Opportunities of Artificial Intelligence
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STUDY Requested by the ITRE committee Opportunities of Artificial Intelligence Policy Department for Economic, Scientific and Quality of Life Policies Directorate-General for Internal Policies Authors: James EAGER, Mark WHITTLE, Jan SMIT, Giorgio CACCIAGUERRA, Eugénie LALE-DEMOZ et al. EN PE 652 713 – June 2020 Opportunities of Artificial Intelligence Abstract This study focuses on presenting the technological, impact and regulatory state of play in the EU, as compared to key competitor countries. This study also highlights industrial areas in which AI will bring significant socioeconomic benefits, before presenting a methodology for scrutinising the fitness of the EU policy and regulatory framework in the context of AI. This document was provided by the Policy Department for Economic, Scientific and Quality of Life Policies at the request of the committee on Industry, Research and Energy (ITRE committee). This document was requested by the European Parliament's committee on Industry, Research and Energy. AUTHORS James EAGER, CSES Mark WHITTLE, CSES Jan SMIT, CSES Giorgio CACCIAGUERRA, CSES Eugénie LALE-DEMOZ, CSES External quality assurance inputs from: Professor João MENDES MOREIRA Dr. Anastasio DROSOU ADMINISTRATORS RESPONSIBLE Frédéric GOUARDÈRES Matteo CIUCCI EDITORIAL ASSISTANT Catherine NAAS LINGUISTIC VERSIONS Original: EN ABOUT THE EDITOR Policy departments provide in-house and external expertise to support EP committees and other parliamentary bodies in shaping legislation and exercising democratic scrutiny over EU internal policies. To contact the Policy Department or to subscribe for updates, please write to: Policy Department for Economic, Scientific and Quality of Life Policies European Parliament L-2929 – Luxembourg Email: [email protected] Manuscript completed: June 2020 Date of publication: June 2020 © European Union, 2020 This document is available on the internet at: http://www.europarl.europa.eu/supporting-analyses DISCLAIMER AND COPYRIGHT The opinions expressed in this document are the sole responsibility of the authors and do not necessarily represent the official position of the European Parliament. Reproduction and translation for non-commercial purposes are authorised, provided the source is acknowledged and the European Parliament is given prior notice and sent a copy. For citation purposes, the study should be referenced as: Eager, J, Opportunities of Artificial Intelligence, Study for the committee on Industry, Research and Energy, Policy Department for Economic, Scientific and Quality of Life Policies, European Parliament, Luxembourg, 2020. © Cover image used under licence from Adobe Stock Opportunities of Artificial Intelligence CONTENTS LIST OF ABBREVIATIONS 5 LIST OF BOXES 8 LIST OF TABLES 8 EXECUTIVE SUMMARY 9 1. INTRODUCTION 12 1.1. Study context and objectives 12 1.2. Scope of the study 13 1.3. Methodological approach 13 2. ARTIFICIAL INTELLIGENCE IN INDUSTRY: STATE OF PLAY IN THE EU 15 2.1. Understanding Artificial Intelligence 15 2.2. Industrial applications of Artificial Intelligence 17 2.2.1. Taxonomy of industrial AI applications 18 2.2.2. Key sectors implementing AI 19 2.2.3. Scale of adoption 21 2.2.4. Challenges and barriers to wider adoption 26 2.2.5. Global position of the EU in AI 27 2.3. Impact of Artificial Intelligence on Industry 35 2.3.1. Opportunities and positive impacts 35 2.3.2. Challenges and negative impacts 45 3. REGULATING ARTIFICIAL INTELLIGENCE: STATE OF PLAY AND EUROPEAN PARLIAMENT APPROACH TO SCRUTINY 48 3.1. Regulating Artificial Intelligence – current state of play 48 3.1.1. Initiatives from industry, civil society and standards bodies 49 3.1.2. EU regulatory approach to AI 51 3.1.3. Third country approaches to regulating AI 63 3.2. Assessing EU rules on Artificial Intelligence 67 3.2.1. Existing methods to assess EU rules 67 3.2.2. Proposed approach to assessing EU rules on Artificial Intelligence 71 4. CONCLUSIONS AND RECOMMENDATIONS 75 4.1. AI technology: state of play 75 4.2. AI opportunities and challenges: State of play 76 4.3. AI policy and regulatory approaches: State of play 77 4.4. Scrutinising EU policy and regulation in the context of AI 80 3 PE 652.713 IPOL | Policy Department for Economic, Scientific and Quality of Life Policies 4.5. Policy recommendations 80 4.5.1. Recommendations on fostering the use of AI in industry 80 4.5.2. Recommendations for the ITRE Committee regarding scrutiny of EU legislation in the context of AI 83 REFERENCES 85 ANNEX 1: LIST OF ORGANISATIONS INTERVIEW 93 ANNEX 2: TIMELINE OF EU POLICY DEVELOPMENTS 94 PE 652.713 4 Opportunities of Artificial Intelligence LIST OF ABBREVIATIONS AI Artificial Intelligence AI HLEG High-Level Expert Group on Artificial