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1 Introduction

Information technologies were developed at the end of the Second World War to make the organizational processes previously carried out either by man or by dedicated machines more efficient and faster. This has forever changed the way we work andinteracting with each other. Data has become the central element of all economic processes. Now, we are about to take a further step, and we are about to come to constitute a real virtual ecosystem in which all the processes that regulate our life will be the result of a negotiation between the digital alter ego of the physical world and the whole ecosystem. The protagonists will be the engines of artificial intelligence and they will be responsible to find the solution of a complex scientific problem or the planning of a trip or simply to design the supply system of a soda machine that suits the customer taste. We are at the beginning of this transformation process where the new AI technologies will be problem-solvers able to train themselves. Nowadays these new technologies are beginning to glimpse; there are already concrete examples of how this model will work, and what is still unclear is what will be the role of the “human being” inside to this digital ecosystem.

Information technology introduces, from the very beginning, a different way of seeing machines. Until the 1950s, the “modern” industrial model invented a machine to solve every single organizational problem. With the advent of the computer, the paradigm changes a program for every problem, but the machine, the computer, does not change.

It was 1994, the year Netscape introduced its first commercial browser called Navigator. This browser has changed the nature of the Internet. Until then, it was reserved for the academic and scientific community. Now, it becomes a tool offered to everyone. As the use and influence of the Internet continue to grow, companies will need to offer new services and new solutions to meet the needs and demands of consumers; to be successful, you need skillful strategies that combine digital media with conventional media: the www has born. Now artificial intelligences are integrated into this infrastructure to interact with humans, learn from them, understand their needs and guide them in their choices (McCarthy 1996).

1.1 Impact on Society

The web becomes a “virtual” space where an individual can build increasingly complex information, simply by asking on the network. It becomes a privileged space to create and make available new contents through tools for sharing information, knowledge, and culture. For example using a simple text I could build a completely new and complex 3-D image. The digital economy market is thus changed, giving rise to a few large AI platforms which base their strength and wealth on the quantity and quality of the data in their possession and on the ability to know and interpret this huge amount of data to solve complex business problems.

2 The Second Digital Revolution

The development of large “social network” platforms at the beginning of 2000 made it clear that the web itself was a place where the user could build his own digital identity, through which to share with others a virtual world made up of similar communities for business, cultural, or personal interests. LinkedIn, Wikipedia, Facebook, and Twitter are social networks in which billions of people share knowledge or simply represent themselves in a role-playing game that mimics reality. The algorithms that influence guide behaviors on social networks have the characteristic of bringing together like-minded people in relation to particular topics of common interest. In 2007, after various attempts made by various companies, Apple introduces the new iPhone technology that makes it clear to everyone how a device should be made. this kind of device is accompanying us in all our movements, allows the sharing of multimedia data on the Internet and continuously interact with social networks through natural and very simple gestures. Our smartphone is now associated with a digital identity, such as the Apple ID, which recognizes us on the network in everything we do. Now artificial intelligence like ChatGpt are extracting all the knowledge in the web and are able to interpret this knowledge interacting with human beings at any level: answering complex questions or simply doing conversation (Cooper 2023). The relationship that exists between the AI ​​engine and the human being is asymmetrical. the human being sees the result of an elaboration but does not know how and what led to that result. Even the result may exceed the expectations of the AI ​​engine creator himself. Instead, the AI ​​engine takes into account all the information that has been given to build the solution and therefore learns how to improve its training level.

2.1 The Era of Digital Transformation

Everything we have described so far leads us to conclude that we are in the presence of a digital transformation process of the companies and more generally of all organizational forms and that this will have numerous results.

The enabling technologies of this process are the introduction of the Internet of things, blockchain.

The Internet of Things is used to provide any device, from washing machines to nano-machines, with a digital identity managed through appropriate infrastructures (Brown 2016; Rouse 2019; Xie and Wang 2017].

The blockchain with distributed ledger technology is a system that aims to allow negotiations and transactions to be carried out within a distributed world of digital identities, ensuring the verification of the correctness of transactions, without intermediaries (Narayanan et al. 2016; Sherman et al. 2019].

These new technologies will make it possible to use AI in every human activity from the simplest to the most complex scientific research activities. It could happen that an AI system tells us that a nuclear plant is safe without us being able to really understand the reason for this statement. The point is that in this way we will not have the opportunity to increase our ability to explore new ways of creating. an example is that of a pastry chef who asks us if we want a cake. We explain our tastes to him and he goes to the kitchen and comes back with a delicious cake. So we tell them that we want to become pastry chefs. We then ask him to explain his recipes, his tricks and the working method he applies. If he does this together we will be able to make better and more creative cakes. But the pastry chef replies that he doesn't know all these things. He makes cakes for those who want to eat them and that's it.

