Governance of Artificial General Intelligence (AGI) Training Course

Course Overview

Governance of Artificial General Intelligence (AGI) has emerged as one of the most significant priorities for governments, regulatory authorities, international organizations, technology companies, research institutions, defence agencies, financial institutions, and public sector leaders seeking to ensure the safe, ethical, transparent, and accountable development and deployment of advanced artificial intelligence systems. The rapid evolution of Governance of Artificial General Intelligence (AGI), Artificial Intelligence Governance, Responsible AI, AGI Safety, AI Regulation, AI Risk Management, AI Ethics, AI Policy, Explainable AI (XAI), AI Alignment, Machine Learning, Deep Learning, Generative AI, Foundation Models, Digital Governance, Cybersecurity, Data Governance, Algorithmic Accountability, AI Auditing, AI Assurance, Digital Public Infrastructure, AI Compliance, AI Innovation, AI Security, Cloud Computing, Big Data Analytics, International AI Standards, Emerging Technologies, Smart Government, and Sustainable Development Goals (SDGs) is transforming global governance, economic development, public administration, scientific research, national security, and digital transformation. This comprehensive training course equips participants with practical knowledge and strategic competencies to develop governance frameworks that promote safe, trustworthy, innovative, and human-centred AGI systems.

The course provides participants with a comprehensive understanding of AGI governance frameworks, international AI regulations, ethical AI principles, AI lifecycle governance, institutional oversight, regulatory compliance, AI risk assessment, AI alignment, algorithmic transparency, cybersecurity governance, data governance, AI procurement, digital sovereignty, innovation management, public policy development, monitoring and evaluation, and cross-sector collaboration. Participants will learn how to formulate AGI governance strategies, establish institutional oversight mechanisms, evaluate AGI risks, strengthen AI accountability, implement responsible AI practices, ensure legal and ethical compliance, manage emerging risks, and support innovation while protecting public interests. The programme incorporates internationally recognized principles and guidance from the Organisation for Economic Co-operation and Development (OECD) AI Principles, UNESCO Recommendation on the Ethics of Artificial Intelligence, International Organization for Standardization (ISO/IEC 42001 and ISO/IEC 23894), National Institute of Standards and Technology (NIST) AI Risk Management Framework, International Telecommunication Union (ITU), United Nations Development Programme (UNDP), World Economic Forum (WEF), and the Sustainable Development Goals (SDGs).

Special emphasis is placed on emerging technologies and governance mechanisms including artificial intelligence alignment, explainable AI, foundation models, generative AI, reinforcement learning, AI assurance frameworks, AI auditing, cloud computing, federated learning, privacy-enhancing technologies, blockchain for AI governance, cybersecurity, digital identity, AI model evaluation, AI monitoring systems, predictive analytics, AI incident response, regulatory sandboxes, digital twins, AI-enabled decision support systems, and international AI governance cooperation. Participants will also examine governance challenges relating to AI safety, autonomous decision-making, misinformation, algorithmic bias, privacy, intellectual property, national security, workforce transformation, cross-border AI regulation, public trust, innovation governance, and responsible technology deployment.

Through practical governance workshops, AI policy laboratories, regulatory simulations, risk assessment exercises, collaborative group work, web-based tutorials, technology demonstrations, and relevant international case studies, participants will develop competencies required to govern AGI responsibly and effectively. Upon successful completion, participants will be equipped to strengthen institutional readiness, improve AI governance capacity, establish robust regulatory frameworks, enhance responsible innovation, improve AI oversight, promote transparency and accountability, support secure digital transformation, and contribute to the safe development and governance of advanced artificial intelligence systems.

