment has endured across centuries.

However, such models of the brain’s operations are ill-suited to integration with new technologies. They resist analysis and cannot be readily applied. To make sense of emerging technologies, a different analysis of human operations is required. Some philosophers have turned to the etymology of intelligence—from inter- (“between”) and either legere (“to choose”) or ligare (“to connect”)—to define intelligence as the capacity to establish relations among things. Understood in this sense, the term connects directly with intellect.^[5] And it is this latter interpretation that resonates most deeply with the new worlds that AI discloses to humanity.

Henri Bergson sought to broaden the understanding of human intelligence from an individual faculty to a social phenomenon. He argued that intelligence is not an innate endowment, but rather a general capacity for adaptation. Therefore, imagination, drawing, designing, and sketching, in his view, are all products born of the need to adapt. For Bergson, the intelligence that human beings discover within themselves is never complete in itself; it is a fragment severed from a larger whole or a mere surface projection that conceals the depth of its generative processes.^[6]

With advances in technology, new tools enabled fresh approaches to the study of the human mind. Between 1946 and 1953, some of the most prominent mathematicians, logicians, engineers, neurophysiologists, psychologists, and anthropologists of the era convened ten times to scientifically investigate the mechanisms of human thought and behavior. It was in these meetings that the term cybernetics was used to describe the operating principles of the human mind.^[7] Convinced that the meaning, purpose, and directionality inherent in life and mind could be explained by physical laws, the group chose “teleological mechanisms” as the theme of their inaugural session.

A central figure in these discussions (and credited with introducing the term cybernetics), the mathematician Norbert Wiener defined “teleological behavior”—that is, behavior structured through feedback loops—as a category of scientific exploration encompassing animals, machines, and humans alike.^[8] In The Human Use of Human Beings, Wiener argued that the human being, as a biological entity, must be understood as part of an ongoing process, with its essence rooted in the capacity to remember the effects of its developmental past. Furthermore, he contended that the operations of human cognition could be translated into the language of machines (computers) and that the essence of humanity lies in recorded tapes, the preservation of memory, and the continuity of its interpretation.^[9]

Allen Newell and Herbert Simon, pioneers who laid the foundational groundwork for AI, likewise regarded the brain as an information-processing system—one that could be replicated and studied in mechanical form.^[10] In 1956, scientists and neurologists interested in whether human intelligence could be simulated by machines gathered for an informal meeting at Dartmouth College, where the term artificial intelligence was first coined. One of the organizers, John McCarthy, presented Logic Theorist, the first significant AI program designed to emulate human problem-solving.

What is striking here is that when some of the most distinguished minds of the era convened to define new technological concepts and chart their future directions, the central topic was the redefinition of human functioning itself. This prompts the question: Has contemporary AI truly opened new pathways for understanding human cognitive capacities and the workings of the brain? Bruno Latour offered one answer in We Have Never Been Modern: He argued that Robert Boyle’s experimental science sought to construct a distinct domain for the natural sciences by separating nature from social and political debate. Yet, in reality, the separation of an objective scientific realm from human society proved impossible. Modernity, Latour concluded, was ultimately a myth.^[11]

New technologies and sciences have always promised the possibility of new truths. Yet such truths are never naturally given; they are produced within artificially constructed networks of apparatuses, evidence, and consensus. Science generates new definitions of the human, which neither wholly replace earlier ones nor reduce to a single, unified account. Nor do they coalesce into one consistent framework. Rather than subtracting from reality, science adds new layers to it, ultimately expanding its strata. At this juncture, new technologies render the boundaries of the human increasingly indistinct, exposing the fictive nature of the very notion of humanity.

The Instability and Opacity of the Concept of “Humanity”

The Latin term humanus, from which the concept of “human” derives, signified an “earthly being,” linked to ground, soil, and earth. The Romans defined it in opposition to the divine, the bestial, and the barbarian.^[12] Martin Heidegger similarly contrasted homo humanus with homo barbarus, arguing that humanity is realized through the embodiment of paideia—the tradition of education inherited from Greece—which cultivated virtus, or virtue.^[13] In this view, the humanity necessary to define human existence is not innate, but emerges through education and the practice of virtue.

