September 28, 2023

Archives for November 2009

Targeted Copyright Enforcement: Deterring Many Users with a Few Lawsuits

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.

New York AG Files Antitrust Suit Against Intel

Yesterday, New York’s state Attorney General filed what could turn out to be a major antitrust suit against Intel. The suit accuses Intel of taking illegal steps to exclude a competitor, AMD, from the market.

All we have so far is the NYAG’s complaint, which tells one side of the case. Intel will have ample opportunity to respond, and the NYAG will ultimately have the burden of backing up its allegations with proof — so caution is in order at this point. Still, the complaint lays out the shape of the NYAG’s case.

The case concerns the market for x86-compatible microprocessors, which are the “brains” of most personal computers. Intel dominates this market but a rival company, AMD, has long been trying to build market share. The complaint offers a long narrative of Intel’s (and AMD’s) relationships with major PC makers (“OEMs”, in the jargon) such as Dell, HP, and IBM — the customers who buy x86 processors from Intel and AMD.

The crux of the case is the allegation that Intel paid OEMs to not buy from AMD. This is reminiscent of one aspect of the big Microsoft antitrust case of 1998, in which one of the DOJ’s claims was that Microsoft had paid people not to do business with Netscape.

I’ll leave it to the experts to debate the economic niceties, but as I understand it there is a distinction between paying someone to buy more of your product (e.g. giving a volume discount) as opposed to paying someone to buy less of your rival’s product. The former is generally fine, but if you have monopoly power the latter is suspect.

As the NYAG tells it, Intel tried to pretend the payments were for something else, but the participants knew what was really going on: that the payments would stop if an OEM started buying more from AMD. The evidence on this point could turn out to be important. Does the NYAG have “smoking gun” emails in which Intel made this explicit? Does the evidence show that OEMs understood the arrangement as the NYAG claims? I assume there’s a huge trove of email evidence that both sides will be digesting.

It will be interesting to watch this case develop. Thanks to tools like RECAP, many of the case documents will be available to the public. Stay tuned for more improvements to RECAP that will provide even better access.

Election Day; More Unguarded Voting Machines

It’s Election Day in New Jersey. As usual, I visited several polling places in Princeton over the last few days, looking for unguarded voting machines. It’s been well demonstrated that a bad actor who can get physical access to a New Jersey voting machine can modify its behavior to steal votes, so an unguarded voting machine is a vulnerable voting machine.

This time I visited six polling places. What did I find?

The good news — and there was a little — is that in one of the six polling places, the machines were properly secured. I’m not sure where the machines were, but I know that they were not visible anywhere in the accessible areas of the building. Maybe the machines were locked in a storage room, or maybe they hadn’t been delivered yet, but anyway they were probably safe. This is the first time I have ever found a local polling place, the night before the election, with properly secured voting machines.

At the other five polling places, things weren’t so good. At three places, the machines were unguarded in an area open to the public. I walked right up to them and had private time with them. In two other places, the machines were visible from outside the building and protected only by an outside door with an easily defeated lock. I didn’t defeat the locks myself — I wasn’t going to cross that line — but I’ll bet you could have opened them quickly with tools you probably have in your car.

The final scorecard: ten machines totally unprotected, eight machines poorly protected, two machines well-protected. That’s an improvement, but then again any protection at all would have been an improvement. We still have a long way to go.