mariovitali
Senior Member
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Apparently machine learning is lousy if the data going into it is skewed by being either too heavily male or female:
https://www.statnews.com/2020/05/25/ai-systems-training-data-sex-bias/
Of course it is @Learner1 , this is a typical example of GIGO (Garbage-In, Garbage Out).
IMO, i would look at bias of any kind :
-A Researcher that specialises in Brain metabolism may be biased to hypothesise that the brain function is important to ME
- A Researcher that specialises in Viruses may be biased to hypothesise that the viruses are important to ME
-An ME Organisation may be biased in providing specific researchers with funding because the commitee of experts of the organisation may be biased in their own ways.
and finally,
-A computer scientist who specializes in Machine Learning may be biased to hypothesise that Machine Learning can find the solution to ME (...)
But, if you ask me -and perhaps being biased myself- algorithms - if used properly- are more likely to find a solution in an unbiased way than any other human (if the input data are not Garbage).