Responsible AI
The practice of developing and deploying AI systems ethically, transparently, and with accountability.
Full Definition
Responsible AI is an umbrella framework for the organisational practices, governance structures, and technical tools needed to develop and deploy AI in ways that are safe, fair, transparent, and accountable. It encompasses fairness and non-discrimination, privacy protection, transparency and explainability, human oversight, environmental sustainability, and accountability for harms. Responsible AI frameworks have been published by governments (EU AI Act), standards bodies (NIST AI RMF), and companies (Google's AI Principles, Microsoft's Responsible AI Standard). Moving responsible AI from principle to practice requires operationalising these values in product decisions, hiring, auditing processes, and incident response.
Examples
A company publishing a model card for each AI product detailing its intended use cases, known failure modes, demographic performance disparities, and training data sources.
A hospital's AI review board evaluating every new AI diagnostic tool against a responsible AI checklist before approving clinical deployment.
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