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MIT AI Risk Initiative
BackDependency on providers
Deceptive alignment
Detection challenges in content

Dependency on providers

A Taxonomy of Systemic Risks from General-Purpose AI

Uuk et al. (2025)

SourceDOI
Sub-category
Risk Domain
6Socioeconomic & Environmental
6.1Power centralization and unfair distribution of benefits

AI-driven concentration of power and resources within certain entities or groups, especially those with access to or ownership of powerful AI systems, leading to inequitable distribution of benefits and increased societal inequality.

"Excessive reliance on specific AI providers can lead to vulnerabilities due to lack of alternatives or interoperability."(p. 12)

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 Uuk et al. (2025) (60)

Control

7.1 AI pursuing its own goals in conflict with human goals or values
AI systemIntentionalPost-deployment

Democracy

6.0 Socioeconomic & Environmental
OtherOtherOther

Discrimination

1.1 Unfair discrimination and misrepresentation
OtherOtherPost-deployment

Economy

6.2 Increased inequality and decline in employment quality
OtherOtherPost-deployment

Environment

6.6 Environmental harm
AI systemUnintentionalPost-deployment

Governance

6.5 Governance failure
AI systemUnintentionalPost-deployment
View all 60 risks from this paper →