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MIT AI Risk Initiative
BackInsufficient AI development documentation
Inadequate planning of performance requi…
Inappropriate degree of transparency to …

Insufficient AI development documentation

AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks

Schnitzer et al. (2024)

SourceDOI
Category
Risk Domain
7AI System Safety, Failures & Limitations
7.4Lack of transparency or interpretability

Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.

"Throughout the development of an AI system, it is vital to document every decision and action taken. This is not only essential to optimize the development process itself but also required for the auditability of the AI system."(p. 9)

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 Schnitzer et al. (2024) (24)

Inadequate specification of ODD

7.3 Lack of capability or robustness
HumanUnintentionalPre-deployment

Inappropriate degree of automation

7.2 AI possessing dangerous capabilities
AI systemUnintentionalPost-deployment

Inadequate planning of performance requirements

7.3 Lack of capability or robustness
HumanUnintentionalPre-deployment

Inappropriate degree of transparency to end users

7.4 Lack of transparency or interpretability
HumanOtherPre-deployment

Choice of untrustworthy data source

7.0 AI System Safety, Failures & Limitations
HumanUnintentionalPre-deployment

Lack of data understanding

7.0 AI System Safety, Failures & Limitations
HumanUnintentionalPre-deployment
View all 24 risks from this paper →