MIT AI Risk Repository · Risk Category · 01.01.00
Type 1: Diffusion of responsibility
Description
Societal-scale harm can arise from AI built by a diffuse collection of creators, where no one is uniquely accountable for the technology's creation or use, as in a classic "tragedy of the commons".
From TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 6.5 Governance failure
- Causal entity
- AI
- Intent
- Unintentional
- Timing
- Other
Subdomain definition: Inadequate regulatory frameworks and oversight mechanisms failing to keep pace with AI development, leading to ineffective governance and the inability to manage AI risks appropriately.
Real-world incidents in this subdomain
- Nippon Life Alleged ChatGPT Practiced Law Without a License in Illinois Disability Case
- OpenAI Allegedly Did Not Alert RCMP After ChatGPT Flagged Violent Chats Before British Columbia School Shooting
- Remotely Operated Taser-Armed Drones Proposed by Taser Manufacturer as Defense for School Shootings in the US
How other frameworks describe this risk
- Liability issues in case of accidents
- Mobility
- Faster scientific progress makes it harder for governance to keep pace with development
- Products Liability Law
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Institutional responsibilities
- Benchmarking (Cross-lingual data contamination)
- Benchmarking (Guideline contamination)
Other entries from Critch2023
- Type 1: Diffusion of responsibility
- Type 1: Diffusion of responsibility
- Type 1: Diffusion of responsibility
- Type 2: Bigger than expected
- Type 2: Bigger than expected
- Type 3: Worse than expected
- Type 3: Worse than expected
- Type 3: Worse than expected
- Type 3: Worse than expected
- Type 3: Worse than expected
- Type 3: Worse than expected
- Type 3: Worse than expected