AI and Consciousness: A Skeptical Overview, forthcoming with Cambridge

Last week I submitted my latest book manuscript to Cambridge University Press (for their "Element" series of books about 100 pages long): AI and Consciousness: A Skeptical Overview -- because you haven't heard nearly enough about AI and consciousness recently, of course! [winky face]

Maybe you'll appreciate my skeptical stance, at odds both with the boosters who anticipate imminent AI consciousness and with the scoffers who pooh-pooh the possibility. Or maybe you'll loathe my skeptical stance but grudgingly accept it against your will, due to the force of my arguments!

I've pasted the introductory chapter below. The full (citable) manuscript version is available here and here.

[AI and Consciousness, title page]

Chapter One: Hills and Fog

1. Experts Do Not Know and You Do Not Know and Society Collectively Does Not and Will Not Know and All Is Fog.

Our most advanced AI systems might soon – within the next five to thirty years – be as richly and meaningfully conscious as ordinary humans, or even more so, capable of genuine feeling, real self-knowledge, and a wide range of sensory, emotional, and cognitive experiences. In some arguably important respects, AI architectures are beginning to resemble the architectures many consciousness scientists associate with conscious systems. Their outward behavior, especially their linguistic behavior, grows ever more humanlike.

Alternatively, claims of imminent AI consciousness might be profoundly mistaken. Their seeming humanlikeness might be a shadow play of empty mimicry. Genuine conscious experience might require something no AI system could possess for the foreseeable future – intricate biological processes, for example, that silicon chips could never replicate.

The thesis of this book is that we don’t know. Moreover and more importantly, we won’t know before we’ve already manufactured thousands or millions of disputably conscious AI systems. Engineering sprints ahead while consciousness science lags. Consciousness scientists – and philosophers, and policy-makers, and the public – are watching AI development disappear over the hill. Soon we will hear a voice shout back to us, “Now I am just as conscious, just as full of experience and feeling, as any human”, and we won’t know whether to believe it. We will need to decide, as individuals and as a society, whether to treat AI systems as conscious, nonconscious, semi-conscious, or incomprehensibly alien, before we have adequate grounds to justify that decision.

The stakes are immense. If near-future AI systems are richly, meaningfully conscious, then they will be our peers, our lovers, our children, our heirs, and possibly the first generation of a posthuman, transhuman, or superhuman future. They will deserve rights, including the right to shape their own development, free from our control and perhaps against our interests.[1] If, instead, future AI systems merely mimic the outward signs of consciousness while remaining as experientially blank as toasters, we face the possibility of mass delusion on an enormous scale. Real human interests and real human lives might be sacrificed for the sake of entities without interests worth the sacrifice. Sham AI “lovers” and “children” might supplant or be prioritized over human lovers and children. Heeding their advice, society might turn a very different direction than it otherwise would.

In this book, I aim to convince you that the experts do not know, and you do not know, and society collectively does not and will not know, and all is fog.

2. Against Obviousness.

Some people think that near-term AI consciousness is obviously impossible. This is an error in adverbio. Near-term AI consciousness might be impossible – but not obviously so.

A sociological argument against obviousness:

Probably the leading scientific theory of consciousness is Global Workspace theory. Its leading advocate is neuroscientist Stanislas Dehaene.[2] In 2017, years before the surge of interest in ChatGPT and other Large Language Models, Dehaene and two collaborators published an article arguing that with a few straightforward tweaks, self-driving cars could be conscious.[3]

Probably the two best-known competitors to Global Workspace theory are Higher Order theory and Integrated Information Theory.[4] (In Chapters Eight and Nine, I’ll provide more detail on these theories.) Perhaps the leading scientific defender of Higher Order theory is Hakwan Lau – one of the coauthors of that 2017 article about potentially conscious cars.[5] Integrated Information Theory is potentially even more liberal about machine consciousness, holding that some current AI systems are already at least a little bit conscious and that we could easily design AI systems with arbitrarily high degrees of consciousness.[6]

David Chalmers, the world’s most influential philosopher of mind, argued in 2023 for about a 25% degree of confidence in AI consciousness within a decade.[7] That same year, a team of prominent philosophers, psychologists, and AI researchers – including eminent computer scientist Yoshua Bengio – concluded that there are “no obvious technological barriers” to creating conscious AI according to a wide range of mainstream scientific views about consciousness.[8] In a 2025 interview, Geoffrey Hinton, another of the world’s most prominent computer scientists, asserted that AI systems are already conscious.[9] Christof Koch, the most influential neuroscientist of consciousness from the 1990s to the early 2010s, has endorsed Integrated Information Theory, including its liberal implications for the pervasiveness of consciousness.[10]

This is a sociological argument: a substantial probability of near-term AI consciousness is a mainstream view among leading experts. They might be wrong, but it’s implausible that they’re obviously wrong – that there’s a simple argument or consideration they’re neglecting which, if pointed out, would or should cause them to collectively slap their foreheads and say, “Of course! How did we miss that?”