Course Objectives

1.     Understand the principles, concepts, and governance frameworks of Artificial General Intelligence (AGI).

2.     Develop comprehensive AGI governance strategies aligned with international standards and national priorities.

3.     Strengthen institutional capacity for AI regulation, oversight, and policy implementation.

4.     Apply responsible AI, AI ethics, AI alignment, and explainable AI principles in governance.

5.     Improve AI risk management, cybersecurity, and digital resilience for advanced AI systems.

6.     Strengthen regulatory compliance through internationally recognized AI governance frameworks.

7.     Promote transparency, accountability, fairness, and human oversight in AGI deployment.

8.     Enhance monitoring, evaluation, auditing, and assurance of AGI systems.

9.     Foster innovation while managing legal, ethical, and societal risks associated with AGI.

10.  Build resilient, secure, trustworthy, and future-ready governance systems for advanced artificial intelligence.

Organizational Benefits

1.     Improved institutional readiness for advanced AI governance and regulation.

2.     Enhanced compliance with international AI governance principles and standards.

3.     Strengthened organizational capacity to manage AI risks and ethical challenges.

4.     Improved transparency, accountability, and responsible AI decision-making.

5.     Enhanced cybersecurity and resilience of AI-enabled public services.

6.     Increased public trust through ethical and human-centred AI governance.

7.     Strengthened innovation governance while safeguarding public interests.

8.     Improved AI procurement, lifecycle management, and performance monitoring.

9.     Enhanced collaboration among government, academia, industry, and international partners.

10.  Sustainable AI adoption supporting digital transformation, economic competitiveness, and public value.

Target Participants

This course is designed for policymakers, government regulators, legislators, public sector executives, chief information officers, chief digital officers, AI governance professionals, AI ethics officers, ICT directors, legal advisors, compliance officers, cybersecurity specialists, risk managers, procurement professionals, digital transformation managers, data governance specialists, researchers, academics, technology innovators, development partners, standards authorities, defence and security professionals, financial regulators, monitoring and evaluation specialists, consultants, and professionals responsible for artificial intelligence governance, digital policy, innovation management, regulatory compliance, and emerging technology oversight.

Course Outline

Module 1: Introduction to Artificial General Intelligence (AGI) Governance

·       Fundamentals of Artificial General Intelligence

·       AGI versus narrow AI

·       Principles of AGI governance

·       Global AGI developments

·       Governance challenges

·       Future AI ecosystems

Case Study: Developing a national governance framework for emerging AGI technologies.

Module 2: International AI Governance Frameworks and Policies

·       OECD AI Principles

·       UNESCO AI Ethics Recommendation

·       ISO AI management systems

·       NIST AI Risk Management Framework

·       National AI strategies

·       Cross-border AI governance

Case Study: Comparing international AI governance frameworks for national implementation.

Module 3: AI Ethics, Human Rights and Responsible Innovation

·       Responsible AI principles

·       Human-centred AI

·       Human rights considerations

·       Fairness and non-discrimination

·       Transparency and accountability

·       Public trust

Case Study: Addressing ethical challenges in high-impact AI decision-making.

Module 4: AI Risk Management and AGI Safety

·       AI risk identification

·       AGI safety concepts

·       Risk mitigation strategies

·       AI alignment principles

·       AI incident management

·       Safety governance

Case Study: Conducting enterprise-wide risk assessments for advanced AI systems.

Module 5: Explainable AI, Transparency and Algorithmic Accountability

·       Explainable AI (XAI)

·       Algorithmic transparency

·       Model interpretability

·       Accountability frameworks

·       AI documentation

·       AI auditing

Case Study: Improving transparency and accountability in AI-assisted public decision-making.

Module 6: Data Governance, Privacy and Cybersecurity

·       Data governance frameworks

·       Privacy protection

·       AI cybersecurity

·       Digital resilience

·       Secure AI infrastructure

·       Identity and access management

Case Study: Protecting sensitive public sector data within AI-enabled environments.

Module 7: Regulatory Compliance and Institutional Oversight

·       AI regulatory models

·       Institutional governance

·       Compliance management

·       Regulatory enforcement

·       Governance reporting

·       Oversight mechanisms

Case Study: Establishing a national AI regulatory authority for advanced AI oversight.

Module 8: AI Procurement, Lifecycle Governance and Assurance

·       AI procurement strategies

·       Vendor governance

·       Lifecycle management

·       AI assurance

·       Performance monitoring

·       Continuous improvement

Case Study: Procuring and governing AI systems within a public sector digital transformation programme.

Module 9: Innovation Governance and International Cooperation

·       Innovation ecosystems

·       Regulatory sandboxes

·       International collaboration

·       Public-private partnerships

·       Research governance

·       Technology diplomacy

Case Study: Balancing innovation with regulation through collaborative AI governance.

Module 10: Monitoring, Evaluation and AI Performance Management

·       AI performance indicators

·       Monitoring frameworks

·       Evaluation methodologies

·       AI impact assessment

·       Governance dashboards

·       Continuous learning

Case Study: Measuring governance effectiveness across national AI initiatives.

Module 11: Societal, Economic and Security Implications of AGI

·       Workforce transformation

·       National security

·       Economic competitiveness

·       Digital sovereignty

·       Public sector modernization

·       Ethical societal impacts

Case Study: Developing governance responses to the societal impacts of advanced AI systems.

Module 12: Future Trends in Governance of Artificial General Intelligence

·       Autonomous AI systems

·       Foundation models

·       Generative AI evolution

·       Global AI governance trends

·       Strategic foresight

·       Long-term governance roadmaps

Case Study: Designing a strategic national roadmap for safe, ethical, and sustainable AGI governance.

General Information

1.     Customized Training: All our courses can be tailored to meet the specific needs of participants.

2.     Language Proficiency: Participants should have a good command of the English language.

3.     Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.

4.     Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).

5.     Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centres. We also offer options for in-house and online training, customized to the client's schedule.

6.     Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.

7.     Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.

8.     Additional Services: Accommodation, pickup services, flight booking, and visa processing arrangements are available upon request at discounted rates.

9.     Equipment: Tablets and laptops can be provided to participants at an additional cost.

10.  Post-Training Support: We offer one year of free consultation and coaching after the course.

11.  Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.

12.  Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.

13.  Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.

14.  Website: Visit our website at www.fdc-k.org for more information.