We are only at the beginning of a rapid period of transformation of our economy and society due to the convergence of many digital technologies. Artificial Intelligence (AI) is central to this change and offers major opportunities to improve our lives. The recent developments in AI are the result of increased processing power, improvements in algorithms and the exponential growth in the volume and variety of digital data. Many applications of AI have started entering into every-day lives, from machine translations, to image recognition, and music generation, and are increasingly deployed in industry, government, and commerce. Connected and autonomous vehicles, and AI-supported medical diagnostics are areas of application that will soon be commonplace. There is strong global competition on AI among the US, China, and Europe. The US leads for now but China is catching up fast and aims to lead by 2030. For the EU, it is not so much a question of winning or losing a race but of finding the way of embracing the opportunities offered by AI in a way that is human-centred, ethical, secure, and true to our core values. The EU Member States and the European Commission are developing coordinated national and European strategies, recognizing that only together one can succeed. We can build on our areas of strength including excellent research, leadership in some industrial sectors like automotive and robotics, a solid legal and regulatory framework, and very rich cultural diversity also at regional and sub-regional levels. It is generally recognized that AI can flourish only if supported by a robust computing infrastructure and good quality data:
- With respect to computing, the auhtors identified a window of opportunity for Europe to invest in the emerging new paradigm of computing distributed towards the edges of the network, in addition to centralized facilities. This will support also the future deployment of 5G and the Internet of Things.
- With respect to data, they argue in favor of learning from successful Internet companies, opening access to data and developing interactivity with the users rather than just broadcasting data.
In this way, an ecosystems of public administrations, firms, and civil society can be developed enriching the data to make it fit for AI applications responding to European needs. One should embrace the opportunities afforded by AI but not uncritically. The black box characteristics of most leading AI techniques make them opaque even to specialists. AI systems are currently limited to narrow and well-defined tasks, and their technologies inherit imperfections from their human creators, such as the well-recognized bias effect present in data. One should challenge the shortcomings of AI and work towards strong evaluation strategies, transparent and reliable systems, and good human-AI interactions. Ethical and secure-by-design algorithms are crucial to build trust in this disruptive technology, but a broader engagement of civil society on the values to be embedded in AI and the directions for future development is also needed. This social engagement should be part of the effort to strengthen resilience at all levels from local, to national and European, across institutions, industry and civil society. Developing local ecosystems of skills, computing, data, and applications can foster the engagement of local communities, respond to their needs, harness local creativity and knowledge, and build a human-centred, diverse, and socially driven AI. There is still very little knowledge about how AI will impact the way we think, make decisions, relate to each other, and how it will affect jobs. This uncertainty can be a source of concern but is also a sign of opportunity. The future is not yet written. It can be shaped based on the collective vision of what kind of future would be desriable.
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