I designed data visualizations for the Algorithmic Bias project as they published their Algorithmic Bias Playbook. This work was conducted through the Center for Applied Artificial Intelligence (CAAI) at the University of Chicago Booth School of Business.

Supervisor: Emily Joy Bembeneck

Description: Algorithmic bias is everywhere and is difficult to spot. Work done by Obermeyer et al shows that bias exists in commercial algorithms in health care systems, leading to Black patients being unfairly deemed “healthier” than equally sick White patients. This leads to a difference in care and has huge impacts on the health of these patients.

A scatterplot showing the risk score calculated by the algorithm compared against the number of active chronic conditions. The plot shows the scores for both white and Black patients. For a given algorithmic risk score, the Black patients have more chronic conditions than the white patients. This means that Black patients had to be sicker (have more chronic conditions) to receive the same treatment was white patients.

Repositories and Websites

Visualization Repository: the code for my visulizations