Date
Publisher
arXiv
The pervasive integration of artificial intelligence (AI) across domains such
as healthcare, governance, finance, and education has intensified scrutiny of
its ethical implications, including algorithmic bias, privacy risks,
accountability, and societal impact. While ethics has received growing
attention in computer science (CS) education more broadly, the specific
pedagogical treatment of {AI ethics} remains under-examined. This study
addresses that gap through a large-scale analysis of 3,395 publicly accessible
syllabi from CS and allied areas at leading Indian institutions. Among them,
only 75 syllabi (2.21%) included any substantive AI ethics content. Three key
findings emerged: (1) AI ethics is typically integrated as a minor module
within broader technical courses rather than as a standalone course; (2) ethics
coverage is often limited to just one or two instructional sessions; and (3)
recurring topics include algorithmic fairness, privacy and data governance,
transparency, and societal impact. While these themes reflect growing
awareness, current curricular practices reveal limited depth and consistency.
This work highlights both the progress and the gaps in preparing future
technologists to engage meaningfully with the ethical dimensions of AI, and it
offers suggestions to strengthen the integration of AI ethics within computing
curricula.
Who is the user?
Who age?
Why use AI?
Study design
