Bias in AI: How to monitor, measure and mitigate it using real-life case studies

Abstract

This talk would focus on some real life use cases of bias in AI and how it had socioeconomic impact, along with practical mitigation strategies to make AI more responsible. The session would dive deep into how and where bias manifests in the overall ML cycle, and ways to measure and remove it.