The Organisation for Economic Co-operation and Development (OECD), which works on establishing evidence-based international standards and develops advice on public policies, has issued updated recommendations (“Recommendation”) on responsible AI to reflect technological and policy developments, including with respect to generative AI, and to further facilitate its implementation.
We recently published Responsible AI – Everyone is Talking About it But What Is It? where we highlighted the need for companies to employ AI governance and adopt policies for the responsible development and deployment of AI. In the article, we referenced a set of publications by NIST (the National Institute of Standards and Technology) and Microsoft. These publications provide examples of efforts by these institutions to develop best practices for responsible AI development. The first section of the Recommendation is largely consistent with but adds to the principles of responsible AI in these prior publications.
The Recommendation includes two substantive sections:
1. Principles for responsible stewardship of trustworthy AI: the first section sets out five complementary principles relevant to all stakeholders: i) inclusive growth, sustainable development and well-being; ii) respect for the rule of law, human rights and democratic values, including fairness and privacy; iii) transparency and explainability; iv) robustness, security and safety; and v) accountability. This section further calls on AI actors to promote and implement these principles according to their roles.
2. National policies and international co-operation for trustworthy AI: consistent with the five aforementioned principles, the second section provides five recommendations to Members and non-Members having adhered to the Recommendation (hereafter the “Adherents”) to implement in their national policies and international co-operation: i) investing in AI research and development; ii) fostering an inclusive AI-enabling ecosystem; iii) shaping an enabling interoperable governance and policy environment for AI; iv) building human capacity and preparing for labour market transformation; and v) international co-operation for trustworthy AI.
The first set of recommendations, relating to the principles for responsible stewardship of trustworthy AI, include the following:
1.1. Inclusive growth, sustainable development and well-being
Stakeholders should proactively engage in responsible stewardship of trustworthy AI in pursuit of beneficial outcomes for people and the planet, such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, well-being, sustainable development and environmental sustainability.
1.2. Respect for the rule of law, human rights and democratic values, including fairness and
Privacy
a) AI actors should respect the rule of law, human rights, democratic and human-centered values throughout the AI system lifecycle. These include non-discrimination and equality, freedom, dignity, autonomy of individuals, privacy and data protection, diversity, fairness, social justice, and internationally recognized labour rights. This also includes addressing misinformation and disinformation amplified by AI, while respecting freedom of expression and other rights and freedoms protected by applicable international law.
b) To this end, AI actors should implement mechanisms and safeguards, such as capacity for human agency and oversight, including to address risks arising from uses outside of intended purpose, intentional misuse, or unintentional misuse in a manner appropriate to the context and consistent with the state of the art.
1.3. Transparency and explainability
AI Actors should commit to transparency and responsible disclosure regarding AI systems. To this end, they should provide meaningful information, appropriate to the context, and consistent with the state of art:
a) to foster a general understanding of AI systems, including their capabilities and limitations,
b) to make stakeholders aware of their interactions with AI systems, including in the workplace,
c) where feasible and useful, to provide plain and easy-to-understand information on the sources of data/input, factors, processes and/or logic that led to the prediction, content, recommendation or decision, to enable those affected by an AI system to understand the output, and,
d) to provide information that enable those adversely affected by an AI system to challenge its output.
1.4. Robustness, security and safety
a) AI systems should be robust, secure and safe throughout their entire lifecycle so that, in conditions of normal use, foreseeable use or misuse, or other adverse conditions, they function appropriately and do not pose unreasonable safety and/or security risks.
b) Mechanisms should be in place, as appropriate, to ensure that if AI systems risk causing undue harm or exhibit undesired behavior, they can be overridden, repaired, and/or decommissioned safely as needed.
c) Mechanisms should also, where technically feasible, be in place to bolster information integrity while ensuring respect for freedom of expression.
