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Comparison of National Strategies to Promote Artificial Intelligence Comparison of National Strategies to Promote Artificial Intelligence Part 2 www.kas.de Imprint Editor: Konrad-Adenauer-Stiftung e. V. 2019, Berlin Authors: Dr. Olaf J. Groth, CEO & Managing Partner Dr. Mark Nitzberg, Principal & Chief Scientist Dan Zehr, Editor-in-Chief Tobias Straube, Project Manager and Senior-Analyst Toni Kaatz-Dubberke, Senior-Analyst Franziska Frische, Analyst Maximilien Meilleur, Analyst Suhail Shersad, Analyst Cambrian LLC, 2381 Eunice Street, Berkeley CA 94708-1644, United States https://cambrian.ai, Twitter: @AICambrian Editorial team and contact at the Konrad-Adenauer-Stiftung e. V. Sebastian Weise Consultant for Global Innovation Policy Post: 10907 Berlin Office: Klingelhöferstraße 23 T +49 30 / 269 96-3516 10785 Berlin F +49 30 / 269 96-3551 [Note: This English-language version was translated from the original publication in German.] Cover image: © sarah5/Mlenny (istockphoto by Getty Images) Images: © p. 11: Matthew Henry, p.16: Manuel Cosentino, p. 23: Dan Gold, p. 30: David Rodrigo, p. 42: Victor Garcia (unsplash); p. 36: byheaven (istockphoto by Getty Images) Design and typesetting: yellow too Pasiek Horntrich GbR The print edition was produced in a carbon-neutral way at Druckerei Kern GmbH, Bexbach, and printed on FSC-certified paper. Printed in Germany. Printed with the financial support of the Federal Republic of Germany. This publication is licenced under the terms of “Creative Commons Attribution-Share Alike 4.0 International”, CC BY-SA 4.0 (available at: https://creativecommons.org/licenses/ by-sa/4.0/) legalcode.de). ISBN 978-3-95721-553-6 Comparison of National Strategies to Promote Artificial Intelligence Part 2 Dr. Olaf J. Groth, CEO & Managing Partner Dr. Mark Nitzberg, Principal & Chief Scientist Dan Zehr, Editor-in-Chief Tobias Straube, Project Manager and Senior-Analyst Toni Kaatz-Dubberke, Senior-Analyst Franziska Frische, Analyst Maximilien Meilleur, Analyst Suhail Shersad, Analyst Table of Contents Preface 4 Background and Definitions 5 Summary 6 Cambrian AI Index © 10 Cambrian AI Index © of countries from part 2 of the study 10 Cambrian AI Index © of countries from part 1 and 2 of the study 10 Canada 11 I.) Introduction 11 II.) Requirements for AI 11 III.) Institutional framework 12 IV.) Research and Development 12 V.) Commercialisation 13 Japan 16 I.) Introduction 16 II.) Requirements for AI 17 III.) Institutional framework 17 IV.) Research and Development 18 V.) Commercialisation 20 Israel 23 I.) Introduction 23 II.) Requirements for AI 24 III.) Institutional framework 24 IV.) Research and Development 24 V.) Commercialisation 25 United Arab Emirates 30 I.) Introduction 30 II.) Requirements for AI 31 III.) Institutional framework 31 IV.) Research and Development 31 V.) Commercialisation 32 India 36 I.) Introduction 36 II.) Requirements for AI 36 III.) Institutional framework 37 IV.) Research and Development 37 V.) Commercialisation 39 Singapore 42 I.) Introduction 42 II.) Requirements for AI 43 III.) Institutional framework 43 IV.) Research and Development 43 V.) Commercialisation 44 Methodology of the Cambrian AI Index © 49 Annexes 58 Annex 1: Overview of resources and research areas of AIST, RIKEN and NICT (Japan) 58 Annex 2: Overview of the research areas of the Fundamental Research Programme of the AI Singapore Initiative 60 Bibliography 61 Acknowledgements 77 The Authors 78 Preface Technologies can rarely be reduced to their mere commercial added value. The history of the Industrial Revolution teaches us that nation states have always endeavored to build or maintain political supremacy through pioneering economic achievements. In the age of digital upheavals, multiple disruptions and immense acceleration, this dictum still applies. The topic of “artificial intelligence” plays a special role here – a technology that is currently being discussed worldwide and increasingly applied. As with any new tech- nology, both the Cassandrian pessimists (such as Steven Hawking or Elon Musk) and the progress optimists (Mark Zuckerberg, Eric Schmidt or Bill Gates) contribute their theses on the future development of humanity. They widely vary from dark dystopia to paradisiacal future prospects. Let us hope that the recently appointed Enquete Commission of the German Bundes- tag will counter an agitated and possibly overheated debate with sober stocktaking. Germany’s AI strategy, which is expected by the end of the year, must define quanti- fiable goals and concrete measures, which will then be vigorously implemented. The political crash barriers necessary for the use of automated machine learning need to be established. Other countries are well ahead in this respect. They have long since defined AI strate- gies, developed business models