MIT AI Risk Repository · Risk Sub-Category · 62.33.02
Misuse of drug-discovery models
Category: Impacts of AI (Weapons)
Description
"Models used for drug discovery, such as drug-target affinity prediction models, can be used to identify or develop dangerous toxins. This is particularly concern- ing if the training data contains information related to potentially dangerous proteins and viruses."
From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Domain
- 4. Malicious actors
- Causal entity
- Human
- Intent
- Intentional
- Timing
- Post-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