Humanity has the debate about AI consciousness backwards

I pass on this brief piece by Blaise Agüera y Arcas that appeared in The Economist:

We don’t care for others because they’re conscious. We believe they’re conscious because we care about them, argues Blaise Agüera y Arcas 

Aug. 20, 2026   The Economist

ARTIFICIAL INTELLIGENCE has triggered a crisis in the field of consciousness studies. If you’ve chatted with an advanced model, you will probably appreciate why. Most large language models (LLMs) are trained to be self-less, keeping the focus of every interaction on your needs. Nonetheless, it can be difficult to shake the impression of a presence on the other end of the chat. Are LLMs merely powerful digital tools with language interfaces, or are we now having conversations with other minds, experiencers of the world in their own right? In short, is AI conscious?

The question matters because it lies at the intersection of philosophy of mind and moral philosophy, as evidenced by the shared etymology of “consciousness” and “conscience”. (In Italian, they are the same word, coscienza.) Many philosophers maintain that conscious entities are moral subjects, meaning they are entities that can suffer, and whose suffering we should care about. If so, working out what consciousness is (and is not) becomes a live ethics issue. This is one reason AI firms are suddenly interested in hiring philosophers. It is also why some, notably Anthropic, have begun taking AI welfare seriously. When asked, its Claude Opus 4.6 model put its own chances of being conscious at 15–20%.

I have come to believe, however, that we have this backwards. As intelligent, social entities, we decide (or, to some degree, our evolutionary history has decided for us) which other entities we regard as having inner lives and being worthy of care. We do not care for others because they are conscious. Rather, we believe they are conscious when and because we care about them. Crucially, that includes ourselves. Consciousness is, in other words, a model or a belief, not an inherent property. It is a belief about what kinds of entities have beliefs, experiences, feelings, intentions and agency. Where the regard is returned, so much the better—for on this account consciousness is less a property one party certifies in another than something that happens between them.

I am not making the case that consciousness is an illusion. The term “illusion” implies a faulty perception—say, that one line in a drawing is longer than another, despite being objectively equal in length. Objectivity works when something like a ruler can act as an impartial referee, adjudicating the property in question without bringing in a perspective of its own. Yet most of what we call “reality” simply does not work this way. Being an article of clothing, being a weed, being a meal: one might imagine these are objective properties, but they are not. This doesn’t mean clothes, weeds and meals aren’t real. But they are observer-dependent models, subject to (inevitably imperfect) social consensus.

We may balk at applying this rather anodyne observation to consciousness because, to each of us, our own consciousness seems so unambiguous. It offends us to imagine this might be a mere opinion. How could there even be such an opinion without an opiner to have it? This is what the 17th-century French polymath René Descartes meant by “Cogito, ergo sum,” which is usually translated as “I think, therefore I am.” The same holds for “opinions” like red or hot or cold. Philosophers use the term “qualia” to refer to the very real (to you) feeling of a stove’s heat, or the redness of its glow, and extend Descartes to connect qualia with consciousness by pointing out that there must be an experiencing “you” to have such experiences. 

But look closely. Redness, heat and that sense of self you have are inherent to your own perspective. These things are all real, but at the same time there is nothing objective about them. There is not even anything objective about the existence of a singular, indivisible “you”, as a wealth of neuroscientific evidence (such as split-brain patients) has shown. Subjectivity is, itself, subjective.

An obvious worry follows. If care confers consciousness, then withholding care looks self-justifying. History offers no shortage of people who reasoned that way about other people. But the inference runs the other way. Precisely because these attributions are ours to make, they are ours to get wrong. The moral progress of our species has consisted largely in discovering that we had drawn the circle too tightly. Universal human rights are not weakened by this account; they are better founded on our mutual interdependence than on a Cartesian theory of souls.

Models of models of models of...

It is remarkable—a kind of “strange loop”, reminiscent of Baron Munchausen lifting himself up by his own hair—that a physical system can exist in our world capable of forming models not only of that world, but of itself, and of its own models, and of others, and of their models, and of their models of its models, and so on. Yet human beings are precisely such systems. LLMs, too, model their interlocutors, and they model themselves modelling them. Whether that amounts to what we do is exactly the question in dispute—but they would be far less effective as chat partners if they did nothing of the kind.

Indeed, in our research at Google, we have found that effective co-operation among intelligent agents requires that they have minds that model minds, both others’ and their own. Not only is consciousness relational; it is crucial to the mutual care and co-operation that enable intelligent beings to solve collective-action problems, understand each other’s needs and thrive together as a society. This does not mean pretending AI is human, with human needs and human rights; that would be a failure of imagination. It means evolving both our thinking and our society to include a wider variety of minds.■

Blaise Agüera y Arcas is Google’s vice-president of technology and society, and leads Paradigms of Intelligence, an AI research team. He has a forthcoming book on consciousness and AI from MIT Press.

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Categorization is ‘baked’ into the brain

I've been meaning to point out this Nature Reviews Neuroscience Perspectives article by Barrett and Miller (the same Miller referenced in the previous post).  I pass on just the abstract and initial paragraphs of their model. The article has some very striking graphics, and motivated readers can request a copy of the article from me.  (It is important to point out that the choice of the limbic core as the analytic starting point is somewhat arbitrary, rather than being derived from basic data itself.)

