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Incident 301: Teenager at Broward College Allegedly Wrongfully Accused of Cheating via Remote Proctoring

Description: Broward College’s use of remote proctoring system and reliance on its flagging algorithm allegedly led to a wrongful accusation of academic dishonesty in a biology exam of a Florida teenager.

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Alleged: Honorlock developed an AI system deployed by Broward College, which harmed unnamed Florida teenager.

Incident Stats

Incident ID
301
Report Count
1
Incident Date
2022-02-15
Editors
Khoa Lam
Applied Taxonomies
MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

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.
 
  1. 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

Incident OccurrenceAccused of Cheating by an Algorithm, and a Professor She Had Never Met
Accused of Cheating by an Algorithm, and a Professor She Had Never Met

Accused of Cheating by an Algorithm, and a Professor She Had Never Met

nytimes.com

Accused of Cheating by an Algorithm, and a Professor She Had Never Met
nytimes.com · 2022

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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