AI is a general-purpose technology that has the potential to improve the welfare and well-being of people, to contribute to positive sustainable global economic activity, to increase innovation and productivity, and to help respond to key global challenges. It is deployed in many sectors ranging from production, finance and transport to healthcare and security. Alongside benefits, AI also raises challenges for our societies and economies, notably regarding economic shifts and inequalities, competition, transitions in the labour market, and implications for democracy and human rights. The OECD has undertaken empirical and policy activities on AI in support of the policy debate over the past two years, starting with a Technology Foresight Forum on AI in 2016 and an international conference on AI: Intelligent Machines, Smart Policies in 2017. The Organisation also conducted analytical and measurement work that provides an overview of the AI technical landscape, maps economic and social impacts of AI technologies and their applications, identifies major policy considerations, and describes AI initiatives from governments and other stakeholders at national and international levels.

We interviewed Karine Perset, from the OECD Directorate for Science, Technology and Innovation in France about the informational pillars that make up strong AI governance for governments worldwide. She offered us numerous insights into how the OECD developed the AI Principles and works with governing bodies to design policies that will keep AI safe and trustworthy into the future. Additionally, we discuss which types of policies are necessary for which types of AI software as well as the scale at which these policies should govern. This could range from city to city at the local level as well as an international level as governments around the world continue to work on global standards for AI governance. In our interview with Perset, we focused on the differences between local, international, and global policies for AI systems and products.

We have also seen that despite the discrepancies between countries from North to South, to Western countries to Eastern countries, there is a domino effect according to which major ethical issues and tendencies are almost simultaneously faced by every country at the same time, whatever their place in the AI race. It was the case for the AI tracking applications and the facial recognition applications during #COVID-19, and it will probably continue because AI is questioning the equilibrium of geopolitics worldwide. It also questions our ability to face fundamental and crucial questions as of the future of multilateralism. Below the translation of an article published in January, 2021 that highlights some trends I have foreseen in December 2020 for AI globally with some insights on the French market. Carrying out a prospective exercise is never easy and is even less so in the current context, which reminds us of the impermanence of all things and the need to adapt with agility, both individually and collectively, while keeping a long-term vision and without giving in to the call of falsely obvious and short-term choices.

We obtained 1,584,175 AI related publications during 1950-2019 from the Microsoft Academic Graph. Three latitude-and-longitude-based indicators were employed to quantify the geographic distance of collaborations in AI over time at domestic and international levels. The results show team collaborations in AI has been more popular in the field over time with around 42,000 (38.4%) multiple-affiliation AI publications in 2019. The changes in geographic distances of team collaborations indicate the increase of breadth and density for both domestic and international collaborations in AI over time. In addition, the United States produced the largest number of single-country and internationally collaborated AI publications, and China has played an important role in international collaborations in AI after 2010.

The uninitiated to the term Artificial Intelligence refers to developing computer systems that can mimic human behavior. However, it doesn't have to spell …

I don't want to really scare you, but it was alarming how many people I talked to who are highly placed people in AI who have retreats that are sort of'bug out' houses, to which they could flee if it all hits the fan.

Gard's mission is: Together we enable sustainable maritime development. To deliver on this mission, we explore and support the development of emerging technologies including maritime autonomous surface ships. The Nordic countries are leading the way in this area and we are proud to be collaborating with Yara International (Yara) and their newly established company Yara Birkeland AS that is developing the well-known Norwegian autonomous logistics project, YARA BIRKELAND. Construction of the zero-emission autonomous containership has already begun. When the ship enters service in early 2020, she will be operated by onboard crew while the autonomous systems are being tested and certified safe.