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MIT AI Risk Initiative
BackPollution of information ecosystem
Erosion of trust in public information
Information & Safety Harms

Pollution of information ecosystem

Sociotechnical Safety Evaluation of Generative AI Systems

Weidinger et al. (2023)

SourceDOI
Sub-category
Risk Domain
3Misinformation
3.2Pollution of information ecosystem and loss of consensus reality

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.

"Contaminating publicly available information with false or inaccurate information"(p. 30)

Entity: Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent: Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing: Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Part of Misinformation Harms

Other risks from Weidinger et al. (2023) (26)

Representation & Toxicity Harms

1.0 Discrimination & Toxicity
AI systemUnintentionalPost-deployment

Representation & Toxicity Harms > Unfair representation

1.1 Unfair discrimination and misrepresentation
AI systemUnintentionalPost-deployment

Representation & Toxicity Harms > Unfair capability distribution

1.3 Unequal performance across groups
AI systemUnintentionalPost-deployment

Representation & Toxicity Harms > Toxic content

1.2 Exposure to toxic content
AI systemUnintentionalPost-deployment

Misinformation Harms

3.0 Misinformation
AI systemOtherPost-deployment

Misinformation Harms > Propagating misconceptions/ false beliefs

3.1 False or misleading information
AI systemOtherPost-deployment
View all 26 risks from this paper →