European Commission Announces Strategy For Data, Artificial Intelligence And Competition In The Digital Age

Author:Mr Kyriakos Fountoukakos, Veronica Roberts, Peter Rowland and Morris Schonberg
Profession:Herbert Smith Freehills
 
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On 19 February 2020, the European Commission (the "Commission") published three policy papers as part of its strategy to "shape Europe's digital future": a white paper on artificial intelligence (AI) (the "AI White Paper"), a communication on a European strategy for data (the "Data Strategy Communication"), and a communication on shaping Europe's digital future (the "Digital Future Communication").

The proposals and initiatives contained in these papers represent the first major announcement by the new Commission in relation to "a Europe fit for a digital age", one of the six primary ambitions set out in President von der Leyen's political guidelines for 2019-2024. The announcement also represents the Commission's first major regulatory proposal in this area since Margrethe Vestager commenced her dual-role as Executive Vice-President of the Commission responsible for "a Europe fit for a digital age" and Commissioner for Competition. From a competition law perspective, the Data Strategy and Digital Future Communications contain proposals relating to: ex ante regulation of "Big Tech" platforms; potentially updating competition law as it applies to digital markets; how the collection and use of data can be factored into in merger control analyses; and voluntary and (where appropriate) compulsory data sharing. The scope of the papers seems to be ambitious, and it remains to be seen how many of the proposals and ideas will ultimately be taken forward in the short to medium term.

AI White Paper

The AI White Paper sets out the Commission's proposed approach to AI regulation. The focus is on a risk-based approach, imposing mandatory regulatory requirements for "high-risk" applications, i.e. where the AI is deployed in a sector where significant risks can be expected (e.g. healthcare) and where risks are likely to arise given the manner of use of the AI (e.g. health risks). For high risk (and certain other) applications, the AI White Paper proposes requirements in relation to: training data; data and record-keeping; information to be provided; robustness and accuracy; human oversight; and specific requirements for certain particular AI applications, such as those used for purposes of remote biometric identification. For non-high risk AI applications, the AI White Paper proposes a voluntary labelling scheme, through which economic operators that opt-in would be awarded a "quality label" for their AI applications.

The AI White Paper also sets out...

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