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Maybe someone already said it, but I just don't see Twitter as a public space -- it is not Hyde Park Corner, it is a large courtyard, very large indeed, but privately owned. From this perspective, I am really not bothered of who is on it and who is not (I am not on it).

The topic discussed in the Twitter thread, on the other hand, is much more interesting. I am a layman in ML (although I have implemented a NN myself, but I am not a data scientist) so I offer my view hoping to get some feedback and be corrected. My view is that the original post was correct and LeCun was not. I just can't see what sort of objective function you can use to solve every potential problem arising in the future about similar issues. You want a "totally unbiased" model? Then, you use total diversity in your training set? Can't it happen that the model will then enforce diversity in a non-diverse picture? Is that your ideal result?

That might be a silly example and maybe not 100% correct for the example discussed, but, in general, my layman feeling is just that ML cannot help in cases where moral judgement is required. It can provide a good tool in any other case where, for example, a quadratic error is a reliable error measure, but that seems a hard limitation.



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