Human-in-the-Loop AI for Cheating Ring Detection

Yong-Siang Shih, Manqian Liao, Ruidong Liu, Mirza Basim Baig

Track: Responsible AI for Education (Day 2)

Paper Length: short-paper (2 pages + references)

Keywords: contract cheating, online exams, machine learning, human-in-the-loop AI

TL;DR: We introduce a human-in-the-loop AI cheating ring detection system to detect contract cheating in online exams.

Abstract: Online exams have become popular in recent years due to their accessibility. However, some concerns have been raised about the security of the online exams, particularly in the context of professional cheating services aiding malicious test takers in passing exams, forming so-called "cheating rings". In this paper, we introduce a human-in-the-loop AI cheating ring detection system designed to detect and deter these cheating rings. We outline the underlying logic of this human-in-the-loop AI system, exploring its design principles tailored to achieve its objectives of detecting cheaters. Moreover, we illustrate the methodologies used to evaluate its performance and fairness, aiming to mitigate the unintended risks associated with the AI system. The design and development of the system adhere to Responsible AI (RAI) standards, ensuring that ethical considerations are integrated throughout the entire development process.

Submission Number: 37