AI meets AI: Artificial Intelligence and Academic Integrity - A Survey on Mitigating AI-Assisted Cheating in Computing Education

Abstract

This paper discusses pressing issues in the area where Artificial Intelligence (AI) meets Academic Integrity (AI). It starts by outlining the potential consequences of AI-assisted cheating, including the risks posed to education quality, fairness, and the credibility of academic institutions. After reviewing an array of strategies reported in the literature to counteract such cheating, this paper calls for rigorous research to assess the effectiveness of those strategies. It further suggests a range of research topics in detecting AI-generated content and highlights a promising research direction focusing on motivating students' interest in learning through innovative AI applications that divert their efforts away from misuse of technology. Lastly, the paper suggests that addressing AI cheating requires ethical education, academia-industry collaboration, integration into AI ethics, and an international consortium. One of the unique contributions of this paper is outlining a range of potential research directions, both technical and non-technical, in this area where AI meets AI.