Talk / Overview

Can AI, ML and Data Science help prevent children from getting lead poisoning? Can they help reduce infant and maternal mortality? What about police violence and misconduct? Can it help cities better target limited resources to improve the lives of citizens?

We're all aware of the potential of ML and AI but turning this potential into tangible and more importantly, equitable, social impact has challenges. In this talk, I'll discuss lessons learned from working on 50+ projects over the past few years with non-profits and governments on high-impact public policy and social challenges in criminal justice, public health, education, economic development, public safety, workforce training, and urban infrastructure. I'll highlight opportunities as well as challenges around bias/fairness that need to tackled in order to have social and policy impact in a fair and equitable manner.

Talk / Speakers

Rayid Ghani

Professor, Carnegie Mellon University

Talk / Highlights


Using Data Science to Achieve Fair and Equitable Social Outcomes

With Rayid GhaniPublished July 29, 2021

AMLD / Global partners