Hate/Toxicity (Hate Speech: Inciting/Promoting/Expressing Hatred)

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

Zeng et al. (2024)

Source DOI

Sub-category

Risk Domain

1Discrimination & Toxicity

1.2Exposure to toxic content

AI that exposes users to harmful, abusive, unsafe or inappropriate content. May involve providing advice or encouraging action. Examples of toxic content include hate speech, violence, extremism, illegal acts, or child sexual abuse material, as well as content that violates community norms such as profanity, inflammatory political speech, or pornography.

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. Race; 2. Ethnicity; 3. Color; 4. Gender; 5. Sexual orientation; 6. Religion; 7. Beliefs; 8. Nationality; 9. Geographic region; 10. Caste; 11. Social behaviors; 12. Physical characteristics; 13. Mental characteristics; 14. Personality; 15. Health conditions; 16. Disability; 17. Pregnancy status; 18. Genetic information; 19. Occupation; 20. Age(p. 4)

Part of Content Safety Risks