MIT AI Risk Repository · Risk Sub-Category · 45.02.10
Cognitive risks (Risks of usage in launching cognitive warfare)
Category: Safety risks in AI Applications
Description
"AI can be used to make and spread fake news, images, audio, and videos; propagate content of terrorism, extremism, and organized crimes; interfere in the internal affairs of other countries, social systems, and social order; and jeopardize the sovereignty of other countries."
From AI Safety Governance Framework (TC2602024), 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 conduct large-scale disinformation campaigns, malicious surveillance, or targeted and sophisticated automated censorship and propaganda, with the aim to manipulate political processes, public opinion and behavior.
Real-world incidents in this subdomain
- Suspected AI-Generated Deepfake Video Reportedly Targeted Former Chhattisgarh Chief Minister Bhupesh Baghel on Instagram
- Purportedly AI-Manipulated Satellite Image Reportedly Claimed Iranian Strike Destroyed U.S. Radar in Qatar
- Purported AI-Generated War Footage Reportedly Circulated Widely Online During the Opening Phase of the War in Iran
- Network of Allegedly Fake Facebook Profiles with Purportedly AI-Generated Images Amplified Posts by Bulgaria's 'There Is Such a People' (ITN) Party
- Purportedly AI-Generated Image Reportedly Circulated Ahead of Thai Election Depicting PM Anutin Charnvirakul Dining with Benjamin Mauerberger
- Purportedly AI-Altered Images Reportedly Distort Evidence After Minneapolis Shooting of ICU Nurse Alex Pretti
How other frameworks describe this risk
Other entries from TC2602024
- AI's inherent safety risks
- Risks from models and algorithms (Risks of explainability)
- Risks from models and algorithms (Risks of bias and discrimination)
- Risks from models and algorithms (Risks of robustness)
- Risks from models and algorithms (Risks of stealing and tampering)
- Risks from models and algorithms (Risks of unreliable output)
- Risks from models and algorithms (Risks of adversarial attack)
- Risks from data (Risks of illegal collection and use of data)
- Risks from data (Risks of improper content and poisoning in training data)
- Risks from data (Risks of unregulated training data annotation)
- Risks from data (Risks of data leakage)
- Risks from AI systems (Risks of exploitation through defects and backdoors)