The creator of LISP and of the term "Artificial Intelligence," died today. A great loss. His work in the field of AI yielded great fruit for the world. A few choice quotes:
Our ultimate objective is to make programs that learn from their experience as effectively as humans do. We shall…say that a program has common sense if it automatically deduces for itself a sufficient wide class of immediate consequences of anything it is told and what it already knows.
On Chess as a target for AI:
Chess programs catch some of the human chess playing abilities but rely on the limited effective branching of the chess move tree. The ideas that work for chess are inadequate for go. Alpha-beta pruning characterizes human play, but it wasn't noticed by early chess programmers - Turing, Shannon, Pasta and Ulam, and Bernstein. We humans are not very good at identifying the heuristics we ourselves use. Approximations to alpha-beta used by Samuel, Newell and Simon, McCarthy. Proved equivalent to minimax by Hart and Levin, independently by Brudno. Knuth gives details.
Alexander Kronrod, a Russian AI researcher, said 'Chess is the Drosophila of AI.' He was making an analogy with geneticists' use of that fruit fly to study inheritance. Playing chess requires certain intellectual mechanisms and not others. Chess programs now play at grandmaster level, but they do it with limited intellectual mechanisms compared to those used by a human chess player, substituting large amounts of computation for understanding. Once we understand these mechanisms better, we can build human-level chess programs that do far less computation than do present programs. Unfortunately, the competitive and commercial aspects of making computers play chess have taken precedence over using chess as a scientific domain. It is as if the geneticists after 1910 had organized fruit fly races and concentrated their efforts on breeding fruit flies that could win these races.
When asked "Can computers think?
Thinking isn't one thing. It has many aspects. For example, computers have the ability to remember information and the ability to play games. Some aspects of thinking, we have not succeeded in. A notable examples is the analysis of situations. A computer cannot break a situation into parts, analyze the parts separately, and then combine the parts to come to a conclusion. A specific manifestation of this is the game "Go". This type of thinking is necessary in "Go", where it is not in Chess. This is why the best computers are as good as people in Chess, but the best computers are much worse than people in "Go".
When asked "Can computers have free will?"
In my paper over free will, I defined "simple deterministic free will," which a computer can have. In fact, modern chess playing computers have this. However, this is not always true for displays of artificial intelligence. Consider two optimal tic-tac-toe playing programs. The first evalutes future situations in order to choose the optimal solution. The other simply looks at the state of the board, for which there are only 3^9 possibilities, and picks a move from a lookup table. The first program exhibits simple deterministic free will, where the second program does not. A chess program cannot have a lookup table because the state is too complex. Thus quantitative considerations are important. Philosophers would have you believe that they are not. That a chess problem and a tic tac toe problem are equivalent. I believe quantitative considerations are important.
On his creation of LISP:
If I hadn't come up with it, someone else would have. Pure Lisp was a discovery, everything that has been done with it since has been an invention. It started out as a formula for conditional expressions (if c then a else b). The logical structure followed from that. I got the idea from Newell and Simon. They came out with a language called IPL in 1956. I heard about it, and thought it was a fascinating idea. I saw the language and thought it was horrible.