Many AI scientists unconsciously assume a metaphysical position. It’s usually materialism

Understanding the Philosophical Foundations of Artificial Intelligence: Materialism and Its Unconscious Assumptions

In the pursuit of artificial intelligence, many researchers and scientists operate under implicit philosophical assumptions—most notably, a materialist view of consciousness and cognition. This perspective suggests that the mind and consciousness are entirely products of physical matter, and often informs how AI development is approached.

Recently, Ilya Sutskever, a prominent AI researcher, articulated a line of reasoning that exemplifies this worldview. In a talk, he stated:

“Since all of us have a brain—biological computers—we can reasonably assume that digital computers mimicking the brain can perform the same functions. Therefore, because the brain is a biological computer, a digital replica of this ‘brain’ should, in principle, be capable of similar cognitive feats.”

You can watch his full statement here.

This line of thinking, common in AI discourse, subtly assumes a metaphysical stance—that physical matter (the brain) is sufficient to explain consciousness, mental processes, and intelligence. Such an assumption is not merely a scientific hypothesis but a philosophical position known as materialism or physicalism—the idea that everything that exists is fundamentally physical.

It’s crucial to recognize that this isn’t an empirically proven fact; rather, it’s one lens through which the nature of mind and consciousness is interpreted. Numerous philosophical perspectives challenge this view, suggesting alternative possibilities such as dualism or existential approaches that consider non-material aspects of consciousness.

Ironically, the belief that one’s stance is purely scientific often masks an underlying metaphysical assumption. When researchers claim to be free of such biases, they might be unaware that they are holding unexamined dogmas.

A more transparent acknowledgment of these philosophical foundations can benefit the AI community. Far from hindering progress, embracing a broader reflection on these assumptions may foster innovation, clarity, and ultimately a deeper understanding of the mind—whether biological, artificial, or something entirely different.