Seth, Block and Tononi: AI consciousness unlikely in silicon

Three senior consciousness researchers have told Nature that today's AI is almost certainly not conscious, and that silicon-based systems may never be.

The essay is co-authored by Anil Seth of the University of Sussex, Ned Block of New York University and Giulio Tononi of the University of Wisconsin–Madison. Starting from different theories of consciousness, they converge on the same verdict about silicon: consciousness in today's AI is "extraordinarily unlikely, at least in the digital, silicon-based systems that underpin today's technologies."

Their first move separates intelligence from experience. The human cerebellum holds "nearly four-fifths of the neurons in the human brain," they note, yet contributes nothing to subjective awareness, so computational sophistication alone cannot be the test. Large language models, they write, are "mirrors that reflect an image of our collective digitized past" rather than minds.

The second reason is substrate. The authors reject computational functionalism, the view that running the right algorithm on any medium is enough. Brains, they write, are not simply "computers that are made of meat."

The third reason leans on Tononi's integrated information theory, which treats consciousness as a product of components tightly interconnected in specific ways that the layered, feed-forward architecture of today's deep-learning systems does not have.

Seven researchers in our Who's Who tracker shared the link within days of publication.