European Vision for AI 2021 – an event for all


by
28 April 2021

share this:

european vision for AI logo

The European Vision for AI event, held on 22 April 2021, provided an opportunity for the public to hear from members of the European artificial intelligence (AI) community and representatives from the European Commission and parliament. The morning-long session was organised by the VISION project partners in cooperation with four networks of AI centres of excellence (AI4Media, ELISE, TAILOR, Humane-AI-Net). These networks were launched within the European Union’s Horizon 2020 Programme in September 2020 and are bringing together scientists across Europe.

This event followed hot on the heels of the announcement from the European Commission regarding proposed new rules and actions for artificial intelligence. During the morning, the speakers provided some context and details around this and there was plenty of interesting discussion on potential paths forward for AI in Europe. In particular, conversations focussed on the European ecosystem of trust and the proposed legal framework, and the development of a European ecosystem of excellence.

The event was chaired by Holger Hoos (Leiden University, Netherlands), coordinator of the VISION Project and Chair of the Board of Directors of CLAIRE. He saw this event as a step towards closer communication between the European AI community and the general public: “We aim to get young people, researchers, innovators, companies, and policy makers, at least virtually, around one table and discuss ambitious European plans for AI as well as the emerging ecosystem of AI excellence.

Throughout the sessions there was a strong emphasis on trustworthy AI that works for all citizens. The “European approach to AI” that the European networks want to see would bring together excellence and trust, with the goal of creating a world-leading ecosystem committed to the “AI for Good” and “AI for All” concepts.

During the event introduction there was an audience participation poll, asking us to share the first word that comes to mind when we hear “European AI”. “Trustworthy” came out on top, followed by “human-centric“. Another poll, later on in the proceedings, revealed that 70% of the audience felt that Europe was “probably” or “absolutely” going to be a leader in trustworthy human-centric AI.

As well as hearing more about the proposed ecosystems of AI excellence, and further details on the proposed regulation, there was also a parallel session with three topics to choose from. Participants could opt to learn more about the European focus on society, industry, or skills and training.

If you are interested in finding out more you can watch the livestream from the event in full here. The programme from the day is here.

About the event organisers

This event was organised by the consortium of partners of the project VISION, the coordination and support action (CSA) awarded under the H2020-ICT-48-2020 call. The aim of VISION is to reinforce, interconnect and mobilise Europe’s AI community. Europe has been investing in the European model of AI, with a new set of four European networks of AI excellence centres.

Launched in September 2020, these four networks of excellence centres – AI4Media, ELISE, TAILOR and Humane-AI-Net – are now working on various aspects of trustworthy, human-centric AI. In parallel to these efforts, the VISION project aims to create connections, synergy and joint initiatives between these networks as well as with key stakeholders across Europe. These projects are key components in the European Commission’s AI strategy.




Lucy Smith , Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



Forthcoming machine learning and AI seminars: May 2021 edition

A list of free-to-attend AI-related seminars that are scheduled to take place between 11 May and 30 June 2021.
11 May 2021, by

Artificial intelligence could be used to triage patients suspected at risk of early stage oesophageal cancer

Find out how Cambridge researchers are using deep-learning to assist pathologists.
10 May 2021, by

Counterfactual predictions under runtime confounding

We propose a method for using offline data to build a prediction model that only requires access to the available subset of confounders at prediction time.
07 May 2021, by


















©2021 - Association for the Understanding of Artificial Intelligence