Artificial intelligence is not all about thinking.

by Forrest Sheng Bao

This article is rated as PG-17 by me because reading this article may cause the collapsing of your world view and/or religious faith, and consequently, a threatening to your life.

I always thought that the introduction or the ending chapters of a textbook are not worth reading. Now I realize that I made such a big mistake on Russell and Norvig's famous AI textbook. I have been thinking about why symbolic AI is not developing fast since yesterday. And, now, I just realize that if i read those parts of the book, i don't have to swamp in Wikipedia pages about AI. I didn't read the 1st chapter and the 5th part of Russell and Norvig's famous AI textbook before I wrote this blog.

OK, let's begin.

Intelligence includes learning, right? But many people define AI as "a machine that can think." Like this one [1]. Thinking is not everything in learning.

2000 years ago, a Chinese guy called Confucius said:"To study and not think is a waste. To think and not study is dangerous. (學而不思則罔,思而不學則殆)"

I would change the definition of AI as "a machine that can perceive and think." Here, ``perceive'' includes learning.

But this is not the end. In the famous Turing test (similar tests like Chinese Room), a machine is supposed to communicate with a human tester. Hence, the machine needs to take some actions according to the knowledge in his ``brain.'' Do you think Aristotle is intelligent if he spoke nothing?

Therefore, I would like to revise my definition to AI into "a machine that can perceive, think and act."

Then I saw Herbert Simon's words:"machines that think, that learn and that create."[2]

And then I saw the title of the 5th part of Russell and Norvig's AI textbook:"Communicating, Perceiving and Acting." But I still would like to say that Russell and Norvig shouldn't put these ideas to the end of their book (before Conclusions). As I stated before, perceiving and acting are necessary parts of intelligence.

I think that people working on symbolic intelligence (mostly logic and reasoning, in contrast to computational intelligence, e.g., machine learning, evolution computing, part of robotics) focus on formulating human logic into symbols and semantics too much. Knowledge acquisition and expression have been underestimated.

[1] The website of Artificial General Intelligence Conference: "The original goal of the AI field was the construction of `thinking machines' "

[2] Wikiquote page of Herbert A. Simon,

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