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

Understanding the Unconscious Metaphysical Assumptions in AI Science

In the realm of artificial intelligence research, it’s intriguing to observe that many scientists implicitly adopt a particular metaphysical standpoint—most often, a materialist perspective. This assumption underpins much of the foundational reasoning behind AI development and expectations for future capabilities.

For instance, prominent AI researcher Ilya Sutskever recently articulated a perspective that exemplifies this line of thought. In a public talk, he stated:

“How can I be so sure of that? The reason is that all of us have a brain. And the brain is a biological computer. That’s why. We have a brain. The brain is a biological computer. So why can’t the digital computer, a digital brain, do the same things?”

This statement encapsulates a common worldview within AI circles: the idea that since the human brain functions as a biological computer, a sufficiently advanced digital computer could replicate or even surpass human cognitive abilities.

Watch Sutskever’s full statement here

While such reasoning seems rooted in scientific understanding, it also reveals an underlying metaphysical assumption—namely, that physical matter alone is sufficient to explain consciousness and mind. This perspective, known as materialism, posits that mental phenomena emerge entirely from physical processes.

It’s crucial to recognize that this belief isn’t a proven scientific fact but a philosophical stance. It assumes that consciousness and subjective experience can be fully reduced to, or generated by, material interactions—a claim that remains debated and far from conclusively established.

Ironically, asserting that one holds no metaphysical beliefs can itself be a form of unexamined dogma. Many so-called “non-metaphysical” positions are in fact implicitly rooted in this materialist view. Being transparent about our philosophical assumptions does not hinder scientific progress; it may, in fact, enhance it by encouraging clearer, more critical thinking.

In the evolving field of artificial intelligence, understanding and questioning these foundational metaphysical premises can open new avenues of inquiry and innovation. Recognizing that our assumptions shape, and sometimes limit, our conceptual frameworks is a vital step toward a more comprehensive understanding of intelligence—whether biological or artificial.