1.5. Accountability
a) AI actors should be accountable for the proper functioning of AI systems and for the respect of the above principles, based on their roles, the context, and consistent with the state of the art.
b) To this end, AI actors should ensure traceability, including in relation to datasets, processes and decisions made during the AI system lifecycle, to enable analysis of the AI system’s outputs and responses to inquiry, appropriate to the context and consistent with the state of the art.
c) AI actors, should, based on their roles, the context, and their ability to act, apply a systematic risk management approach to each phase of the AI system lifecycle on an ongoing basis and adopt responsible business conduct to address risks related to AI systems, including, as appropriate, via co-operation between different AI actors, suppliers of AI knowledge and AI resources, AI system users, and other stakeholders. Risks include those related to harmful bias, human rights including safety, security, and privacy, as well as labour and intellectual property rights.
The second set of recommendations, relating national policies and international co-operation for trustworthy AI, include the following:
Adherents implement the following recommendations, consistent with the principles in section 1, in their national policies and international co-operation, with special attention to small and medium-sized enterprises (SMEs).
2.1. Investing in AI research and development
a) Governments should consider long-term public investment, and encourage private investment, in research and development and open science, including interdisciplinary efforts, to spur innovation in trustworthy AI that focus on challenging technical issues and on AI-related social, legal and ethical implications and policy issues.
b) Governments should also consider public investment and encourage private investment in opensource tools and open datasets that are representative and respect privacy and data protection to support an environment for AI research and development that is free of harmful bias and to improve interoperability and use of standards.
2.2. Fostering an inclusive AI-enabling ecosystem
Governments should foster the development of, and access to, an inclusive, dynamic, sustainable, and interoperable digital ecosystem for trustworthy AI. Such an ecosystem includes inter alia, data, AI technologies, computational and connectivity infrastructure, and mechanisms for sharing AI knowledge, as appropriate. In this regard, governments should consider promoting mechanisms, such as data trusts, to support the safe, fair, legal and ethical sharing of data.
2.3. Shaping an enabling interoperable governance and policy environment for AI
a) Governments should promote an agile policy environment that supports transitioning from the research and development stage to the deployment and operation stage for trustworthy AI systems. To this effect, they should consider using experimentation to provide a controlled environment in which AI systems can be tested, and scaled-up, as appropriate. They should also adopt outcome-based approaches that provide flexibility in achieving governance objectives and co-operate within and across jurisdictions to promote interoperable governance and policy environments, as appropriate.
b) Governments should review and adapt, as appropriate, their policy and regulatory frameworks and assessment mechanisms as they apply to AI systems to encourage innovation and competition for trustworthy AI.
2.4. Building human capacity and preparing for labour market transformation
a) Governments should work closely with stakeholders to prepare for the transformation of the world of work and of society. They should empower people to effectively use and interact with AI systems across the breadth of applications, including by equipping them with the necessary skills.
b) Governments should take steps, including through social dialogue, to ensure a fair transition for workers as AI is deployed, such as through training programmes along the working life, support for those affected by displacement, including through social protection, and access to new opportunities in the labour market.
c) Governments should also work closely with stakeholders to promote the responsible use of AI at work, to enhance the safety of workers, the quality of jobs and of public services, to foster entrepreneurship and productivity, and aim to ensure that the benefits from AI are broadly and fairly shared.
2.5. International co-operation for trustworthy AI
a) Governments, including developing countries and with stakeholders, should actively co-operate to advance these principles and to progress on responsible stewardship of trustworthy AI.
b) Governments should work together in the OECD and other global and regional fora to foster the sharing of AI knowledge, as appropriate. They should encourage international, cross-sectoral and open multi-stakeholder initiatives to garner long-term expertise on AI.
c) Governments should promote the development of multi-stakeholder, consensus-driven global technical standards for interoperable and trustworthy AI.
d) Governments should also encourage the development, and their own use, of internationally comparable indicators to measure AI research, development and deployment, and gather the evidence base to assess progress in the implementation of these principles.
The issues with AI continued to evolve. But through the continued efforts of organizations such as the OECD, NIST and industry leaders such as Microsoft, a set of best practices is emerging to help companies develop corporate policies on the responsible development and deployment of AI and governments to adopt sound AI regulatory policies.
