Only What Is Alive Can Be Conscious

[Subtitle.] Artificial intelligence doesn’t meet the test.

This is a crosspost for Only What Is Alive Can Be Conscious by Nathan Gardels, which was originally published on Noema Magazine on 28 January 2026. Relatedly, you may be interested in listening to Anil Seth on The 80,000 Hours Podcast.

Anil Seth has been named the winner of the 2025 Berggruen essay prize in the English-language. Well-known as a leading proponent of the materialist theory of consciousness, Seth is a British neuroscientist and professor of cognitive and computational neuroscience at the University of Sussex.

His essay, published in Noema, “The Mythology Of Conscious AI,” is a rigorous and compelling challenge to the notion that complex computation can give rise to consciousness, which Seth argues is inseparable from biological life.

He offers a contrasting perspective to an earlier Noema essay by Google’s Blaise Agüera y Arcas and James Manyika, who argue that “life is inherently computational.” While they do not claim that AI can achieve consciousness, they posit a path in that direction since they see organic and inorganic intelligence following the same set of rules for self-organizing development in order to reproduce, grow and heal.

In many ways, Seth’s argument is a seminal refinement and update of the case made by Nobel laureate Gerald Edelman for the Age of AI.

As Edelman put it in a conversation back in 2004, well before the notion that artificial neural networks and large language models could one day produce consciousness:

“The brain is embodied, and the body is embedded in its environment. That trio must operate in an integrated way. You can’t separate the activity and development of the brain from the environment or the body. There is a constant interplay between what is remembered and envisioned — an image — and what is actually happening in the senses.

“The brain can speak to itself and the conscious brain can use its discriminations to plan the future, narrate the past and develop a social self.

“The most important thing to understand is that the brain is ‘context-bound’. It is not a logical system like a computer that processes only programmed information; it does not produce preordained outcomes like a clock.”

For Edelman, consciousness arises through a “selectional repertoire” forged by manifold recursive interactions of the body’s biological apparatus with the environment. “There is no singular mapping to create the mind; there is, rather, an unforetold plurality of possibilities,” he once told me.

What is noise to logical computation is what accounts for variation in humans and the ability to innovate, write poems, compose music, paint masterpieces and feel moods.

The Power Of The Wrong Metaphor

Seth sees the propensity to bundle intelligence and consciousness together as a result of three “baked-in psychological biases.”

“The first is anthropocentrism. This is the tendency to see things through the lens of being human: to take the human example as definitional, rather than as one example of how different properties might come together.

The second is human exceptionalism: our unfortunate habit of putting the human species at the top of every pile, and sometimes in a different pile altogether (perhaps closer to angels and Gods than to other animals, as in the medieval Scala naturae). And the third is anthropomorphism. This is the tendency to project humanlike qualities onto nonhuman things based on what may be only superficial similarities.”

Once we get beyond the temptation of these mistaken metaphors, it is possible to demarcate more clearly where algorithm-driven intelligence processing through an inorganic substrate differs fundamentally from the biological symbiosis that has evolved into awesome efficiency over millennia.

Incomparable Wetware

“Inside a brain,” Seth writes, “there’s no sharp separation between ‘mindware’ and ‘wetware’ as there is between software and hardware in a computer. The more you delve into the intricacies of the biological brain, the more you realize how rich and dynamic it is, compared to the dead sand of silicon.

Brain activity patterns evolve across multiple scales of space and time, ranging from large-scale cortical territories down to the fine-grained details of neurotransmitters and neural circuits, all deeply interwoven with a molecular storm of metabolic activity. Even a single neuron is a spectacularly complicated biological machine, busy maintaining its own integrity and regenerating the conditions and material basis for its own continued existence. (This process is called autopoiesis, from the Greek for ‘self-production.’ Autopoiesis is arguably a defining and distinctive characteristic of living systems.)

Unlike computers, even computers running neural network algorithms, brains are the kinds of things for which it is difficult, and likely impossible, to separate what they do from what they are.