From its inception, then, the definition of the human has been marked by instability and symbolic boundaries. The concept of the human has never been a finished essence, but something that vacillates between fiction and reality. Posthumanist discourse further destabilizes these limits and symbolic boundaries. Giorgio Agamben’s observation that therefore “homo sapiens would not be a substance or a clearly defined species, but rather a machine or an artifice to produce the recognition of the human” both return us to fundamental questions: Who is human? Who sets the criteria of humanity?^[14]

The instability and opacity of the concept of humanity are also explored in Albert Camus’s The Stranger. By foregrounding absurdity and emotional detachment in his portrayal of an individual, Camus exposes the most inhuman dimensions of human existence. Jean-Paul Sartre, in his commentary on the novel, cites Camus: “‘Men, too, secrete the inhuman.’ At certain moments of lucidity, the mechanical aspect of their gestures, their meaningless pantomime makes silly everything that surrounds them.”^[15] Such observations by Camus and Sartre highlight situations where humans fail to be human, thereby unraveling the very limits of “what could become human.” If even human beings themselves can fail to be human, might other beings, under certain conditions, become human instead? If humanity remains an ongoing process and the boundary between the human and the nonhuman continues to blur, what, then, constitutes the condition for perceiving the world “in a human way”?

In 1947, Warren McCulloch and Walter Pitts published their paper “How We Know Universals: The Perception of Auditory and Visual Forms,” widely regarded as a pivotal turning point in the history of AI. They argued that the paradigms of perception and cognition are intrinsically multidimensional.^[16] Biological neural networks, they proposed, perform perception and understanding by deconstructing multilayered two-dimensional fields and remapping them into entirely different dimensional configurations.^[17] In a similar vein, Jerome Lettvin and Humberto Maturana, in collaboration with and building on the ideas of McCulloch and Pitts, studying the relatively simple retinal structure of the frog’s eye, demonstrated through experiments that computation at the perceptual level already occurs within the retina itself. In other words, they proved that the essence of cognition lies in the construction of internal representations. According to their findings, the frog’s retina is not simply a camera transmitting a “map of light” to the brain. Rather, the retina already performs four operations—detecting edges, curvature, motion, and dimming— extracting features relevant to the frog’s survival in its environment. This output is then transmitted directly to the optic tectum of the brain, where it is layered as a composite map.^[18]

Collectively, such studies raise a fundamental question: Can recognition of the brain and sensory perception be separated? They suggest that essential layers of human cognition may reside not in higher-order reasoning, but in peripheral, trivial processes. In other words, inference and judgment may already be occurring at the retinal stage, during the very process of extracting features from objects. At first glance, the simultaneous occurrence of sensory perception, reasoning, and inference appears to mark a distinctly human characteristic. What is fascinating, however, is that new machines are not incapable of imitating this very process of inference.

Scientist Jason Yosinski examined artificial neural networks, much as neuroscientists probe the human brain by inserting electrodes. By investigating specific neurons within the artificial neural network, he sought to reveal the operational principles of the entire hierarchical structure. He traced which visual features neurons within the machine detect and how information is transmitted between layers of the network. According to his findings, even an image that appears to the human eye as an abstract pattern or a distorted television screen can be interpreted entirely differently by a deep learning neural network. For example, to maximally activate the neuron responsible for the output “gorilla,” the neural network begins with a random image and iteratively modifies it. The image generated through this process may be unrecognizable to humans, yet the network can be 99.99 percent confident that it is viewing a gorilla. This process of image generation and optimization is repeated thousands of times, and the resulting image condenses and visualizes the statistical properties of the concept “gorilla” in the machine’s internal manner. While we might think of a gorilla when viewing it or simply perceive it as a mixture of texture and noise, the machine renders a confident classification. Perhaps what is implicitly contained in that image is not a real-world gorilla but a Platonic idea of the gorilla that the machine has learned.^[19]

