MIT AI Risk Repository · Risk Category · 05.11.00
Governance - Regulation
Description
In response to the multitude of new risks associated with generative AI, papers advocate for legal regulation and governmental oversight. The focus of these discussions centers on the need for international coordination in AI governance, the establishment of binding safety standards for frontier models, and the development of mechanisms to sanction non-compliance. Furthermore, the literature emphasizes the necessity for regulators to gain detailed insights into the research and development processes within AI labs. Moreover, risk management strategies of these labs shall be evaluated. However,
From Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 6.5 Governance failure
- Causal entity
- Not coded
- Intent
- Not coded
- Timing
- Not coded
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
- Type 1: Diffusion of responsibility
- Products Liability Law
- Institutional responsibilities
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Benchmarking (Cross-lingual data contamination)