Unlike humans, who have these pesky things called rights, we can abuse our computer programs to deduce why they made decisions. I can see a future where that has to happen. From my experience in trying to best the stock market with an algorithm I can tell you that you have to be able to explain why something happened, or the CEO will rest control away from the engineers.
Picture a court case where the engineers for an electric car are called upon to testify about why a child was killed by their self driving car. The fact that the introduction of the self-driving car has reduced the accident rate by 99% doesn’t matter, because the court case is about this car and this child. The 99% argument is for the closing case, or for the legislature, but it’s early yet. The Manufacturer throws up their arms and says “we dunno, sorry”. Meanwhile, the plaintiff has hired someone who has manipulated the inputs to the neural net, and they’ve figured out that the car struck the child, because the car was 100% sure the tree was there, but it could only be 95% sure the child was there. So it ruthlessly aimed for the lesser probability. The plaintiff’s lawyer argues that a human would have rather hit a tree than a child. Jury awards $100M in damages to the plaintiffs. I would think it would be possible to do “differential” analysis on AGZ positions to see why AGZ made certain moves. Add an eye to a weak group, etc. Essentially that’s what we’re doing with MCTS, right? It seems like a fun research project to try to build a system that can reverse engineer AGZ, and not only would it be fun, but its a moral imperative. Pierce
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