💾 Archived View for gmi.noulin.net › mobileNews › 6652.gmi captured on 2023-01-29 at 04:04:09. Gemini links have been rewritten to link to archived content
⬅️ Previous capture (2021-12-03)
-=-=-=-=-=-=-
2018-09-21 11:57:56
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.