'European Artificial Intelligence Policy: Mapping the Institutional Landscape' (Data Justice Lab, 2020) by
Jędrzej Niklas and Lina Dencik
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In the last few years, Artificial Intelligence (AI) has gained prominence across consumer, business, scientific and government sectors, often as a ‘buzzword’ propelling new forms of policies and governance. Some countries, such as the United Kingdom, have set up a number of different bodies that form and discuss public policies largely focused on AI and other data-intensive technologies and there have been widespread calls across government and industry power dynamics, taxation and displacement of labour. In that sense AI policy needs to be understood as a horizontal area of policy that stretches across different domains and sectors, with all the challenges that come with that.
A key player in this debate is the European Union (EU) that for the last few years has been trying to create political strategies, financial policies and regulatory regimes that focus on AI and data-driven technologies. In this Working Paper we take stock of some of those efforts, mapping the debate and outlining key institutional arrangements and funding strategies. We see this as a useful exercise for getting to grips with the composition, accountability and power dynamics in the EU policy debate surrounding AI. As such, this is a starting point for further research into policy responses to the transformative aspects of AI as they pertain to social justice concerns.
The Working Paper outlines the positions of relevant actors in the EU policy landscape. For this paper, we focus on the European Commission and other European institutions such as the European Parliament, consultative committees or executive agencies and their efforts to define a common strategy in relation to AI. In order to do this, we bring together the dual aspects of liberal state interventions in technology and innovation that cover both principles of public funding of society, think thanks etc. have developed numerous initiatives that focus on ethical principles and for innovation in regulation.
At the same time different companies, business associations, civil toolkits to address value tensions associated with the deployment of AI.
institutional, legal and industry efforts together constitute what Ryan Calo (2017) refers to as ‘AI policy’: a separate and distinctive area of policymaking that addresses different challenges tied to AI and similar technologies, including justice and equity, safety and certification, privacy and research on the one hand, and regulatory interventions for industry on the other. Across these areas, a myriad of instruments and bureaucratic mechanisms shape the nature of contemporary EU policy debates on AI. We start by outlining some of the historical context, before mapping key features of the main policy documents published by the European Commission pertaining to AI. We then go on to discuss strategies for funding and investment, and outline contributions from so-called 'expert groups‘ and resolutions and debates held by European Parliament and other consultative bodies, before ending with a brief mapping of key policy challenges intersecting with digital policies as documented by the Commission. ...
The EU’s engagement with AI follows historical patterns and on-going geopolitical concerns, such as competition with the US and China. This is clear, for example, with its emphasis on notions of ‘technological sovereignty’ and ‘European values’ that underpin several of its policy proposals. The horizontal nature of AI policy means that it stretches across different sectors (climate change, data policy, international cooperation, policing amongst many others) and engages with broad issues (e.g. regulation, deployment, ethical concerns, liability). At the same time, the EU’s efforts on AI predominantly follow traditional ways of making technological policy and involve two streams of decision-making: investments and support for science and innovations and regulating risks. The first area is organised around widespread funding programmes, financial assistance and grants for research entities and start-ups, and creating networks for cooperation that indicate a significant spending plan on AI and the digital. The second area involves regulation and the creation of standards through not just GDPR, but ethical codes and principles and the proposition of a risk-based approach as set out in the White Paper on AI that the EU sees as central to strengthening its position in the global debate on AI.
Importantly, the resolutions and statements from various bodies and groups highlight that the EU’s engagement with AI is continuously being shaped by different interests and concerns pertaining to such actors. Altogether those institutional dynamics, legislative initiatives, statements, flows of money and international policies create a specific space for a discussion about rights and democratic decision-making that focus on data-driven technology. In mapping this complex landscape, this working paper provides an outline of the composition of contemporary AI policy within the European Union that will inform further analysis as we progress with our projec
