MIT AI Risk Repository · Risk Sub-Category · 18.02.03
Pollution of information ecosystem
Category: Misinformation Harms
Description
"Contaminating publicly available information with false or inaccurate information"
From Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 3. Misinformation
- Causal entity
- AI
- Intent
- Other
- Timing
- Post-deployment
Subdomain definition: Highly personalized AI-generated misinformation creating “filter bubbles” where individuals only see what matches their existing beliefs, undermining shared reality, weakening social cohesion and political processes.
Real-world incidents in this subdomain
- Google Books Appears to Be Indexing Works Written by AI
- Uptick in Low-Quality AI-Produced Content Degraded Publishers' Submission Management
- Korean Politician Employed Deepfake as Campaign Representative
- Facebook Political Ad Delivery Algorithms Inferred Users' Political Alignment, Inhibiting Political Campaigns' Reach
How other frameworks describe this risk
- Information degradation
- Radicalisation
- Institutional trust loss
- Widespread use of persuasive tools contributes to splintered epistemic communities
- Reduced decision-making capacity as a result of decreased trust in information
- Worsened epistemic processes for society
- AI contributes to increased online polarisation
- Degradation of the information environment
Other entries from Weidinger2023
- Representation & Toxicity Harms
- Unfair representation
- Unfair capability distribution
- Toxic content
- Misinformation Harms
- Propagating misconceptions/ false beliefs
- Erosion of trust in public information
- Information & Safety Harms
- Privacy infringement
- Dissemination of dangerous information
- Malicious Use
- Influence operations