In this creatively interdisciplinary article, Dragana Favre explores the temporality of artificial intelligence in relation to Chronos, Kairos, and Aion, examining how its heterogeneous regimes of computation differ from humanly structured experience of time.

The question opens onto a deeper concern: whether human beings may lose the symbolic grounding through which they relate to time, meaning, and transformation, as AI comes to survey the landscape of meaning with unprecedented power, while remaining unable to inhabit it.

Introduction

The question of artificial intelligence and temporality can no longer be approached solely through the lens of computational speed or performance. To reduce AI’s temporality to a mere gain in acceleration relative to human time is to project onto the machine an impoverished conception of time itself, inherited from an industrial and productivist imaginary.

Time is never a neutral parameter. It is lived, modulated, symbolized, and socially organized. Thinking AI in relation to time therefore requires a shift in perspective: no longer comparing two speeds, but instead understanding the coexistence of heterogeneous, sometimes incompatible, temporalities within a single techno-human ecology.

Chronos and the plasticity of human time

In the classical tradition, Chronos is often understood as linear, homogeneous, measurable time: the time of clocks and calendars. Yet even in the most ordinary human experience, Chronos is never truly uniform.

Experimental psychology and neuroscience have shown that the perception of time varies considerably according to emotional state, attention, stress level, and bodily engagement. A minute of anxious waiting does not possess the same density as a minute of deep concentration or contemplation.

The human brain does not process time as a sequence of abstract instants, but as durations laden with meaning. This temporal plasticity rests on precise neurobiological mechanisms—dopaminergic modulation, retrospective and prospective memory, sensorimotor integration—but can never be reduced to them. It is inseparable from a living body, exposed to fatigue, aging, and death.

The disjointed temporalities of AI

This internal heterogeneity of human time already marks a first rupture with the temporality of AI. Where the human being lives time as a fragile continuity, traversed by subjective accelerations and decelerations, AI operates through multiple temporal structures, superimposed and dissociated. One may thus distinguish:

a material time, linked to processor speed and energetic constraints,
an algorithmic time, corresponding to iterations, network depths, and optimization cycles,
a learning time, often long and opaque, made of stagnant phases and sudden shifts,
an interactional time, that perceived by the user through latency or the apparent immediacy of responses,
a socio-technical time, marked by updates, deployments, and the rapid obsolescence of systems.

These temporalities are neither synchronous nor coherent with one another. They produce an illusion of continuity where in fact there is only a juxtaposition of disjointed temporal regimes.

The loop without experience

This illusion is reinforced by the very structure of machine-learning systems, founded on recursivity and the loop. The training of a model relies on massive repetition:

a data loop,
a backpropagation loop,
an optimization loop,
and then a usage loop, in which human interactions indirectly feed back into future adjustments.

This circular logic has found a popular resonance in certain contemporary works of fiction, most notably the series Dark, which stages a looped, deterministic time in which the future acts upon the past. The metaphor is illuminating, but it quickly reaches its limits.

In Dark, the characters suffer, precisely because they remember. Repetition transforms them, wears them down, fractures them. The loop is lived as destiny (see article Paradox-born subjects and Jungian depth psychology in “Dark”).

In AI, by contrast, the loop is never lived. It produces neither autobiographical memory, nor identity, nor suffering. Each iteration modifies a mathematical function, not a subject.

Algorithmic time is a time without interiority.

This difference becomes especially visible in the phenomenon known as grokking, observed in deep learning. After a long phase of poor performance, a model suddenly attains a robust capacity for generalization. This shift is often described as a moment of “understanding”, even as a flash of lucidity. Yet such a reading is profoundly anthropomorphic.

Grokking does not correspond to an experience, but to a deferred effect of optimization. Where a human being may live a Kairos moment—a decisive, irreversible instant, charged with affect and existential transformation—AI crosses no symbolic threshold. It simply changes statistical regime.

The danger here is less technical than projective: by attributing moments of understanding to AI, we lend it a temporal depth it does not possess.

Psychic time and the relational dimension

From a Jungian perspective, human Kairos corresponds to a conjunction between the conscious and the unconscious: a moment in which an archetypal content becomes integrable within the psyche and durably transforms the trajectory of the subject.

In Aion: Researches into the Phenomenology of the Self, Jung insists on the qualitative and symbolic dimension of psychic time, which cannot be reduced to mere chronological succession.

By contrast, IA knows neither the unconscious nor any threshold of symbolic integration. It does not live time; it operates on states.

Chronos and Kairos, in this perspective, appear as fundamentally relational temporalities. Chronos enables social coordination, schedules, deadlines, collective rhythms, whereas Kairos enables intersubjective attunement, the sense of the right moment to speak, to act, or to remain silent. These temporalities always presuppose an other who can be affected. They emerge within a field of relations.

AI, for its part, evolves within a temporality that is not relational in its essence.

It has no need for the right moment, only for a valid state. This radical difference invites us to rethink the very metaphor of AI temporality. Rather than comparing it to human time, it may be more accurate to conceive of it as an aerial, even orbital, temporality.

Compared with human time—earthbound, embodied, subject to the gravity of the body and to finitude—the temporality of AI hovers without inhabiting. It moves across symbolic landscapes, texts, images, myths, forms of knowledge, without ever taking root in them. It depends upon a massive yet largely invisible infrastructure, much as an aircraft depends upon technical networks that no passenger truly inhabits.

This temporality is neither Chronos, nor Kairos, nor even Aion. It is functional, trans-temporal, detached from symbolic grounding. It affords an overview, but not the experience of place.

