Human-in-the-Loop AI for Cheating Ring Detection
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866916170951557120 |
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| author | Shih, Yong-Siang Liao, Manqian Liu, Ruidong Baig, Mirza Basim |
| author_facet | Shih, Yong-Siang Liao, Manqian Liu, Ruidong Baig, Mirza Basim |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_14711 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Human-in-the-Loop AI for Cheating Ring Detection Shih, Yong-Siang Liao, Manqian Liu, Ruidong Baig, Mirza Basim Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning 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. |
| title | Human-in-the-Loop AI for Cheating Ring Detection |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2403.14711 |