Responsible AI
An approach to design, develop and deploy AI that respects law, human rights and ethical principles and that manages harms through governance, transparency and accountability.
How the laws define this
Global frameworks and national strategies consistently define responsible artificial intelligence as an ethical lifecycle approach centered on fairness, transparency, accountability, human rights, privacy, and harm mitigation. However, instruments diverge on whether the concept functions as a non-binding guiding principle or an operationalized governance standard. For instance, the Argentine Multidisciplinary AI Center (presentation) and the National Artificial Intelligence Centre (NAIC) — CSIRO Data61 treat responsible AI as a guiding or normative concept rather than a binding legal standard. Conversely, the Ghana National Artificial Intelligence Strategy 2023-2033 applies it directly to procurement standards, risk assessments, and documentation, while the Ethical Guidelines for the Development, Implementation and Use of Reliable and Responsible AI require explicit role-based accountability and redress. Frameworks such as the Global Partnership on Artificial Intelligence (GPAI) further mandate alignment with democratic values.
Synthesised from the 26 statutory definitions below. Each one is quoted in full, with its source.
How jurisdictions differ
What is distinctive in each definition, binding law in force first. Showing 10 of the 26 instruments that define this term; all are listed under Definitions below.
| Jurisdiction | Instrument | Status | What is distinctive |
|---|---|---|---|
| Australia | National Artificial Intelligence Centre (NAIC) — CSIRO Data61 | In Force | Prioritises safety, fairness, transparency and privacy as guiding concepts for NAIC resources, training and tools without statutory legal definitions. |
| North Carolina, United States | North Carolina State Government Responsible Use of Artificial Intelligence Framework | In Force | Aligns AI development and behavior to established goals and values, ensuring consistency with democratic values throughout the lifecycle. |
| United States | U.S. Department of Agriculture Fiscal Year 2025–2026 AI Strategy | In Force | Emphasizes deploying AI systems that respect privacy, safeguard data, minimize biases, and prioritize human rights, health, and safety. |
| India | Proposed amendments with respect to assigning responsibility for the use of artificial intelligence tools by Market Infrastructure Institutions, Registered Intermediaries and other persons regulated by SEBI | Proposed | Encompasses ethical principles and practices to ensure AI is safe, reliable, fair, transparent, and accountable, mitigating risks like bias and privacy breaches. |
| Norway | Datatilsynet Regulatory Sandbox for privacy-friendly innovation and AI (Sandbox for Responsible AI) | In Force | Operationalises lawfulness, transparency, fairness and accountability through risk assessments, documentation, privacy-enhancing technologies and governance in a sandbox. |
| World Economic Forum | World Economic Forum AI Governance Alliance | In Force | Emphasizes safety, fairness, accountability, and respect for human rights as guiding principles for design, deployment, and governance by a multi-stakeholder alliance. |
| New Zealand | Responsible AI in action: Guidance for Regulators | In Force | Defined implicitly through emphasis on ethical considerations, accountability, transparency, and maintaining human judgment in regulatory decision-making. |
| Iceland | Iceland's AI Action Plan 2025-2027 | In Force | Frames ethical, transparent, and accountable AI respecting human rights, fairness, and societal well-being as the guiding objective for national research and adoption. |
| GPAI | Global Partnership on Artificial Intelligence (GPAI) | In Force | Limits to development, deployment, and use of AI consistent with democratic values and human rights, emphasizing fairness and accountability. |
| Sweden | Sweden's National Artificial Intelligence Strategy (2026) | In Force | Specifies adherence to ethics, transparency, explainability, non-discrimination, and respect for privacy and fundamental rights for trustworthy societal integration. |
What it triggers
- In SEBI-regulated entities in India, proposed amendments would require assigning clear responsibility for the use of AI tools to ensure accountability.source
- In the Datatilsynet Regulatory Sandbox for privacy-friendly innovation and AI in Norway, it promotes risk assessments, documentation, privacy-enhancing technologies and governance measures.source
- The National Artificial Intelligence Centre in Australia uses it as a guiding concept for resources, training and tools to promote ethical and lawful AI development and deployment.source
Definitions (26)
A guiding commitment to develop and deploy AI systems in ways that respect human rights, ensure transparency, protect privacy, and incorporate human oversight and non-discrimination; used as an operational principle to guide CamIA's ethics, governance and capacity-building activities rather than as a binding legal standard.
An approach to developing and using AI that emphasises fairness, safety, transparency, respect for rights and inclusion, in line with Australia’s AI Ethics Principles and intended to mitigate harms while promoting public trust.
Defined in the document as approaches to AI that prioritise safety, fairness, transparency and privacy; used as a guiding concept for NAIC resources, training and tools to promote ethical and lawful AI development and deployment. This term describes normative practices rather than establishing statutory legal definitions within the policy.
A governance concept encompassing ethical principles and practices to ensure AI systems are fair, transparent, accountable, and beneficial to society. The strategy uses Responsible AI as the foundation for oversight mechanisms, the planned Center for Responsible AI, and integration of the Egyptian Charter for Responsible AI into practice.
A principle that AI development and deployment should be ethical, transparent, and accountable, ensuring respect for human rights, fairness, and societal well-being. The Action Plan frames Responsible AI as the guiding objective for research, public-sector adoption, and private-sector incentives.
AI development and deployment practices that prioritise social benefit, non-discrimination, transparency, privacy preservation and human-centric oversight; used as a working principle throughout the summit to guide ethical AI adoption and program design.
