TY - JOUR
AU - 
AB - The domain of Artificial Intelligence (AI) ethics is not new, with discussions going back at least 40 years. Teaching the principles and requirements of ethical AI to students is considered an essential part of this domain, with an increasing number of technical AI courses taught at several higher-education institutions around the globe including content related to ethics. By using Latent Dirichlet Allocation (LDA), a generative probabilistic topic model, this study uncovers topics in teaching ethics in AI courses and their trends related to where the courses are taught, by whom, and at what level of cognitive com- plexity and specificity according to Bloom’s taxonomy. In this exploratory study based on ©2022 AI Access Foundation. All rights reserved. Javed, Nasir, Borit, Vanhée, Zea, Gupta, Vinuesa & Qadir unsupervised machine learning, we analyzed a total of 166 courses: 116 from North Amer- ican universities, 11 from Asia, 36 from Europe, and 10 from other regions. Based on this analysis, we were able to synthesize a model of teaching approaches, which we call BAG (Build, Assess, and Govern), that combines specific cognitive levels, course content topics, and disciplines affiliated with the department(s) in charge of the course. We critically as- sess the 
TI - Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula
JF - Journal of Artificial Intelligence Research
DO - 10.1613/jair.1.13550
DA - 2022-03-26
UR - https://www.deepdyve.com/lp/unpaywall/get-out-of-the-bag-silos-in-ai-ethics-education-unsupervised-topic-zCF37PbLCc
DP - DeepDyve
ER -