and subjected ground-breaking applications to initial practical tests. Therefore, it is worth taking a close look at how other economies are dealing with the digital revolution: What regulatory framework conditions have they defined? How do they implement policy strategies and programs to create new indus- trial policy facts? With this two-part publication, the Konrad Adenauer Foundation intends to give a com- parative overview of the AI strategies of major national economies in order to provide food for thought and inspire the German debate. We believe: “Tech is politics” – and pol- itics and civil society should give this more attention and discuss this more vigorously. I hope you find this publication an inspiring read. Yours Dr. Gerhard Wahlers Dr. Gerhard Wahlers is Deputy Secretary General and Head of the Principal Department for European and International Cooperation of the Konrad-Adenauer-Stiftung. 4 Background and Definitions Artificial intelligence: This overview, however, focuses on the analysis of rapid developments and designs of the AI framework conceptss in six countries and how initial conceptual AI frameworks. they deal with the revolutionary potential of Artifi- cial Intelligence. In July 2018, the German federal government published a key issues paper on the German The following definition is used as a basis strategy with regard to artificial intelligence (AI) for the terminology: and there they acknowledge: “Artificial intelli- “In the broadest sense, artificial intelli- gence has reached a new stage of maturity in gence is the ability of machines to learn, recent years and is becoming a driver of digitiza- to think, to plan and to perceive; i. e. the tion and autonomous systems in all spheres of primary qualities that we identify with 1 life.” Therefore, the state, society, the economy, human cognition. This ability is achieved the government, and science are urged to con- by digital technologies or digital-phys- sider artificial intelligence in depth and to deal ical hybrid technologies, which imitate with its chances and risks. the cognitive and physical functions of humans. For that purpose, AI systems A comprehensive German AI strategy was pre- do not only process data, they recognize sented at the Digital Summit in December 2018. patterns, draw conclusions, and become The aim is to prominently embed the topic of AI more intelligent over time. Their ability to in the digital policy of the federal government. adopt and refine newly developed skills In this way, Germany is catching up with a large has improved significantly since the turn number of countries which in recent years have of the century. This also means that what seen extensive initiatives for AI strategy finding is referred to as AI changes with each 2 processes. major technological breakthrough, and the definition must therefore be periodi- These strategies are motivated by partly spec- cally adjusted.” tacular progress in research and application of AI systems, based on techniques of Machine Learning (ML) as well as its subdiscipline of Deep 1 Cf. German Federal Government, Key Points of the Federal Learning (DL) and its large varieties of neuronal Government for an Artificial Intelligence Strategy(July 2018), https://www.bmbf.de/files/180718%20 Eckpunkte_ networks. KI-Strategie%20final%20Layout.pdf. 2 To this end, see the OECD overviews, for example, The global relevance of AI technologies is dem- http://www.oecd.org/going-digital/ai/initiatives-worldwide/, onstrated by their prominent representation on Future of Life Institute, https://futureoflife.org/ai-policy/, the Smart Data Forum, https://smartdataforum.de/ en/ this year’s international agenda – from the Munich services/international-networking/international-ai- Security Conference in February, to the presenta- strategies/, Charlotte Stix, https://www.charlottestix.com/ tion of the EU Commission’s3 AI paper in April, to ai-policy-resources, und Tim Dutton, https://medium. the joint AI declaration of the G7 states in Canada com/politics-ai/an-overview-of-national-ai-strategies- 2a70ec6edfd, all last retrieved on 17.9.2018. in June (“Charlevoix Common Vision for the Future 3 Cf. European Commission, Artificial Intelligence for 4 of Artificial Intelligence”). Europe (April 2018), http://ec.europa.eu/newsroom/dae/ document.cfm?doc_id=51625. The role of Artificial Intelligence as a potential key 4 See Canadian G7 Presidency, Charlevoix Common Vision for the Future of Artificial Intelligence (June technology of dystopian future concepts, social 2018), https://g7.gc.ca/wp-content/uploads/2018/06/ control, and autocratic world power fantasies is FutureArtificialIntelligence.pdf. also increasingly finding its way into public debate. 5 Summary The following summary describes the insights and assessments of the
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