Why we might have digital twins in the years ahead

Meta (Facebook) CEO Mark Zuckerberg is facing his hologram incarnation of Metavers, a world created by Meta.

Atlantico: With the development of new technologies and meta (Facebook) projects, tomorrow’s virtual universes could make it possible to have a digital twin. What makes this technology today, its business operation? How does it work? What is it based on?

Thierry Berthier: A digital twin is a digital replica of an entity, object, physical system, or biological organism. In its operation, this replica must be reproduced as faithfully as possible, the process, the reaction, the interaction, the exchange with the external environment, and the transformation of the original entity. Ideally, the digital twin can be considered as a trusted projection of a source entity in cyberspace, without loss of information, complexity and effective simplification of its digital details. Of course, the more basic the original model, the easier it will be to produce and operate the digital twin. The complexity of the source entity completely determines its digital counterpart. A human digital twin is, by definition, the most complex replica ever created. It must be considered an abstract boundary that we do not know how to reach through current knowledge, technology and calculations. In 2022, when a human being is considered a digital twin, it could be just a hyper-simplifying projection, a functional reduction or a very incomplete digital imitation of an individual. The digital twin of a nuclear power plant, an industrial production line, an aircraft carrier or a wind turbine mimics the virtualized reproduction, dependence link and flow of all systems, in fact, the functionality of the physical infrastructure. Precisely, all the sensors engaged in the physical entity to mimic live data that are then collected, processed and then re-inserted into the digital twin. Once fed with this data, the virtual replica can be used to test hypotheses, verify protocols, perform simulations or predictions by accelerating time. The digital twin is not a common simulation although it can rely on simulated sequences to simulate its model. There are differences in scale between simulations that model a particular process and digital twins that simulate the system uniformly through dual flows of data, from the source sensor to its twin and vice versa. The twins’ interest in partial simulation lies in their ability to deal with complex problems that go beyond the framework of simulation. They can improve products and processes. Engaged in the digital twin’s data architecture, artificial intelligence makes it possible to animate, make it dynamic. AI acts as a replica of the nervous system and the brain.

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One question that seemed like science fiction, but some researchers put on the table, is whether humans are likely to be digital twins in the future. What about?

Generally speaking, you have to be very careful when talking about human digital twins. Let’s start by listing what we don’t know yet in 2022 (which is a myth):

First, we don’t know how to create a computer system that “thinks” like humans because we don’t understand how the human brain works or creates thoughts.

Second, we do not know how to create a computer system that mimics or imitates human consciousness.

Third, we still do not know how to create a computer system that is “aware” of its own functionality, its state, in an autonomous way.

Since the 1960s, numerous research works, articles and theses on the construction of artificial consciousness models have made it possible to advance knowledge but have not been satisfactorily implemented.

This time, let’s list what can be achieved in 2022: We are able to collect and consolidate all the data, metadata, voluntary or involuntary digital traces we have created throughout our lives as we interact with the sensors and computer systems around us. This heterogeneous data set is our digital reflection. It was studied and conceived in 2017 (by T. Berthier & B.Teboul) as an overall algorithmic projection of an individual. The corpus consisting of all our generated data identifies us numerically. It develops from birth to death and is a source of knowledge for future digital twins. When performing a “first name last name” type query in a powerful search engine (Google for example), a person gets a very incomplete overview of the overall algorithmic projection, which is specified by the engine. This first set of data must be complemented by our daily interactions with connected objects, video surveillance cameras, sensors on the transport, and so on.

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Global algorithmic projection is a good start to consider the digital twin without falling into science fiction. All that remains is to “animate” this projection to get an evolutionary system. We are slowly getting there with the evolutionary format of evolution in the virtual universe (such as Metaverse Metaverse or immersion simulation space for pilots, surgeons, firefighters or fighter training). The combination of a person’s global algorithmic projection, real-time machine learning capabilities, multi-source sensors and computational capabilities will make it possible to animate the digital twin at a very early stage. This is the first possible step, in the short term, towards the digital twin.

What are the potential risks or excesses of this technology when it comes to daylight, especially ethically?

Before talking about the potential risks associated with the digital twin concept, above all, it is necessary to emulate the virtual model, to a satisfactory level, projecting the individual into cyberspace. We still don’t know how, directly or indirectly, a model of synthetic consciousness can “bring life” to our global algorithmic projection (simulate). On the other hand, we are going to develop the ability to learn new streaming which, fed by many sensors continuously, will strengthen an individual’s algorithmic projection.

The risks are not all identified today. One can always imagine the neurological disorders or schizophrenic psychosis that can occur in a fragile individual that no longer distinguishes between its digital twins and the evolution of its own existence. We can also imagine a potential cyber attack targeting the digital twin and its biological origins, with all the more or less toxic feedback loops that could occur during this attack. Finally, the generalized digital twin can be exploited by public surveillance systems that serve corrupt actors or authoritarian governments.

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In the face of potential risks, the contributions and benefits of digital twins also need to be considered, especially for decision support, risk mitigation, training and education or medical monitoring of individuals through their twins. The more interaction between the digital twin and its biological model on both sides, the greater the benefits.

Conversely, what would be the potential benefits of developing digital twins, to think or not?

Repeat: a digital duo that “feels” like humans are science fiction today. Advances in computing, computing and machine learning will lead to AI solutions that are more efficient, more reliable, more general. This collective evolution of “data-AI-sensor-calculation” will accelerate the evolution of the digital twin to examine the hypotheses, options, and arbitrage that the source person must perform in the short or medium term. This ability to accelerate the evolution of one’s own digital twin opens a window into forecasting, risk reduction and optimization of decisions and their positive or negative consequences. Ultimately, the placement of twins in the increasingly immersive digital space will contribute to the virtual mobility and cyber-physical perfection of the individual.

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