Chris Stucchio wrote an interesting blog post which changed my mind on this. Instead of exacerbating it, a Machine Learning model can actively correct for bias.
Bias correction is possible, but, tautologically, a model whose structure cannot capture a bias cannot correct for that bias. This means that a modeller must either understand the bias, and accommodate for it in their model, or use a model that might be able to capture unknown structures and run the (serious) risk of over-fitting that model.
Bias correction is possible, but, tautologically, a model whose structure cannot capture a bias cannot correct for that bias. This means that a modeller must either understand the bias, and accommodate for it in their model, or use a model that might be able to capture unknown structures and run the (serious) risk of over-fitting that model.