A European approach on Artificial Intelligence

The European Commission puts forward a European approach to artificial intelligence and robotics. It deals with technological, ethical, legal and socio-economic aspects to boost EU’s research and industrial capacity and to put AI at the service of European citizens and economy.

Artificial intelligence (AI) has become an area of strategic importance and a key driver of economic development. It can bring solutions to many societal challenges from treating diseases to minimising the environmental impact of farming. However, socio-economic, legal and ethical impacts have to be carefully addressed.

It is essential to join forces in the European Union to stay at the forefront of this technological revolution, to ensure competitiveness and to shape the conditions for its development and use (ensuring respect of European values).

A European approach to Artificial Intelligence

In its communication, the European Commission puts forward a European approach to Artificial Intelligence based on three pillars:

Being ahead of technological developments and encouraging uptake by the public and private sectors

The Commission is increasing its annual investments in AI by 70% under the research and innovation programme Horizon 2020. It will reach EUR 1.5 billion for the period 2018-2020. It will:

connect and strengthen AI research centres across Europe;
support the development of an “AI-on-demand platform” that will provide access to relevant AI resources in the EU for all users;
support the development of AI applications in key sectors.

However, this represents only a small part of all the investments from the Member States and the private sector. This is the glue linking the individual efforts, to make together a solid investment, with an expected impact much greater than the sum of its parts.

Given the strategic importance of the topic and the support shown by the European countries signing the declaration of cooperation at the digital day, we can hope that Member States and the private sector will make similar efforts.

Joining forces at European level, the goal is to reach all together, more than EUR 20 billion per year over the next decade.

Prepare for socio-economic changes brought about by AI

To support the efforts of the Member States which are responsible for labour and education policies, the Commission will:

support business-education partnerships to attract and keep more AI talent in Europe;
set up dedicated training and retraining schemes for professionals;
foresee changes in the labour market and skills mismatch;
support digital skills and competences in science, technology, engineering, mathematics (STEM), entrepreneurship and creativity;
encourage Members States to modernise their education and training systems.

Ensure an appropriate ethical and legal framework

Some AI applications may raise new ethical and legal questions, related to liability or fairness of decision-making. The General Data Protection Regulation (GDPR) is a major step for building trust and the Commission wants to move a step forward on ensuring legal clarity in AI-based applications. In 2019 the Commission will develop and make available:

AI ethics guidelines;
Guidance on the interpretation of the Product Liability directive.

You can also consult the Staff Working Document for emerging digital technologies.

Declaration of cooperation on Artificial Intelligence

On 10 April 2018, 25 European countries signed a Declaration of cooperation on Artificial Intelligence. It builds further on the achievements and investments of the European research and business community in AI. The Commission will now work with Member States on a coordinated plan on AI to be delivered by the end of the year.

Background information

Artificial intelligence (AI) endows systems with the capability to analyse their environment and take decisions with some degree of autonomy to achieve goals.

Machine learning denotes the ability of a software/computer to learn from its environment or from a very large set of representative data, enabling systems to adapt their behaviour to changing circumstances or to perform tasks for which they have not been explicitly programmed.

To build robust models at the core of AI-based systems, high quality data is a key factor to improve performances. The Commission adopted a legislation to improve data sharing and open up more data for re-use. It includes public sector data as well as research and health data.

Silvia Martinelli