In May we ran our new online course, ‘Artificial Intelligence: Technology, Governance, and Policy Frameworks’ for the first time. It was a fantastic experience to develop and deliver a course around such a timely topic. In this blog post, we want to share some of our experiences and lessons-learned. The course was aimed at policymakers, regulators, diplomats, and staff of international organisations. It is different from other artificial intelligence (AI) courses as it covers a broad spectrum of areas, encompassing technical, political, legal, economic, security, and ethical issues related to AI. The course gives an introduction to the technological side of AI, covering big data, machine learning, neural networks, deep learning, and related topics. It can be hard to strike a balance when it comes to how to demanding the course is. The feedback we received tells us that for some participants, these more technical parts were just about enough or almost too challenging, while others wanted to learn more and delve deeper into the technological background of AI, with for example, neural networks. In order to address these needs, we decided to add supplementary materials to the next version of the course, which will cater to those interested a bit more in the technical side of things. Having said that, no course can cater to everyone’s needs, and for those who are beginners but want to go even further in understanding the technical side of AI, we recommend the free self-paced online course Elements of AI, which was developed by the University of Finland. At Diplo we try to bring our latest research and policy work to our online courses. This is important for all our courses but especially important for a course as timely as this one. In order to achieve this, we follow two key approaches: incorporating the latest research in our course texts; and, continuously adding new developments to the course discussions. First, our course texts, which form the core of the course and its continuous discussion, incorporate our latest research done as part of our AI Lab. The texts build on our report on Mapping AI’s challenges and opportunities for the conduct of diplomacy, and in particular, the overview of national AI strategies and analysis of international co-operation and competition. Since AI is such a fast-moving target, our research on AI strategies was updated only a few months after it came out and published as part of our Digital Watch Newsletter. This overview also found its way into our course texts. In addition, there is ongoing research done by Diplo’s Data Team. Our colleagues in that team use text mining approaches to look at how AI has been discussed over the last years in the global media. Currently, they are training IBM Watson with their custom language model in order to perform this task. These findings will be progressively added to the course materials. Second, the continuous interaction and discussions between lecturers and participants, and among participants themselves is a key element of course interaction. It is only natural that we include the latest news and articles on AI, and that participants bring news and articles they came across to the course discussion. For this course, we institutionalised this by sharing recent developments, news, and articles as, ‘AI news we came across this week’ in our course blog. This is a tradition we will definitely continue. The timely updates to the AI trend page on our GIP Digital Watch observatory will feed right into this. Participants who attended the AI course were frequently motivated by professional needs. Either they had been requested to work with topics that have been impacted by AI, or they wanted to acquire skills that would allow them to move to an AI-related field in the near future. Because of that, it was important to combine sound theoretical knowledge with a hands-on approach. At the end of the course, participants were able to develop concrete products, such as drafting the key elements of a national or institutional AI strategy, and articulating a critical thought-piece for a media outlet about emerging issues, such as the impact of AI on the future of decision-making, and on democracy. The development of practical skills was achieved through the methods of evaluation used in the course, which aimed not only at testing the knowledge acquired by participants, but first and foremost, at making them think about challenges and opportunities, developing a critical view on AI. Participants were capable of putting themselves in the shoes of different stakeholders – government, businesses, and citizens – making short-, mid-, and long-term decisions on areas of investment, policy, or advocacy priorities. With that, we are confident that they will be prepared to achieve their professional goals. The next session of the course on Artificial Intelligence: Technology, Governance, and Policy Frameworks will be offered in October 2019 and you can still apply until 20 September.Technical but not too technical
Staying up to date and incorporating our latest research
Promoting the development of practical skills
