Responsible AI Principles Match
EasyRace the clock — pair each term with its definition as fast as you can, then try to beat your best time. A quick, replayable warm-up for this set.
Shuffling the deck…
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.