Responsible AI
The practice of developing and deploying AI systems in ways that are ethical, fair, transparent, and accountable — encompassing bias mitigation, explainability, and governance frameworks.
Only 32% of organizations using AI have formal governance frameworks. The EU AI Act mandates transparency and accountability requirements. Over 70 countries have published national AI strategies addressing responsible development. The gap between AI capability advancement and governance implementation is growing — the pace of regulation lags well behind the pace of capability development. Six national AI Safety Institutes have been established to address responsible AI challenges.
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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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