Skip to main content
This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .
MIT AI Risk Initiative
BackDangerous development races
Complexity-induced knowledge gap
Deceptive alignment

Dangerous development races

A Taxonomy of Systemic Risks from General-Purpose AI

Uuk et al. (2025)

SourceDOI
Sub-category
Risk Domain
6Socioeconomic & Environmental
6.4Competitive dynamics

AI developers or state-like actors competing in an AI ‘race’ by rapidly developing, deploying, and applying AI systems to maximize strategic or economic advantage, increasing the risk they release unsafe and error-prone systems.

"Competitive pressures could lead to the neglect of safety measures in AI development."(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 →