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Can the EU become another AI superpower?

Taking on America and China will be hard

ANGELA MERKEL, Germany s chancellor, has a reputation for being dour. But if

she wants to, she can be quite funny. When asked at a recent conference

organised by Ada, a new quarterly publication for technophiles, whether robots

should have rights, she dead-panned: What do you mean? The right to electric

power? Or to regular maintenance?

The interview was also striking for a different reason. Mrs Merkel showed

herself preoccupied by artificial intelligence (AI) and its geopolitics. In

the US, control over personal data is privatised to a large extent. In China

the opposite is true: the state has mounted a takeover, she said, adding that

it is between these two poles that Europe will have to find its place.

Such reflections are part of a wider realisation in Europe: that AI could be as

important to its future as other foundational technologies, like electricity or

the steam engine. Some countries, including Finland and France, have already

come up with national AI strategies, and Germany is working on one. Once it is

finished later this year, the European Union will condense these efforts into a

co-ordinated plan on AI. Unsurprisingly, it is all highly Eurocratic: dozens of

committees and other bodies are involved. But the question raised by Mrs Merkel

is as vital for Europe as the ones about Brexit or immigration: can it secure a

sizeable presence in between the AI superpowers of America and China?

People in Silicon Valley are sceptical. It will screw this up, just as it has

done with cloud computing, says Jack Clark of OpenAI, a company that aims to

promote human-friendly AI. Hardly anyone in the Bay Area can imagine Europe

becoming a force in machine learning, the AI technique that has seen most

progress in recent years. It involves feeding reams of data (pictures of faces,

for instance) through algorithms so they learn to interpret other data (in this

example, to recognise people in videos).

That scepticism is not only because of self-inflicted weaknesses such as Europe

s tendency to favour incumbent business over disruptive newcomers , in the

words of Greg Allen of the Centre for a New American Security, a think-tank.

The region also has a structural disadvantage: a lack of scale. Benefiting from

huge, homogeneous home markets, America s and China s tech giants have a

surfeit of the most vital resource for AI: data.

This advantage creates others. Having more data means that firms can offer

better services, which attract more users and generate more profits money that

can be used to hire more data scientists. And having a lot of data creates

demand for more computing power and faster processors. All the big

cloud-computing providers, including Amazon and Microsoft, are developing their

own specialised AI chips, an area where Europe is also behind.

Yet look beyond machine learning and consumer services, and the picture for

Europe is less dire. A self-driving car cannot run on data alone but needs

other AI techniques, such as machine reasoning, which is done by algorithms

that are coded rather than trained an area in which Europe has some strength.

Germany has as many international patents for autonomous vehicles as America

and China combined, and not only because it has a big car industry.

Nor are ever-larger pools of data and ever-more powerful chips the only way to

go. More researchers are looking into what can be done with small data ie,

using fewer data to train algorithms particularly in manufacturing and the

internet of things. This is where Europe, home to many industrial firms, could

have an advantage. As AI gets more complex, Europe will have opportunities,

predicts Virginia Dignum of Umea University in Sweden.

Old Europe and wiser AI

Europe s biggest opportunity, however, may be political and regulatory rather

than technical. As Mrs Merkel noted, America and China represent two fairly

extreme models on AI which leaves room in the middle. Europe could become the

leader in AI governance, says Kate Crawford, co-founder of the AI Now

Institute, a research centre at New York University. Europe could pioneer rules

to limit potential harm from AI systems when, for instance, algorithms are

biased or run out of control. Many people hope that Europe will set global

standards in AI, as it is doing with its new privacy law, the General Data

Protection Regulation, whose principles have been widely copied elsewhere.

Other types of regulation offer a similar opening. Both America and China are

centralised data economies, in which this resource is controlled by a few

firms. Europe has a shot at developing a more decentralised alternative, in

which data are traded or shared between firms. That could involve defining

access rights to data (the equivalent of property rights in the digital realm)

and what types of data, including commercial ones, need to be made open because

of their social value much as European banks must give fintech startups access

to certain data if customers agree to this. That could make Europe the

preferred home for new types of data firms.

To get there, Europe has to get a lot right. On paper, things look promising.

The French and Finnish national AI strategies make for more interesting reading

than the American and Chinese plans that inspired them, offering a balanced mix

of measures, ranging from public spending on research and training data

scientists to rules for the data economy and using AI in government. The

European Commission s communication on AI is long on such useful things as

making more data available and bringing AI to small businesses .

Plenty could still go wrong in the implementation stage, however. To become

more of a force in AI, Europe will have to pool its resources in research and

data. But the EU tends to spread things out in order to satisfy both national

and commercial interests. Expect the commission at some point to announce the

launch of a loose AI research network rather than anything with a central hub.

Another reason for pessimism is institutional inertia. Much of the money

earmarked for AI research will end up in existing academic institutions, which

may not be the best place for it. Many European research institutes founded

decades ago survived the long AI winter in the 1990s and 2000s, when reduced

interest and funding killed off efforts elsewhere. The German Research Centre

for Artificial Intelligence, founded in 1988, claims to be the world s largest

with more than 1,000 employees, but it is certainly not the best known. Its

strengths lie in robotics and classical AI rather than in machine learning.

Most worryingly, Mrs Merkel s interest notwithstanding, Germany does not seem

ready to get fully behind AI and to team up with its European neighbours. A big

reason for that is its existing economic strength. Policymakers, industry

leaders and researchers tend to argue that Germany is already an AI power and

that it will suffice to inject more of the technology into the continent s

industrial products and manufacturing machinery. Co-operation with France does

not appear to be a priority. Plans for a joint AI research centre, mentioned in

the German government s coalition agreement, have been abandoned.

To become a powerhouse in AI, Europe will have to overcome its divisions,

digital and otherwise. That seems unlikely in the current climate. But where

there is a political will, there may be a way. In the 1980s, when Europe felt

under economic threat from Japan, Helmut Kohl and Fran ois Mitterrand, the then

German chancellor and French president respectively, pushed through an EU-wide

wireless standard, which came to be called 2G and helped Europe dominate the

mobile-phone industry for decades. To be sure, AI is a much more complex beast

than a wireless standard. But it shows what may be possible.