Really just getting to the actual thing for more people to understand: none of these “AIs” are intelligent at all, and calling them artificial “intelligence” is completely misleading and causes people to make very dumb assumptions about how they work.

“Traditional” AI is just writing models to quantify things and then weighting decision-making based on those metrics. It’s just playing Guess Who? with outcomes. “Oh, we can get rid of all the candidates we don’t want by asking if they have a mustache and filtering out the ones who don’t.” Decisions like that, over and over. As you said, nested if statements.

Neural Networks are just doing the same thing, but without the authors actually making decisions about those intermediate questions. You feed dependent variables in along with lists of covariates and let an algorithm randomly stumble and guess around with them until it comes up with the relative quantification itself. This means you don’t KNOW if it is including discrimination in its process.

Which is why laws like this are necessary. If you don’t know how the “AI” model is arriving at its outcomes, you don’t know if it is discriminating. You have to be able to audit it. Because my “traditional” AI example, you can see it’s likely discriminating against women, but with all the hidden layers and complex relationships in the NN you won’t know it did the same until decades later.