Description: Facebook, Instagram, and Twitter wrongly blocked or restricted millions of pro-Palestinian posts and accounts related to the Israeli-Palestinian conflict, citing errors in their automated content moderation system.
Entities
View all entitiesAlleged: Facebook , Instagram and Twitter developed and deployed an AI system, which harmed Palestinian social media users , Facebook users , Instagram users , Twitter Users and Facebook employees having families affected by the conflict.
Incident Stats
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

Just days after violent conflict erupted in Israel and the Palestinian territories, both Facebook and Twitter copped to major faux pas: The companies had wrongly blocked or restricted millions of mostly pro-Palestinian posts and accounts re…
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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