MIT AI Risk Repository · Risk Sub-Category · 20.01.02
Responsibility and accountability
Category: AI Law and Regulation
Description
"The challenge of responsibility and accountability is an important concept for the process of governance and regulation. It addresses the question of who is to be held legally responsible for the actions and decisions of AI algorithms. Although humans operate AI systems, questions of legal responsibility and liability arise. Due to the self-learning ability of AI algorithms, the operators or developers cannot predict all actions and results. Therefore, a careful assessment of the actors and a regulation for transparent and explainable AI systems is necessary (Helbing et al., 2017; Wachter et
From The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration (Wirtz2020), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Subdomain
- 6.5 Governance failure
- Causal entity
- Other
- Intent
- Other
- 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
- 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
- Products Liability Law
- Institutional responsibilities
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Benchmarking (Cross-lingual data contamination)
Other entries from Wirtz2020
- AI Law and Regulation
- Governance of autonomous intelligence systems
- Governance of autonomous intelligence systems
- Privacy and safety
- AI Ethics
- AI-rulemaking for human behaviour
- Compatibility of AI vs. human value judgement
- Moral dilemmas
- AI discrimination
- AI Society
- Workforce substitution and transformation
- Social acceptance and trust in AI