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Where I think you are wrong here is that you fail to consider the fact that the same programmer must decide which dataset/training data they will use for the AI

Where I think you are wrong here is that you fail to consider the fact that the same programmer must decide which dataset/training data they will use for the AI. So implicit biais is not just external to the programmer, it's definitely caused by the programmer. And implicit biais goes way beyond their training dataset. Did they put a clause "if pregnant, then...", likely not. However, what conditions did they use for testing this algorithm and ensure if it works? Testing is really much part of the process as well.

MontyCarloHall 5y ago
> So implicit biais is not just external to the programmer, it's definitely caused by the programmer. I agree in the case of things like facial recognition, but in the case of search results, Google can’t exactly choose whether websites it indexes present “Black teens” in a poor light and “White teens” in a good light. Perfectly unbiased algorithms trained on data produced by society will always exactly reflect the unfortunate biases of society. (Ironically, attempting to correct for society’s biases in the algorithm would by definition bias the algorithm itself!) This is (likely) not the case with Amazon drivers, since the training data are (presumably) strictly job performance-related, e.g. fraction of on-time deliveries, or number of times a worker showed up late. And even if these happen to correlate to demographics (e.g. if Black workers lived further from the warehouse than White workers [or vice-versa] and were thus more likely to show up to work late), tracking employees based on their on-time performance is not bias on Amazon’s part, since a White worker who showed up late would be just as likely to be fired as a Black worker who showed up late. The fact that one demographic (by no fault of its own) happens to show up late more often is not bias on the part of Amazon.

MontyCarloHall 5y ago

> So implicit biais is not just external to the programmer, it's definitely caused by the programmer. I agree in the case of things like facial recognition, but in the case of search results, Google can’t exactly choose whether websites it indexes present “Black teens” in a poor light and “White teens” in a good light. Perfectly unbiased algorithms trained on data produced by society will always exactly reflect the unfortunate biases of society. (Ironically, attempting to correct for society’s biases in the algorithm would by definition bias the algorithm itself!) This is (likely) not the case with Amazon drivers, since the training data are (presumably) strictly job performance-related, e.g. fraction of on-time deliveries, or number of times a worker showed up late. And even if these happen to correlate to demographics (e.g. if Black workers lived further from the warehouse than White workers [or vice-versa] and were thus more likely to show up to work late), tracking employees based on their on-time performance is not bias on Amazon’s part, since a White worker who showed up late would be just as likely to be fired as a Black worker who showed up late. The fact that one demographic (by no fault of its own) happens to show up late more often is not bias on the part of Amazon.