Artificial Intelligence

Although I did some research on the subject of Artificial Intelligence, I make no pretence to any technical accuracy in my description of the making of Coyote and her emerging consciousness and sense of self. There is a vast and confusing literature to which the following excerpt may serve as an introduction to the subject for those who wish to learn more about AI and its potential, real and imagined. AI Growing Up: The Changes and Challenges” James F. Allen http://www.aaai.org/ojs/index.php/aimagazine/article/view/1422/1321

“AI has always been a strange field. Where else could you find a field where people with no technical background feel completely comfortable making claims about viability and progress? We see articles in the popular press and books regularly appear telling us that AI is impossible, although it is not clear what the authors of these publications mean by that claim. Other sources tell us that AI is just around the corner or that it’s already with us. Unlike fields such as biology or physics, apparently you don’t need any technical expertise in order to evaluate what’s going on in this field.

“But such problems are not limited to the general public. Even within AI, the researchers themselves have sometimes misjudged the difficulty of problems and have oversold the prospects for short-term progress based on initial results. As a result, they have set themselves up for failure to meet those projections. Even more puzzling, they also downplay successes to the point where, if a project becomes successful, it almost defines itself out of the field. An excellent example is the recent success of the chess-playing program DEEP BLUE, which beat the world chess champion in 1997. Many AI researchers have spent some effort to distance themselves from this success, claiming that the chess program has no intelligence in it, and hence it is not AI. I think this is simply wrong and will spend some time trying to argue why.”

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“For instance, to us, processes such as seeing, language understanding, and commonsense reasoning appear straightforward and obvious, while tasks such as doing mathematics or chess playing seem difficult. In contrast, it is the perceptual and commonsense reasoning tasks that are most difficult for machines to capture, whereas more formal problems like game playing are much more manageable. Thus, the generalizations that one might make by thinking of machines as people will tend to be highly inaccurate. For instance, one might think that because a machine can play excellent chess, it must be superintelligent, possibly more intelligent than any human. In order to defend against this “threat,” people feel they have to put down work. In contrast, if machines become capable of some truly difficult task such as understanding natural language, people may very well take this in stride and focus on how “intelligent” the system appears to be given what it says.”

Also: What is Artificial Intelligence?   http://www-formal.stanford.edu/jmc/whatisai/ 

Wikipedia at http://en.wikipedia.org/wiki/Artificial_intelligence