3 Sources of Bias in AI

” … Math really is pure, has certain truth, it’s eternal, it would be the same without any particular sentient species looking at it. That’s because math is an abstraction that doesn’t exist in the real world. Computation is a physical process.

… the first source of AI bias:  unintentionally uploading the implicit human biases that pervade our culture … There’s no real way to fix this without fixing our culture first, so we need to compensate for it when we design our systems.

… the second source of AI bias is poorly-selected training data for machine learning, or poorly reasoned rules … when we detect these errors we can fix them, so we can expect that these types of AI biases should iteratively improve and hopefully eventually disappear

… the third source of AI bias is evil programmers.  Or corporations, or governments … The way to deal with this is to insist on the right to explanation, on due process.  All algorithms that affect people’s lives should be subject to audit.”

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