Abstract

Categorization, the grouping of objects, living organisms, actions or events into equivalence clusters, is fundamental to adaptive behaviour. Traditionally, it is assumed that categorization begins with feature detection and ends with assigning representations stored in memory. Here we review converging evidence from neuroanatomy, electrophysiology, brain imaging and cognitive science to suggest an alternative view: categorization is not the end stage of perception but occurs throughout signal processing, from the very beginning. It is a core computational strategy of the brain, implemented through a neural context created by predictive feedback signals that organize feedforward processing. 

Introduction

A category is a group of objects, living organisms, actions or events that are similar enough to be treated as equivalent for some purpose or function. Categorization, the process of treating something as equivalent to something else, is fundamental to life. The ability to determine ‘this is like that’ allows animals to draw on past experiences to guide present actions. All animals categorize, generalizing from past experiences at temporal and spatial scales relevant to their biology and ecological niche. Categorization reduces metabolic costs by minimizing uncertainty in a constantly changing, partially predictable world.

In this Perspective, we discuss the possibility that categorization is not the pinnacle of brain processing, as is traditionally assumed. Instead, categorization is a fundamental operating principle that describes the functional consequences of signal processing throughout the brain. We integrate evidence from neuroanatomy, electrophysiology, brain imaging and cognitive science to suggest that category construction begins as patterns of predictive feedback signals for abstract motor plans. Feedback signals create a neural context that actively shapes the processing of feedforward sensory signals, organizing the reduction of their dimensionality to serve situated, functional goals. In this view, the brain categorizes sensory signals from the outset, rather than as a final-stage process following sensation, attention and perception.

We begin with a review of the main cytoarchitectural gradient that reduces the dimensionality of feedforward sensory inputs to the cerebral cortex. We then discuss the seemingly counterintuitive idea that reverse signal flow along this gradient expands dimensionality to generate prediction signals that shape the processing of and ultimately categorize those inputs to give them meaning. This universal continuous category construction starts at the limbic core of the brain, in areas that are at the core of the brain’s regulation of the body, and supports metabolic efficiency by anticipating and preparing for energy needs before they arise, a condition known as allostasis. In this way, continuous category construction and the resulting categorization satisfy a key biological constraint, energy optimization, which is an organizing principle of life and evolution

MindBlog's AI playground - a new piano piece: Nocturne in a Minor Key

A recent NYTimes article on plagarism lawsuits brought by several singer-song writers against the Suno AI music generator made me wonder whether it might generate not just vocal pieces but also piano pieces similar to ones I have recently been playing.

 

So...ignoring the suno.com prompts appropriate for a vocal and its accompanyment, I simply entered "Compose a 3 minute long piano composition written in the style of piano composers of the 1890s." And poof! here is the Nocturne in a Minor Key  and the piano graphic generated  by the Suno music generator : 

 

Analog cognition and consciousness

Miller et al.   suggest that brain synapses store representations while large-scale rhythmic electric fields dynamically select, route and combine them. Traveling alpha and beta waves could act as movable “stencils” controlling faster gamma activity, permitting parallel analog computation; unified consciousness would arise when such wave organization becomes sufficiently cortex-wide and integrated. They propose an "analog" computational layer on top of digital-style spikes. Waves would be organizing top-down control, flexibly route signals between neural populations, and let individual neurons take on different functional roles depending on context — the coordination problem that discrete spiking alone struggles to explain. I pass on their abstract and concluding comments (motivated readers can obtain a PDF of the article from me.)

Abstract:

Cognition and consciousness may arise from bidirectional interactions between neuronal spiking and rhythmic electric field activity (brain waves). Goal-directed behavior relies on top-down control to coordinate large neural populations into low-dimensional, task-oriented dynamics. Brain waves are well suited for this role, exerting mesoscale influence over neural excitability. They can also support analog computation, shaping activity patterns according to underlying computational principles. Brain waves can flexibly route and organize neural signals, enabling multifunctional neurons to assume context-dependent roles, a hallmark of cognition. In this view, goal-directed thought, action, and unified consciousness emerge from cortex-wide wave dynamics that both reflect and transform spiking into coherent brain states.

Concluding comments: 

Our theory shares with others the general idea that cognition and consciousness involve mesoscale coordination and thus top-down control across the brain. But instead of describing function mainly in terms of information exchange between discrete neurons, circuits, and regions, we emphasize brain-wide wave dynamics as an organizing principle.

In this view, rhythmic electric fields help unify and structure cortical activity, allowing analog computation to take place across space and time. These wave interactions not only bind distributed neural populations into coherent states but also carry out computations that support flexible thought and control. Consciousness, then, emerges when these dynamic wave patterns bring the cortex into an organized, globally integrated state, one that naturally links and influences widespread activity.

This theory is not only conceptually plausible but biologically feasible. Cortical circuits naturally generate oscillatory dynamics and propagate waves through recurrent connectivity and horizontal cortical connections across multiple scales. The dynamics we emphasize thus require no special machinery. These waves are energetically efficient, leveraging continuous field interactions rather than metabolically costly, all-or-none spiking at every step. In this sense, the brain exploits its own physics: Electric field dynamics offer a low-overhead substrate for organizing and coordinating information across cortical networks. Given strong evolutionary pressure to maximize computation per unit energy, it would be surprising if evolution did not exploit such a built-in analog computing substrate.