With new technology come new responsibilities. Examining artificial intelligence (AI) and its applications through an ethical lens has become increasingly important. Academia can play a critical role in shaping graduates who may work in both the ethical and technical spheres. To better understand how this may be integrated into higher education institutions, we assessed the content covered on AI ethics using Natural Language Processing (NLP) syllabi. A total of 45 AI ethics syllabuses made publicly available online were examined. Some important features captured from each syllabus were the course description, topics, department, and year. We observed overarching patterns across the AI ethics syllabi through supervised and unsupervised clustering and Latent Dirichlet Allocation (LDA) analysis. Some of these included information across various academic departments and the pre-post Chat-GPT era. This study is insightful as it offers a baseline for investigating various AI ethics topics that are described in academic departments, as well as uncovering potential gaps in the contents of AI ethics syllabi.
