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LM101-001: Welcome to the Big Artificial Intelligence Magic Show!
Episode Summary:
This episode discusses the similarities between designing an android that can command a starship and designing an android that can play a game of checkers. In addition, the mystery underlying both artificial intelligence and biological intelligence is discussed.
Show Notes:
Artificial Intelligence (AI) is a field of Scientific Inquiry concerned with the problem of building systems that behave in an intelligent manner. A classic example of AI is the “android” DATA on Star Trek: The Next Generation. In the TV series, DATA is a robot but his behavior and mannerisms are so life-like that he could easily be mistaken for a human (with a few quirky habits).
The design and construction of DATA is an example application of artificial intelligence. Currently, an android with DATA’s capabilities is not available and probably will not be available until in the far distant future. On the other hand, there have been numerous impressive successes in the field of artificial intelligence over the years. The design of an android with DATA’s capabilities capable of commanding a starship would be extremely challenging. Like all problems encountered in everyday life, the android must make a sequence of decisions where each decision results in a different set of possible alternative decisions and the consequence of this decision sequence is not available until some point in the distant future.
Still, despite the technical challenges posed by this problem, many problems in the real world share important commonalities with the android design problem. For example, checkers is a board game which is much simpler in its complexity than the board games of Chess and GO yet more complex than the board game tic-tac-toe. Each player moves a playing piece on the board according to specific rules and tries to “capture” or “block” the opponents playing pieces. When one player can not make a move, then that player loses the game and the other player wins the game.
The checker game problem is interesting for several reasons. First, the particular configuration of the playing pieces on the checkerboard is analogous to a “situation” which the android might encounter on the starship. Second, selecting a particular checker piece to move is analogous to “making a decision” in the context of that situation. In the starship command problem, the average number of possible decisions at any given instant in time is virtually infinite but the in the checkers program the average number of possible decisions per situation in checkers is only about 5 moves. Third, the “goal” to win the game of checkers is not realized until multiple moves or decisions into the future (analogous to making a sequence of decisions as a starfleet commander). A starship commander might conceivably make thousands of crucial decisions over a several day time period before the outcome of those decisions is realized. The checkers playing problem is similar to the starship commander problem in the sense that the consequences of a particular decision are not understood until the distant future. But, whereas the distant future for the starship commander might be tens of thousands of decisions into the future. For a checker playing android, the distant future is probably no more than about 50 or hundred decisions into the future. That is, the number of “turns” in the checker game probably won’t exceed more than 50 or hundred turns. And fourth, the “situation” of winning the game is very well defined in contrast to the real world where the concept of success is typically more nebulous.
Thus, the checkers game problem (although vastly less complex than the starship commander problem) shares the essential core ingredients associated with the problem of commanding a starship. Specifically, given a situation, make a decision. Furthermore, the consequences of that decision may not be apparent until after many more decisions and an extended period of time. If we could figure out how to build an android or program a computer to play checkers, we might be able to extend these basic principles to approach the more complicated problem of designing an android capable of commanding a starship.
The key point is that although building an android to play Checkers is certainly a worthy endeavor such a task has the additional benefit of allowing us to investigate the underlying principles of more complex and sophisticated forms of artificial intelligence in a controlled setting.
In fact, an important breakthrough in artificial intelligence was a computer that could play checkers against very good checkers players. The computer program wasn’t able to meet national checker champions but it did compete with expert human checker players. It had this ability to make decisions about checker board situations that it had never seen before in its life and it also had the ability to learn from experience. And finally, the underlying principles that were the basis of this intelligent checker playing program involved not only logical deduction but the ability to learn from its experiences in an almost human manner. Thus, when the inventor of this program first started up the computer, the inventor played some games against the computer which learned from these experiences. As the computer played more games, it became smarter and smarter. And finally, one of the mechanisms underlying this computer program is similar to a biological mechanism that exists in human brains. Before discussing this fantastic breakthrough in greater detail however, it is important that we have a brief digression.
How many of you have ever gone to a magic store where they sell magic tricks to magicians? Typically the sales people are magicians and demo the magic but will only explain how to do something after you purchase it. One example piece of magic is the rising card trick. The magician asks you to pick a card and then it is placed back into the deck. The deck is shuffled. The magician waves his hand over the deck, and the card magically rises, it is the card chosen by the participant! The magic can be done within a few feet of the spectator in any lighting conditions, there are no threads or strings that can be seen. This seems like real magic. You are skeptical and ask to examine the deck. It is an ordinary deck of cards.
You ask the sales person if it is a hard piece of magic to learn. They say it is easy to learn but it costs $60. You don’t want to spend the money but you imagine amazing your friends and family with some real magic. Not some cheap trick that comes for free in a cereal box. You pay the $60 which is nonrefundable since the sales person explains the cost includes the secret. The sales person then gives you an ordinary deck of cards, instructions, and a tiny piece of scotch tape. The trick works by having a little piece of scotch tape on your thumb which you press against the spectators card. You can make the card rise by moving your thumb which is attached to the card. You feel a little disappointed..maybe even cheated because You have paid $60 for a piece of scotch tape and instructions. Also the magic trick just seems like a trick now. It doesn’t seem like real magic.
Artificial intelligence and perhaps natural biological intelligence is like a magic show. We are amazed and astounded by the intellectual feats of humans, animals, and machines yet each time we learn and advance our scientific understanding of the true underlying mechanisms of these Intellectual feats we may feel that we are not implementing True artificial intelligence but rather solving an understood engineering problem. A magic trick whose secret is not known is perceived as truly magical. A smart phone or smart robot or smart checker playing program which learns from experience and can solve problems that it has never seen before is perceived as artificially intelligent. However when the secret to the magic trick is revealed…we suddenly change our mind and say that’s not real magic. Similarly, when the methodology used by an artificially intelligent checkers program is revealed we have a tendency to say that’s not real artificial intelligence. Real artificial intelligence would be more like Data on Star Trek.
This digression is important because this series of podcasts will be like a magician revealing all of the secrets he or she uses to perform magic. As each secret is revealed it is important that you appreciate how simple concepts like a piece of tape or a simple learning mechanism can generate truly amazing and astounding phenomena. Instead of being disappointed that you paid $60 for a piece of scotch tape, you should be impressed and amazed with how much one can accomplish with a tiny piece of scotch tape!!
In two weeks, we will discuss the secret to the magic of the smart checker playing robot!!!
Hope to see you then!!!
Further Reading:
1. Marvin Minsky (1986). The Society of Mind. Simon and Schuster.
Copyright Notice:
Copyright © 2014 by Richard M. Golden. All rights reserved.