A temporality without rootedness

This idea echoes Gilbert Simondon, for whom technical objects possess a mode of existence proper to themselves, irreducible to that of human beings. The contemporary error lies in believing that speed is equivalent to depth, and that the accumulation of data mechanically produces meaning.

From a Jungian point of view, Aion is not the time of information, but of meaning, the Self, and archetypal repetition. AI does not belong to Aion; it manipulates its traces.

By processing vast cultural corpora (mythological, religious, philosophical), AI acts as an archetypal amplifier. It does not generate new archetypes, but intensifies those already in circulation. In this sense, it functions like an externalized collective dream without a dreamer, which helps explain the power of the messianic or apocalyptic projections it arouses.

AI activates Aionic figures (the Oracle, the Demiurge, the Golem) without ever embodying them.

Contemporary cognitive science reinforces this distinction. The work of Francisco Varela has shown that human cognition is fundamentally enactive: it emerges from the dynamic interaction between body, environment, and lived time. The brain does not process abstract instants, but meaningful durations rooted in action. AI, by contrast, processes discrete states.

The relation between brain and AI thus becomes an interface between duration and instant, between lived time and calculated time. This desynchronisation is not neutral. As Bernard Stiegler has argued, the control of technical rhythms is also a form of control over subjectivities. To accelerate certain temporalities and compress others is to reconfigure the very conditions of attention, decision, and meaning.

An ecology of temporalities

The question then arises: can one truly say that AI possesses a temporality of its own? If we turn to contemporary physics, the answer becomes more nuanced.

In relativity, time is not absolute but depends on the frame of reference. In quantum physics, the status of time becomes problematic, at times even secondary to correlations between states. Certain approaches, particularly in quantum gravity and thermodynamics, suggest that time is not a fundamental substance, but an emergent phenomenon linked to entropy or information.

In this perspective, the temporality of AI could be understood as an emergent computational time, indexed to the succession of states and energetic dissipation, yet devoid of a lived present. This time exists, but it is not phenomenological. There is neither past remembered as history, nor future anticipated as project.

AI does not project itself into time; it passes through it.

Hence, rather than seeking to humanize AI temporality by attributing to it intentions, intuitions, or moments of understanding, it may be more fruitful to think in terms of an ecology of temporalities. Such an ecology would recognize the irreducible plurality of times:

a human time, embodied and symbolic, oriented by Kairos and Aion,
a technical time, functional and aerial, structured by loops and states,
and interfaces charged with translating—without conflating—these heterogeneous temporal regimes.

From this standpoint, AI is not a temporal subject, but a technical milieu of time, in Gilbert Simondon’s sense.

A Jungian reading thus reminds us that the central issue is not to give time to the machine, but to preserve our own.

The risk is not that AI may become too fast or too intelligent, but that human beings may lose the symbolic grounding in which their relation to time, meaning, and transformation is rooted. AI may survey the landscape of meaning with unprecedented power, but it cannot inhabit it.

Our task, then, is less technological than cultural and psychic: to maintain the distinction between map and territory, between speed and depth, between the calculation of time and its lived experience.

Original Article & translation by Dragana Favre.

July 2026

Further reading

Read also Rachel Huber’s article Psychic temporalities of Chronos, Kairos, and Aion.

References

View references cited in this article

Aristote. (1994). Physique (J. Tricot, Trad.). Vrin.

Deleuze, G. (1968). Différence et répétition. Presses Universitaires de France.

Heidegger, M. (1962). Being and time (J. Macquarrie & E. Robinson, Trans.). Harper & Row.

Hofstadter, D. R. (2007). I am a strange loop. Basic Books.

Jung, C. G. (1959). Aion: Researches into the phenomenology of the self (R. F. C. Hull, Trans.). Princeton University Press.

Odar, B., & Friese, J. (2017–2020). Dark [TV series]. Netflix.

Power, A., Burda, Y., Edwards, H., Babuschkin, I., & Misra, V. (2022). Grokking: Generalization beyond overfitting on small algorithmic datasets (arXiv:2201.02177). arXiv.

Prigogine, I., & Stengers, I. (1984). Order out of chaos: Man’s new dialogue with nature. Bantam Books.

Rovelli, C. (2018). The order of time. Riverhead Books.

Simondon, G. (1958). Du mode d’existence des objets techniques. Aubier.

Smolin, L. (2013). Time reborn: From the crisis in physics to the future of the universe. Houghton Mifflin Harcourt.

Stiegler, B. (1994). La technique et le temps 1 : La faute d’Épiméthée. Éditions Galilée.

Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. The MIT Press.

Dragana Favre, MD, PhD

Dragana Favre is a Swiss psychiatrist (FMH) and neuroscientist specialized in analytical psychotherapy. Trained at the University Hospitals of Geneva and the Antenna Romande of the C.G. Jung Institute in Küsnacht, she maintains a private practice in Geneva and lectures internationally on Jungian psychology, consciousness, and symbolization.

She holds a PhD in neuroscience from the University of Alicante and a Master’s degree from Göttingen, and develops an integrative approach grounded in archetypal dynamics, psychic temporality, and the phenomenology of consciousness.

She serves on the board of the International Association for Jungian Studies (IAJS), co-chaired the annual IAJS conferences in 2024 and 2025, and hosts the Jungian Salon, a living forum at the crossroads of clinical practice and contemporary thought.

Personal website: www.draganafavre.ch.

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