!img-0.jpeg Republic of Zambia Ministry of Technology and Science
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# NATIONAL ARTIFICIAL INTELLIGENCE STRATEGY
2024-2026
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# Contents
Foreword ... 1 Acknowledgement ... 3 1. Executive Summary ... 8 2. Introduction ... 10 2.1 The Promise of AI for Zambia ... 10 2.2 Ethical Commitment and International Alignment ... 10 2.3 Strategic Imperatives for Zambia ... 11 3 Strategy Development Approach ... 13 4. Situation Analysis ... 18 4.1 Overview ... 18 4.2 AI Ecosystem Development ... 18 4.3 Governance Framework ... 19 4.4 Enabling Factors ... 20 4.5 Policy and Regulation ... 20 4.6 Infrastructure ... 21 4.7 International Benchmark Insights ... 21 5. Vision and Guiding Principles ... 23 5.1 Vision ... 23 5.2 Guiding Principles ... 23 6. Strategic Initiatives ... 26 6.1 Strategic Objectives ... 26 6.2 Key Strategic Pillars ... 28 7. Implementation and Governance Framework ... 30 7.1 Governance Structure ... 30 7.2 Technical Working Groups (TWGs) ... 30 7.3 Coordination Entities ... 31 7.4 National Emerging Technologies Centre of Excellence ... 32 7.5 Roles and Responsibilities ... 32 7.6 Implementation Mechanisms ... 33 7.7 Stakeholder Engagement ... 34 7.8 Risk Management ... 34 8 Implementation Plan ... 36 9. Monitoring and Evaluation Framework ... 40
Glossary of Terms
Artificial Intelligence (AI):
A branch of computer science focusing on creating systems that can perform tasks requiring human intelligence, such as learning, reasoning, problem-solving, perception (listening and seeing) and understanding language.
National AI Strategy:
Formal plan to develop, regulate, and promote AI technologies for national development, economic growth, and social advancement.
Machine Learning:
A subset of AI where algorithms improve automatically through experience by analysing data and identifying patterns without being explicitly programmed.
Digital Infrastructure:
The foundational technologies that enable the functioning and integration of digital technologies, such as broadband connectivity, cloud computing, and data centres.
AI Ecosystem:
The collective framework of government, academic institutions, private sector, civil society, and international partners working together to develop, apply, and regulate AI technologies.
Ethics of AI:
Principles and standards ensuring that AI systems are developed and deployed in ways that respect human rights, promote fairness, and prevent biases or harm.
AI for Development:
AI applications specifically aimed at solving challenges and driving progress in low- and middle-income countries, such as improving healthcare, education, agriculture, and governance.
National AI Council:
An advisory body responsible for giving strategic advice on AI policy development, regulation, and strategic implementation at the national level.
Data Privacy:
Protecting personal and sensitive information from unauthorized access or misuse, ensuring compliance with legal frameworks such as data protection laws.
High-Performance Computing (HPC):
Advanced computing capabilities enabling large-scale processing and analysis, essential for running complex AI models and algorithms.
Centre of Excellence (CoE):
Dedicated hub or institution focusing on advanced research, development, and innovation in AI and related technologies.