iSchool Capstone

AI, Anti-Bias and Accessibility

Project tags:

data science & visualization

equity & inclusion

information literacy

One of the most challenging topics in healthcare today is thinking about the impact of AI. This project centered on developing accessible teaching material using an anti-bias and equity lens. The crux of the challenge was creating content that spoke to Faculty, C-Suite decision makers and clinicians. Unfortunately, expertise is often siloed across these groups leading to negative outsized impacts. The key take-way was demonstrating the importance of expertise and demographic diversity across the data provenance pipeline in order to achieve more equitable healthcare outcomes. This collaborative work will continue towards making healthcare AI models more accessible and transparent.

Project participants:

Elle Dimopoulos

MLISOnline