Catastrophic AI Risk
The potential for AI systems to cause widespread, severe, and potentially irreversible harm to society through misuse, accidents, or loss of human control over increasingly powerful systems.
Catastrophic risk scenarios include AI-enabled bioweapons, large-scale cyberattacks, economic disruption, and loss of human agency. The Frontier Model Forum, founded by OpenAI, Anthropic, Google, and Microsoft, was established partly to address catastrophic risks. Anthropic's responsible scaling policy includes commitments to pause development if models demonstrate dangerous capabilities. Six national AI Safety Institutes have been established to evaluate catastrophic risk potential. AI safety spending remains under 1% of total AI R&D, raising concerns about whether sufficient resources are allocated to preventing worst-case scenarios.
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Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
AI Alignment
The research field focused on ensuring AI systems behave in accordance with human values and intentions, particularly as systems become more capable.
AI Safety
The interdisciplinary field focused on preventing AI systems from causing harm, encompassing alignment, robustness, interpretability, and governance of AI technologies.
Deepfake
AI-generated synthetic media — images, video, or audio — that realistically depict events or statements that never occurred, created using deep learning techniques.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
Hallucination
When an AI model generates plausible-sounding but factually incorrect or fabricated information, presenting it with the same confidence as accurate responses.
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