Human-in-the-Loop AI for Cheating Ring Detection
Yong-Siang Shih Manqian Liao Ruidong Liu Mirza Basim Baig
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.