System Safety Engineering for Social and Ethical ML Risks: A Case Study

no code implementations • 8 Nov 2022 • Edgar W. Jatho III, Logan O. Mailloux, Shalaleh Rismani, Eugene D. Williams, Joshua A. Kroll

Governments, industry, and academia have undertaken efforts to identify and mitigate harms in ML-driven systems, with a particular focus on social and ethical risks of ML components in complex sociotechnical systems.

From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML

no code implementations • 6 Oct 2022 • Shalaleh Rismani, Renee Shelby, Andrew Smart, Edgar Jatho, Joshua Kroll, AJung Moon, Negar Rostamzadeh

Inappropriate design and deployment of machine learning (ML) systems leads to negative downstream social and ethical impact -- described here as social and ethical risks -- for users, society and the environment.

Cultural Vocal Bursts Intensity Prediction Management