A set of principles—fairness, accountability, transparency, ethics, privacy protection, and inclusive design—applied throughout the AI development lifecycle to ensure technologies benefit all Filipinos and minimize potential harms, guiding research, deployment, and evaluation practices.
An approach to building and deploying AI systems that prioritizes ethical principles—such as beneficence, non-maleficence, autonomy, justice, and explicability—while ensuring transparency, accountability, and human oversight to minimize harm and protect rights. The policy uses this concept as the guiding standard for AI adoption across public and private sectors.
AI systems designed, built, and deployed in ways that are ethical, transparent, fair, accountable, and that respect human rights. The roadmap frames Responsible AI as a guiding principle for governance, including bias mitigation, explainability, and safeguards for privacy and equity.
Principles and practices for developing and deploying AI in ways that respect human rights, ensure fairness and non-discrimination, promote transparency and explainability, and establish accountability mechanisms. It guides regulatory approaches, sector adaptations, and ethical guidelines promoted by the strategy.
AI developed, deployed, and operated with explicit accountability arrangements, assigning roles and responsibilities to actors (e.g., developers, deployers) to ensure oversight, transparency, and redress for outcomes.
A principle-driven approach to AI development and deployment that requires ethical design, transparency, and conformity with human rights standards; intended to ensure AI benefits people and society while managing risks. The strategy uses this term to frame obligations and best practices across governance, deployment, and oversight activities.
A working policy concept encompassing ethics, fairness, accountability and transparency that guides procurement standards, risk assessment, sectoral deployment and documentation requirements; intended to align AI adoption with human rights, data governance and ethical best practices under the national framework.
Systems designed, developed and deployed with attention to lawfulness, transparency, fairness and accountability, operationalised through risk assessments, documentation, privacy‑enhancing technologies and governance measures promoted by the sandbox.
AI developed and deployed in accordance with ethical principles, emphasizing safety, fairness, accountability, and respect for human rights; used by the Alliance as a guiding principle for design, deployment, and governance of AI systems.
An AI system that aligns its development and behavior to established goals and values, ensuring consistency with democratic values. This approach prioritizes ethical considerations throughout the AI lifecycle.
The development, deployment, and use of AI systems in a manner that is consistent with democratic values and human rights, emphasizing fairness and accountability.
AI systems designed to be ethical, transparent, and aligned with human rights standards. It ensures that technology serves the public good without bias.
The development and use of artificial intelligence in a manner that respects human rights, promotes fairness, equity, inclusivity, and democracy, and contributes positively to the public good, aligning with principles such as those outlined in the OECD Recommendation on AI.
Responsible AI involves deploying artificial intelligence systems in a manner that respects privacy, safeguards data, minimizes biases, and ensures transparency and accountability throughout the AI lifecycle. It prioritizes human rights, health, and safety.
Defined implicitly through its emphasis on ethical considerations, accountability, transparency, and the maintenance of human judgment in decision-making processes, particularly in regulatory contexts.
Responsible AI encompasses principles and practices ensuring that AI systems are designed, developed, and deployed in a manner that is fair, transparent, accountable, and respects fundamental human rights. It aims to mitigate risks such as bias, discrimination, and privacy violations.
Responsible AI encompasses the ethical design, development, and deployment of AI systems that prioritize human rights, fairness, transparency, and accountability. It aims to ensure that AI benefits society while mitigating potential risks and harms.
AI systems that adhere to principles of ethics, transparency, explainability, non-discrimination, and respect for privacy and fundamental rights, ensuring beneficial and trustworthy integration into society.
'Responsible AI' extends beyond safety to encompass ethical considerations, ensuring that AI systems are developed and used in a manner that respects human rights, promotes fairness, prevents discrimination, and upholds democratic values.
Responsible AI encompasses a set of ethical principles and practices aimed at ensuring that AI systems are developed and deployed in a manner that is safe, reliable, fair, transparent, and accountable. It seeks to mitigate risks such as bias, discrimination, privacy breaches, and unintended societal harms, promoting beneficial and trustworthy AI.
Not to be confused with
AI Ethics refers to norms and practices across the AI lifecycle, while Responsible AI often frames broader approaches to design, development, and deployment.
Responsible Use of AI focuses on ethical, transparent use respecting human rights, whereas Responsible AI encompasses full development and deployment practices.
Questions and answers
What does responsible AI mean in the context of Australia's NAIC?
It prioritises safety, fairness, transparency and privacy as guiding concepts for NAIC resources, training and tools. This describes normative practices rather than statutory legal definitions.
How is responsible AI defined under SEBI's proposed amendments in India?
It encompasses ethical principles ensuring AI is safe, reliable, fair, transparent, and accountable, mitigating risks like bias and privacy breaches. The proposal assigns clear responsibility for AI tool use by regulated entities.
What principles does GPAI emphasize for responsible AI?
GPAI defines it as AI development, deployment, and use consistent with democratic values and human rights, emphasizing fairness and accountability. It serves as a guiding principle in their multi-stakeholder initiative.
Related Terms
Responsible Use of AI
Ethical, transparent AI use that respects human rights....
AI Ethics
Norms and practices ensuring AI respects human rights, fairness, safety, transparency and accountability across the AI lifecycle....
Responsible AI measures
Risk assessment, documentation and mitigation aligned with law....
Ethical, reliable and trustworthy AI
AI systems following transparency, accountability, fairness, privacy and safety....
Accountability (OECD)
AI actors are responsible for proper system functioning....