MIT AI Risk Repository · Risk Sub-Category · 34.02.03
Mesa-Optimization Objectives
Category: Double edge components
Description
"The learned policy may pursue inside objectives when the learned policyitself functions as an optimizer (i.e., mesa-optimizer). However, this optimizer's objectives may not alignwith the objectives specified by the training signals, and optimization for these misaligned goals may leadto systems out of control (Hubinger et al., 2019c)."
From AI Alignment: A Comprehensive Survey (Ji2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Other
Subdomain definition: AI systems that develop, access, or are provided with capabilities that increase their potential to cause mass harm through deception, weapons development and acquisition, persuasion and manipulation, political strategy, cyber-offense, AI development, situational awareness, and self-proliferation. These capabilities may cause mass harm due to malicious human actors, misaligned AI systems, or failure in the AI system.
How other frameworks describe this risk
- Safety Risks from Affordances Provided to LLM-agents
- Agentic LLMs Pose Novel Risks
- Goal-Directedness Incentivizes Undesirable Behaviors
- Capabilities that could be used to reduce human control - Cyber offence
- Capabilities that could be used to reduce human control - Autonomous replication and adaptation
- Capabilities that could be used to reduce human control - Manipulation
- Subagents
- AI Influence