User:CharlesGillingham/More/AI Winter

External Hype
"AI experienced a ... premature optimism", writes Ray Kurzweil, "While the widespread expectations for revolutionary change are accurate, the are inccorrectly timed." He explains: The technology 'hype cycle' for a paradigm shift — railrouds, AI, internet, telecommunications....— typically starts with a period of unrealiistic expectations based on a lack of understand of all the enabling factors involved required. Although utilization of the new paradigm does increase exponentially, early growth is slow until the kneee of the exponentional is realized. While the widespread expectations for revolutionary change are accurate, the are inccorrectly timed. When the prospects do not quicky pan out, a perdiod of disillusionment sets in. Nevertheless exponential growth continues unabated and years later a more mature and realistic transformation does take place. We saw this in the widespread railroad frenzy of the nineteenth century ... and we are still feeling effects of the e-commerce and telecommunications busts.

Internal Hype
The first generation of AI researchers made these predictions about their work:
 * 1958, Allen Newell: "within ten years a digital computer will the world's chess champion" and "within ten years a digital computer will discover and prove an important new mathematical theorem."
 * 1965, H. A. Simon: "machines will be capable, within twenty years of doing any work a man can do"
 * 1967, Marvin Minsky: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."
 * 1970, Marvin Minsky (in Life Magazine): "In from three to eight years we will have a machine with the general intelligence of an average human being."

Daniel Crevier gives several reasons to explain why AI has always (and still does) generate such incredible hyperbole: ....

McCorduck on bad predictions:

Newell & Simon's exagerrated predictions p. 218-225 (the same ones, of course)

Simon, defending his predictions, blamed two things: man-hours and the commonsense knowledge problem. "There we just vastly underestimated two things: first, how little, how few man years would go into this; and second how much very specifci knowledge had to be poured into it. Maybe we left out some other things, but those are the only things I'm willing to admit we left out!" S, quoted in M, p. 220

Herbert Simon said that they had "vastly underestimated" the commonsense knowledge problem and the man-hours. In reference to the Chess prediction, Minksy also blames man-hours. p. 220.

Simon also blames the timidity of some researchers. p. 221 (really!)

He complains that his predictions are no worse than others made in other fields. Everybody's doing it. "You someone can go around with the smallest scintilla of evience and make a new kind of universe that expands or contracts or is permanently in one state or another. Cosmologists go around doing this all the time, and tey're regarded as good scientists in astronomy because that's part of the mores of that filed.... Biologists on the whole are much more careful, in that sense of careful" (I don't buy this for a second, by the way.)

Limits and brick walls
Finally, a case can be made that these researchers actually believed that these things were possible. They were unaware or did not appreciate how difficult the problems they faced would be, problems like commonsense reasoning ...

raw computer power, intractability and combinatorial explosion,

IBM ends support for AI in 1960
The very first computers were referred to in the press as "electronic brains." The public's reaction was one of horror. When IBM researcher Herbert Gelernter told people about his experiments in AI, IBM abruptly shut him down and stopped all research in to AI. The executives at IBM realized that, to sell computers, it was important to sell the idea that computers could "only do what they were told." They no longer allowed their machines to be called "giant brains" and instead preferred more innocous nicknames like "number crunchers."

"'The Dartmouth conference represents a change in support for AI, from private industry to government. Thus, the activities surrounding the Dartmouth workshop were, at the outset, linked with the cutting-edge research at a leading private research laboratory (AT&T Bell Laboratories) and a rapidly emerging industrial giant (IBM). Researchers at Bell Laboratories and IBM nurtured the earliest work in AI and gave young academic researchers like McCarthy and Minsky credibility that might otherwise have been lacking. Moreover, the Dartmouth summer research project in AI was funded by private philanthropy and by industry, not by government. The same is true for much of the research that led up to the summer project.'" "What made AI different was that the very idea of it arouses a real fear and hostility in some human breasts. So you are getting very strong emotional reactions. But that's okay. We'll live with that." A Conversation with Herbert Simon. By Reuben L. Hann. Gateway IX(2): 12-13 (1998).

"'Yet, in spite of the early activity of Rochester and other IBM researchers, the corporation's interest in AI cooled. Although work continued on computer-based checkers and chess, an internal report prepared about 1960 took a strong position against broad support for AI.' from Developments in Artificial Intelligence from"