Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract)

Get Out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula (Extended Abstract)

Rana Tallal Javed, Osama Nasir, Melania Borit, Loïs Vanhée, Elias Zea, Shivam Gupta, Ricardo Vinuesa, Junaid Qadir

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
Journal Track. Pages 6905-6909. https://doi.org/10.24963/ijcai.2023/780

This study explores the topics and trends of teaching AI ethics in higher education, using Latent Dirichlet Allocation as the analysis tool. The analyses included 166 courses from 105 universities around the world. Building on the uncovered patterns, we distil a model of current pedagogical practice, the BAG model (Build, Assess, and Govern), that combines cognitive levels, course content, and disciplines. The study critically assesses the implications of this teaching paradigm and challenges practitioners to reflect on their practices and move beyond stereotypes and biases.
Keywords:
AI Ethics, Trust, Fairness: General
Data Mining: General
Data Mining: DM: Exploratory data mining