In the great global dash to sell cutting-edge Artificial
Intelligence, there’s a widespread view that the picture looks
like this: the US and China surging forwards, with the US a chest
ahead; then thin air; then Europe puffing, sweating, and frankly
not doing as well as it should.
Is this fair?
Well, we’ve seen several recent papers suggesting Europe lags
behind the rest of the world when it comes to AI patents.
There are a number of ways of ranking AI competitiveness. But
however you do it, the outcome is basically the same: the US
performs strongest, closely followed by China, and then Europe.
The papers blame everything from lack of investment in research
and innovation, to limited AI adoption by businesses, to a shortage
of skills in the European workforce.
So why is Europe behind?
One issue is historical. In the last wave of digital innovation
it was technology giants that fostered development. Microsoft,
Apple, Facebook, Google, Twitter and Amazon – the AI superpowers
– are US-based and grew out of Silicon Valley.
In China there are the tech giants too, including Alibaba and
Tencent, and they have captured the market. These companies tower
far over any European-based firms.
The dominance of the overseas giants creates an issue for Europe
– the generation of, and access to, data – particularly from
consumers. AI technology needs fuel – which means data. And many
AI applications are consumer-based: they rely on access to vast
amounts of user information to create effective products and
services.
Most European organisations simply don’t have that access.
Partly that is deliberate: the EU is careful to protect consumer
privacy through regulations such as GDPR.
They are right to be careful. The EU is world-leading in
respecting privacy and data regulation.
However, there is a balance to be struck between successful AI
innovation and protecting people’s rights. By taking the latter
more seriously than the US or China, Europe holds a strong position
in B2B applications but is behind in the consumer market.
Then of course there is the financial support by national
governments to help foster innovation and support start-ups. The US
and China spend far more than European countries on AI R&D and
funding start-ups.
This investment helps create an AI-ready ecosystem, where
innovation can be developed in partnership between academia and
industry, commercialised, and then sold in the marketplace.
Other areas that contribute to the AI gap between Europe and
other countries are the AI-readiness of businesses; the
understanding of AI by senior management; the access to people with
the right AI knowledge and skills; the establishment of trust with
consumers; and access to national computational resources, such as
supercomputers and data centres.
So how can Europe compete?
To become a market leader, Europe should play to its strengths.
Talent. Protection of privacy and sound AI governance. B2B
applications. And developing local solutions that work better for
specific jobs than those offered from Silicon Valley and China.
But this will still be hard. Products offered by the tech giants
are very popular. Perhaps national governments or the EU may decide
to regulate the competition more. That already happens in China,
where it is difficult to market foreign products.
One strength is Europe’s wealth of highly skilled AI
specialists and academics. However, the lack of funding for
research and development – and often low salaries when compared
to Silicon Valley – are driving our scientific leaders to other
countries, and not attracting the very best talent into Europe.
Europe’s focus on data privacy and governance need not inhibit
innovation. Regulation of artificial intelligence is seen as the
next GDPR, and the EU can lead on this. European businesses could
collaborate to govern data and protect privacy. There is little
sharing amongst the giant tech firms, so this could be the
opportunity for researchers and industry to work together to
develop innovative AI solutions.
There are many other ways that Europe can get ahead too.
Training and developing the next generation of AI specialists.
Developing novel and innovative AI products and services –
especially in B2B applications: Europe leads the way in
manufacturing and automotive digital innovation, such as using
robotics on the shop floor.
If Europe can succeed here, big prizes glitter in the
mid-distance. The consultants McKinsey, suggest that if Europe
starts to punch its weight in AI, to match its current assets and
digital position, it could add €2.7 trillion, or 20 per cent, to
its combined economic output by 2030.
But to get there might not mean competing head-to-head with the
US and China in areas where they have the edge. Instead it might
mean focussing on a different race.
Originally published by
Professor Paul Clough, Head of Data Science at Peak Indicators |
December 1, 2020
Analytyics
Insight