HomeData AnalyticsThe new tech arms race: a review of national AI strategies

The new tech arms race: a review of national AI strategies

France’s national AI strategy is only the latest promise in an intensifying political arms race. Enterprise IoT Insights considers the seven most significant national AI strategies to date, including state AI blueprints from the US, Canada, the UK, China and Japan.

France’s bold plan to establish itself as a European heartland for the development of new artificial intelligence (AI) technologies, unveiled in late March, has been welcomed by the tech industry. But it is only the latest promise in an intensifying political arms race, and other nations have better form at researching and developing AI already.

The US unveiled its own AI strategy back in 2016, on delivered blueprints for ambitious state-sponsored AI schemes. In Europe, across the channel, the UK has built a steady reputation as an effective engine room for AI innovation; its government had a six-month jump on the French with its own strategy, and Budget package.

Here, ahead of Europe’s union-wide pronouncements on AI at the end of April, Enterprise IoT Insights considers the finer points of the seven most significant national AI strategies to date.

FRANCE (March 2017)

French president Emmanuel Macron (pictured) said at the end of March his government would invest €1.5 billion ($1.85 billion) in AI research in the period through to 2022, the end of his term in office. The move is an essential part of Macron’s strategy to establish France as a leading technology centre, stimulate its economy, and keep pace with the tech powerhouses of the US and China.

“We have to be in a position to build, in France and in Europe, an artificial intelligence ecosystem,” he said.

Detail was scant, but the message was about grass-roots stimulation of the French economy. His maths covers €100 million ($122.8m) “in the coming months” to help launch start-up companies, with a view to attract a further €500 million ($613.8m) from private firms. Macron wants twice as many people studying AI in France. The French Institute for Research in Computer Science and Automation (INRIA) will create a national AI research program with five industrial partners.

“I think artificial intelligence will disrupt all the different business models and it’s the next disruption to come. So I want to be part of it; otherwise I will just be subjected to this disruption without creating jobs in this country,” Macron told Wired, in an interview after the AI for Humanity conference in Paris.

“That’s where we are. And there is a huge acceleration and as always the winner takes all in this field. So that’s why my first objective in terms of education, training, research, and the creation of start-ups is to streamline a lot of things, to have the adaptable systems, the adapted financing, the adapted regulations, in order to build champions here and to attract the existing champions.”

Macron’s speech had immediate, albeit stage-managed, effect, as it was swiftly attended by announcements from various tech firms committing investment in AI expertise to France. Among them, Samsung said it would expand its team of experts in the Paris area from 15 to 50 by the end of the year, and 100 some time after.

Fujitsu and Google-owned DeepMind both said they will set-up AI centers in France. Meanwhile, Microsoft said it will invest $30 million over three years in a project, called Impact AI, to address ethical and societal issues associated with AI. Orange, France’s top telecoms provider, also said it will invest in AI jobs and training.

UNITED KINGDOM (October 2017)

The British government reckons AI could add $814 billion (£630bn) to the UK economy by 2035. “Our vision is for the UK to become the best place in the world for businesses developing and deploying AI to start, grow and thrive, to realise all the benefits the technology offers,” it said in a statement in October 2017, at the same time raising the long shadow of Alan Turing, the British scientist considered to be the father of AI.

“While other countries and international companies are investing heavily in AI development, the UK is still regarded as a centre of expertise, for the present at least.” The impetus is plain: UK tech industries contribute around £170 billion to the UK economy, and are growing at about 22 per cent per year, reckons Tech City, a government-sponsored start-up incubator.

The digital sector is creating jobs two times faster than the non-digital sector, it claims. In 2016, UK digital tech investment reached £6.8 billion, 50 per cent higher than any other European country. But more needs to be done, clearly – to “build on Turing’s legacy” and “ensure the UK remains among the leaders in AI.”

The government has made its own loose promises around data sharing, including the establishment of ‘data trusts’ to secure and simplify access to public and private agencies. Education is high on the agenda, as ever in forward-looking political statements: the October review called for skilled experts, presently in short supply, and proposed an industry-funded Masters programme, 200 new PhD places, more credit-bearing online courses, and an AI fellowship.

The Alan Turing Institute should be the national institute for data science, it said, and an AI Council should be set up to manage inter-sector initiatives and training. Public sector systems at large should be threaded with new AI algorithms. There was also mention of tax breaks and support for inward investment.

The British government’s recommendations, in late 2017, were followed swiftly by a promise in the autumn budget of new funds, including at least £75 million for AI, as part of a £500 million support package for tech, including for 5G infrastructure and driverless cars. “A new tech business is funded every hour and I want one every half hour,” said the British chancellor. Philip Hammond (pictured).


The United Arab Emirates (UAE) unveiled its national AI strategy in October 2017, as a means to usher in a “next generation of government” – and ultimately to deliver on its ‘UAE Centennial 2071’ promise to make the country the “best in the world” by 2071. Public detail of the plan is non-existent, but a fancy marketing video says AI will enable the UAE government to take risks, “invent future opportunities”, and compete with global elites.

Its strategy covers transport, health, space, energy, water, and education, with operational costs, environmental concerns, and economic opportunities at large presented as benefits in each case. A new AI Council will run “workshops, programmes, initiatives and field visits”; skills and training is a priority. By 2031, AI will help boost the country’s GDP by 35 per cent, reduce government costs by 50 per cent, and make the nation practically immune to financial crisis.

CHINA (July 2017)

China already leads the planet on AI research, publishing more academic papers (and better quoted papers) than any other nation, including the US. The opportunity from AI is phenomenal, it reckons; the core market will be worth 150 billion RMB ($25bn) by 2020, 400 billion RMB ($65bn) and one trillion RMB ($160bn) by 2030.

