Part III: Can We Build a Better Machine? Designing AI That Sees What Doctors Don’t or Won’t

Healthcare AI can amplify bias or dismantle it. The difference? Whether we design for equity, not just accuracy. The future of care depends on it.

Part III: Can We Build a Better Machine?

Designing AI That Sees What Doctors Don’t—or Won’t

By now, the promise and peril of AI in healthcare should feel familiar. We’ve seen how training algorithms on biased data can reinforce the inequities that medicine should fix. We’ve looked at the slow-motion disaster of diagnostic delay for women and how those delays are magnified when machines inherit the same blind spots as their human predecessors.

But this isn’t a dead end.
It’s a fork in the road.

Because for all the (justified) fear about algorithmic bias, a new cohort of researchers, data scientists, and public health advocates are asking a better question:

What if we built AI not to replicate medicine as it is, but to imagine what it could be?