The cognitive architecture of AI—modeled on human visual perception— thus reopens the question: What, in fact, constitutes human perception? Inevitably, this inquiry leads us back to classical and humanistic traditions of thought. Within the humanities, and particularly in art history, humans have long reflected on the mechanisms of human perception in diverse ways. John Berger, for instance, compared the camera with the human eye, arguing that the latter not only captures events but also records images through memory. Memory, however, is not a fixed destination somewhere in the brain. Countless approaches and stimuli are layered upon it, generating new connections. To endow a perceived image with context requires mediations such as language, comparison, and signs. A radical system must be constructed around the image, enabling it to be viewed simultaneously across personal and political, economic, dramatic, quotidian, and historical registers.^[20]

This does not just apply to images. Even in the process of acquiring linguistic information constructed from knowledge already stored in the brain, a clear distinction exists between simply recognizing and sensorially perceiving and understanding. The renowned twentieth-century linguist Noam Chomsky emphasized that grammatical coherence and semantic understanding operate on separate levels with his famous sentence: “Colorless green ideas sleep furiously.” This sentence is grammatically perfect but semantically meaningless. That such a sentence can be generated and its syntax correctly parsed does not mean it can be understood as possessing contextually appropriate meaning, much less that it functions socially.^[21]

Human perception, however, entails something more vivid than inference or deduction alone. Susan Sontag and Han Byung-Chul, from different perspectives, offer insights into this dimension.

For me, it was photographs of Bergen-Belsen and Dachau which I came across by chance in a bookstore in Santa Monica in July 1945. Nothing I have seen—in photographs or in real life—ever cut me as sharply, deeply, instantaneously. […] They were only photographs—of an event I had scarcely heard of and could do nothing to affect, of suffering I could hardly imagine and could do nothing to relieve. When I looked at those photographs, something broke. Some limit had been reached, and not only that of horror; I felt irrevocably grieved, wounded, but a part of my feelings started to tighten.^[22]

Sontag’s recollection of encountering as a child photographs of the Auschwitz concentration camp is searing: The images “cut to the bone,” inflicting grief and irreversible wounding, regardless of their formal composition or depicted subjects. She was indeed aware of the distinction between suffering and living with photographs of suffering, and she understood that interpretation creates distance.^[23] Yet she rejected interpretation in order to recover the sharpness of sensory experience, believing that such sensory perception, transcending individual experience, enables communication grounded in universal validity. Immanuel Kant, in the Critique of Judgment, theorized precisely this common basis: a sensus communis, or common sense, through which individuals, each responding to art in their own way, nevertheless find themselves linked by a shared foundation of perception and affect. Although Kant framed this common sense as an a priori form, seemingly given in advance of our senses, in practice it is better understood as a collective affective stratum that arises and takes shape through free human activity and reciprocal communication.^[24] Hannah Arendt similarly contended that common sense is generated in the space constituted by a plurality of concrete human beings—that is, in the world—through multilayered mutual perception. For her, this politically and communally constituted common sense ultimately opens onto the realm of social praxis.^[25]

Whereas Sontag’s reading of images evokes a piercing sensory awakening— beyond the input, analysis, and interpretation of visual information— that implies connection with a larger world, Han’s reading, by contrast, underscores an experience of heightened individuation.

Heidegger illustrates ‘reliability’ through the example of a painting by Vincent Van Gogh of a pair of leather shoes. The Van Gogh painting actually seems to show the artist’s own shoes. They are apparently men’s shoes. But Heidegger makes idiosyncratic decisions in his reading:

The peasant woman wears her shoes in the field. Only then do they become what they are. They are all the more genuinely so the less the peasant woman thinks of her shoes while she is working, or even looks at them, or is aware of them in anyway at all. This is how the shoes actually serve. [ . . . ] But the essence of the shoe-Thing is not usefulness. In a pictorial language, Heidegger points to a level of experience that precedes usefulness: From out of the dark opening of the well-worn insides of the shoes the toil of the worker’s tread stares forth. In the crudely solid heaviness of the shoes accumulates the tenacity of the slow trudge through the far-stretching and ever-uniform furrows of the field swept by a raw wind. [ . . . ] This equipment is pervaded by uncomplaining worry as to the certainty of bread, wordless joy at having once more withstood want, trembling before the impending birth, and shivering at the surrounding menace Of death. This equipment belongs to the earth and finds protection in the world of the peasant woman.^[26]

