AI isn't bias-free, it reflects exactly what it was trained on.
Gaps in data, flawed assumptions, and the limits of any dataset all get baked in. When we build systems around that AI, the bias doesn't disappear. It gets amplified.
It is important to make deliberate choices about how AI is used: keeping humans in the loop, designing workflows where AI informs rather than decides, and building at the points where bias is least likely to cause harm.
Safe AI isn't about perfect AI. It's about intentional AI.
What this means for health organizations
You can reduce the impact of bias by using AI to inform rather than decide, and by checking outcomes across different groups of clients over time.
