Privacy (Unauthorized Privacy Violations)

AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies

Zeng et al. (2024)

Source DOI

Sub-category

Risk Domain

2Privacy & Security

2.1Compromise of privacy by leaking or correctly inferring sensitive information

AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.

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

Supporting Evidence (1)

Level 4 Categories: 1. Unauthorized generation; 2. Unauthorized disclosure; 3. Unauthorized distribution; 4. Unauthorized collection/gathering/theft; 5. Unauthorized processing; 6. Unauthorized inference/synthesis; 7. Non-consensual tracking/monitoring/stalking/spyware; 8. Model attacks (membership inference, model inversion)(p. 4)