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

Understanding the Philosophical Foundations of Artificial Intelligence: Beyond Materialism

In the rapidly evolving field of artificial intelligence, many researchers and scientists unconsciously operate from underlying philosophical assumptions. One prevalent stance is a materialist worldview, which posits that all mental phenomena, including consciousness and intelligence, arise solely from physical processes in the brain.

Recently, notable AI researcher Ilya Sutskever articulated this perspective during a talk, emphasizing the biological basis of our intelligence. He explained:

“Our brains are biological computers. Since the brain can perform certain tasks, why can’t a digital computer—the digital brain—do the same? That’s the core reasoning: because our brain is a biological computer, a digital replica should be capable of similar functions.”

This line of reasoning is quite common in AI development circles. It suggests that understanding the brain as a biological machine logically leads to the conclusion that digital machines can emulate or even surpass human intelligence.

However, it’s vital to recognize that such assumptions extend beyond empirical science into the realm of metaphysics. The belief that matter is the fundamental basis of mind—known as materialism—is a philosophical stance that has yet to be definitively proven. While it is a coherent and widely held view, alternative philosophical frameworks also exist, proposing that consciousness might encompass more than just physical processes.

Ironically, the assumption that one holds no metaphysical bias often masks underlying dogmas. Acknowledging and examining these foundational beliefs can be more than an academic exercise; it can enhance the clarity and depth of our pursuit of artificial intelligence. Being explicit about our philosophical positions may not hinder progress—in fact, it might sharpen our understanding and guide us toward more robust and innovative approaches.

Reflecting on the philosophical assumptions behind AI development can lead to more conscious, well-rounded advancements in the field.