Efforts to Nationalise AI, and Why We Need to Stop Calling it “AI Race”


Photo by Ciprian Pardău on Unsplash

Much of the work done in AI is of the intangible quality, and will drive spillovers

French President Emmanuel Macron announced his intention to make France an AI leader and avoid “dystopia”, supported by €1.5bn in investment. France is not the first country to surge ambitiously towards establishing itself as a “leader” in AI. Putin famously stated that “whoever becomes the leader in this sphere will become the ruler of the world”. China has a three-year action plan to establish itself at the top. Canada’s Trudeau discussed on multiple occasions the consequences of automation, and the opportunities of artificial intelligence. Macron demonstrates nuanced understanding of the opportunity — both technological and social — of artificial intelligence in this must-read interview.

This sort of thing can only help capitalise on the value of these technologies. I do believe that cultural and intellectual diversity (and France has those when arrayed with China and the US) can only help in the development of appropriate AI systems. The equivalent UK number is only about £75m (€85m), which is a pity considering the nation’s intellectual heritage across both humanities and technology domains, and bottom-up appetite for the Internet over the past 30 years. More importantly, few world leaders have expressed such adroitness with this sea change than Macron has.

The last technological paradigms (software based on the Internet) were driven predominantly from the Silicon Valley and the US, which while not a monoculture, was not as diverse as the complex fabric of society these technologies now mediate.

I’m not a huge fan of thinking about this as a “race”. It implies that there is a finish line. In absence of good explanation of what that finish line is, perhaps it suggests super-intelligence or the singularity. Much of the work done in AI is of the intangible quality, and so will drive spillovers. The knowledge is published, networked and disseminated widely wherever it is researched. We could all benefit.

In addition, the race to an AI state is not merely about harnessing data and smart maths-types. If you believe the hypothesis, then investing in the thinking about what society & businesses should look like after “AI” is also important. AI is a technology that could drive returns to superstars and severe inequality — which could lead to severe political risk, a.k.a. “pitchforks”. (More a consideration in the US than Europe). AI is a technology that glues together and layers on top of existing IT. Chinese medium and large enterprises have woefully underinvested in enterprise IT over the past decades. Is their fabric as ripe for AI enhancement as more pro-IT Western firms?

It’s a complex picture. We need to look further than data and doctorates and into how societies and polities can ready themselves for a world enabled by these technologies.

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