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

TL;DR

This paper reviews the ethical and societal challenges of Generative AI in higher computing education, proposing a framework to guide educators and policymakers in responsible integration.

Contribution

It introduces the ESI-Framework, synthesizing literature and policies to address ethical and societal impacts of GenAI in computing education.

Findings

Developed the ESI-Framework for ethical guidance

Conducted systematic literature review on GenAI impacts

Analyzed international policies on GenAI in education

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.