Skip to main content

Here's Betting a Computer Can't Play Poker

Poker is a game of nerves, and a computer doesn't have any

“A computer can be programmed to "want" to win, but it cannot "fear" losing, in the sense of suffering consequences beyond the loss of the game itself.” – Steven Lubet

This article originally appeared in the Chicago Tribune on April 6, 2016.

By Steven Lubet

IBM's Deep Blue has apparently "solved" the game of chess — having defeated the reigning human world champion in 1997. Much more recently, Google's AlphaGo defeated an 18-time world Go champion. Can it be long before computer programs are able to trounce humans in every sort of intellectual game? The developers of AlphaGo certainly think so, as the lead researcher just posted a paper in which he claimed to have created a program capable of playing poker at the level that "approached the performance of human experts and state-of-the-art methods." Specifically, the paper asserts that the program, called NSFP, has "got within reach" of solving the game of Limit Texas Hold 'em.

While I don't doubt that the program was able to win a good many simulated poker games, it cannot "solve" Texas Hold 'em any more than a powerful robot can solve boxing. Poker is not simply a game of odds, moves and calculations. It is a game of controlled and exploited emotions — including greed, fear, over-confidence and anger. Because a computer does not experience emotions, it cannot play poker any more than a motorcycle can run a marathon. Whatever NSFP was doing — and no matter how well it was done — it was only a facsimile of real poker.

As has often been said, you don't actually play the cards in poker, you play your opponents. Properly understood, poker is a betting game, not a card game. If you don't believe that, try playing for bottle caps or toothpicks. You will quickly find out that the game is pointless; no more strategic than War and involving less skill than Go Fish.

Poker only becomes meaningful when played for real money, at which point considerations of fear, greed, over-confidence and self-doubt come into play. A good player is able to keep his or her emotions under control while exploiting the weaknesses of opponents. There are players who can excel at low stakes, but who get progressively worse as the stakes increase — finally falling completely apart in no-limit games with everything on the line. A computer obviously does not care about money, however, and therefore has neither fear of losing nor anticipation of winning. It cannot be intimidated or tricked; it cannot falter at a crucial moment; it cannot worry about the rent; it cannot fall into debt. Thus the human and the computer are not playing the same game.

This is not as easy as it sounds, and most players cannot avoid falling into patterns or showing "tells." The computer program, however, can build in true randomization, which solves the problem of creating identifiable patterns, but only in the sense that a laser scope solves the problem of aiming a rifle or Auto-Tune solves the problem of singing on key. Errors are eliminated, but only by changing the nature of the activity itself.

Poker legend Jack Straus was said to be the "master of the withering bluff," who was able to intimidate opponents into folding good hands, for fear that Strauss somehow held a winning pocket pair. That tactic could not work against a computer program — which cannot feel a sense of loss, worry or inadequacy.

A computer can be programmed to "want" to win, but it cannot "fear" losing, in the sense of suffering consequences beyond the loss of the game itself. Most games can be played simply as a contest of skills — chess and Go, for example — entirely within the parameter of the game. Winning can be its own reward, and the loss itself the only undesirable consequence. (You can bet on chess, of course, but that is not essential to the game.) Poker, however, is different, perhaps uniquely so, because each player is trying to take the others' money, not simply to achieve a defined goal or outcome. The objective in poker is not holding the best cards, or even winning the most hands — instead, it is manipulating your opponents into making the most bad decisions at the highest cost.

Playing human poker for real money is like walking on a high wire — perhaps over Niagara Falls, if the stakes are great enough. For a computer, however, it is as though the tightrope is suspended only a foot or so above the ground. You may not want to fall off, but nothing bad will happen if you do.

Or to put it differently, poker is a game of nerves, and a computer doesn't have any. A computer cannot fall prey to provocation, cajolery, manipulation, irritation, envy, embarrassment or dashed expectations, which means that it cannot be outplayed. We can think of many other games that can be "solved" by eliminating the human element, but so what? If an engineer were to create an unhittable pitching machine, no one would suggest that it had solved the game of baseball. Likewise, a kid with night-vision goggles has not solved hide-and-seek.

Perhaps the developers of NSFP can eventually teach us something about the process of complex decision-making with incomplete information. But they just aren't playing poker.

- Steven Lubet is a law professor at Northwestern University and the author of "Lawyers' Poker: 52 Lessons that Lawyers Can Learn from Card Players."

Topics: Chicago, Opinion

Editor's Picks

Back to top