Description: Dartmouth's Geisel School of Medicine reportedly used Canvas learning-management activity logs and an internal analysis process to investigate remote-exam cheating during the 2020–2021 academic year. Seventeen medical students were charged after the school inferred that they accessed course materials during exams, but students and outside technical reviewers said automated Canvas activity may have been misread as intentional misconduct. Dartmouth later dropped the charges.
Editor Notes: This record is retained as an incident because it describes a specific academic-misconduct investigation in which Geisel School of Medicine reportedly used Canvas learning-management activity logs and an internal analysis process to accuse students of cheating. The record is AIID-borderline because the implicated system appears to be a semi-opaque activity-log analysis rather than a conventional AI model; retention depends on treating the log-analysis process as an algorithmic decision-support system used in a high-stakes disciplinary context.
Entities
View all entitiesAlleged: Geisel School of Medicine's Technology staff and Canvas developed an AI system deployed by Geisel School of Medicine, which harmed Sirey Zhang , Geisel School of Medicine's students , Geisel School of Medicine's professors , Geisel School of Medicine's accused students , students , Medical students , Epistemic integrity , Educational communities and University students.
Alleged implicated AI systems: Canvas , Automated proctoring systems and Learning management system activity logs
Incident Stats
Incident ID
302
Report Count
1
Incident Date
2021-03-15
Editors
Sean McGregor, Daniel Atherton
Applied Taxonomies
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- AI system safety, failures, and limitations
Entity
Which, if any, entity is presented as the main cause of the risk
AI
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline
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HANOVER, N.H. — Sirey Zhang, a first-year student at Dartmouth’s Geisel School of Medicine, was on spring break in March when he received an email from administrators accusing him of cheating.
Dartmouth had reviewed Mr. Zhang’s online activ…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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