MIT AI Risk Repository · Risk Sub-Category · 54.01.05
Security
Category: Negative impacts of AI use
Description
"There is growing concern that AI-based systems can discover and exploit vulnerabilities in software or cyberinfrastructure [354]."
From Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024 ), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Post-deployment
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
Other entries from Leech2024
- Negative impacts of AI use
- Under-recognized work
- Environmental cost
- Discrimination, toxicity, and bias
- Privacy
- Harm caused by incompetent systems
- Harm caused by unaligned competent systems
- Specification gaming
- Emergent goals
- Deceptive alignment
- Within-country issues: domestic inequality
- Demographic diversity of researchers