MIT AI Risk Repository · Risk Sub-Category · 24.09.03
Collective action problems
Category: Cooperation
Description
"Collective action problems are ubiquitous in our society (Olson Jr, 1965). They possess an incentive structure in which society is best served if everyone cooperates, but where an individual can achieve personal gain by choosing to defect while others cooperate. The way we resolve these problems at many scales is highly complex and dependent on a deep understanding of the intricate web of social interactions that forms our culture and imprints on our individual identities and behaviours (Ostrom, 2010). Some collective action problems can be resolved by codifying a law, for instance the social
From The Ethics of Advanced AI Assistants (Gabriel2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
Subdomain definition: Humans delegating key decisions to AI systems, or AI systems making decisions that diminish human control and autonomy, potentially leading to humans feeling disempowered, losing the ability to shape a fulfilling life trajectory or becoming cognitively enfeebled.
Real-world incidents in this subdomain
- DisMech AI Curation Agent Reportedly Completed GitHub Issue Intended as New Contributor's Learning Task
- Waymo Driverless Taxi Allegedly Stalled During Pedestrian Harassment Incident in San Francisco
- California Police Turned on Music to Allegedly Trigger Instagram’s DCMA to Avoid Being Live-Streamed
- Hawaii Police Deployed Robot Dog to Patrol a Homeless Encampment
How other frameworks describe this risk
Other entries from Gabriel2024
- Capability failures
- Lack of capability for task
- Difficult to develop metrics for evaluating benefits or harms caused by AI assistants
- Safe exploration problem with widely deployed AI assistants
- Goal-related failures
- Misaligned consequentialist reasoning
- Specification gaming
- Goal misgeneralisation
- Deceptive alignment
- Malicious Uses
- Offensive Cyber Operations (General)
- AI-Powered Spear-Phishing at Scale