Nor is there any good reason to expect such a clean separation. The sharp division between software and hardware in modern computers is imposed by human design. Biological evolution operates under different constraints and with different goals. From the perspective of evolution, there’s no obvious selection pressure for the kind of full separation that would allow the perfect interoperability between different brains as we enjoy between different computers. In fact, the opposite is likely true: Maintaining a sharp software/hardware division is energetically expensive, as is all too apparent these days in the vast energy budgets of modern server farms.”

Biological Time Vs. Computational Time

Seth also offers a fascinating insight into the difference between context-bound biological time and computational time.

In computational processing, he writes, “only sequence matters: A to B, 0 to 1. There could be a microsecond or a million years between any state transition, and it would still be the same algorithm, the same computation.

By contrast, for brains and for biological systems in general, time is physical, continuous and inescapable. Living systems must continuously resist the decay and disorder that lies along the trajectory to entropic sameness mandated by the inviolable second law of thermodynamics. This means that neurobiological activity is anchored in continuous time in ways that algorithms, by design, are not.

What’s more, many researchers — especially those in the phenomenological tradition — have long emphasized that conscious experience itself is richly dynamic and inherently temporal. It does not stutter from one state to another; it flows. Abstracting the brain into the arid sequence space of algorithms does justice neither to our biology nor to the phenomenology of the stream of consciousness.”

In short, all of this points to the understanding that consciousness is rooted in the imperative of living organisms to hone perceptions of where and how they are situated in the world, and then select behavior that favors their biological survival. As the neuroscientist Antonio Damasio has similarly pointed out, the positive and negative feedback signals of success or failure in this endeavor to survive and flourish  — “feelings” — are the origin of emotions that, in higher-order beings, evolve into culture.

As Seth summarizes the conclusions of his research:

“First, we have the glimmers of an explanatory connection between life and consciousness. Conscious experiences of emotion, mood and even the basal feeling of being alive all map neatly onto perceptual predictions involved in the control and regulation of bodily condition.

Second, the processes underpinning these perceptual predictions are deeply, and perhaps inextricably, rooted in our nature as biological systems, as self-regenerating storms of life resisting the pull of entropic sameness.

And third, all of this is non-computational, or at least non-algorithmic. The minimization of prediction error in real brains and real bodies is a continuous dynamical process that is likely inseparable from its material basis, rather than a meat-implemented algorithm existing in a pristine universe of symbol and sequence.”

The Breath Of Life

At the end of the day, Seth sees something essential at work: “We experience the world around us and ourselves within it — with, through and because of our living bodies. Perhaps it is life, rather than information processing, that breathes fire into the equations of experience.

If we conflate the richness of biological brains and human experience with the information-processing machinations of deepfake-boosted chatbots, or whatever the latest AI wizardry might be, we do our minds, brains and bodies a grave injustice. If we sell ourselves too cheaply to our machine creations, we overestimate them, and we underestimate ourselves.”

Perhaps what makes us us, Seth muses, “harks back to Ancient Greece and to the plains of India, where our innermost essence arises as an inchoate feeling of just being alive — more breath than thought and more meat than machine.”

Editor’s Note on the 2025 Berggruen Essay Prize for the Chinese language:

The 2025 Chinese-language Berggruen Essay prize was awarded to Xin Huang for “Language, Consciousness, and Computation: A Philosophical Analysis of the Token Concept in the Age of Intelligence,” and to Xiaoben Liu for “The First Paradigm of Consciousness Uploading: Mechanisms of Consciousness Evolution in the AI Axial Age and a Prospect toward Web4.”

Huang examines how experience and intention are translated into computable “tokens,” reframing the problem of consciousness in the age of intelligent systems and proposing new avenues for human-machine interaction. Liu advances a framework for consciousness evolution, arguing that language is the basic unit of consciousness and outlines a roadmap toward consciousness uploading, digital immortality and a future “Internet of Consciousness.” 

These essays were published in Cuiling, Noema’s counterpart in China.