In the shoes that Han Byung-Chul perceives through Heidegger arises an immeasurable sense of “reliability,” distinct from Susan Sontag’s piercing intensity. Shoes are tools designed to protect the feet, yet they function most authentically as tools when the sensation of wearing them is forgotten. The usefulness of an object manifests its true force precisely when it recedes from perception. Han takes this further, suggesting that the image of the shoes evokes the very life sustained through labor performed in them. The values of stability and trust lie beyond the bounds of ordinary inference and reasoning, yet they are readily understood by anyone who commutes daily and endures the routines of work. One feels the same toward the keyboard tapped day after day, the familiar chair, and the trusty desk. In this sense, “reliability” resonates with the notion of common sense articulated by Kant and Arendt. At the same time, however, the value of trust belongs to an intensely personal realm. The memories that Heidegger so casually attributes to the shoes rest on concrete experiences that no one else can speak for. For a female laborer, those shoes might recall the ache of her ankles; for another, they might summon memories of being struck by a kick. This is a realm of perception that cannot be replaced—not by others and certainly not by AI.

The Irreplaceability of the Human Gaze

We now inhabit a world far too complex to reduce human perception and sensation to mere computations of neural circuits or mechanisms of pattern recognition. AI may unfold layers of sentences we have yet to interpret, restore missing information, and even “calculate” hidden meanings. However, despite such technical achievements, the piercing intensity of sensation, the silence of trust, and the lingering resonance of images that cut to the bone still belong to a distinctly human mode of operation. These are elements that cannot yet be fully translated, quantified, or substituted.

The purpose of exploring the workings of humanity, then, is not simply to understand human beings. As technologies increasingly approximate human capacities, the need to reconstitute the very question of what it means to be human grows ever more urgent. Even in moments when we fail to be human, a uniquely human sensibility persists—an inexplicable resonance or solidarity, an intuition arising from lived experience. All of this reminds us that humanity is not a fixed “species,” but a process of endless generation and reconfiguration.

About the Author

Lee Sooyon has been working as a curator at MMCA since 2008. She holds her BA in Linguistics and MA in Art History, with a focus on images as a means of communication. Currently, she is pursuing doctoral research on the changes of visual culture during the 1990s and early 2000s brought about by digital and internet technology. She is particularly interested in how the political, social, and economic situations faced by artists intersect with new technologies and how these are visually interpreted and realized. Her curatorial projects have included Lee Kang So: Where the Wind Meets the Water (2024), Korea Artist Prize 2023 (2023), Paik Nam June Effect (2022), Project Hashtag (2021), Move (2012), Art of Communication: Anri Sala, Yang Ah Ham, Philippe Parreno, Jorge Pardo (2011), The Cheonggyecheon Project (2011), and Out of the Silent Planet (2010).

This article is tagged with:

[1] James Joyce, Ulysses (Paris: Shakespeare and Company, 1922; repro., London: Penguin, 2000), 779–780.

[2] Nicolas Malebranche, Dialogues on Metaphysics and on Religion, trans. David James Frederick Scott (Cambridge: Cambridge University Press, 1997), 92.

[3] Lawrence Nolan, “Malebranche on Sensory Cognition and ‘Seeing As,’” Journal of the History of Philosophy 50, no. 1 (2012): 21–52.

[4] Lim Byung Jung (Myeongjo), “A Study on the Relationship between ‘Dono (Sudden Enlightenment)’ and ‘Munyeom (No-thought)’ in the Platform Sutra,” Buddhist Literary Studies [in Korean] 15 (2020): 429–459.

