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Incident 382: Instagram's Exposure of Harmful Content Contributed to Teenage Girl’s Suicide

Description: Instagram was ruled by a judge to have contributed to the death of a teenage girl in the UK allegedly through its exposure and recommendation of suicide, self-harm, and depressive content.

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Alleged: Instagram developed and deployed an AI system, which harmed Molly Rose Russell , the Russell family , teenage girls and teenagers.

Incident Stats

Incident ID
382
Report Count
1
Incident Date
2017-11-21
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
 

1.2. Exposure to toxic content

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 OccurrenceBritish Ruling Pins Blame on Social Media for Teenager’s Suicide
British Ruling Pins Blame on Social Media for Teenager’s Suicide

British Ruling Pins Blame on Social Media for Teenager’s Suicide

nytimes.com

British Ruling Pins Blame on Social Media for Teenager’s Suicide
nytimes.com · 2022

Sitting in the witness box of a small London courtroom this week, a Meta executive faced an uncomfortable question: Did her company contribute to the suicide of a 14-year-old named Molly Russell?

Videos and images of suicide, self-harm and …

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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