Ethical and Societal Impacts of Generative AI in Higher Computing Education: An ACM Task Force Working Group to Develop a Landscape Analysis - Perspectives from the Global Souths and Guidelines for CS1/CS2/CS3

Abstract

Generative AI has a wide range of impacts on how we access and use information, particularly as educational settings and perspectives differ greatly across different locations. These effects extend broadly across our society and include negative impacts on intellectual and creative works and the potential infringement of authorship. They also include positive effects on engagement with social responsibility and the societal role of computing. The differences in institutional Generative AI policies, available funding, accessibility to tools translated in relevant languages may create challenges to equal and equitable tool access, their responsible use, and ethical questions about the use of AI tools and the impact of uneven student knowledge of their benefits and limitations. In addition, Generative AI introduces questions concerning academic integrity, bias, and data provenance. All these aspects have increasingly been the focus of computing education research studies, however our analysis has found that Global South perspectives are largely missing from the corpus of work. In this paper we conduct a landscape analysis on Global South ethical perspectives related to the use of Generative AI tools in computing education contexts. We identify critical supports of Global South ethical frameworks and explore how these are considered across the Global South computing education literature.