MIT AI Risk Repository · Risk Sub-Category · 67.01.01
Degradation of the information environment
Category: Societal harms
Description
"Frontier AI can cheaply generate realistic content which can falsely portray people and events. There is potential risk of compromised decision-making by individuals and institutions who rely on inaccurate or misleading publicly available information, as well as lower overall trust in true information."
From Capabilities and Risks from Frontier AI (DSIT2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 3. Misinformation
- Causal entity
- Other
- Intent
- Other
- Timing
- Other
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
- Worsened epistemic processes for society
- Reduced decision-making capacity as a result of decreased trust in information
- Widespread use of persuasive tools contributes to splintered epistemic communities
- AI contributes to increased online polarisation
- Clickbait and feeding the surveillance advertising ecosystem
Other entries from DSIT2023
- Societal harms
- Degradation of the information environment
- Degradation of the information environment
- Degradation of the information environment
- Degradation of the information environment
- Labour market disruption
- Labour market disruption
- Bias, Fairness and Representational Harms
- Bias, Fairness and Representational Harms
- Bias, Fairness and Representational Harms
- Bias, Fairness and Representational Harms
- Misuse risks