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EN EN EU R O PEAN C O M M I SSIO N B russe ls, 19 .2.2020 C OM( 2020) 65 fina l WHI T E P A P E R On Ar tif icial I n te ll igenc e - A Eu r op e an ap p r oac h to e xc e ll e n c e an d tr u st 1 White Paper on Artificial Intelligence A European approach to excellence and trust Artificial Intelligence is developing fast. It will change our lives by improving healthcare (e.g. making diagnosis more precise, enabling better prevention of diseases), increasing the efficiency of farming, contributing to climate change mitigation and adaptation, improving the efficiency of production systems through predictive maintenance, increasing the security of Europeans, and in many other ways that we can only begin to imagine. At the same time, Artificial Intelligence (AI) entails a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in our private lives or being used for criminal purposes. Against a background of fierce global competition, a solid European approach is needed, building on the European strategy for AI presented in April 20181. To address the opportunities and challenges of AI, the EU must act as one and define its own way, based on European values, to promote the development and deployment of AI. The Commission is committed to enabling scientific breakthrough, to preserving the EUs technological leadership and to ensuring that new technologies are at the service of all Europeans improving their lives while respecting their rights. Commission President Ursula von der Leyen announced in her political Guidelines2 a coordinated European approach on the human and ethical implications of AI as well as a reflection on the better use of big data for innovation. Thus, the Commission supports a regulatory and investment oriented approach with the twin objective of promoting the uptake of AI and of addressing the risks associated with certain uses of this new technology. The purpose of this White Paper is to set out policy options on how to achieve these objectives. It does not address +the development and use of AI for military purposes.The Commission invites Member States, other European institutions, and all stakeholders, including industry, social partners, civil society organisations, researchers, the public in general and any interested party, to react to the options below and to contribute to the Commissions future decision-making in this domain. 1. INTRODUCTION As digital technology becomes an ever more central part of every aspect of peoples lives, people should be able to trust it. Trustworthiness is also a prerequisite for its uptake. This is a chance for Europe, given its strong attachment to values and the rule of law as well as its proven capacity to build safe, reliable and sophisticated products and services from aeronautics to energy, automotive and medical equipment. Europes current and future sustainable economic growth and societal wellbeing increasingly draws on value created by data. AI is one of the most important applications of the data economy. Today most data are related to consumers and are stored and processed on central cloud-based infrastructure. By contrast a large share of tomorrows far more abundant data will come from industry, business and the public sector, and will be stored on a variety of systems, notably on computing devices working at the edge of the network. This opens up new opportunities for Europe, which has a strong position in 1 AI for Europe, COM/2018/237 final 2 ec.europa.eu/commission/sites/beta-political/files/political-guidelines-next-commission_en.pdf. 2 digitised industry and business-to-business applications, but a relatively weak position in consumer platforms. Simply put, AI is a collection of technologies that combine data, algorithms and computing power. Advances in computing and the increasing availability of data are therefore key drivers of the current upsurge of AI. Europe can combine its technological and industrial strengths with a high-quality digital infrastructure and a regulatory framework based on its fundamental values to become a global leader in innovation in the data economy and its applications as set out in the European data strategy3. On that basis, it can develop an AI ecosystem that brings the benefits of the technology to the whole of European society and economy: for citizens to reap new benefits for example improved health care, fewer breakdowns of household machinery, safer and cleaner transport systems, better public services; for business development, for example a new generation of products and services in areas where Europe is particularly strong (machinery, transport, cybersecurity, farming, the green and circular economy, healthcare and high-value added sectors like fashion and tourism); and for services of public interest, for example by reducing the costs of providing services (transport, education, energy and waste management), by improving the sustainability of products4 and by equipping law enforcement authorities with appropriate tools to ensure the security of citizens5, with proper safeguards to respect their rights and freedoms. Given the major impact that AI can have on our society and the need to build trust, it is vital that European AI is grounded in our values and fundamental rights such as human dignity and privacy protection. Furthermore, the impact of AI systems should be considered not only from an individual perspective, but also from the perspective of society as a whole. The use of AI systems can have a significant role in achieving the Sustainable Development Goals, and in supporting the democratic process and social rights. With its recent proposals on the European Green Deal6, Europe is leading the way in tackling climate and environmental-related challenges. Digital technologies such as AI are a critical enabler for attaining the goals of the Green Deal. Given the increasing importance of AI, the environmental impact of AI systems needs to be duly considered throughout their lifecycle and across the entire supply chain, e.g. as regards resource usage for the training of algorithms and the storage of data. A common European approach to AI is necessary to reach sufficient scale and avoid the fragmentation of the single market. The introduction of national initiatives risks to endanger legal certainty, to weaken citizens trust and to prevent the emergence of a dynamic European industry. This White Paper presents policy options to enable a trustworthy and secure development of AI in Europe, in full respect of the values and rights of EU citizens. The main building blocks of this White Paper are: 3 COM(2020) 66 final. 4 AI and digitalisation in general are critical enablers of Europes Green deal ambitions. However, the current environmental footprint of the ICT sector is estimated at more than 2% of all global emissions. The European digital strategy accompanying this White Paper proposes green transformation measures for digital. 5 AI tools can provide an opportunity for better protecting EU citizens from crime and acts of terrorism. Such tools could, for example, help identify online terrorist propaganda, discover suspicious transactions in the sales of dangerous products, identify dangerous hidden objects or illicit substances or products, offer assistance to citizens in emergencies and help guide first responders. 6 COM(2019) 640 final. 