Raw LLM Responses

> (a) the test’s probability estimates are systematically skewed upward or downward for at least one gender; This is undesirable because it results in inaccurate estimates. >(b) the test assigns a higher average risk estimate to healthy people (non-carriers) in one gender than the other; or (c) the test assigns a higher average risk estimate to carriers of the disease in one gender than the other. Why are these undesirable? I would expect both of these to hold true in a fair algorithm. One gender is more at risk of the disease than the other; risk estimates for that gender should be higher on average, or what you're calculating isn't a risk estimate. If you knew ahead of time who was healthy and who was a carrier, you wouldn't need a risk estimate, so the average estimate for members of that gender should be higher whether or not they are a carrier. That's if literally the only data point you're looking at is gender (not a very effective risk estimate); if you try to give women and men the same average risk rating when more of one gender is a carrier than the other, you're asking your algorithm to lie to you.