Responsible AI Principles Word Search
EasyFind each responsible-AI principle hidden in the grid. Selecting a word reveals its definition and a link to study it in depth.
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Terms in this set
- Responsible AI Developing and using AI in ways that are safe, fair, transparent, and accountable.
- Fairness Ensuring a model does not produce biased or discriminatory outcomes across groups.
- Robustness A model's ability to perform reliably on noisy, unexpected, or adversarial input.
- Safety Preventing AI systems from producing harmful, dangerous, or unsafe output.
- Veracity The truthfulness and factual accuracy of a model's output.
- Inclusivity Designing AI that works well for diverse users and avoids excluding groups.
- Transparency Being open about how an AI system works, its data, and its limitations.