AI Governance – foundational elements that Governments need to consider
There are a number of things governments need to consider as part of their efforts to build national level Artificial Intelligence (AI) capabilities. Endless opportunities constantly emerge from new AI trends, technologies and applications. As attractive as these opportunities may be, it is critical governments undertake foundational AI associated work to manage the risks of unintended and/or undesirable outcomes.
Governments seeking to build their Artificial Intelligence (AI) capabilities need to develop the following foundational elements:
Strategy and policy: Governments should prioritize the development of comprehensive strategies and policies that outline their vision, goals, and the guiding principles for AI governance. This requires research, engaging with relevant stakeholders (including industry, academia, civil society organisations, and the public), and considering international best practices. The strategy and policy phase should encompass a broad understanding of the potential benefits, risks, and societal implications of AI technologies.
Governance framework. Governments need to establish a governance framework to provide oversight of the implementation phases of AI strategies and policies. This framework needs to define the roles and responsibilities of different public entities involved in AI governance, ensuring coordination, accountability, and effective decision-making.
Codes of conduct: Governments should proactively establish codes of conduct pertaining to the development, deployment, and utilization of AI. These codes should delineate the ethical principles, guidelines, and responsibilities that all stakeholders—government agencies, the private sector, and research institutions adhere to.
Ethical principles: Governments need to implement frameworks and operational tools that actively promote ethical principles within AI systems. These measures should be aimed at combating bias and embedding fairness, transparency, and accountability. Robust mechanisms should be devised to identify and address biases in algorithms, datasets, and in AI applications, to prevent adverse effects on specific individuals or groups.
Development benchmarks: To ensure responsible implementation of AI, governments must develop evaluation benchmarks and metrics. These standards will allow the assessment of AI system performance, effectiveness, and impact. Regular evaluations should be conducted to gauge compliance with ethical standards, identify areas for improvement, and ascertain the achievement of desired outcomes.
Technical standards: Governments should work with technical experts and industry stakeholders to establish and promote technical standards for AI. These standards should address challenges such as data privacy, security, interoperability, and system reliability. A shared approach to technical standards will facilitate responsible and interoperable deployment of AI across sectors and support consistency with governance practices.
Pilot projects. Governments should support pilot projects and the use of safe environments such as ‘sandboxes’ to encourage AI experimentation and innovation. These initiatives provide controlled environments for testing AI systems in real-world scenarios while adhering to regulatory frameworks. By promoting safe experimentation, governments can facilitate learning, identify potential risks, and develop effective governance mechanisms.
Building diverse AI workforce: Governments need to focus on creating a workforce that has a mix of technical expertise as well as ethical, legal, and social aspects. This multidisciplinary approach is crucial to manage the complexity of AI governance. Governments should invest in AI education and training programs to equip professionals with technical and non-technical skills necessary for the development, regulation, and management of AI technologies.
Summary
By developing these foundational elements governments can more confidently support and invest in AI innovation while balancing the inherent risks. There are a number of helpful resources available to support governments develop these foundations. Active participation in international forums and standards development is recommended as a pragmatic way to expedite these steps.
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