“To develop new technologies means building infrastructure and skills while balancing risks of excessive or improper use vs under- utilization”
Artificial Intelligence and Big Data already represent fundamental tools for industries and SMEs, while HPC and eventually Quantum Computing are helping in exploring the scientific challenges and keeping up with an increasingly complex system.
When there is an opportunity to use technology, a twofold risk arises: on the one hand, there is excessive or improper use, leading to the creation of a society that has no choice but to rely exclusively on technology to carry out a large number of activities; on the other hand, there is the risk of “under-utilization” of the available technologies: this happens when you have a clear goal and the means to achieve it, but you refrain from using them because you are not sure of the consequences and impacts that could result from our action. Finding the right balance between these two risks is necessary to transform them into opportunities.
Undoubtedly, a first step would be to encourage the digitalization of our society to provide the citizens with the proper means to make better decisions.
Furthermore, it is clear that any new technology, if unregulated, can pose a risk and be abused by governments and companies. Therefore, institutional and non-institutional stakeholders must play a crucial role in this process to support the development of those tools that can ensure a competitive advantage and outline a regulatory framework that prevents any form of abuse.
Therefore, it is necessary to be clear about the digitization process harmful effects and prevent them from compromising the emergence of the positive ones for economic and social welfare.
Big Data (BD) is crucial to developing new technologies. It is the “raw material” of today’s and tomorrow’s world. In light of this, it is vital to ensure that everyone has easy access to data by providing platforms for their use.
Creating open platforms through which data can be obtained and processed is one of the main objectives to be pursued
At the same time, it is essential to ensure adequate training to learn how to analyze and interpret data.
Of course, we have seen that the ever-widening dissemination of data entails many risks, particularly related to the protection of privacy and surveillance. In addition, social networks can use people data to manipulate and change their opinions, which poses a considerable risk to society and democracy. Therefore, governmental intervention is needed to set limits and stringent criteria for their use to avoid an incorrect use that damages citizens. The benefits and opportunities provided by Artificial Intelligence (AI) are perhaps most obvious and easier to identify. We have become accustomed to hearing about robotics, automation and machine learning: AI is already an integral part of everyone’s lives and will become increasingly so.
Automation has always been a goal for humans, and today it allows us to learn and make decisions even about things that have never been seen before. AI offers tremendous opportunities in every field, from medicine to transport. It can replace or assist humans in many activities, performing actions that humans cannot or don’t like.
AI development also comes with intensely debated risks and issues. For example, it raises significant ethical issues due to human responsibility’s potential continuous and progressive erosion.
Moreover, since AI replaces humans in many tasks and, in some cases, makes decisions autonomously, strict regulations are needed to govern both the actions and activities that an AI tool can perform and the consequences of any accidents or damage it may cause.
High-Performance Computing (HPC) offers relevant opportunities to develop new technologies, enabling the computational solution of highly complex problems that traditional computational techniques could not solve. For example, it is possible to make quantum leap advancements in weather prediction and climate change prevention with HPC. This is done by creating the aforementioned digital twins, which are increasingly adopted in several fields, from macro (digital twin of the Earth) to micro (digital twin of a single object or a person).
One of the main difficulties concerns HPC tools since they are highly complex and expensive infrastructures. This can represent a limitation of use by subjects that do not belong to the academic world.
Therefore, the goal must be to remove barriers so that the private sector can also access the available infrastructures, data and, most of all, skills.
A second problematic aspect concerns the approach of SMEs, which do not always have the vision and capacity to develop ambitious projects in the realm of data analysis and computing.
At the same time, it is necessary to invest in training and education to develop the resources that will work with these technologies. It is crucial to create a new breed of experts and bridge the gap between Academia and the private sector to address these critical issues. This can be successfully achieved by bringing young people from the research closer to companies. One way of doing this is to clarify the added value that a young researcher can bring to the private sector. Building bridges between Academia and private sector, after all, is not only a matter of sharing and developing physical infrastructures but also investing in software, skills and people.
Quantum Computing (QC), through precise methods of calculation, could provide an effective solution for specific problems, even if it is at its early stages. Quantum computers can solve some issues currently not addressable, but clear use cases of actual applications are still to come.
The “hype” around Quantum Computing is high; however, like any new technology in this stage, its development involves uncertainty and risks, the biggest one being “over-expectation” around QC. If we move into territories never explored before, the risk of failure is high, but the history of science taught us that we have to push towards unique and unexplored frontiers, and something good will come up anyway. In this fascinating exploration, we will surely encounter unanticipated, unexpected and unimaginable discoveries, and this will probably be the most exciting aspect of such a path.
Quantum Computing could open up several opportunities in chemistry, biology, medicine.
Quantum computers may be better suited to perform simulations of the microscopic world, understanding our molecules better. In that sense, this could substantially impact all fields of medicine, drug design, and drug discovery. Other examples of potential practical applications of QC are in the industrial sector, where basic research could translate into actual products.
Other risks to be addressed are those related to national security. Once quantum computers technologies are mature enough, they will be so powerful to create a substantial competitive advantage to those countries or companies that will manage them.