MIT AI Risk Repository · Risk Category · 31.08.00
Products Liability Law
Description
"Like manufactured items like soda bottles, mechanized lawnmowers, pharmaceuticals, or cosmetic products, generative AI models can be viewed like a new form of digital products developed by tech companies and deployed widely with the potential to cause harm at scale....Products liability evolved because there was a need to analyze and redress the harms caused by new, mass-produced technological products. The situation facing society as generative AI impacts more people in more ways will be similar to the technological changes that occurred during the twentieth century, with the rise of industr
From Generating Harms - Generative AI's impact and paths forwards (EPIC2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 6.5 Governance failure
- Causal entity
- Human
- Intent
- Other
- Timing
- Post-deployment
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
- Mobility
- Liability issues in case of accidents
- Faster scientific progress makes it harder for governance to keep pace with development
- Type 1: Diffusion of responsibility
- Institutional responsibilities
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Benchmarking (Cross-lingual data contamination)
- Benchmarking (Guideline contamination)