The 2019 OECD framework for an AI strategy (The Framework) provides a helpful structure for the development of a national AI strategy.
The Framework suggests breaking the approach into the 'baseline' - which is an assessment of the organisations current strategic situation and challenges that AI might help address; 'objectives' - what the organisation wants to achieve using AI and the principles that will underpin the actions it takes to achieve them; and 'approaches' - which are the concrete actions that will be undertaken to achieve these objectives.
A good strategy will require active monitoring for a clear overview. The elements should also be developed concurrently and iterated as the context evolves
Baseline components
Determine current strengths and weaknesses by mapping:
Internal AI capabilities.
Government and external data assets.
Existing government AI and data science projects.
Assess the strategic context:
Public and workforce attitudes to government and AI .
Current legal and regulatory framework.
Existing government and international commitments, institutions.
Academic and private sector expertise that might be drawn upon.
Identify specific operational problems that AI has the potential to help solve:
Adopt a multi-disciplinary and diverse approach to decide whether AI is the best solution to a policy problem, and if so, how it should be designed and implemented.
Put in place processes to understand user needs.
Create mechanisms to match resources to priority problems.
Define the specific decision AI will make or support.
Consider who will be impacted by this decision and associated risks if it fails.
Explore how the service will need to be redesigned to leverage the impact of AI.
Objectives
Decide what goals the AI should help government achieve:
Articulate how AI will generate public value and specify missions to which AI can be part of the solution.
Engage stakeholders in goal definition.
Make space for experimentation and learning.
Define and communicate to stakeholders the principles that will shape how AI is used in government:
Fairness and unbiasedness.
Transparency and accountability.
Privacy and individual autonomy.
Approaches
Ensure government access to AI capability and capacity:
Construct talent pipelines, and develop recruitment and retention plans for internal technical expertise.
Harness external expertise through partnerships and collaboration.
Design effective public sector AI procurement processes.
Build a cadre of civil servants who understand the legal, ethical, technical and managerial issues around AI.
Establish funding schemes and secure the availability of resources in the government’s fiscal plans.
Secure ethical access to, and use of, quality data and infrastructure:
Determine what data are needed to address the problems.
Decide how to obtain input data of sufficient quality and that are sufficiently representative of the target population to make accurate predictions with minimal bias.
Develop a data strategy that complies with data protection law and best practice and is consistent with AI principles.
Ensure important data infrastructure are in place (e.g., hybrid cloud services).
Put in place legal, ethical and technical frameworks to operationalise the principles:
Monitor compliance with principles during implementation to track progress, and identify and respond to emerging issues.
Put in place safeguards against bias and unfairness.
Clarify the appropriate role for humans in the decision-making process.
Develop open and transparent accountability structures.
Prepare for future shifts:
Ensure openness and flexibility in future plans and contracts.
Follow OPSI Anticipatory Innovation Governance concepts
Conclusion
Countries developing an AI strategy could consider using the OECD framework for an AI strategy as a helpful organising structure. The three parts (baseline, objectives, approaches) should all be considered in parallel and with the expectation that the output (strategy) will be a highly dynamic guideline for AI across government and beyond.
References:
OECD (2019c), “Using digital technologies to improve the design and enforcement of
public policies”, OECD Digital Economy Papers, No. 274, OECD Publishing, Paris,
https://dx.doi.org/10.1787/99b9ba70-en.
European Commission (2018a), Artificial Intelligence: A European Perspective,
European Commission, Brussels, https://ec.europa.eu/jrc/en/publication/eur-scientific-
and-technical-research-reports/artificial-intelligence-european-perspective
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