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Dsti/Cdep(2017)2/Chap7 For Official Use DSTI/CDEP(2017)2/CHAP7 Organisation de Coopération et de Développement Économiques Organisation for Economic Co-operation and Development 28-Apr-2017 ___________________________________________________________________________________________ _____________ English - Or. English DIRECTORATE FOR SCIENCE, TECHNOLOGY AND INNOVATION COMMITTEE ON DIGITAL ECONOMY POLICY For Official Use Official For DSTI/CDEP(2017)2/CHAP7 Digital Economy Outlook CHAPTER 7: TECHNOLOGY OUTLOOK 17-19 May 2017 Attached is chapter 7 of the Digital Economy Outlook 2017. CDEP delegates are invited to discuss the chapter and provide comments by 31 May. The chapter will be declassified by written procedure. Karine Perset: E-mail: [email protected]; Mr. David Gierten: E-mail: [email protected] Mr. Laurent Bernat : E-mail : [email protected] English JT03413378 Complete document available on OLIS in its original format - This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the Or. English delimitation of international frontiers and boundaries and to the name of any territory, city or area. DSTI/CDEP(2017)2/CHAP7 TABLE OF CONTENTS 7. TECHNOLOGY OUTLOOK ..................................................................................................................... 3 Introduction .................................................................................................................................................. 3 7.1. Artificial Intelligence ............................................................................................................................ 3 Artificial Intelligence (AI) is going mainstream, driven by recent strides in machine learning .............. 4 AI promises to improve efficiency, productivity, and to help address complex challenges .................... 7 The rise of AI amplifies existing policy challenges and raises new challenges ..................................... 10 7.2. Blockchain .......................................................................................................................................... 14 Blockchain technology is a source of “trustless trust” ........................................................................... 14 Blockchain applications provide many new opportunities ..................................................................... 18 Disintermediated blockchain applications raise policy issues ................................................................ 22 NOTES .......................................................................................................................................................... 24 REFERENCES .............................................................................................................................................. 25 Figures Figure 1. Confirmed Bitcoin Transactions Per Day .............................................................................. 15 Boxes Box 1. ‘Supervised’ and 'unsupervised’ machine learning algorithms ........................................................ 5 Box 2. Expert discussions on AI networking in Japan .............................................................................. 10 Box 3. What decentralised applications exist today? ................................................................................. 21 2 DSTI/CDEP(2017)2/CHAP7 7. TECHNOLOGY OUTLOOK Introduction 1. Reflecting on the past 30 or 40 years of ICT innovation, each decade has seen a new form of technological revolution: "personal computers" in the 1980s, the Internet in the 1990s, mobile computing and smartphones in the 2000s and the Internet of Things (IoT) in the current decade. Basic computing and networking technologies continue to improve over time through, for example, continued miniaturisation of devices, increased processing power and storage capacity at declining cost, and availability of higher speed on fixed and wireless networks. 2. However, future potential economic and social benefits increasingly depend on more recent technologies that, in turn, rely on these existing and more mature fundamental building blocks, including cloud computing, big data analytics, artificial intelligence, and blockchain. This set of technologies form an ecosystem in which each technology both exploits and fosters the development of the others. Cloud computing is based on always-on everywhere-available and high-speed Internet connectivity and is essential to big data analytics, which relies on cheap and massive processing power and storage capacity. Big data also critically depends on sophisticated algorithms that, in turn, form the basis of Artificial Intelligence (AI). To comprehend their - virtual or physical - environment and make appropriate decisions, machines such as robots and drones rely on artificial intelligence that often uses big data to identify patterns. The characteristics of each of these technologies create a specific set of opportunities and challenges and, as such, can be considered separately. However, it is increasingly necessary to also analyse them within the broader context of the digital ecosystem without which they could not thrive, and to which they contribute. 3. This chapter explores the characteristics, opportunities of and challenges raised by two of the currently most promising technological developments: machines performing human-like cognitive functions, also known as artificial intelligence, and blockchain, a fundamentally decentralised and distributed ledger technology that facilitates economic transactions and peer-to-peer interactions without the need for any trusted authority or intermediary operator. 7.1. Artificial Intelligence 4. This section first describes the distinctive characteristics of Artificial Intelligence (AI) and how over the past few years AI has become main stream, rapidly permeating and transforming our economies and societies. Compared to other technological developments, many are surprised by the speed of AI's diffusion, but views vary widely on both the likelihood and time horizon of developments such as Artificial General Intelligence (AGI) or technology singularity. 5. The potential benefits and opportunities offered by AI are introduced in the following section, along with examples of applications in various areas. AI promises to generate productivity gains, to improve the efficiency of decision-making and save costs, since it allows data processing at enormous scales and accelerates the discovery of patterns. By helping scientists to spot complex cause and effect relationships, AI is expected to contribute to solving complex global challenges such as those related to the environment, transportation or health. AI could radically enhance quality of life, impacting healthcare, 3 DSTI/CDEP(2017)2/CHAP7 transportation, education, security, justice, agriculture, retail commerce, finance, insurance and banking, among others. 6. Finally, the last section introduces some of the main policy challenges that AI raises; both amplifying existing policy challenges and raising new challenges. AI is expected to replace and/or augment human labour in both skilled and unskilled routine jobs, requiring policies to facilitate professional transitions and to help workers develop the skills to benefit from, and to complement, AI. AI is also expected to increase income inequality and power concentration in winner-takes-most markets. Another issue is that of ensuring transparency and oversight of AI-powered decisions that impact people and of preventing algorithmic biases and discrimination and privacy abuses. AI also raises new liability, responsibility, security and safety questions. Artificial Intelligence (AI) is going mainstream, driven by recent strides in machine learning Artificial Intelligence is about machines performing human-like cognitive functions 7. There is no universally-accepted definition of AI. AI-pioneer Marvin Minsky defined AI as "the science of making machines do things that would require intelligence if done by men". The present report uses the definition provided by Nils J. Nilsson (2010): "Artificial intelligence is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment". Machines understanding human speech, competing in strategic game systems, driving cars autonomously or interpreting complex data are currently considered to be AI applications. Intelligence in that sense intersects with autonomy and adaptability through AI's ability to learn from a dynamic environment. 8. It is important to note that the boundaries of 'AI' are not always clear and evolve over time. For example, in some cases techniques developed by AI researchers to analyse large volumes of data are identified as “Big Data” algorithms and systems (White House, 2016). Optical character recognition, for example, has become a routine technology and is no longer considered to be AI. A core objective of AI research and applications over the years has been to automate or replicate intelligent behavior. Machine learning, big data and cloud computing have enabled AI’s recently accelerated progress 9. Despite fluctuations in public awareness, AI has been making steady progress since its inception in the 1950s. AI's principle was conceptualised by John McCarthy, Alan Newell, Arthur Samuel, Herbert Simon and Marvin Minsky in the Dartmouth Summer Research
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