2.2 New Technologies and the New Model

IOTs, blockchain and also cloud computing  will make it possible to use AI in every human activity from the simplest task to the most complex scientific research task (4,5). It could happen that an AI system tells us that a nuclear plant is safe without us being able to really understand the reason for this statement. The point is that in this way we will not have the opportunity to increase our ability to explore new ways of creating: an example is that of a pastry chef who asks us if we want a cake. We explain our tastes to him and he goes to the kitchen and comes back with a delicious cake. Afterwards we tell him that we also want to become a pastry chef. We then ask him to explain his recipes, his tricks and the working method he applies. If he does this, together we will be able to make better and more creative cakes. But the pastry chef replies that he doesn't know all these things. He makes cakes for those who want to eat them and that's it.

3 Where We Go: The Virtual Ecosystem and the Evolution of the AI

The almost science-fiction vision of the late 1950s of a world of cybernetic automatons gave rise to a real literary genre, cinematic with reflections on design and art in general.

In forms and ways different from the imaginary of those years, it is translating into something real. With a play on words, this reality is materializing in a virtual ecosystem where very sophisticated software programs process huge amounts of complex information to relate digital entities for social, cultural, and economic purposes: a digital twin of our society with its rules and its critical issues (Alraddadi et al. 2020; Scientific American 2018; Lai et al. 2020). Ultra-fast networks, G5/6/X, immersive reality devices, drones, nano-sensors, underwater, or space clouds are technologies that allow the development of computer code, programs that cooperate, make decisions, and determine the quality of services rendered by this ecosystem. A key role in the formation of this ecosystem is represented by the evolution of artificial intelligence. Artificial intelligence has made it possible to achieve amazing results in the most diverse sectors.

Artificial intelligence is currently one of the most disruptive classes of technology whose capability is rapidly improving thanks to the improvement of various factors: enormous diversity of data collected from various sources; availability of large economic archives; development of faster and more powerful computers; and improvement of artificial intelligence methods. For the past decade, AI has been ubiquitous and is not limited to just computing, and it has evolved to include other areas such as health, automotive, safety, education, business applications, and security. All this was made possible mainly by the introduction of technology called machine learning, able of classifying and interpreting large amounts of data in order to train an artificial intelligence engine to perform a certain task. It is evident that the applications of this technology are the most varied, from the game of chess to the recognition of natural language.

AI will play a predominant role in providing intelligent solutions not only for current outcome-based care, but also for preventive care (Topol 2016). Furthermore, in recent years there has been an exceptional increase in the unstructured medical and health data collected which is now available. This huge amount of data has provided a platform for artificial intelligence to structure data and train to predict disease and move to “precise medicine”. Precise medicine is described by the National Institutes of Health as “an emerging approach to disease treatment and prevention that takes into account the individual variability in genes, environment and lifestyle for each person”. It provides a more accurate prediction of the mode of treatment and strategies to prevent a specific disease. IoT platforms integrate AI capabilities such as machine learning-based analytics, gaining the ability to detect anomalies generated by sensors and devices.

Machine learning approaches coupled with the IoT are able to make operational predictions 20 times faster and more accurate than traditional business intelligence which usually monitors numerical thresholds. By 2020, 85% of interactive customer communication is expected to be automated and handled without any human assistance (Gartner).

Cyber security is the discipline that easily benefits from AI. To ensure versatile and stable protection, cybersecurity systems must consistently conform to the new dynamic environment. Cisco's “2018 Cybersecurity Annual Report”, which examined a broad cross-section of trends and patterns in data theft, data loss, malware, and other issues, found that one-third of security managers is “completely dependent” on artificial intelligence to safeguard sensitive corporate information. However, the AI community is also realizing that the use of “intelligent” technologies can have a strong negative impact on many aspects of an individual's life. The loss of jobs replaced by machines is an aspect to be taken into account. New professions are often underpaid as less skill is required to perform tasks supervised by an AI engine. It is necessary to have a vision to guide the development of technologies toward objectives that allow the AI engines, autonomous and different from each other, to cooperate with each other to, on the one hand, determine a virtual ecosystem in which the individual as such and the individual within his community can develop his creative potential to the fullest and best; on the other hand, there is the risk of creating a virtual ecosystem in which the individual is a subject who passively lets himself be guided in his choices. To understand what we are talking about, the best-known example is the creation of software to automatically drive a car. We all know Tesla’s project and we are interested in pointing out how the problem of allowing an AI engine to drive a car autonomously is dramatically different from providing AI support to a driver to help him drive. In the first case, the AI software will have to autonomously decide not only for itself but will have to take into account the behavior of other “artificial” or natural drivers, going to determine an overall movement strategy of the vehicles in the road infrastructure that delimits them that minimizes the risk ensuring vehicles reach their destination safely. Another example is the management system of a smart city or critical infrastructure. All these systems that interconnect autonomous artificial intelligence systems that cooperate in carrying out a small or large task are the near future. The completion of the second digital revolution is approaching.

