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Because "computer says so" isn't good enough when your decisions affect someone else's life. The standards are set in other areas of statistical modelling, not
by ploika 7y ago
Because "computer says so" isn't good enough when your decisions affect someone else's life. The standards are set in other areas of statistical modelling, not other areas of software development.
There are countless examples in the public domain of AI systems improperly discriminating on race and gender when processing job applications, aiding medical diagnoses or targeting ads for housing and career opportunities. These outcomes can vary from annoying to morally questionable to explicitly illegal, and are all the more common when you don't really understand what your model is doing.
Statistical inference is important, and it's hard to get right. Centuries of thought have been put into methods to explain the effect of X on Y, accounting for Z. It's not the same goal as maximising the AUC or minimising the MSE. In many cases too, it's far more important.
- p1esk 7y agoIf “computer says so” and it’s been shown to be right more often than my doctor, I will trust the computer more. I already have very little trust in what doctors say, because their error rates are pretty high.
- ploika 7y agoYou're talking about prediction and classification, not inference. Why was I denied car insurance? How come I didn't get past the initial algorithmic screening phase of that job application? If you can't answer those questions properly you're in legal trouble in many jurisdictions. So going back to the original comment, that's why people are trying to understand neural networks, and why statistical inference and not just raw predictive power is important.
- p1esk 7y agoWould you prefer the model which is more correct, or more explainable? Let's assume for a second it's one or another.