MIT AI Risk Repository · Risk Sub-Category · 24.06.02
Limiting users’ opportunities for personal development and growth
Category: Appropriate Relationships
Description
some users look to establish relationships with their AI companions that are free from the hurdles that, in human relationships, derive from dealing with others who have their own opinions, preferences and flaws that may conflict with ours. "AI assistants are likely to incentivise these kinds of ‘frictionless’ relationships (Vallor, 2016) by design if they are developed to optimise for engagement and to be highly personalisable. They may also do so because of accidental undesirable properties of the models that power them, such as sycophancy in large language models (LLMs), that is, the tenden
From The Ethics of Advanced AI Assistants (Gabriel2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- Other
- Intent
- Intentional
- Timing
- Post-deployment
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