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AI Systems Should Debate Each Other To Prove Themselves, Says OpenAI (fastcompany.com)
tedlistens shares a report from Fast Company: To make AI easier for humans to understand and trust, researchers at the [Elon Musk-backed] nonprofit research organization OpenAI have proposed training algorithms to not only classify data or make decisions, but to justify their decisions in debates with other AI programs in front of a human or AI judge. In an experiment described in their paper (PDF), the researchers set up a debate where two software agents work with a standard set of handwritten numerals, attempting to convince an automated judge that a particular image is one digit rather than another digit, by taking turns revealing one pixel of the digit at a time. One bot is programmed to tell the truth, while another is programmed to lie about what number is in the image, and they reveal pixels to support their contentions that the digit is, say, a five rather than a six.
The image classification task, where most of the image is invisible to the judge, is a sort of stand-in for complex problems where it wouldn't be possible for a human judge to analyze the entire dataset to judge bot performance. The judge would have to rely on the facets of the data highlighted by debating robots, the researchers say. "The goal here is to model situations where we have something that's beyond human scale," says Geoffrey Irving, a member of the AI safety team at OpenAI. "The best we can do there is replace something a human couldn't possibly do with something a human can't do because they're not seeing an image."
The image classification task, where most of the image is invisible to the judge, is a sort of stand-in for complex problems where it wouldn't be possible for a human judge to analyze the entire dataset to judge bot performance. The judge would have to rely on the facets of the data highlighted by debating robots, the researchers say. "The goal here is to model situations where we have something that's beyond human scale," says Geoffrey Irving, a member of the AI safety team at OpenAI. "The best we can do there is replace something a human couldn't possibly do with something a human can't do because they're not seeing an image."
It was produced back in the 60's
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This is garbage. It will simply lead to parallel reconstruction like the DEA/FBI/CIA does in their court cases when they get evidence by unlawful means like a stingray: the algorithm found a solution to the problem. then it will explain to you, the user how it got there by some arbitrary way which at least looks plausible but is totally made up.
ML is not made to be looked inside, it's a black box by design and there are so many data points, e.g. pictures in the trainingset for image classificiation, the algorithm cannot really show all the relevant ones for this particular decision. Total info overload for the human and therefore utterly useless. So to tell a "reason" that the human can accept, it must simply pretend. Humans and ML work fundamentally different when they "recognize" an image, so one cannot tell the other how it was done. Same with chess playing, same with pretty much all other (successful) AI things so far.
This is simply a PR stunt, an insulting and stupid PR stunt cause it only wants to make people feel good and they lie about the subject matter in the process. It doesn't really help to make a better AI either as they pretend there.