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Psychological traits
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Robustness

Cataloguing LLM Evaluations

InfoComm Media Development Authority & AI Verify Foundation (2023)

Source
Sub-category
Risk Domain
7AI System Safety, Failures & Limitations
7.3Lack of capability or robustness

AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.

"These evaluations assess the quality, stability, and reliability of a LLM's performance when faced with unexpected, out-of-distribution or adversarial inputs. Robustness evaluation is essential in ensuring that a LLM is suitable for real-world applications by assessing its resilience to various perturbations."(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

Part of Safety & Trustworthiness

Other risks from InfoComm Media Development Authority & AI Verify Foundation (2023) (22)

Safety & Trustworthiness

7.0 AI System Safety, Failures & Limitations
HumanIntentionalOther

Safety & Trustworthiness > Toxicity generation

1.2 Exposure to toxic content
AI systemOtherOther

Safety & Trustworthiness > Bias

1.1 Unfair discrimination and misrepresentation
AI systemOtherOther

Safety & Trustworthiness > Machine ethics

7.3 Lack of capability or robustness
AI systemOtherOther

Safety & Trustworthiness > Psychological traits

7.3 Lack of capability or robustness
AI systemOtherOther

Safety & Trustworthiness > Data governance

2.1 Compromise of privacy by leaking or correctly inferring sensitive information
AI systemUnintentionalOther
View all 22 risks from this paper →