In a new perspective recently published in the journal PNAS Nexus, Athanassios S. Fokas explores a timely question: the potential of artificial intelligence (AI) to achieve and possibly exceed human cognitive capabilities. Historically, the focus has been on assessing computer models based on their proficiency in complex tasks, like triumphing in Go or engaging in conversations indistinguishable from those with humans.
According to Fokas, this approach has a key methodological limitation. Any AI would have to be tested on every single conceivable human goal before anyone could claim that the program was thinking as well as a human.
Alternative methodologies are therefore needed.
The Limitations of AI
In addition, the “complex goal” focus does not capture features of human thought, such as emotion, subjective experience, or understanding.
Furthermore, AI is not truly creative: AI cannot make connections between widely disparate topics, using methods such as metaphor and imagination, to arrive at novel results that were never explicit goals.
AI models are often conceptualized as artificial neural networks, but human thinking is not limited to the neurons; thinking involves the entire body, and many types of brain cells, such as glia cells, that are not neurons.
Fokas argues that computations reflect a small part of conscious thinking and that conscious thought itself is just one part of human cognition. An immense amount of unconscious work goes on behind the scenes. Fokas concludes that AI is a long way from surpassing humans in thought.
Reference: “Can artificial intelligence reach human thought?” by Athanassios S Fokas, 19 December 2023, PNAS Nexus.