Red Teaming
The practice of systematically probing AI systems for vulnerabilities, biases, harmful outputs, and safety failures by simulating adversarial attacks and edge cases before deployment.
Red teaming has become standard practice for frontier AI model releases. OpenAI, Anthropic, and Google all employ red teams — both internal and external — to test models before launch. The Biden administration's Executive Order on AI recommended red teaming for models above certain compute thresholds. Major red teaming exercises have uncovered jailbreaking techniques, bias patterns, and dangerous capability demonstrations. DEF CON's 2023 AI Village hosted the largest public AI red teaming exercise, with 2,200+ participants testing models from multiple providers. Effective red teaming requires diverse perspectives and adversarial creativity.
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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.
EU AI Act
The European Union's comprehensive AI regulation, which entered into force on August 1, 2024, classifying AI systems by risk level and imposing requirements from transparency disclosures to outright bans.
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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