History of AI

He focuses on the fine differences between "true" and "artificial" (if at all) intelligence. This book is not a technical tome and makes for relatively easy reading. However, it would help if the reader was already somewhat familiar with basic AI approaches (in which the book's appendices help). Ekbia discusses computer chess (e.g. Deep Blue), case-based reasoning (e.g. Coach), artificial commonsense (e.g. Cyc), "emotional" robots (e.g. Kismet) and a selection of other examples which provide a good overview of the different perspectives both the public and researchers have about AI accomplishments. Some of Ekbia's arguments are difficult to argue against. For example, it is true that some researchers overstate their case in terms of just how "intelligent" or significant a particular approach is. Computers, after all, work in a mechanical fashion and have no real conception about the things they are working with. In many cases, this is obvious once you look "under the hood"; but in others, it is possibly just a matter of perspective. Take chess, for example. While the brute-force approach seems to work well and is purely mechanical, we cannot overlook the significance of the heuristic evaluation functions which are equally important. These are usually specifically designed by humans. Not to mention that this combination has resulted in programs running on desktop machines that can today outplay even grandmasters. In fairness, Ekbia does not trivialize this type of "success" in AI but suggests, rightfully, that we have perhaps just found a different approach to "thinking" in chess, and chess alone. But this is how it is in AI. The approach used in chess is neither required nor expected (at least these days) to be directly applicable to other areas with equal effectiveness. This, however, does not mean that at least some of the work done in that domain has not been useful in other domains or fields of research.Most of the book, including some gems in the footnotes at the back, hover around the point that we are somehow missing something in AI that would put us on the "right path", and that we are, at least, approaching this path slowly, perhaps without even realizing it. With a rich and colorful history behind AI, its future is unlikely to suffer from exactly the same mistakes despite the necessary evil or growing temptation faced by researchers to somewhat mislead industry-related benefactors into thinking they are financing something truly significant. I found myself generally sobering up to Ekbia's insights into AI and learning of happenings in the field that I was previously unaware of myself. Many books on AI will likely come off as highly technical and complicated (a lot of math is usually involved) but this one takes a "higher level" or philosophical approach which, I now think, should not be neglected even in undergraduate study of the field. One should, however, be careful not to give undue reverence to the idea of simply "being human" just because of the current shortcomings in AI. I am nevertheless certainly glad I made it a point to read the book while waiting for my viva voce.https://www.amazon.com/Artificial-Dreams-Quest-Non-Biological-Intelligence/dp/0521703395
--- Ayzed 4.0 out of 5 stars AI is Not What it Seems Reviewed in the United States on January 21, 2009 Verified Purchase
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AI; History of AGI