2 ms·

So, you are going back to the training data ;)

• danans 6y ago
  > So, you are going back to the training data ;) You asked about the biases of the people building the model, which is what I answered. You didn't ask about the biases that occur during the requirements specification stage, or the biases that occur during operational implementation of the trained model. Those are just as important - and arguably even more important - than the choice of the training data and the technical implementation. The responsibility for the ethics of using ML neither begins nor ends with the ML engineer who builds the machine, and there are serious questions arising from the application of ML in certain domains that cannot simply be addressed by "better training data".