AI in Public Policy making and Governance: Strategic view#400824

• Analyse the impact of future trends on the development and application of AI in the public sector.
• Identify key challenges and opportunities within the policy landscape, considering how AI can be used to address issues like public health, infrastructure, and social welfare.
• Develop a strategic vision for integrating AI into policymaking and governance frameworks, ensuring responsible and ethical use.
• Explore various AI applications relevant to public policy areas, such as predictive analytics for crime prevention, AI-powered traffic management systems, and personalized social services delivery.
• Gain a basic understanding of machine learning algorithms and data analysis techniques relevant to AI applications in public policy.
• Evaluate the potential risks and societal impacts of AI in the public sphere, addressing issues like bias and algorithmic fairness in policy decisions.
• Develop innovative policy frameworks for governing AI development and deployment within the public sector, considering transparency, accountability, and human control.
• Build a personalized action plan outlining steps to explore and potentially implement AI solutions to address public challenges within their specific roles or departments.

• Policymakers, government officials, and public servants looking to understand the potential of AI for policy development and implementation.
• Urban planners, public health officials, and social service professionals interested in utilizing AI for data-driven decision-making.
• Regulatory bodies and legal professionals concerned with the ethical implications and governance of AI in the public sector.
• Anyone interested in understanding the future potential of AI and its impact on public policy and governance.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: The Future of Governance & AI
• Welcome and program overview.
• AI for Public Good: Exploring the transformative potential of AI in tackling complex public challenges across various sectors, such as healthcare, education, and environmental sustainability.
• Future Studies for Public Policy: Learning how to incorporate future studies methodologies like scenario planning and horizon scanning to anticipate potential disruptions and opportunities related to AI in the public sphere.
• The Geopolitical Landscape of AI: Discussing the global competition in AI development and its implications for international cooperation and policymaking.
• Guest Speaker: A prominent leader in the field of AI policy or a government official who successfully implemented AI for public good can be invited to share their insights and answer participant questions.

Day 2: Leveraging AI for Public Policy & Governance
• AI Applications in Public Policy: Exploring specific applications of AI in different policy areas, such as:
o Predictive analytics: For crime prevention, resource allocation, and risk assessment.
o AI-powered infrastructure management: For optimizing traffic flow, energy distribution, and public transportation systems.
o Personalized social services: For targeted interventions, fraud detection, and social welfare programs.
• Data for Public AI: Discussing the importance of data quality, accessibility, and ethical data governance for effective AI applications in public policy.
• Hands-on Workshop: analysing Public Data with AI Tools: Participants will gain practical experience using user-friendly platforms or introductory coding environments to explore real-world public datasets and perform basic data analysis tasks relevant to policy questions.
Day 3: The Ethics of AI in Public Policy
• Bias and Fairness in AI Policymaking: Exploring the potential for bias in AI algorithms and its impact on public policy decisions, considering issues like racial profiling and algorithmic discrimination.
• Algorithmic Transparency & Explainability: Discussing the importance of transparency and explainability in AI used for public policy, ensuring public trust and accountability.
• The Right to Privacy in the AI Age: Addressing privacy concerns associated with data collection, analysis, and use of AI in the public sector.
• Case Study: analysing a real-world example of a government initiative that encountered ethical challenges with AI implementation, discussing lessons learned and strategies to avoid similar issues.
• Group Discussion: Participants engage in a facilitated discussion to explore potential ethical dilemmas related to AI applications in specific policy areas relevant to their work.

Day 4: Building a Policy Framework for AI Governance
• Developing Responsible AI Policies: Learning key principles for governing AI development and deployment within the public sector, focusing on transparency, accountability, and human control.
• AI Regulation & Legal Considerations: Discussing existing and emerging legal frameworks for regulating AI in the public sphere, addressing issues like liability and data protection.
• Public Engagement & Building Trust: Learning strategies for effective public engagement and communication about AI in government, fostering trust and understanding among citizens.
• Building Capacity for AI Governance: Exploring strategies for building internal capacity within government agencies to manage AI projects responsibly and effectively.
• Case Study: analysing a real-world example of a government agency with a strong framework for AI governance, exploring their guiding principles and best practices.
Day 5: The Future of AI & Public Policy
• The Future of Work & AI in the Public Sector: Exploring the potential impact of AI on public service jobs and skills, focusing on strategies for workforce development and human-AI collaboration.
• Artificial General Intelligence (AGI) & Long-Term Risks: Discussing potential future scenarios and long-term risks associated with advanced AI, and how public policy can address them.
• Global Cooperation & Policy Harmonization: Exploring the need for international collaboration in developing responsible AI principles and harmonized policies on AI governance.
• Developing Your AI Action Plan: Participants create personalized action plans outlining steps to explore and potentially implement AI solutions within their specific public sector roles or departments. This may include:
o Identifying policy areas where AI could be beneficial for data-driven decision-making.
o Researching existing AI applications relevant to their field and exploring ethical considerations.
o Advocating for responsible AI governance frameworks within their government agencies.
o Identifying potential training opportunities for themselves and colleagues on AI and its implications for public policy.
• Course Wrap-Up & Ongoing Learning: Reviewing key takeaways from the program, addressing any remaining questions, and discussing ongoing learning resources for staying informed about advancements in AI and its impact on public policy.
• Networking & Policy Dialogue: Participants engage in a facilitated discussion to share their AI action plans and explore collaborative efforts to advance responsible AI in government. They can also discuss potential policy recommendations based on their learnings.