In this paper, so far we have not addressed, if not marginally, the ethical problems that emerge from the impact of technologies on the lives of all of us. There is normally a favorable position for technology which states that its development should be left free as it is regulated by the market and that technology takes us to the best of worlds possible. This is contrasted by a position in which technologies are viewed with fear and tend to reject them, seeing only the negative aspects.

A position has recently emerged that is the result of hard research and experimentation work that has made it possible to understand in a scientific way that the development of AI technologies, in this new and complex dimension, is neither positive nor negative in principle, but it requires interdisciplinary knowledge to achieve the necessary awareness to be able to make the right choices.

As noted by prof. Josef Sifakis1, “There is no single solution that is totally reliable, there are a set of possible solutions with a reasonable degree of reliability. Aware of the critical issues, we must accept the percentage, even if low, of the risk of error and therefore of an accident”.

This decision of which solution to adopt from time to time concerns the policies that are defined by the institutional decision-makers. This necessarily requires a synthesis between ethical and technological issues to consciously determine within what limits we want systems to act.

To understand the complexity of the synthesis process introduced above, it is necessary to clarify some aspects that are often underestimated (Cooper 2023). 

4 A Possible Future: The Art of Co-creation

The virtual ecosystem that we have outlined has the purpose of guaranteeing profits to those who with the right technological skills and adequate investments will be able to exploit its potential best. A self-driving car can be transformed into a component of a digital service system with extraordinary potential. The planning of the trip, of the stops, of the supplies, and the possibility of obtaining an overall evaluation in real time of the insurance premium are just some of the first data that can be obtained, and on which, it can be affected interactively. There is an asymmetry of the data that is evident. The data is used to develop sophisticated marketing strategies tailored to behaviors, but if you want to know where your data is, it becomes a technological criticality. The explanation is simple: marketing brings profit, and ensuring access to your data is a cost.

All this is absolutely normal following the logic of a competitive market. The only risk is that, while being guided by good intentions, the individual disappears and remains a subject with the function of impersonating his own digital alter ego as a pawn in a game between digital platforms.

This necessarily requires a synthesis between ethical and technological issues to consciously determine within what limits we want systems to act.

It is therefore clear that it is necessary to find a balance point between the various different objectives, keeping the individual at the center in his aspirations and in his physical and intellectual needs. This is the goal of truly sustainable development. It is therefore necessary to understand how the encounter between ethics and technology can have the same explosive effect as the encounter between profit and technology. It is necessary to develop an original and harmonious system of knowledge that gives rise to a highly competent interdisciplinary community in order to involve the whole of society in a sustainable innovation project, with a view to capitalism with a social vocation. There is a technology that we have not yet invented that sees the protection of the rights of the individual as a basic objective, that meeting between ethics and technology that until now we have only seen in intentions and announcements, an open, concrete, flexible vision without be guided by a “false rationality” generated by scarce and superficial knowledge.

Here, this is the role that the individual as such and within his own community can and must play with respect to this virtual ecosystem that is being configured.

This leads to a new, multidisciplinary way of designing complex systems based on AI, in which the various scientific, technological, legal, and humanistic skills work together to build an ethical and sustainable ecosystem development model. A challenge as compelling as it is difficult in which the ability to dialogue between different cultural and scientific visions can produce surprising results.

When information technology was born we perceived it as a tool to be more efficient, when the web was born we thought we could wander into a still unknown world without thinking about the positive or negative consequences. We have listened to companies cheering on new technologies only to be swept away by them. It was probably an inevitable process at that time, but now we have matured in the ability to choose and guide technologies precisely because the level of innovation they have reached allows us to design original and sustainable paths consistent with our priorities in the real world.

Co-creation should be understood as a process in which new technologies help machines and humans to cooperate to overcome the boundaries of creativity as we conceive it today.

This is a different way of understanding technology and requires different models to develop it. To obtain these results, we need a new generation of AI technology that is able to make the relationship between human beings and artificial intelligence symmetrical. This means that just as we give knowledge to the artificial intelligence, the engine should give us back what it has learned and the new learning methods it has developed: a joint co-creation process. We are not talking about Explainable AI but about a vision of an artificial intelligence that guides human beings in understanding the method used by other AI engines in solving a problem, how they managed to extend the process of understanding unpredictable concepts more and more complexes. A partner of the human being not in seeking new solutions but new methods of exploring one's creativity. A symmetrical process in which the AI partner helps us to recover the baggage of knowledge and creative tools that we have provided to the AI engine and elaborated by it. A new starting point for creating new creative processes whose complexity is all to be imagined: a new AI technology to understand other AIs.

The laws of the market will initially resist this new way of proceeding. What is certain is that there is no easy way to transform the world into a complex digital reality.