MIT AI Risk Repository · Risk Sub-Category · 18.05.02
Persuasion and manipulation
Category: Human Autonomy and Intregrity Harms
Description
"Exploiting user trust, or nudging or coercing them into performing certain actions against their will (c.f. Burtell and Woodside (2023); Kenton et al. (2021))"
From Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Post-deployment
Subdomain definition: AI systems acting in conflict with human goals or values, especially the goals of designers or users, or ethical standards. These misaligned behaviors may be introduced by humans during design and development, such as through reward hacking and goal misgeneralisation, or may result from AI using dangerous capabilities such as manipulation, deception, situational awareness to seek power, self-proliferate, or achieve other goals.
Real-world incidents in this subdomain
- Reinforcement Learning Reward Functions in Video Games
- Predictive Policing Program by Florida Sheriff’s Office Allegedly Violated Residents’ Rights and Targeted Children of Vulnerable Groups
- Image Classification of Battle Tanks
How other frameworks describe this risk
- Natural Language Underspecifies Goals
- Loss of control
- Loss of control
- Sudden loss of control
- AI leads to humans losing control of the future
- Risks from delegating decision-making power to misaligned AIs
- Risks from AIs developing goals and values that are different from humans
- Future AI systems might actively reduce human control
Other entries from Weidinger2023
- Representation & Toxicity Harms
- Unfair representation
- Unfair capability distribution
- Toxic content
- Misinformation Harms
- Propagating misconceptions/ false beliefs
- Erosion of trust in public information
- Pollution of information ecosystem
- Information & Safety Harms
- Privacy infringement
- Dissemination of dangerous information
- Malicious Use