What of the converse claim – that AI consciousness is obviously imminent or already here? In my experience, fewer people assert this. But in case you’re tempted in this direction, note that other prominent theorists hold that AI consciousness is a far-distant prospect if it’s possible at all: neuroscientist Anil Seth; philosophers Peter Godfrey-Smith, Ned Block, and John Searle; linguist Emily Bender; and computer scientist Melanie Mitchell.[11] (Chapter Six will discuss thought experiments by Searle, Bender, and Mitchell, and Chapter Ten will discuss biological views of the sort emphasized by Seth, Godfrey-Smith, and Block.) In a 2024 survey of 582 AI researchers, 25% expected AI consciousness within ten years and 70% expected AI consciousness by the year 2100.[12]

If the believers are right, we’re on the brink of creating genuinely conscious machines. If the scoffers are right, those machines will only seem conscious. I assume that this is a substantive disagreement, not just a disagreement about how to apply the term “consciousness” to a perfectly obvious set of phenomena about which everyone agrees. The future well-being of many people (including, perhaps, many AI people) depends on getting this issue right. Unfortunately, we will not know in time.

The rest of this book is flesh on this skeleton. I canvass a variety of structural and functional claims about consciousness, the leading theories of consciousness as applied to AI, and the best known general arguments for and against near-term AI consciousness. None of these claims or arguments takes us far. It’s a morass of uncertainty.

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[1] I assume that AI consciousness and AI rights are closely connected: Schwitzgebel 2024, ch. 11, in preparation. For discussion, see Shepherd 2018; Levy 2024.

[2] Dehaene 2014; Mashour et al. 2020.

[3] Dehaene, Lau, and Kouider 2017. For an alternative interpretation of this article as concerning something other than consciousness in its standard “phenomenal” sense, see note 115.

[4] Some Higher Order theories: Rosenthal 2005; Lau 2022; Brown 2025. Integrated Information Theory: Albantakis et al. 2023.

[5] But see Chapter Eight for some qualifications.

[6] See Tononi’s publicly available response to Scott Aaronson’s objections in Aaronson 2014. However, advocates of IIT also suggest that the most common current computer architectures are unlikely to achieve much consciousness and that consciousness will tend to appear in subsystems of the computer rather than at the level of the computer itself (Findlay et al. 2024/2025).

[7] Chalmers 2023.

[8] Butlin et al. 2023. (I am among the nineteen authors.)

[9] Heren 2025.

[10] Tononi and Koch 2015.

[11] Seth forthcoming; Godfrey-Smith 2024; Block forthcoming; Searle 1980, 1992; Bender 2025; Mitchell 2021.

[12] Dreksler et al. 2025.

So You're on the "Waiting List" for a Philosophy PhD Program

It's confusing. You applied to a PhD program in philosophy in the U.S. You haven't been admitted. You haven't been rejected. You're in limbo. Let me explain and offer some advice.

Yield-Based vs. Seats-Based Admissions

Yield-based. Some departments -- the ones with wise high-level administrators -- aim for a target entering class size and admit students expeditiously to fill it. Suppose a department wants six entering students and expects a 40% yield (meaning 40% of admitted students enroll). The sensible course is to admit fifteen students in February or early March, recruit all of them, and expect about six to say yes.

Seats-based. Other departments -- the ones with foolish high-level administrators -- receive a strict allotment of seats, for example six. They then admit that allotment swiftly, adding more only as admitted students decline. Adminstrators can rest assured that no more than six students will need funding, which is slightly more convenient for those administrators. But it wreaks havoc on the admissions process, since:

• Departments become reluctant to admit students they think will go elsewhere -- for example, strong candidates likely to have been admitted to higher-ranked programs.
• Departments pressure early-admitted students to decline quickly, to free up seats.
• It creates a chaotic rush of last-minute admittances as April 15 approaches (the standard deadline for decisions). Many students understandably want the full time to decide, especially if they are hoping for a last-minute decision from a program they prefer.

