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AI Risk

Accountability

An essential feature of decision-making in humans, AI, and also HLI-based agents is accountability. Implementing this feature in machines is a difficult task because many challenges should be considered to organize an AI-based model that is accountable. It should be noted that this issue in human decision-making is not ideal, and many factors such as bias, diversity, fairness, paradox, and ambiguity may affect it...

AI Risk7. AI System Safety, Failures, & Limitations7.4 > Lack of transparency or interpretability3 - Other

Record summary

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain7. AI System Safety, Failures, & LimitationsThe broad risk area this belongs to.

Risk profile

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An essential feature of decision-making in humans, AI, and also HLI-based agents is accountability. Implementing this feature in machines is a difficult task because many challenges should be considered to organize an AI-based model that is accountable. It should be noted that this issue in human decision-making is not ideal, and many factors such as bias, diversity, fairness, paradox, and ambiguity may affect it. In addition, the human decision-making process is based on personal flexibility, context-sensitive paradigms, empathy, and complex moral judgments. Therefore, all of these challenges are inherent to designing algorithms for AI and also HLI models that consider accountability.

Domain7. AI System Safety, Failures, & Limitations
Subdomain7.4 > Lack of transparency or interpretability
Entity2 - AI
Intent2 - Unintentional
Timing3 - Other
CategoryAccountability
Subcategoryn/a

Suggested mitigations

Defenses that may help with related attacks.

No propagated mitigations. No defense is available through the connected attack methods.

Source

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