Making Europe a leader in AI: in conversation with Venki Ramakrishnan, Antoine Petit and Martin Stratmann


by
09 October 2020

share this:

AI-Europe event

An online event organised by the Royal Society, the Centre National de la Recherche Scientifique (CNRS) and the Max Planck Society took place on 7 October. It focussed on AI in Europe and considered topics such as European collaboration, trustworthy AI and the role of regulation.

Involved in the discussion were Venki Ramakrishnan, President of the Royal Society, Antoine Petit, Chairman and Chief Executive Officer of the Centre National de la Recherche Scientifique (CNRS), and Martin Stratmann, President of the Max Planck Society. We also heard from Marta Kwiatkowska (University of Oxford), Stéphane Mallat (Collège de France) and Nuria Oliver (Commissioner for AI Strategy and Data Science, Valencian Region, and also representing ELLIS).

You can watch the event in full below.

It was noted that Europe has been a leader in considering the social and ethical implications of AI. However, the participants were keen to stress that in order for Europe to compete with the USA and China, all European countries must continue to collaborate and work together to advance research. Key to unlocking Europe’s potential to become a leading research destination for AI will be the ability to attract talent.

Another point highlighted concerned the importance of links between academia and industry, with the general feeling being that there is much progress required in this area. AI will change the job market and careful management of the transition will be key. The participants also stressed the need for domain experts to be involved in AI development and deployment.




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