Description: During a February 2022 online biology exam, Honorlock reportedly flagged a Florida teenager taking a Broward College class as suspicious. The student denied cheating, but Broward College allegedly relied on the remote-proctoring system's flag in pursuing an academic-dishonesty accusation that the student said was unfounded.
Entities
View all entitiesAlleged: Honorlock developed an AI system deployed by Broward College, which harmed Unnamed Broward College student , University students , Students , Epistemic integrity and Educational communities.
Alleged implicated AI systems: Honorlock remote proctoring system , Automated proctoring systems and AI-enabled decision support systems
Incident Stats
Incident ID
301
Report Count
1
Incident Date
2022-02-15
Editors
Khoa Lam, Daniel Atherton
Applied Taxonomies
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
1.1. Unfair discrimination and misrepresentation
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.
- Discrimination and Toxicity
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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A Florida teenager taking a biology class at a community college got an upsetting note this year. A start-up called Honorlock had flagged her as acting suspiciously during an exam in February. She was, she said in an email to The New York T…
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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