The numbers are staggering, and rise vertiginously to one trillion RMB ($160bn), five trillion RMB ($790bn) and 10 trillion RMB ($1.6tn) when taken with associated revenues from parallel markets. Whatever, the prize is grand, indeed, and China will have its share.

The county’s strategic plan on AI, from the middle of 2017, makes a schedule for its progress with next-generation AI technologies, including big data intelligence, swarm intelligence and autonomous intelligence systems. It wants “iconic advances” in products, software and services by 2020 – and it wants the world to know, of course. There is reference from the start to China’s contribution to AI rules and regulations, as well.

But these are only short-term ambitions. AI is not just a trending novelty item for marketers, after all; it is the brain of the new digital era. By 2025, AI will be established as the driving force for China’s industrial and economic transformation, according to its government’s formidable plan on AI, from the middle of 2017.

By 2030, China will be the default leader for AI theories, technologies, and applications, and the world’s primary AI innovation centre – having cultivated many of the planet’s “AI backbone enterprises”, as well. A new-generation of AI will be established in manufacturing, medicine, city governance, agriculture, and national defence, among other industries, it says.

Chinese president Xi Jinping (pictured) has promised to “vigorously use governmental and social capital” to implement its major AI programmes. China is not afraid to put numbers against its targets, either.

Besides the bombast, the difference is in the detail; where other governments AI plans look like woolly promises about research and training, only to be believed when they are put into process, Beijing makes clear from the start that funding will be available, and plentiful – from a “multiple-channel financial input by government and markets”.

CANADA (March 2017)

Close on the heels of its cousins south of the border (see below), the Canadian government put together a $125-million ‘pan-Canadian AI strategy’ back in March 2017, appointing the Canadian Institute for Advanced Research (CIFAR) to execute on it.

Much of the money is going towards three new AI institutes in Canada’s three major centres for deep learning and reinforcement learning research – Amii in Edmonton, the Vector Institute in Toronto and MILA in Montreal. These three centres will work with researchers, industry and other stakeholders across Canada, and spearhead the strategy with CIFAR.

The major theme of Canada’s five-year AI strategy is familiar, focused on stimulating academia to drive a conveyor of graduates, excellence in industry and growth in the economy. The government also wants the country to have an international profile and ‘thought leadership’ position on the economic, ethical, policy and legal implications of AI. The government will also fund policy-relevant working groups to these ends.

CIFAR will appoint around 50 chairs at the three AI institutes, with half recruited from outside Canada. Seven members have already been appointed to the advisory committee, including from the likes of Google, DeepMind, Facebook and the French national science agency.

JAPAN (March 2017)

Japan’s strategy focuses on research in the first instance. A length strategy document, published by NEDO, the country’s industrial technology development agency, notes the country’s slower run-rate with academic papers on AI, compared with the US and China.

“In order for Japan to lead the world, it is necessary to come up with a challenging roadmap oriented towards industrialisation based on AI and other technologies – based on the strengths Japan possesses,” it says. “It is also necessary for the wisdom of industry, academia, and the government to come together.”

The Japanese government established a strategic council for AI technologyback in 2016, as a ‘control tower’ to promote research and development in the field, and manage a number of key academic institutions, including NEDO and its national ICT (NICT) and science and tech (JST) agencies. The council also covers various government departments with major big data remits, including the cabinet office, and ministries of health, transport and tourism.

In March 2017, the government published a roadmap for national industrialisation – based on AI and data science, and built upon the country’s successes with robotics – in March 2017. Its plan based on the “fusion of AI and other related technologies”.

Its priority areas are productivity, welfare and mobility. A fourth area, information security, is to crossover with each. This roadmap for national industrialisation has been pegged to three phases. These are described as the “utilization and application” of AI in the period through to 2020; public usage of AI in the period through to 2025-2030; and an “ecosystem built by connecting multiplying domains” in the period after.

UNITED STATES (October 2016)

The US has been at the forefront of the AI movement, as it has all developments in digital technology in the last 30 years. But the country’s most celebrated tech firms have made the running, and not its government. Federal interventionism is rare, especially in an industry that is increasingly propping up the wider economy.

Even so, the last US presidential administration, under Barack Obama (pictured), was relatively quick to research the risks and rewards associated with AI, publishing at least two key papers in late 2016 – a review of AI and automation, and a strategic plan – that describe a loose plan to establish the country as the undisputed king of industrial AI, and to hoist up and shore up its economy at the same time.

Combined, they include eighty-eight pages and twenty-five recommendations. Crucially, they state the US workforce at large is unprepared – and that a serious education programme, through online courses and in-house schemes, will be required, alongside the aggressive import of rarefied software engineering talent from abroad. The report notes as well a major injection of federal funds will be needed to complement the giant leaps by the private sector.

The plan also points to the rising debate around regulation, and the urgent role of national governments to ensure compliance and also stimulate innovation. Like any industry, government functions will benefit from AI as well through simpler processes, whether familiar bureaucratic ones or complex new applications like cyber-security.

The plan acknowledges China is now leading the way in AI in terms of published and quoted research papers, over-taking the US in 2014. And yet, it was released during the last weeks of a presidential campaign race, and rather lost in the noise – and the subsequent administration has been quick to shelve the recommendations. Hardly a word has been heard of AI at state level since, and increased funding for the National Science Foundation has been frozen.

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  1. […] Strategy in March 2017.  This strategy includes an Industrialization Roadmap and focuses the development of AI into three phases: the “utilization and application” of AI through 2020, the public’s use of AI from 2025-2030, […]