Chapter 09 · Sustainability & AISustainability & AI
Responsible AI
Definition
Principles and practices intended to ensure AI is developed and used in ways that are ethical, accountable and beneficial, encompassing fairness, transparency, privacy, safety and — increasingly — environmental impact.
References
This source provides part of the technical or institutional basis for the definition.
This source supports the explanation of how the term is applied, measured or governed in practice.
This source supports the wider sustainability significance and context described in the entry.
Overview
What it means
Responsible AI matured from corporate principles documents into operational programmes: review boards, impact assessments, model documentation and red-teaming. Frameworks such as the OECD principles, UNESCO's Recommendation and ISO/IEC 42001 give it intergovernmental and standards form; environmental sustainability is an emerging pillar.
How it is used
Organisations run responsible-AI programmes as management systems — increasingly certified to ISO/IEC 42001 — covering use-case review, risk assessment and monitoring of deployed systems, with disclosure expectations rising under the EU AI Act.
Why it matters
The phrase is everywhere and means everything from legal compliance to marketing posture. Its value depends on operationalisation: without assessment processes, documentation and accountability owners, 'responsible AI' is itself a claim requiring substantiation.