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Incident 803: Facebook's Algorithm Reportedly Amplifies AI-Generated Content, Fueling Misleading Posts

Description: AI-generated spam images are increasingly filling Facebook feeds, with the platform’s algorithm reportedly amplifying these posts. Many of these images are bizarre, fake, and used in scams, misleading users into engaging with non-existent products or clickbait.

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Entities

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Alleged: Meta and Facebook developed and deployed an AI system, which harmed Meta users and Facebook users.

Incident Stats

Incident ID
803
Report Count
1
Incident Date
2024-05-14
Editors
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
 

3.1. False or misleading information

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. Misinformation

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
 

Intentional

Incident Reports

Reports Timeline

+1
AI-generated spam is starting to fill social media. Here's why
AI-generated spam is starting to fill social media. Here's why

AI-generated spam is starting to fill social media. Here's why

npr.org

AI-generated spam is starting to fill social media. Here's why
npr.org · 2024

Casey Morris, an attorney in Northern Virginia, recently started checking Facebook again after a long break. Among posts from friends and family, she noticed a strange trend.

"The caption will say, 'Close your eyes 70% and see magic.' And w…

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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