3 The policy framework setting out measures to align efforts at European, national and regional level. In partnership between the private and the public sector, the aim of the framework is to mobilise resources to achieve an ecosystem of excellence along the entire value chain, starting in research and innovation, and to create the right incentives to accelerate the adoption of solutions based on AI, including by small and medium-sized enterprises (SMEs). The key elements of a future regulatory framework for AI in Europe that will create a unique ecosystem of trust. To do so, it must ensure compliance with EU rules, including the rules protecting fundamental rights and consumers rights, in particular for AI systems operated in the EU that pose a high risk7. Building an ecosystem of trust is a policy objective in itself, and should give citizens the confidence to take up AI applications and give companies and public organisations the legal certainty to innovate using AI. The Commission strongly supports a human-centric approach based on the Communication on Building Trust in Human-Centric AI8 and will also take into account the input obtained during the piloting phase of the Ethics Guidelines prepared by the High-Level Expert Group on AI. The European strategy for data, which accompanies this White Paper, aims to enable Europe to become the most attractive, secure and dynamic data-agile economy in the world empowering Europe with data to improve decisions and better the lives of all its citizens. The strategy sets out a number of policy measures, including mobilising private and public investments, needed to achieve this goal. Finally, the implications of AI, Internet of Things and other digital technologies for safety and liability legislation are analysed in the Commission Report accompanying this White Paper. 2. CAPITALISING ON STRENGTHS IN INDUSTRIAL AND PROFESSIONAL MARKETS Europe is well placed to benefit from the potential of AI, not only as a user but also as a creator and a producer of this technology. It has excellent research centres, innovative start-ups, a world-leading position in robotics and competitive manufacturing and services sectors, from automotive to healthcare, energy, financial services and agriculture. Europe has developed a strong computing infrastructure (e.g. high-performance computers), essential to the functioning of AI. Europe also holds large volumes of public and industrial data, the potential of which is currently under-used. It has well- recognised industrial strengths in safe and secure digital systems with low-power consumption that are essential for the further development of AI. Harnessing the capacity of the EU to invest in next generation technologies and infrastructures, as well as in digital competences like data literacy, will increase Europes technological sovereignty in key enabling technologies and infrastructures for the data economy. The infrastructures should support the creation of European data pools enabling trustworthy AI, e.g. AI based on European values and rules. Europe should leverage its strengths to expand its position in the ecosystems and along the value chain, from certain hardware manufacturing sectors to software all the way to services. This is already happening to an extent. Europe produces more than a quarter of all industrial and professional service robots (e.g. for precision farming, security, health, logistics.), and plays an important role in developing and using software applications for companies and organisations (business-to-business applications such as Enterprise Resource Planning, design and engineering software) as well as applications to support e-government and the intelligent enterprise. 7 Although further arrangements may need to be put in place to prevent and counter misuse of AI for criminal purposes, this is outside the scope of this white paper. 8 COM(2019) 168. 4 Europe leads the way in deploying AI in manufacturing. Over half of the top manufacturers implement at least one instance of AI in manufacturing operations9. One reason for Europes strong position in terms of research is the EU funding programme that has proven instrumental in pooling action, avoiding duplications, and leveraging public and private investments in the Member States. Over the past three years, EU funding for research and innovation for AI has risen to 1.5 billion, i.e. a 70% increase compared to the previous period. However, investment in research and innovation in Europe is still a fraction of the public and private investment in other regions of the world. Some 3.2 billion were invested in AI in Europe in 2016, compared to around 12.1 billion in North America and 6.5 billion in Asia10. In response, Europe needs to increase its investment levels significantly. The Coordinated plan on AI11 developed with Member States is proving to be a good starting point in building closer cooperation on AI in Europe and in creating synergies to maximise investment in the AI value chain. 3. SEIZING THE OPPORTUNITIES AHEAD: THE NEXT DATA WAVE Although Europe currently is in a weaker position in consumer applications and on online platforms, which results in a competitive disadvantage in data access, major shifts in the value and re-use of data across sectors are underway. The volume of data produced in the world is growing rapidly, from 33 zettabytes in 2018 to an expected 175 zettabytes in 2025 12 . Each new wave of data brings opportunities for Europe to position itself in the data-agile economy and to become a world leader in this area. Furthermore, the way in which data are stored and processed will change dramatically over the coming five years. Today 80% of data processing and analysis that takes place in the cloud occurs in data centres and centralised computing facilities, and 20% in smart connected objects, such as cars, home appliances or manufacturing robots, and in computing facilities close to the user (“edge computing”). By 2025 these proportions are set to change markedly13. Europe is a global leader in low-power electronics which is key for the next generation of specialised processors for AI. This market is currently dominated by non-EU players. This could change with the help of initiatives such as the European Processor Initiative, which focuses on developing low-power computing systems for both edge and next generation high-performance computing, and the work of the Key Digital Technology Joint Undertaking, proposed to start in 2021. Europe also leads in neuromorphic solutions14 that are ideally suited to automating industrial processes (industry 4.0) and transport modes. They can improve energy efficiency by several orders of magnitude. Recent advances in quantum computing will generate exponential increases in processing capacity15. Europe can be at the forefront of this technology thanks to its academic strengths in quantum computing, as well as European industrys strong position in quantum simulators and programming environments for quantum computing. European initiatives that aim to increase the availability of quantum testing and experimentation facilities will help apply these new quantum solutions to a number of industrial and academic sectors. 9 Followed by Japan (30%) and the US (28%). Source: CapGemini (2019). 10 10 imperatives for Europe in the age of AI and automation, McKinsey (2017). 11 COM(2018) 795. 12 IDC (2019). 13 Gartner (2017). 14 Neuromorphic solutions means any very large-scale system of integrated circuits that mimi
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