Good proctor or “big brother”? Ethics of online exam supervision technologies
Open accessAbstract
Online exam supervision technologies have recently generated significant controversy and concern. Their use is now booming due to growing demand for online courses and for off-campus assessment options amid COVID-19 lockdowns. Online proctoring technologies purport to effectively oversee students sitting online exams by using artificial intelligence (AI) systems supplemented by human invigilators. Such technologies have alarmed some students who see them as a "Big Brother-like" threat to liberty and privacy, and as potentially unfair and discriminatory. However, some universities and educators defend their judicious use. Critical ethical appraisal of online proctoring technologies is overdue. This essay provides one of the first sustained moral philosophical analyses of these technologies, focusing on ethical notions of academic integrity, fairness, non-maleficence, transparency, privacy, autonomy, liberty, and trust. Most of these concepts are prominent in the new field of AI ethics, and all are relevant to education. The essay discusses these ethical issues. It also offers suggestions for educational institutions and educators interested in the technologies about the kinds of inquiries they need to make and the governance and review processes they might need to adopt to justify and remain accountable for using online proctoring technologies. The rapid and contentious rise of proctoring software provides a fruitful ethical case study of how AI is infiltrating all areas of life. The social impacts and moral consequences of this digital technology warrant ongoing scrutiny and study.
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Automated online proctoring has unfairly penalized people with disabilities through algorithms that flag some gestures and eye movements as "abnormal" or "unacceptable" exam behavior.
“For example, automated online proctoring has unfairly penalized people with disabilities through algorithms that flag some gestures and eye movements as “abnormal” or “unacceptable” exam behavior”
From Algorithmic harms and digital ageism in the use of surveillance technologies in nursing homes (2022) · cites this paper as Coghlan et al., 2021
In the Fairness—Bias, Discrimination, and AI-facilitated Determination of Cheating section (page not provided), the paper says that flagging gestures and tracking eye movements may produce false cheating flags for people with disabilities. It describes unfair penalties as a potential harm, not as something it establishes has occurred; the claim overstates that point. (LLM, conf=0.88)
Experimental — accuracy not yet measuredDisability studies scholars and activists have demonstrated how the introduction of automated algorithmic decision making in education, employment, and insurance promotes discrimination against embodied difference.
“Disability studies scholars and activists have demonstrated how the introduction of automated algorithmic decision making in education, employment, and insurance promotes discrimination against embodied difference in ways of communicating, interacting, and being.”
From Algorithmic harms and digital ageism in the use of surveillance technologies in nursing homes (2022) · cites this paper as Coghlan et al., 2021
The section “Fairness—Bias, Discrimination, and AI-facilitated Determination of Cheating” (page unavailable) says automated exam proctoring may flag disabled or neurodiverse students’ behavior as suspicious, supporting the education-related concern. It does not establish disability-related discrimination in employment or insurance, or attribute such a demonstration to disability studies scholars and activists; its employment example concerns bias favoring male applicants. (LLM, conf=0.86)
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- Authors
- Coghlan, S., Miller, T., & Paterson, J.
- Affiliations
- The University of Melbourne (AU)
- Corresponding author
- Coghlan, Simon
- Venue
- Philosophy & Technology
- Published
- 2021-08-31
- Volume
- 34
- Issue
- 4
- Pages
- 1581-1606
- ISSN
- 2210-5433 (ISSN-L)
- 2210-5441
- PMC
- PMC8407138
- OpenAlex
- W3197804775
- Cited by
- 219
- References
- 79
- Citations by year
- 2026: 42 · 2025: 34 · 2024: 46 · 2023: 54 · 2022: 35 · 2021: 8
- FWCI
- 44.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Philosophy & Technology (publishedVersion, public-domain)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Keywords
- online proctoring, AI ethics, academic integrity, privacy, student independence, fairness, non-maleficence, transparency, trust, surveillance
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