Evidence/algorithm bias – Ziad Obermeyer
October 7, 2020
Drawing on lessons from his work on algorithmic bias, Ziad Obermeyer talks about how seemingly small choices can snowball into large biases. In particular, that a subtle error—the conflation of health dollars with health needs—distorts both health algorithms and health policy, and discuss how to avoid that trap.