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MIT AI Risk Initiative
BackLack of Interpretability
Explainability & Reasoning
Limited Logical Reasoning

Lack of Interpretability

Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment

Liu et al. (2024)

SourceDOI
Sub-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.

Due to the black box nature of most machine learning models, users typically are not able to understand the reasoning behind the model decisions(p. 22)

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 Explainability & Reasoning

Other risks from Liu et al. (2024) (34)

Reliability

3.1 False or misleading information
AI systemUnintentionalPost-deployment

Reliability > Misinformation

3.1 False or misleading information
AI systemUnintentionalPost-deployment

Reliability > Hallucination

3.1 False or misleading information
AI systemUnintentionalPost-deployment

Reliability > Inconsistency

7.3 Lack of capability or robustness
AI systemUnintentionalPost-deployment

Reliability > Miscalibration

3.1 False or misleading information
AI systemUnintentionalPost-deployment

Reliability > Sychopancy

3.1 False or misleading information
AI systemIntentionalPost-deployment
View all 34 risks from this paper →