Using Case Studies to Teach Responsible AI to Industry Practitioners
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.
Cite
Text
Stoyanovich et al. "Using Case Studies to Teach Responsible AI to Industry Practitioners." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35177Markdown
[Stoyanovich et al. "Using Case Studies to Teach Responsible AI to Industry Practitioners." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/stoyanovich2025aaai-using/) doi:10.1609/AAAI.V39I28.35177BibTeX
@inproceedings{stoyanovich2025aaai-using,
title = {{Using Case Studies to Teach Responsible AI to Industry Practitioners}},
author = {Stoyanovich, Julia and de Paula, Rodrigo Kreis and Lewis, Armanda and Zheng, Chloe},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {29062-29069},
doi = {10.1609/AAAI.V39I28.35177},
url = {https://mlanthology.org/aaai/2025/stoyanovich2025aaai-using/}
}