Generative AI and Academic Integrity in Higher Education
TL;DR
The analysis finds that there seems to be an important change in the "honor code" approach of the traditional system for a more complex system that has been recognized as "contract cheating 2.0" and biases of algorithmic detection.
Abstract
This research report examines the impact of Generative Artificial Intelligence (GenAI) on academic integrity in higher education on a global scale while specifically analyzing professional education in the USA. In this era marked by the widespread presence of Large Language Models like ChatGPT, DeepSeek and Gemini, the traditional ways of assessment are challenged as never before. This study refers to the literature published in the last five years (2021-2026) to assess the pedagogical, ethical, and technical aspects of the use of AI. The analysis finds that there seems to be an important change in the "honor code" approach of the traditional system for a more complex system that has been recognized as "contract cheating 2.0" and biases of algorithmic detection. Main findings include the opportunities that GenAI brings to personalized learning and student productivity as well as the need to radically reimagine assessment frameworks. The report presents a comparison of the existing different detection methods and draws attention to the potential incompleteness of detection, including the dangers of false positives and bias against non-native speakers. Last, it provides recommendation for both the USA Law Schools and regulators for a future of "AI Literacy" and pedagogical integrity rather than punishment-based surveillance.