An approach to AI development and deployment that integrates ethical principles and governance practices throughout the AI lifecycle. Responsible AI aims to ensure AI systems are fair, transparent, accountable, secure, and aligned with human values and societal benefit.

Responsible AI represents a comprehensive framework for ensuring AI systems are developed and used in ways that respect human rights, promote wellbeing, and avoid harms. It encompasses technical practices like bias testing and explainability methods alongside governance processes like impact assessments and stakeholder engagement. Rather than treating ethics as an afterthought, responsible AI approaches incorporate ethical considerations into every stage of the AI lifecycle, from problem formulation and data collection through deployment and monitoring.

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A healthcare organisation implementing responsible AI practices for a clinical decision support system, including diverse data collection, fairness testing across patient demographics, explainable recommendations for clinicians, rigorous clinical validation, and ongoing monitoring for unintended consequences.