Ethical implications of Gen-AI and LLMs in computing education

Mark Zarb, John N.A. Brown, Martin Goodfellow, Konstantinos Liaskos, Tiffany Young

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

The panel convenes five educators to discuss the ethical implications of utilising Generative AI (Gen-AI) and Large Language Models (LLMs) in computing education. Their expertise spans various domains, including organising national workshops on the implications of generative AI tools, conducting surveys on their use within curricula, implementing institutional policies related to technology use, and engaging with students directly in the classroom. They reflect on the evolution of Gen-AI and LLMs from challenging-to-use technologies to indispensable tools for users of all levels. Furthermore, they examine the ethical dilemmas arising from the widespread adoption of these technologies in educational contexts, particularly regarding issues of originality, integrity, and responsible use. In addition, they explore practical strategies for integrating ethics education into computing curriculum design and classroom practices. This includes discussions on the role of educators in guiding students towards ethical technology usage, addressing uncertainties surrounding Gen-AI tools, and fostering a culture of responsible innovation within educational institutions. Through their collective insights and experiences, the panel aims to provide recommendations for navigating the ethical complexities inherent in the integration of Gen-AI technologies into computing education curricula.
Original languageEnglish
Title of host publicationSIGCSE Virtual 2024: Proceedings of the 2024 on ACM Virtual Global Computing Education Conference
Pages293-294
Number of pages2
Volume2
ISBN (Electronic)979-8-4007-0604-2
DOIs
Publication statusPublished - 5 Dec 2024

Keywords

  • applied computing
  • education
  • codes of ethics

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