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MIT AI Risk Initiative
BackCoercion / manipulation
Sexualization
Over-reliance

Coercion / manipulation

A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents

Li et al. (2025)

SourceDOI
Sub-category
Risk Domain
4Malicious Actors & Misuse
4.1Disinformation, surveillance, and influence at scale

Using AI systems to conduct large-scale disinformation campaigns, malicious surveillance, or targeted and sophisticated automated censorship and propaganda, with the aim of manipulating political processes, public opinion, and behavior.

"Use of a technology system to covertly alter user beliefs and behaviour using nudging, dark patterns and/or other opaque techniques"

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

Other risks from Li et al. (2025) (40)

Autonomy

5.2 Loss of human agency and autonomy
OtherOtherOther

Autonomy > Impersonation / identity theft

4.3 Fraud, scams, and targeted manipulation
HumanIntentionalPost-deployment

Misinformation Harms

3.1 False or misleading information
AI systemOtherPost-deployment

Representation and Toxicity

1.0 Discrimination & Toxicity
AI systemUnintentionalPost-deployment

IP / copyright / personality / rights loss

4.3 Fraud, scams, and targeted manipulation
HumanIntentionalPost-deployment

Autonomy / agency loss

5.2 Loss of human agency and autonomy
OtherOtherOther
View all 40 risks from this paper →