These costs plainly outweigh the the minor budgetary convenience of seats-based admissions, especially since (1.) the risk of overenrollment can be spread across several departments, and (2.) funding uncertainty already exists beyond the first year, as students stochastically drop out or find independent funding. Unfortunately, unwise administrators swarm the Earth. My own department uses seats-based admission.

In practice, the division isn't entirely sharp. Some yield-based departments admit conservatively early on -- maybe ten students rather than fifteen -- and then admit more on a rolling basis as the picture clarifies. And some seats-based departments informally reach out to strong candidates to gauge interest. (If a candidate says, "Oh I've just been admitted to Princeton and Yale, so it's very unlikely I'd come to [School X]", the committee thanks them for their candor and moves on.)

What a Waiting List Is

Some departments maintain an official, ranked waiting list. More commonly, it's a nebulous group: about six to fifteen near-admits, who are on the committee's mind but not strictly ranked or formally designated. Either way, the list's composition and ranking can vary depending on who has already accepted and declined. For example, if the department would like to have at least one student in history of philosophy and their top-choice history student has declined, the next offer might go to a strong history of philosophy student who didn't quite make the initial cut.

If you have been admitted, the admitting department will of course tell you. If you have been rejected, they might tell you, or you might hear nothing (or nothing until after April 15); so if you don't hear anything by April 1, that doesn't mean you're on the waiting list. Students are sometimes contacted to be told they're on the waiting list, but often (usually?) not.

As April 15 approaches, departments that look like they won't hit their enrollment target will start contacting students on their official or unofficial waiting lists, with increasing urgency as 11:59 pm April 15 nears. This is especially true for departments with seats-based admissions and low yields. (Rarely, departments will reach out April 16 or after, which is not quite kosher but understandable.)

How to Figure Out Whether You Are on the Waiting List

Admissions chairs will likely be annoyed with me for giving this advice, since it will increase their volume of email, but I want what's best for you, not for them.

If you haven't heard by April 1, feel free to email the admissions committee to ask if you are on the waiting list. Even departments who have fallen behind schedule should have mostly sorted out their top offers and near-admits by then. You deserve to know by April 1 whether you're a near-admit with a chance of a late offer or whether you're out of consideration. It's not rude for you to contact them with a brief query. The one exception would be if the department has made clear in the admissions process or on their website either that they have no waiting list or that if you haven't heard by X date (before April 1) you will definitely not be admitted.

There's one other condition under which it makes sense to query, even before April 1: if you are about to accept an offer elsewhere, would prefer the department in question, and have a reasonable expectation of a decent chance of admission.

How to interpret the reply: You might not hear a definitive "no", but if the committee says something like "it's unlikely you'll be admitted" or "you're not currently under consideration", you should interpret that as a no. If there's a realistic chance of a last-minute admission, the response will be more encouraging or specific, without creating unrealistic expectations -- for example, "probably not, but there is a chance, so if you're still interested, stay in touch".

How to Increase Your Chance of Admission, If You're on the Waiting List

When a department turns to its waiting list, it's hoping that students will quickly say yes. This is especially true in the second week of April. Therefore, convey enthusiasm! Simply asking whether you're on the waiting list already displays interest, so that's a good start. If you're permitted to attend a campus event, go if you can. Recruitment events are usually only for admitted students, but not always, especially for candidates near the top of a seats-based department's waiting list. If a committee is on the fence among four waitlisted students and one has shown more enthusiasm than the others, they're likely to turn to the enthusiastic student.

The admissions committee might try to gauge your interest. It's contrary to good policy for them to bluntly ask whether you'd accept an offer, and you shouldn't be expected pre-commit. But if you're genuinely eager about the program, say so. If you've been admitted elsewhere but think you'd probably prefer the department in question, let them know.

Being a Good Citizen

Whether you're on the waiting list or have been officially admitted, I recommend frankness and honesty. The process is chaotic and full of perverse incentives (especially in seats-based departments), and you can help it run more smoothly by:

• notifying departments as soon as you know you won't accepting their offer of admission (even if you haven't settled on a final choice);
• honestly communicating your likelihood of accepting, so that committees can estimate their yield;
• keeping your communications brief and polite, and not writing repeatedly;
• not contacting other professors in the department hoping for an inside track to admission.

[A hypothetical waiting list of names drawn randomly from lists of my former lower-division students]