The World Economic Forum's Jayant Narayan flagged up the figure in a debate on Artificial Intelligence (AI) at the European Economic and Social Committee's July plenary session, saying that to compete Europe needs to invest in medium- to long-term actions to create an ecosystem where AI can thrive.

The EESC's last plenary session before the summer break included a debate on Artificial Intelligence and real values: our digital future with Jayant Narayan, leader of the World Economic Forum's Global AI Alliance.

Focusing on the challenges facing SMEs looking to deploy AI, Jayant Narayan stressed that while new solutions were starting to emerge such as no-code AI, which allows companies and individuals to work on AI solutions without having fully trained data scientists on their payrolls, this was no silver bullet. There also needed to be a medium- to long-term focus on empowering SMEs to develop the necessary local, in-house capacity to deploy AI. That was where essential aspects such as skills came into play, which, in the case of AI and data science, could not be developed overnight. Funding and support for innovation played a key role in this process.

When asked why Europe was lagging behind the US and China, Mr Narayan said that while there were multiple reasons for this, government support and funding had played a major role, from the emergence of Silicon Valley to the bipartisan approval of the recent Innovation and Competition Act, entailing a USD 250 billion spend on technology and innovation.

"That funding creates the kind of market where most of your top researchers and data scientists will end up as well. And this is not a short-term solution, but more of a medium- to long-term view of creating an ecosystem where you don't just generate local value, but you also lead in it". He quoted recent studies showing that Europe was home to 18% of the world's top tier AI scientists, only 10% actually work in Europe.

Mr Narayan also addressed the question of AI and civil society and whether AI development was truly for all or was rather serving the interests of certain groups.

Quoting studies which show that between 30 and 40% of Amazon's recent revenue came though AI-driven recommendations to consumers, Mr Narayan stressed that AI is indeed very pervasive, and that this was why robustness, explainability, trust and transparency were so essential. Progress was being made on explainability and safety, but through cutting edge solutions which not everyone could be expected to have access to.

While there was no lack of principles "out there", he said the biggest concern was whether they were truly being put into practice and civil society's interests safeguarded. He predicted that progress in implementation would come from a mixture of public sector regulation and industry frameworks. Through dialogue between industry and regulators things would evolve, possibly reaching a point where industry would start taking action even on a voluntary basis. (dm)