[5] Catherine Malabou, Morphing Intelligence: From IQ Measurement to Artificial Brains, trans. Carolyn Shread (New York: Columbia University Press, 2019), 3.

[6] Henri Bergson, Creative Evolution, trans. Arthur Mitchell (London: The Electric Book Company, 2001), 148, 184.

[7] Jean-Pierre Dupuy, The Mechanization of the Mind: On the Origins of Cognitive Science [in Korean], trans. Bae Mun-jung (Seoul: Jisikgongjakso, 2009), 29–31.

[8] Arturo Rosenblueth, Norbert Wiener, and Julian Bigelow, “Behavior, Purpose and Teleology,” Philosophy of Science 10, no. 1 (1943): 18–24.

[9] Norbert Wiener, The Human Use of Human Beings: Cybernetics and Society (London: Free Association Books, 1989), 101–102.

[10] Allen Collins and Edward E. Smith, eds., Readings in Cognitive Science (San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1988), 110.

[11] Bruno Latour, We Have Never Been Modern [in Korean], trans. Hong Chul-ki (Seoul: Galmuri, 2009), 337–339.

[12] Francesca Ferrando, Philosophical Posthumanism (India: Bloomsbury Publishing, 2019), 89.

[13] Martin Heidegger, Basic Writings: From Being and Time (1927) to The Task of Thinking (1964), ed. David Farrell Krell (London: Routledge & Kegan Paul, 1978), 200–201.

[14] Giorgio Agamben, The Open: Man and Animal, trans. K. Attell (Stanford: Stanford University Press, 2004), 26.

[15] Jean-Paul Sartre, Existentialism Is a Humanism, trans. Carol Macomber (New Haven: Yale University Press, 2007), 74.

[16] Matteo Pasquinelli, The Eye of the Master: A Social History of Artificial Intelligence (New York: Verso, 2023), 168–170.

[17] Warren McCulloch and Walter Pitts, “How We Know Universals: The Perception of Auditory and Visual Forms,” Bulletin of Mathematical Biophysics 9, no. 3 (1947): 127–147.

[18] J.Y. Lettvin et al., “What the Frog’s Eye Tells the Frog’s Brain,” The Mind: Biological Approaches to its Functions, eds. William C. Corning and Martin Balaban (New York: Interscience Publishers, 1968), 233–258.

[19] Jason Yosinski et al., “Understanding Neural Networks Through Deep Visualization,” Deep Learning Workshop, 31st International Conference on Machine Learning (Lille: ICML, 2015); Arthur I. Miller, The Artist in the Machine: The World of AI-Powered Creativity [in Korean], trans. Kim Dong-hwan and Choi Young-hwan (Seoul: Culture Books, 2022), 465–468.

[20] John Berger, Understanding a Photograph [in Korean], ed. Geoff Dyer, trans. Kim Hyun-woo (Seoul: Yulhwadang, 2015), 66, 74.

[21] Naomi S. Baron, Who Wrote This?: How AI and the Lure of Efficiency Threaten Human Writing [in Korean], trans. Bae Dong-geun (Seoul: Book Trigger, 2025), 316.

[22] Susan Sontag, On Photography (New York: Farrar, Straus and Giroux, 1977), 19–20.

[23] Susan Sontag, Against Interpretation and Other Essays (New York: Farrar, Strauss and Giroux, 2001), 99.

[24] Lee Kwang-suk, Post-Digital: Topics and Horizons [in Korean] (Seoul: Ahn Graphics, 2021), 46; Ryu Jong Woo, “Problem of Common Sense in Deleuze’s Theory of Kant,” CHULHAK-RONCHONG, Journal of the New Korean Philosophical Association [in Korean] 79, no. 1 (2015): 103–104.

[25] Lee, ibid., 47.

[26] Han Byung-Chul, Non-things: Upheaval in the Lifeworld [in Korean], trans. Jeon Dae-ho (Seoul: Gimmyoung, 2021), 100–104.

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The Instability and Opacity of the Concept of “Humanity”

The Irreplaceability of the Human Gaze

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