Responsible AI
An approach to AI development and deployment that prioritizes fairness, accountability, transparency, ethics, and safety.
Full Definition
Responsible AI is an umbrella approach to developing and deploying artificial intelligence systems that prioritizes ethical principles including fairness (avoiding discrimination and bias), accountability (clear ownership of AI outcomes), transparency (explainable decision-making), privacy (protecting personal data), safety (preventing harmful outcomes), and sustainability (considering environmental and societal impact). For organizations deploying autonomous AI agents, responsible AI translates into concrete technical requirements: bias detection and mitigation, comprehensive audit trails, explainability features, privacy-preserving data handling, safety guardrails, and continuous monitoring. Major AI regulations (EU AI Act, NIST AI RMF) are fundamentally codifications of responsible AI principles into legal and technical requirements.
Related Terms
AI Governance
The framework of policies, processes, and technologies used to ensure AI systems operate ethically, transparently, and in compliance with regulations.
Bias Detection
The automated identification of systematic unfairness or discrimination in AI system outputs across different demographic groups.
Explainability
The ability to understand and communicate why an AI system made a specific decision or produced a particular output.