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

Fuente: arXiv
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Auteurs principaux: Mak, Janice, Nakatumba-Nabende, Joyce, Clear, Tony, Clear, Alison, Albluwi, Ibrahim, Andrei, Oana, Angeli, Lorenzo, MacNeil, Stephen, Oyelere, Solomon Sunday, Rattigan, Matthew Hale, Sheard, Judy, Zhu, Tingting
Format: Preprint
Publié: 2025
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author Mak, Janice
Nakatumba-Nabende, Joyce
Clear, Tony
Clear, Alison
Albluwi, Ibrahim
Andrei, Oana
Angeli, Lorenzo
MacNeil, Stephen
Oyelere, Solomon Sunday
Rattigan, Matthew Hale
Sheard, Judy
Zhu, Tingting
author_facet Mak, Janice
Nakatumba-Nabende, Joyce
Clear, Tony
Clear, Alison
Albluwi, Ibrahim
Andrei, Oana
Angeli, Lorenzo
MacNeil, Stephen
Oyelere, Solomon Sunday
Rattigan, Matthew Hale
Sheard, Judy
Zhu, Tingting
contents 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.
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id arxiv_https___arxiv_org_abs_2511_15768
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education
Mak, Janice
Nakatumba-Nabende, Joyce
Clear, Tony
Clear, Alison
Albluwi, Ibrahim
Andrei, Oana
Angeli, Lorenzo
MacNeil, Stephen
Oyelere, Solomon Sunday
Rattigan, Matthew Hale
Sheard, Judy
Zhu, Tingting
Computers and Society
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.
title Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education
topic Computers and Society
url https://arxiv.org/abs/2511.15768