​Opening remarks: Ahmad R​. Sharafat, ​Chairman, ITU-D Study Group 2 ​

Trainer: Rémi Laurent Emmanuel Sabonnadiere, ​EPFL Extension School (Switzerland) ​[Presentation​​]

What is AI, what can AI do, what can AI not do?
​Terminology of AI: narrow AI, general AI, machine learning, neural networks, deep learning, supervised learning, unsupervised learning, reinforcement learning. Examples of what AI can do. Examples of where AI goes wrong. A non-technical explanation of how neural networks and deep learning work. A non-technical overview of AI tools.​ ​ ​​


What is data and why does it matter in the context of AI? ​
Data accessibility and consistency. Data as a limiting factor. The secret AI sauce: the machine learning equation – data, computational power and expertise. Collection, analysis and inference of data. The role of data. How to become data literate. Why you will need to learn how to use data. Why sharing data is so important.​ ​ ​​

How to integrate a data culture in your organization, and why it matters?
​Digital transformation, organization challenges, lifelong learning, implementation strategies, etc.  

Trainer: Zhifeng Zhang, Huawei (People’s Republic of China) ​[Presentation​​]

​​​​​Key technologies in AI, their characteristics and key AI applications in different areas. Trends in AI and the current status of associated technology and its anticipated impact. Opportunities and challenges in the field of AI. AI as a new general purpose technology and the AI industry. ​

Facilitator: Aminata Amadou Garba, ITU Telecommunication Development Bureau (BDT) ​[Presentation]

​​​​H​ow can AI be applied to address development challenges? How can governments use mobile dat​a and AI to analyze the socio-economic challenges and better serve the p​opulation?​

​​​​Moderator: James Njeru, , Communications Authority of Kenya, Kenya

In which areas of AI be the most effective, and what are some practical use cases of AI in these areas? What are the associated benefits and challenges? What are the lessons learned and future steps to ensure that AI is applied in a more efficient way in these specific areas?”