> if the AIs that are supposed to do our jobs turn out to be very fallible as well? To state that AIs can be foiled by a specifically crafted adversarial attac

> if the AIs that are supposed to do our jobs turn out to be very fallible as well? To state that AIs can be foiled by a specifically crafted adversarial attack, does not mean the AI is very fallible. Under normal circumstances it still outperforms humans. But let's say the error rate of a net is on average 3%, and an attack works only if it is crafted for a specific net (where the weights are known etc.). Like a team of humans is able to come up with better solutions than individual team members, so does an ensemble of nets (usually) outperform any of its individual members. For instance, the final model generalizes better, because it uses information and predictions from all the nets. Foil one out of ten nets, and the other nine will cancel out the bad prediction with their votes. In an automated future jobs will be taken up by AI. A security guard then becomes a supervisor: 100s of nets will try to detect disturbances in a mall, and when they find one, they notify the supervisor. A judgement call is then made by a human. This is currently happening with law expert systems. A judge will input the case and get a prediction for punishment. Then make a final adjustment to this punishment, looking at the context of the case. Such a system prevents racially based sentences (the AI will not care about race, but look at precedent), while still giving emotions, judgment and reasoning a final say. > it seems that some problems are inherently prone to making mistakes. Can it be avoided at all? Some problems are incomputable, like finding the shortest program to reproduce a larger string. In others, like lossy compression, mistakes may be made in representing lossless information, that humans are unable to spot. I think this is a very interesting, but difficult question to answer. > who do we blame when an AI makes a "mistake" like that? The training set? We blame the AI researcher that build the net :). And she will blame the training set :).