Just as in the Renaissance, we are at a turning point today: a time when the possibility of seizing unrepeatable opportunities travels together with the worry of being cut off from the world of the future. For Professor Alberto Sangiovanni Vincentelli, an Italian Digital Renaissance is possible, but only through the development of a long-term strategy that includes improving relations between businesses, universities and research centers and opening up to a multidisciplinary education geared toward understanding the major technological, political and social issues that govern the world.

"All change starts with good education and training. Florence, for example, one of the great capitals of Renaissance finance, had enlightened rulers who financed research and art. Another emblematic feature of that era was 'interdisciplinarity. All the geniuses who lived in that period, from Leonardo to Michelangelo or Leon Battista Alberti, understood mathematics, letters, philosophy, and were all great artists.

Today this transversal capacity has been lost due to the influence of the development model imported from the United States, which, for a time, favored a vertical education aimed primarily at specialization. This meant that even the great entrepreneurs of Silicon Valley, highly prepared in their disciplines, had knowledge of history, geography or politics that was sometimes very modest indeed.

But the U.S. also has another great asset: the ability to adapt and the ability to change and follow what is new. That is why American universities today have abandoned that kind of model and moved toward a more open and inclusive educational plan aimed at promoting broad knowledge base. This is because developments in technology, particularly those that have taken place in the fields of biology and medicine, have never taken place within a specialization, but have arisen from the contamination between different subjects such as, for example, chemistry and engineering. If we look, for example, at synthetic biology, that is, the ability to create life forms that do not exist, it comes from the confluence of chemistry, biology and engineering: this combination brings innovation. The effect will perhaps be seen in 10 years, but in the meantime something is beginning to move. So for our young people to be prepared, the fundamentals cannot be ignored, and the fundamentals of science are mathematics, physics, and now biology and computer science.

When it comes to companies, however, technological development is and has been an incredibly fast phenomenon. Especially in the world of high innovation, the most important thing is the speed with which a product is brought to market, not the protection of the results achieved. But again, this is an achievement that comes from a path of knowledge that has unraveled over time.

Take artificial intelligence for example: this is a concept that originated in 1950 when people began to study the development of hardware and software systems capable of autonomously pursuing a defined purpose by making decisions. Basically, we talk about artificial intelligence by referring to the definition of algorithms that process a huge amount of data from which it is the system itself that has to derive its understanding and reasoning capabilities. The first wave of interest in AI came in the 1980s with neural networks, when huge research investments were allocated that did not yield the desired results. Then with the arrival of the "diluvio of data" and the need to interpret it arose the need to create a system that today boasts infinite computing power. Hence the return to AI, this time in the form of Machine Learning. To keep up with these continuing evolutions and possible applications of the technology, What we need to do is train our young people in critical thinking, To have a solid foundation to appeal to and not to settle for, To go beyond what they are taught.

In addition to the importance of training, the other key issue in dealing with technology is that of ethics. Indeed, machines excel only where space is finite and solutions can be determined. But in all that is gri- gio, undetermined, they cannot provide answers. In this sense, it becomes necessary to understand what role to give machines. Take for example the large systems that take information from the web, use our data to send us commercial surveys with the aim of reducing the time between the moment a user sees an advertisement and the purchase of the promoted product: this is an activity that can undoubtedly condition us and force us to take certain actions. The same thing is proposed when we rely on machines for personnel selection and evaluation, or when we delegate certain occupational safety tasks to them. This makes us realize that when we get to put tasks in the hands of technologies that normally belong to humans we also have to think about how to regulate those activities. The good thing is that these operations force us to determine what to teach machines and, consequently, to think about what is right for us."

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