Earlier quoted context omitted.
I'm not OP, but I don't think the claim was specifically that models themselves are biased. It is that models are inherently biased because the data they are based on is biased. That might sound the same, but there is a nuanced difference. If you are able to strip the bias from the data, the models will work fine. The problem is the data and not the models.
At what point does this stop being AI's fault and start being an accurate observation of things that are society's fault? Let's say you have a racially-neutral observation of lower income, maybe disability status or a criminal rap in the past. That looks like a bad bet for a loan regardless of color, it just so happens that our society's created a statistical imbalance in those metrics.
I mean it is never truly the "AI's fault". It is the fault of the systems that resulted in the biased data and the people who ignored that bias while still delegating the decision making to that AI allowing it to be a tool that propagates those biases. You end up with a dangerous and self-perpetuating system like this:
1. Data is biased against Black people due to historic racism.
2. AI is built of this biased data.
3. AI results in a biased system that disadvantages Black people.
4. Black people get discriminated against due to the results from the AI.
5. New data is now even more biased against Black people.
6. Go to step 1.