In a previous blog, I compared the approaches from China and the US as they compete in the global AI race. In short, China proposed a government-led approach while the US is leaning on a business-led approach. The European approach represents an attempt to balance both business’ and government’s efforts in directing AI innovation, therefore showing a third way to compete in the global AI race.
Great Britain recently announced a national AI strategy. In a mixture of private, academic and government resources, the country is pledging $ 1.4 Billion in investment. A remarkable piece of the plan is allocated funding for a Center for Data Ethics. The center will develop codes for safety and ethical use of machine learning. Another noteworthy part of the plan is the initiative to fund 1,000 new PhDs and 8,000 teachers for UK secondary schools. This move will not only spur further innovation but also ensure the British workforce is prepared to absorb the changes brought by AI developments. It is essential that governments plan ahead to prepare the next generation for the challenges of opportunities of emerging technologies like AI. In this area, the UK’s plan sets a good precedent for others countries to follow as they look for ways to prepare their workforce for future AI disruptions. Such moral leadership will be a guide not only to European institutions but also help companies worldwide make better choices with their AI technologies. This perspective is essential to ensure AI development does not descend into an uncontrolled arms race.
In the European Union, France has also announced a national plan following a similar approach as the UK. Beyond the mix of private and government investment to the total of 1.5 billion euros, the country is also setting up an open data approach that both helps businesses and customers. On the one hand business can look at a centralized place for data on the other customers get centralized transparency of how their data is being collected and used. If executed well, this central data place can both provide quality data for AI models while still ensuring privacy concerns are mitigated. The strategy also includes innovative ideas such as harnessing the power of AI to solve environmental challenges and a narrow focus on industries that country can compete in. Similar to the British approach, the French plan also includes funding for an Ethics center.
While Germany has not announced a comprehensive plan to date, the country already leads in AI within the automotive industry. Berlin is considered the 4th largest hub for AI startups. An area in Southern Germany known as Cyber Valley is becoming a hub for collaboration between academia and industry for AI. Even without a stated national strategy, the country is well-positioned to become a hub of AI innovation for years to come.
These countries individual strategies are further bolstered by a regional strategy that aims to foster collaboration between countries. Earlier this year, the European commission pledged 20 Billion Euros over the next 2 years for the 25 country bloc. It proposed a three-pronged approach: 1) increase investment in AI; 2) prepare for socio-economic changes; 3)Devise an appropriate ethical and legal framework. This holistic approach may not win the race but will certainly keep Europe as the moral leader in the field.
Conclusion
This short survey from these two blogs gives us a glimpse of the unfolding global AI race. The list here is not complete but represent three different types of approaches. In an axis of government involvement, China is at one extreme (most) compared to the US on the other (least). Europeans countries sit somewhere in the middle. In all cases, advances in AI will come from education, government and private enterprise. Yet a nation’s ability to coordinate, focus and control the development of AI can be the difference between harnessing the upcoming technological revolution for prosperity of their people and those that will struggle to survive its disruptions. Unlike previous races, this is not just about military supremacy. It touches every aspect of society and could become the dividing line between thriving and struggling nations.
Furthermore, how countries pursue this race can also have global impacts on the application of AI. This is where I believe the European model holds the most promise. The plans put forth by France and the UK could not only ensure these countries geo-political position but could have benefits for all nations. The regional approach and focus can also yield significant fruits for the future. Tying AI development efforts with ethical principles and sound policy is the best way to ensure that AI will be used towards human flourishing. I hope other countries follow their lead and start anticipating how they want AI to be used inside their borders. The true winner of the global AI race should not be any nation or region but humanity as a whole. Here is where France’s intention to use AI innovation to address environmental challenges is most welcome. When humanity wins, all countries benefit and the planet is better for it.
