While at world level the uptake of digital tools and solutions to guarantee the continuation of business during the Covid pandemic has once-and-for-all made us understand we are capable of living in a 4.0 planet, we cannot say the same for Artificial Intelligence (AI). “Digitization, imposed by the change in our work habits, accelerated by the pandemic, is destined to remain a permanent feature of our societies. It has become a necessity" said few weeks ago, Mario Draghi, former president of the European Central Bank. Indeed digitalization of the public sector or of the most reluctant industry sectors, or even of education is now a reality that we could not foresee six months ago.
But given the status of conversations and the hype around AI over the last couple of years one, would have hoped for AI to be applied everywhere in order to converge with the current demands for a more reliable, efficient and effective way to cope with several of the thousand problems the world is facing, because this is the sense we got so far. AI may lead to transformative applications within a wide range of industrial, intellectual and social applications, far beyond those generated by previous industrial revolutions. In the last few years governments, think-tanks, industry and research hubs around the globe started a race on strategizing the implementation of AI at global scale. Simultaneously with the publication of the Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions on Artificial Intelligence for Europe and the Policy and Investment Recommendations for Trustworthy AI of the High-Level Expert Group on Artificial Intelligence (AI HLEG), a new race started for the development of ethical guidelines on AI. This said the reality looks a bit different as there is unfortunately still a large gap between words and deeds both in the commitment and the implementation aspects leading to the application of AI at a truly global scale.
Currently the state of the art around the development and application of AI around the globe is extremely scattered and delineates increasing discrepancies in the maturity of strategic policies and in the way AI is developed and used. There are not only main differences between continents but inside countries the gap of innovation and the use of AI technologies is growing extensively. While the recommendations of the United Nations and several other international bodies suggested using AI to bridge inequalities and support an overall development of the wellbeing of the world population, the race for AI supremacy has left many behind. Nations have recognized the transformational potential of AI. Its advances will impact all facets of society. A spate of recently released national strategic AI plans provides valuable insights into how nations are considering their future trajectories. These strategic plans offer a rich source of evidence to understand national level strategic actions, both proactive and reactive, in the face of rapid technological innovation. But a lot of these strategies are not being followed by operational plans able to boost investments in infrastructures, interoperability platforms, data management and – most important – a clear and effective plan for education and research that could allow the development of AI technologies.
At global level the reality is that the USA and China remain the two main sellers of AI solutions at global scale with the latter being the country that experiments the most at governmental level. Europe and Israel are slowly trying to catch up. But one of the main issues linked to the overall development of AI stays with the development of what needs to be the fuel of AI: data. Progress in AI activity is compelled by data and without a proper data-driven governance it will be very difficult to effectively bridge the gap with big tech companies that have spent billions on giving value to data over the last decades. A good example is the investment done in Colombia by the Constitutional Court that has recently launched a predictive system of intelligent detection of sentences and information called Pretoria to facilitate the work of judges. The development of this AI solution required months into analyzing how data was managed in the Court and the results look impressive. This is the result of a profitable collaboration between Colombia and Argentina, where Prometea is leading the AI technology in the justice system.
The European Union decided to go in a similar direction developing a data strategy that aims to make the EU a leader in a data-driven society. For the current Commission, creating a single market for data will allow it to flow freely within the EU and across sectors for the benefit of businesses, researchers and public administrations. This is also why the EU strategy on AI was launched at the same time of the data strategy.
One of the other issues linked to the uptake of AI is indeed procurement. The World Economic Forum recently published a toolkit where experts remark that government procurement officials cannot be expected to have the most up-to-date knowledge in every highly specialized field. To safeguard the responsible future use of AI technologies, a multi-stakeholder effort with cross-sector participation and interdisciplinary expertise is required to create authoritative guidelines.
This to say that knowledge is the pivotal element behind AI, the ones investing in it, will be the ones able to drive us into an AI-based (and trustworthy) era.
Le opinioni espresse dall'autore sono strettamente personali e non riflettono necessariamente quelle della Commissione Europea
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