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One reason the record industry’s strategy of suing online infringers ran into trouble is that there are too many infringers to sue. If the industry can only sue a tiny fraction of infringers, then any individual infringer will know that he is very unlikely to be sued, and deterrence will fail.

Or so it might seem — until you read The Dynamics of Deterrence, a recent paper by Mark Kleiman and Beau Kilmer that explains how to deter a great many violators despite limited enforcement capacity.

Consider the following hypothetical. There are 26 players, whom we’ll name A through Z. Each player can choose whether or not to “cheat”. Every player who cheats gets a dollar. There’s also an enforcer. The enforcer knows exactly who cheated, and can punish one (and only one) cheater by taking $10 from him. We’ll assume that players have no moral qualms about cheating — they’ll do whatever maximizes their expected profit.

This situation has two stable outcomes, one in which nobody cheats, and the other in which everybody cheats. The everybody-cheats outcome is stable because each player figures that he has only a 1/26 chance of facing enforcement, and a 1/26 chance of losing $10 is not enough to scare him away from the $1 he can get by cheating.

It might seem that deterrence doesn’t work because the cheaters have safety in numbers. It might seem that deterrence can only succeed by raising the penalty to more than $26. But here comes Kleiman and Kilmer’s clever trick.

The enforcer gets everyone together and says, “Listen up, A through Z. From now on, I’m going to punish the cheater who comes first in the alphabet.” Now A will stop cheating, because he knows he’ll face certain punishment if he cheats. B, knowing that A won’t cheat, will then realize that if he cheats, he’ll face certain punishment, so B will stop cheating. Now C, knowing that A and B won’t cheat, will reason that he had better stop cheating too. And so on … with the result that nobody will cheat.

Notice that the trick still works even if punishment is not certain. Suppose each cheater has an 80% chance of avoiding detection. Now A is still deterred, because even a 20% chance of being fined $10 outweighs the $1 benefit of cheating. And if A is deterred, then B is deterred for the same reason, and so on.

Notice also that this trick might work even if some of the players don’t think things through. Suppose A through J are all smart enough not to cheat, but K is clueless and cheats anyway. K will get punished. If he cheats again, he’ll get punished again. K will learn quickly, by experience, that cheating doesn’t pay. And once K learns not to cheat, the next clueless player will be exposed and will start learning not to cheat. Eventually, all of the clueless players will learn not to cheat.

Finally, notice that there’s nothing special about using alphabetical order. The enforcer could use reverse alphabetical or any other order, and the same logic would apply. Any ordering will do, as long as each player knows where he is in the order.

Now let’s apply this trick to copyright deterrence. Suppose the RIAA announces that from now on they’re going to sue the violators who have the lowest U.S. IP addresses. Now users with low IP addresses will have a strong incentive to avoid infringing, which will give users with slightly higher IP addresses a stronger incentive to avoid infringing, and so on.

You might object that infringers aren’t certain to get caught, or that infringers might be clueless or irrational, or that IP address order is arbitrary. But I explained above why these objections aren’t necessarily showstoppers. Players might still be deterred even if detection is a probability rather than a certainty; clueless players might still learn by experience; and an arbitrary ordering can work perfectly well.

Alternatively, the industry could use time as an ordering, by announcing, for example, that starting at 8:00 PM Eastern time tomorrow evening, they will sue the first 1000 U.S. users they see infringing. This would make infringing at 8:00 PM much riskier than normal, which might keep some would-be infringers offline at that hour, which in turn would make infringing at 8:00 PM even riskier, and so on. The resulting media coverage (“I infringed at 8:02 and now I’m facing a lawsuit”) could make the tactic even more effective next time.

(While IP address or time ordering might work, many other orderings are infeasible. For example, they can’t use alphabetical ordering on the infringers’ names, because they don’t learn names until later in the process. The ideal ordering is one that can be applied very early in the investigative process, so that only cases at the beginning of the ordering need to be investigated. IP address and time ordering work well in this respect, as they are evident right away and are evident to would-be infringers.)

I’m not claiming that this trick will definitely work. Indeed, it would be silly to claim that it could drive online infringement to zero. But there’s a chance that it would deter more infringers, for longer, than the usual approach of seemingly random lawsuits has managed to do.

This approach has some interesting implications for copyright policy, as well. I’ll discuss those next time.