Intelligence AI-SAFE Automated Intelligent System for Assuring Safe Working Environments AR Augmented Reality B2B Business-to-Business B2C Business-to-Consumer BAU Business as Usual CAGR Compound Annual Growth Rate CCPA California Consumer Privacy Act CEN European Committee for Standardisation CENELEC European Committee for Electrotechnical Standardisation Joint Undertaking on Electronic Components and Systems for European ECSEL JU Leadership EESC European Economic and Social Committee EMPL European Parliament Committee on Employment and Social Affairs ENI Experiential Networked Intelligence ESO European Standards Organisations ETSI European Telecommunications Standards Institute EU-OSHA EU Agency for Safety and Health at Work FP7 7th Framework Programme GDP Gross Domestic Product GDPR EU General Data Protection Regulation GVC Global Value Chains 5 PE 652.713 IPOL | Policy Department for Economic, Scientific and Quality of Life Policies HMI Human Machine Interface HR Human Resources ICT Information and Communications Technology IEEE Institute of Electrical and Electronics Engineers IES Intelligent Energy Storage IoT Internet of Things ISG Industry Specification Groups ISO International Organisation for Standardisation IT Information Technology ITI Information Technology Industry Council KET Key Enabling Technologies ML Machine Learning NGO Non-Governmental Organisation NLP Natural Language Processing OCD Obsessive-compulsive disorder OEE Overall Equipment Effectiveness OT Operational Technology P&L Profit and Loss PPE Personal Protective Equipment PPP Public-Private Partnership RoI Return on Investment SAI Securing Artificial Intelligence SDG UN Sustainable Development Goals SIIA Software and Information Industry Association PE 652.713 6 Opportunities of Artificial Intelligence TB Terabyte TRAN Committee on Transport and Tourism R&D Research and Development VR Virtual Reality ZSM Zero touch network and Service Management 7 PE 652.713 IPOL | Policy Department for Economic, Scientific and Quality of Life Policies LIST OF BOXES Box 1: Key concepts 16 Box 2: Case study: Real-life AI application in the chemicals sector 36 Box 3: Forecasted scale of the efficiency benefits to be delivered by smart factories 37 Box 4: Case study: Real-life AI application for workplace safety 40 Box 5: Case study: Real-life applications of AI in the healthcare sector 42 Box 6: Key concepts: Art 22. Of the GDPR 46 Box 7: Summary of EU policy initiatives on Artificial Intelligence 54 Box 8: EU level policy developments on ethics and AI 56 Box 9: EU investment in AI: Smart specialisation partnership in AI and HMI 58 Box 10: White Paper on Artificial Intelligence: Definition of high-risk AI applications 60 Box 11: OECD Activities on AI 66 Box 12: Objectives and key mechanisms of the EU’s Better Regulation agenda 68 Box 13: Checklist: Scrutinising possible new EU legislation on AI 72 Box 14: Case study: Assessment of AI impacts in the context of the Machinery Directive (2006/42/EC) 73 Box 15: EU Recovery Package and its relevance to AI 79 LIST OF TABLES Table 1: Examples of AI processes 17 Table 2: Company Uses Cases of AI application 20 Table 3: AI projects funded by Horizon 2020 21 Table 4: Proportion of respondents by industry stating to have used a given AI Technology 24 Table 5: Barriers to AI implementation 26 Table 6: Talent Distribution between the US, EU and China in 2017 28 Table 7: AI papers in US, EU and China in 2017 29 Table 8: Key indicators and investments in US, EU and China's AI ecosystems 29 Table 9: Firms and AI in the US, EU and China (2018) 30 Table 10: Big data levels in US, EU and China in 2018 31 Table 11: Key EU industrial product legislation and AI 62 PE 652.713 8 Opportunities of Artificial Intelligence EXECUTIVE SUMMARY This study on ‘Opportunities of Artificial Intelligence’ aims to assess the state of play of Artificial Intelligence (AI) adoption in European industry from a technological, impact and regulatory perspective, before presenting a methodology to scrutinise the EU policy and regulatory framework in the context of AI. AI technology and impacts: State of play A vast range of AI applications are being implemented by European industry, which can be broadly grouped into two categories: i) applications that enhance the performance and efficiency of processes through mechanisms such as intelligent monitoring, optimisation and control; and ii) applications that enhance human-machine collaboration. At present, such applications are being implemented across a broad range of European industrial sectors. However, some sectors (e.g. automotive, telecommunications, healthcare) are more advanced in AI deployment than others (e.g. paper and pulp, pumps, chemicals). The types of AI applications implemented also differ across industries. In less digitally