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Incident 317: Bug in Facebook’s Anti-Spam Filter Allegedly Blocked Legitimate Posts about COVID-19

Description: Facebook was reported by users for blocking posts of legitimate news about the coronavirus pandemic, allegedly due to a bug in an anti-spam system.

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Alleged: Facebook developed and deployed an AI system, which harmed Facebook users posting legitimate COVID-19 news and Facebook users.

Incident Stats

Incident ID
317
Report Count
1
Incident Date
2020-03-17
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
 

7.3. Lack of capability or robustness

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. AI system safety, failures, and limitations

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 is wrongly blocking news articles about the coronavirus pandemic
Facebook is wrongly blocking news articles about the coronavirus pandemic

Facebook is wrongly blocking news articles about the coronavirus pandemic

businessinsider.com

Facebook is wrongly blocking news articles about the coronavirus pandemic
businessinsider.com · 2020

Facebook is blocking users from posting some legitimate news articles about the novel coronavirus in what appears to be a bug in its spam filters.

On Tuesday, multiple Facebook users reported on Twitter that they found themselves unable to …

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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