WIPO Technology Trends 2019 Artificial Intelligence WIPO Technology Trends 2019 Artificial Intelligence The user is allowed to reproduce, distribute, adapt, translate and publicly perform this publication, including for commer- cial purposes, without explicit permission, provided that the content is accompanied by an acknowledgement that WIPO is the source and that it is clearly indicated if changes were made to the original content. Suggested citation: WIPO (2019). WIPO Technology Trends 2019: Artificial Intelligence. Geneva: World Intellectual Property Organization. Adaptation/translation/derivatives should not carry any official emblem or logo, unless they have been approved and validated by WIPO. Please contact us via the WIPO website to obtain permission. 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First published 2019 The mention of specific companies or products of manu- facturers does not imply that they are endorsed or recom- World Intellectual Property Organization mended by WIPO in preference to others of a similar nature 34, chemin des Colombettes, P.O. Box 18 that are not mentioned. CH-1211 Geneva 20, Switzerland Photo credit: cover montage created with images by ISBN: 978-92-805-3007-0 © Margarita Lyr / iStock / Getty Images Plus and © Daria Dombrovskaya / iStock / Getty Images Plus Attribution 3.0 IGO Printed in Switzerland (CC BY 3.0 IGO) Artificial intelligence is a new digital frontier that will have a profound impact on the world, transforming the way we live and work. WIPO Director General, Francis Gurry Preface 1 Introduction 3 Evolution 7 of AI patent The past, present and future of AI: what research and applications innovation trends can reveal; the data used in this report and and how it is analyzed; and a scheme for categorizing scientific Foreword AI technologies. publications 8 18 The historical development of AI innovation: analysis of trends in patents and scientific literature since 2 the emergence of AI, and About the Trends breakdown by techniques, functional applications and contributors in artificial application fields. 10 intelligence 38 Overall trends emerging from the data and analysis of changes over time, by region and industry and the most 4 Acknowl- prominent entities. Key edgments 30 players in 12 AI patenting The top applicants for AI patents: how companies and universities/public research organizations compare, which Executive entities are most active in each area and where they summary are filing. 13 58 5 Geography 7 Key issues Selected AI of patent arising from categories filings AI and policy and terms responses 146 Comprehensive analysis of geographical trends, based on the offices where patents are Views from AI experts filed, including both first and on the key policy and subsequent filings. regulatory issues raised by AI applications, plus examples of 82 policies proposed or enacted Further in various jurisdictions. reading 120 150 6 Market trends 8 The future related to AI of AI and the Analysis of the use of AI IP system technologies: data on acquisitions, funding, open source and patent litigation The opportunities presented and oppositions. by AI for business, society and culture, and how AI and IP 104 rights interact with each other in the promotion of innovation. 138 WIPO Technology Trends 2019 5 This new report aims to shed light on the trends in innovation in AI since the field first developed in the 1950s. WIPO Director General, Francis Gurry Preface I am pleased to present the first report in a new put into practice). One of the most striking flagship series, WIPO Technology Trends. This findings of the report is that 50 percent of all AI first edition features artificial intelligence (AI) as patents have been published in just the last five the theme. It is a fitting topic for the launch of years – a remarkable illustration of how rapidly the series as AI is a cutting-edge technology innovation is advancing in this field. with impacts on a wide range of businesses and activities. This report identifies the key players in AI from both the corporate and public AI is fast becoming part of our everyday lives, sectors across different research areas and changing how we work, shop, travel and industries. Furthermore, the analysis of the interact with each other. Yet we are only at data and the inputs from AI experts address the beginning of discovering the many ways many of the policy issues raised by AI, such in which AI will have an impact on – and as the regulation and control of data, the indeed challenge – business, society and incentivization of further research, the role of culture. There are numerous misconceptions intellectual property (IP) protection and the and misgivings about the nature of AI, and in development of human-centered and ethical AI particular the challenge it poses to humankind. to benefit all. Given these widely held reservations and concerns, it is essential to have a factual basis Together, the analysis of technological trends for policy discussions about innovation in AI. presented in this report and the voices of AI Through this report, we hope to contribute experts collected here are a valuable new evidence and bring clarity to this important addition to a growing knowledge base on AI. area of debate. I hope that this contribution will help to shift Based on a detailed study of patents and other debate away from speculative interpretation information, this new report aims to shed light and toward evidence-based projections, on the trends in innovation in AI since the field thereby informing global policymaking on first developed in the 1950s. Research has the future of AI, its governance and the IP involved the analysis of patent data related framework that supports it. to AI inventions, as well as data on scientific publications, litigation filings and acquisition activity. These data findings are discussed in detail and accompanied by commentary and industry perspectives from more than 20 of the world’s leading experts in AI; more complete Francis GURRY datasets, patent search methodology and Director General expert contributions are openly available on the WIPO website. We hope that this report will prove an invaluable resource for businesses, researchers and policymakers in the field, as well as for those general readers who want to find out how AI research has so far developed – and where it is going. The analysis offers unique insights into trends in AI techniques (i.e., the different approaches used in AI, such as machine learning and fuzzy logic), AI functional applications (such as natural language processing, speech processing and computer vision) and AI application fields (i.e., those industries and other sectors in which AI innovation is being WIPO Technology Trends 2019 7 Foreword Andrew Ng CEO, Landing AI and deeplearning.ai neural network, the better the neural network performed. We started looking for the biggest computers we could find. That discovery, and the idea of using distributed computing to scale up neural networks, led to the creation of Google Brain in 2011. Since then, deep learning has made great progress as we’ve collected more data and created the powerful computers to make it work. But we still have a long way to go in the field. For example, a toddler can usually recognize a cat after just one encounter, but a computer still needs more than one example to learn. We need to find ways to train computers on training datasets as small as 100, or even I remember watching the final chess match 10. Manufacturing lines, for example, use between Deep Blue and Gary Kasparov while computer vision to check for defects in parts I was a graduate student at MIT in the 1990s. but hopefully they will never have a million When Kasparov resigned, I jumped out of examples of defects to train on. Effective my chair in excitement – the AI community “unsupervised learning” – learning without had finally triumphed over the human labelled data – remains a holy grail of AI. chess champion! Even without this “holy grail,” AI is already This moment stands out for me, among creating massive economic value in the world many milestones in the development of AI, today. In covering AI, the media tends to focus such as the rise of deep learning, lessons in on images, speech and natural language scalability and the DARPA Grand Challenge. processing because those types of data AI is automation on steroids, and we had are very human. Everyone can understand “automated” the process of playing chess. I what it means for a computer to identify a was once captain of my high school chess cat or recognize your speech. But a lot of the team and used to play competitively, but at economic value today is driven through deep that moment I was happy to retire and leave it learning on “structured data.” Think of this as to the computers. This was not a sad event for machine learning applied to massive Excel me; on the contrary, I was thrilled to give up spreadsheets (only bigger than the biggest chess this way.