TITLE: Learning to Program is a Loser's Game AUTHOR: Eugene Wallingford DATE: March 10, 2015 4:45 PM DESC: ----- BODY: After a long break from playing chess, I recently played a few games at the local club. Playing a couple of games twice in the last two weeks has reminded me that I am very rusty. I've only made two horrible blunders in four games, but I have made many small mistakes, the kind of errors that accumulate over time and make a position hard to defend, even untenable. Having played better in years past, these inaccuracies are irksome. Still, I managed to win all four games. As I've watched games at the club, I've noticed that most games are won by the player who makes the second-to-last blunder. Most of the players are novices, and they trade mistakes: one player leaves his queen en prise; later, his opponent launches an underprepared attack that loses a rook; then the first player trades pieces and leaves himself with a terrible pawn structure -- and so on, the players trading weak or bad moves until the position is lost for one of them. My secret thus far has been one part luck, one part simple strategy: winning by not losing. This experience reminded me of a paper called The Loser's Game, which in 1975 suggested that it was no longer possible for a fund manager to beat market averages over time because most of the information needed to do well was available to everyone. To outperform the market average, a fund manager has to profit from mistakes made by other managers, sufficiently often and by a sufficient margin to sustain a long-term advantage. Charles Ellis, the author, contrasts this with the bull markets of the 1960s. Then, managers made profits based on the specific winning investments they made; in the future, though, the best a manager could hope for was not to make the mistakes that other investors would profit from. Fund management had transformed from being a Winner's Game to a Loser's Game.
the cover of Extraordinary Tennis for the Ordinary Tennis Player
Ellis drew his inspiration from another world, too. Simon Ramo had pointed out the differences between a Winner's Game and a Loser's Game in Extraordinary Tennis for the Ordinary Tennis Player. Professional tennis players, Ramo said, win based on the positive actions they take: unreturnable shots down the baseline, passing shots out of the reach of a player at the net, service aces, and so on. We duffers try to emulate our heroes and fail... We hit our deep shots just beyond the baseline, our passing shots just wide of the sideline, and our killer serves into the net. It turns out that mediocre players win based on the errors they don't make. They keep the ball in play, and eventually their opponents make a mistake and lose the point. Ramo saw that tennis pros are playing a Winner's Game, and average players are playing a Loser's Game. These are fundamentally different games, which reward different mindsets and different strategies. Ellis saw the same thing in the investing world, but as part of a structural shift: what had once been a Winner's Game was now a Loser's Game, to the consternation of fund managers whose mindset is finding the stocks that will earn them big returns. The safer play now, Ellis says, is to minimize mistakes. (This is good news for us amateurs investors!) This is the same phenomenon I've been seeing at the chess club recently. The novices there are still playing a Loser's Game, where the greatest reward comes to those who make the fewest and smallest mistakes. That's not very exciting, especially for someone who fancies herself to be Adolf Anderssen or Mikhail Tal in search of an immortal game. The best way to win is to stay alive, making moves that are as sound as possible, and wait for the swashbuckler across the board from you to lose the game. What does this have to do with learning to program? I think that, in many respects, learning to program is a Loser's Game. Even a seemingly beginner-friendly programming language such as Python has an exacting syntax compared to what beginners are used to. The semantics seem foreign, even opaque. It is easy to make a small mistake that chokes the compiler, which then spews an error message that overwhelms the new programmer. The student struggles to fix the error, only to find another error waiting somewhere else in the code. Or he introduces a new error while eliminating the old one, which makes even debugging seem scary. Over time, this can dishearten even the heartiest beginner. What is the best way to succeed? As in all Loser's Games, the key is to make fewer mistakes: follow examples closely, pay careful attention to syntactic details, and otherwise not stray too far from what you are reading about and using in class. Another path to success is to make the mistakes smaller and less intimidating: take small steps, test the code frequently, and grow solutions rather than write them all at once. It is no accident that the latter sounds like XP and other agile methods; they help to guard us from the Loser's Game and enable us to make better moves. Just as playing the Loser's Game in tennis or investing calls for a different mindset, so, too does learning to program. Some beginners seem to grok programming quickly and move on to designing and coding brilliantly, but most of us have to settle in for a period of discipline and growth. It may not be exciting to follow examples closely when we want to forge ahead quickly to big ideas, but the alternative is to take big shots and let the compiler win all the battles. Unlike tennis and Ellis's view of stock investing, programming offers us hope: Nearly all of us can make the transition from the Loser's Game to the Winner's Game. We are not destined to forever play it safe. With practice and time, we can develop the discipline and skills necessary to making bold, winning moves. We just have to be patient and put time and energy into the process of becoming less mistake-prone. By adopting the mindset needed to succeed in a Loser's Game, we can eventually play the Winner's Game. I'm not too sure about the phrases "Loser's Game" and "Winner's Game", but I think that this analogy can help novice programmers. I'm thinking of ways that I can use it to help my students survive until they can succeed. -----