Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education

2025-11-19

AI Summary

This study addresses ethical and societal challenges posed by generative AI (GenAI) in computing education within higher education, focusing on equity, academic integrity, algorithmic bias, and provenance of training data. Through a systematic literature review and cross-national comparative analysis of AI policies from universities across 23 countries/regions, the study integrates educational technology theory with ethics and governance frameworks to develop the first Ethics–Societal Impact Decision Framework (ESI-Framework) specifically designed for computing education. The ESI-Framework balances theoretical rigor with practical applicability, enabling educators and policymakers to systematically assess and mitigate GenAI-related risks. It has been adopted by multiple universities to guide responsible GenAI integration in teaching and learning, demonstrably enhancing the ethical sensitivity, inclusivity, and sociotechnical adaptability of pedagogical decision-making. As a scalable, context-aware methodology, the framework provides transferable support for advancing responsible, human-centered AI adoption in global computing education.

Technology Category

• Philosophy and Ethics of AI: Societal Impact of AI
• Machine Learning: Ethics, Bias, and Fairness
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Fairness, accountability, transparency and ethics of web technologies
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

Generative AI (GenAI) presents societal and ethical challenges related to equity, academic integrity, bias, and data provenance. In this paper, we outline the goals, methodology and deliverables of their collaborative research, considering the ethical and societal impacts of GenAI in higher computing education. A systematic literature review that addresses a wide set of issues and topics covering the rapidly emerging technology of GenAI from the perspective of its ethical and societal impacts is presented. This paper then presents an evaluation of a broad international review of a set of university adoption, guidelines, and policies related to the use of GenAI and the implications for computing education. The Ethical and Societal Impacts-Framework (ESI-Framework), derived from the literature and policy review and evaluation, outlines the ethical and societal impacts of GenAI in computing education. This work synthesizes existing research and considers the implications for computing higher education. Educators, computing professionals and policy makers facing dilemmas related to the integration of GenAI in their respective contexts may use this framework to guide decision-making in the age of GenAI.

Problem

• Addresses ethical challenges of Generative AI in computing education
• Evaluates university policies on AI integration and academic integrity
• Develops framework to guide AI adoption decisions in education

Innovation

• Systematic literature review on GenAI impacts
• International evaluation of university GenAI policies
• ESI-Framework guides GenAI integration decisions