The global race for Artificial Intelligence (AI) is on. The European Commission (EC) has developed an ambitious AI strategy and its implementation will require member states to join forces. Yet in the face of a pandemic, fractures among states have appeared to only be widening. What is at stake for Europe and how could it achieve a pole position?
What is at stake?
While the international community hasn’t yet agreed a universal definition of the term ‘artificial intelligence’, the High-Level Expert Group on Artificial Intelligence (AI HLEG) set up by the EC has recently proposed a rather comprehensive definition:
“Artificial intelligence (AI) systems are software (and possibly also hardware) systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information, derived from this data and deciding the best action(s) to take to achieve the given goal. AI systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions. As a scientific discipline, AI includes several approaches and techniques, such as machine learning (of which deep learning and reinforcement learning are specific examples), machine reasoning (which includes planning, scheduling, knowledge representation and reasoning, search, and optimisation), and robotics (which includes control, perception, sensors and actuators, as well as the integration of all other techniques into cyber-physical systems).”
While this definition is certainly useful, it doesn’t offer a clear insight on why AI has become a strategic priority for countries around the world.
In order to understand why governments are jostling to become world leaders in AI, one must understand the importance of ‘intelligence’ in the formulation of any strategy. In fact, the strategist is dependent on the ingredients that he/she has to work with—in essence, the more comprehensive and prescient that intelligence, the more likely the strategy is to be successful.
Intelligence as a strategic capability precedes the artificial one. However, this branch of computer science coupled with the increased availability of computing power and large datasets, can produce intelligence of a quality and at a speed which is unprecedented.
That’s why many governments consider AI to be a critical capability for their future military and industrial supremacy.
Who will win the AI race?
Looking at existing national AI strategies adopted by governments around the world, the capabilities that are considered key in the race to achieve AI mastery are very much alike: including but not limited to computing power, large datasets, continuous investment in R&D, human capital skills and vast adoption of AI technologies.
It follows that nations with strong IT, computing infrastructure and large datasets will be able to develop superior AI technologies. This is provided they have AI-capable human resources.
However, AI is of limited utility if it isn’t adopted at scale. Therefore, countries that are advancing quickly in digital technologies and literacy will be able to adopt AI faster compared to those with meagre digitalisation.
What steps has Europe undertaken so far?
The United States and China are both in the driving seat when it comes to AI, although countries such as Israel, Russia, Singapore, and South Korea are also investing heavily in these innovative technologies.
While Europe has considerably ramped up its AI efforts over the past three years, it still has a lot of catching-up to do.
2018 was a landmark year for AI in Europe with the ‘Declaration of Cooperation on Artificial Intelligence’ signed by EU members states, Norway and Switzerland. The EC achieved other important milestones in the same year, including the ‘Communication on Artificial Intelligence’ which set out the European vision for an AI strategy, the appointment of the AI HLEG and the issuing of the ‘Coordinated Plan on AI’.
In 2019 ‘The Artificial Intelligence for the EU’ (AI4EU) was launched bringing together different stakeholders to build a focal point for AI resources. During the same year the AI HLEG published two important documents; the ‘Ethics Guidelines for Trustworthy AI’ paving the way for a ‘made in Europe’ human-centric, trustworthy AI and the ‘Policy and Investment Recommendations for Trustworthy Artificial Intelligence’.
Building on this body of work, in February 2020 the EC released a ‘White Paper on Artificial Intelligence – A European Approach to Excellence and Trust,’ and two other complementary documents – the ‘European Strategy for Data,’ and ‘A Strategy for Europe Fit for the Digital Age’.
The White Paper underwent an open public consultation in the EU and internationally and the report summarising the results is available here.
In a nutshell, the white paper outlines a dual-track strategy for AI; first the progression of an ‘ecosystem of excellence’ and in order to do that the EC has proposed a rich array of policy initiatives aimed at supporting the development and uptake of AI technologies. Second, the EC plans to build an ‘ecosystem of trust’ through the design of an EU-wide regulatory framework for a ‘human-centric and trustworthy AI’.
Europe’s Achilles’ heel
Europe’s biggest weaknesses for the development and uptake of strong AI technologies is first and foremost its structural disadvantage if compared with United States and China.
Second, the UK was playing a leading role on AI in Europe; therefore, unless the EU and UK are able to achieve a healthy post-Brexit digital ecosystem, the EC will struggle to fill the gap left by the UK.
Lastly, although Europe’s battle with the coronavirus has highlighted the vital importance of digital technology, the danger of a deeper and more protracted European recession is very real, and this may well affect the size and priorities of the long-term EU budget.
Europe’s silver bullet
Although it has been criticised for overly focusing on AI regulation, Europe actually considers a ‘made in the EU’, ‘trustworthy AI’ its silver bullet.
Given the overwhelming global acknowledgment of the societal, ethical, and regulatory challenges posed by AI, the so-called ‘Brussels effect’ could indeed set Europe apart from its global competitors. Yet leading on AI regulation alone won’t be sufficient.
In order to achieve a successful ‘ecosystem of excellence and trust’, Europe will need not only to catch up on digitalisation and complete the establishment of the ‘Digital Single Market’ but also deploy substantial investment for an EU-wide development and adoption of AI. Important areas of investment remain its academic centres of excellence and start-ups. Europe should also encourage adoption of AI across public and private sectors as well as focus on AI areas where it has an edge, as for example, advanced robotics. Turning back to AI regulation, Europe should be careful not to overregulate this new technology as this may stifle innovation.
To conclude, as the window of opportunity for Europe to consolidate its position in the global AI arena is closing fast, it could consider playing to its strengths rather than trying to catch up with the scale of other countries.
Contributed by Elisabetta Zaccaria, founder, Secure Chorus, a not-for-profit membership organisation serving as a platform for multi-stakeholder cooperation, for the development of forward-looking strategies, common technology standards and tangible capabilities in the field of information security.