MIT AI Risk Repository · Risk Sub-Category · 53.02.02
Acquisition of a goal to harm society
Category: Dangerous capabilities in AI systems
Description
"cases of AI systems being given the outright goal of harming humanity (ChaosGPT);"
From Advancing AI Governance: A Literature Review of Problems, Options, and Proposals (Maas2023), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 4. Malicious actors
- Causal entity
- Human
- Intent
- Intentional
- Timing
- Pre-deployment
Subdomain definition: Using AI systems to develop cyber weapons (e.g., coding cheaper, more effective malware), develop new or enhance existing weapons (e.g., Lethal Autonomous Weapons or CBRNE), or use weapons to cause mass harm.
Real-world incidents in this subdomain
- Anthropic's Claude Was Reportedly Jailbroken To Allegedly Help Steal Sensitive Mexican Government Data
- OpenAI ChatGPT Models Reportedly Jailbroken to Provide Chemical, Biological, and Nuclear Weapons Instructions
- Anthropic Reportedly Identifies AI Misuse in Extortion Campaigns, North Korean IT Schemes, and Ransomware Sales
- LAMEHUG Malware Reportedly Integrates Large Language Model for Real-Time Command Generation in a Purported APT28-Linked Cyberattack
- Reported AI-Aided Development of Explosive Devices by Long Island Resident Michael Gann
- AI Chatbot Allegedly Used to Research Explosive Materials in Palm Springs Fertility Clinic Bombing
How other frameworks describe this risk
Other entries from Maas2023
- Alignment failures in existing ML systems
- Faulty reward functions in the wild
- Specification gaming
- Reward model overoptimization
- Instrumental convergence
- Goal misgeneralization
- Inner misalignment
- Language model misalignment
- Harms from increasingly agentic algorithmic systems
- Dangerous capabilities in AI systems
- Situational awareness
- Acquisition of goals to seek power and control