Using Case Studies to Teach Responsible AI to Industry Practitioners

TL;DR

This paper presents an interactive case study approach for teaching Responsible AI to industry practitioners, demonstrating improved understanding and motivation through workshops co-developed with Meta.

Contribution

It introduces a stakeholder-first educational method using case studies and reports on successful implementation with Meta to enhance RAI learning among practitioners.

Findings

Participants found the workshops engaging.

Participants reported improved understanding of RAI.

Participants showed increased motivation to apply RAI principles.

Abstract

Responsible AI (RAI) encompasses the science and practice of ensuring that AI design, development, and use are socially sustainable -- maximizing the benefits of technology while mitigating its risks. Industry practitioners play a crucial role in achieving the objectives of RAI, yet there is a persistent a shortage of consolidated educational resources and effective methods for teaching RAI to practitioners. In this paper, we present a stakeholder-first educational approach using interactive case studies to foster organizational and practitioner-level engagement and enhance learning about RAI. We detail our partnership with Meta, a global technology company, to co-develop and deliver RAI workshops to a diverse company audience. Assessment results show that participants found the workshops engaging and reported an improved understanding of RAI principles, along with increased motivation to apply them in their work.