MIT AI Risk Repository · Risk Sub-Category · 24.11.02
Degraded and homogenised information environments
Category: Misinformation risks
Description
"Beyond this, the widespread adoption of advanced AI assistants for content generation could have a number of negative consequences for our shared information ecosystem. One concern is that it could result in a degradation of the quality of the information available online. Researchers have already observed an uptick in the amount of audiovisual misinformation, elaborate scams and fake websites created using generative AI tools (Hanley and Durumeric, 2023). As more and more people turn to AI assistants to autonomously create and disseminate information to public audiences at scale, it may beco
From The Ethics of Advanced AI Assistants (Gabriel2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 3. Misinformation
- Causal entity
- Human
- Intent
- Intentional
- 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
- Radicalisation
- Information degradation
- Institutional trust loss
- Worsened epistemic processes for society
- AI contributes to increased online polarisation
- Widespread use of persuasive tools contributes to splintered epistemic communities
- Reduced decision-making capacity as a result of decreased trust in information
- Degradation of the information environment
Other entries from Gabriel2024
- Capability failures
- Lack of capability for task
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Safe exploration problem with widely deployed AI assistants
- Goal-related failures
- Misaligned consequentialist reasoning
- Specification gaming
- Goal misgeneralisation
- Deceptive alignment
- Malicious Uses
- Offensive Cyber Operations (General)
- AI-Powered Spear-Phishing at Scale