Where Artificial Intelligence and Neuroscience meet; A New Frontier

Intelligence has been a topic of investigation for many centuries, dating back to the ancient Greek philosophers. But it is fair to say that it is a topic of a more scientific approach for just about 60 years. Crucial in this respect is the emergence of artificial intelligence (AI) in the mid 20th century. As the word “artificial” suggests, AI aimed and aims not only to understand intelligence but also to build intelligent devices. The latter aim adds something to the study of intelligence that was missing until then: a focus on the mechanisms that generate intelligence and cognition (here, I will make no distinction between these two concepts).

The focus on mechanisms touches upon the core of what intelligence and cognition are all about. Intelligence and cognition are about mechanisms. Only a true mechanistic process can transform a sensory impression into a motor action. Without it, cognition and intelligence would not have any survival value. This is quite clear for processes like pattern recognition or motor planning, but it also holds for “higher” forms of intelligence (cognition), like communication or planning. Consequently, a theory of a cognitive process that does not describe a true mechanism (one that, at least in principle, can be executed) is not a full theory of that process, but at best an introduction to a theory or a philosophical account.

In this respect, AI is not different from other sciences like physics, chemistry, astronomy, and genetics. Each of these sciences became successful because (and often when) they focussed on an understanding of the mechanisms underlying the phenomena and processes they study. Yet, the focus on mechanisms was not always shared by other sciences that study intelligence or cognition, like psychology or neuroscience. For the most part, psychology concerned (and still concerns) itself with a description of the behavior related to a particular cognitive process. Neuroscience, of course, studied and studies the physiology of neurons, which aims for a mechanistic understanding. Yet, for a long time it stopped short at a translation from physiology to cognition.

Referenced from: https://www.hindawi.com/journals/aai/2010/918062/

 

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