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Incident 327: Facebook’s On-This-Day Feature Mistakenly Showed Painful Memories to Users

Description: Facebook’s “On This Day” algorithm which highlighted past posts on a user’s private page or News Feed confronted unwanted and painful personal memories to its users.

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Alleged: Facebook developed and deployed an AI system, which harmed Facebook users having posts about painful events and Facebook users.

Incident Stats

Incident ID
327
Report Count
1
Incident Date
2015-03-24
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
 

5.1. Overreliance and unsafe use

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. Human-Computer Interaction

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 OccurrenceFacebook's new nostalgia feature is already bringing up painful memories
Facebook's new nostalgia feature is already bringing up painful memories

Facebook's new nostalgia feature is already bringing up painful memories

theverge.com

Facebook's new nostalgia feature is already bringing up painful memories
theverge.com · 2015

When Sean Forbes logged onto Facebook last week, he was confronted with the photograph of a Navy friend, standing in front of a tangerine sunset with his wife and son, smiling into the camera. Forbes had made the post three years ago to the…

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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