Using Case Studies to Teach Responsible AI to Industry Practitioners (2407.14686v3)
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.
- Julia Stoyanovich (56 papers)
- Rodrigo Kreis de Paula (1 paper)
- Armanda Lewis (3 papers)
- Chloe Zheng (1 paper)