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Cognitive Digital Twins: bridging minds and machine – III: Personal Digital Twins

Back in 2018 the EU called for a Flagship Cooperative projuct aiming at developing a Digital Twin for every European citizen as a way to dramatically improve healthcare. Image credit: European Commission and Barcelona Supercomputing Center

Technologically speaking, stepping up from Digital Twins applied in Industry to Digital Twins applied in Healthcare (hospital equipment, medical equipment, pharma…) was a small step, like it was a small step to move from equipment and processes used in healthcare to modelling people although this modelling had to take into account the sensitivity of data and related privacy issues. Besides, moving into personal space opens up issues related to the ownership of data. As an example: my personal digital twin can accrue data coming from medical exams that I took in the last few years (in perspective, for future generations, all the exams since I was born). On the one hand these are MY data, on the other hand these data are the result of laboratory processes whose property, or at least co-property, could be claimed by the lab. Similarly, who is the owner of a diagnoses? Is it the doctor, that levering on her knowledge made it, or is the subject of the diagnoses, that is “me”? These are not trivial issues. It is clear that the doctor by looking at me, at my exams, at the outcome of her prescriptions is increasing her knowledge space. Do I have a claim on this increased knowledge that I am contributing to?

Well, at first glance we can confidently state that data resulting from my exams are “MINE” but that the increased knowledge deriving from my data is “HER”. However, the digitalisation makes the access and processing of data so much easier to the point of muddying the waters. as it is already the case in the heated discussion on search engines that are leveraging on the (behavioural) information we are providing by using their services to generate a huge business.

The creation of personal digital twins, on the one hand could empower the person in a better management of her data, on the other hand (depending on who is actually controlling/enabling the personal digital twin) it can ease the exploitation of data by third parties.

Schematic representation for using Personal Digital Twins, PDT, in epidemics control. The authority set the scene by reuiring the PDT to monitor certain data patterns generated by its physical twin, PyT. Once a pattern is detected a red flag is generated and processed by the healthcare institution through global analytics taking into account several data streams. This might result in prescriptive actions, like imposing testing/quarantine, and it contributes to increase the PDT/PyT local awareness. Nearby PTDs may interact based on this local awareness to ensure warning and appropriate behavior

The pandemic has accelerated the adoption of personal digital twins (the “green pass” is a minimalistic personal digital twin). Some Countries, particularly in the Far East, have adopted Personal Digital Twin to monitor the epidemic and assess the contagion risk in specific areas.

As shown in the graphic a personal digital twin, designed for epidemic monitoring and control, mirrors some aspects of a person, like physiological parameters, the record of the places (and time) visited, the potential contacts over a given period of time…

These data can be used locally, by the personal digital twin, to assess both the potential risk of exposure and the probability of being infected -by monitoring symptoms. Additionally they can be (partly shared) with a medical institution charged with the monitoring of the epidemic. In turns, the medical institution can provide the personal digital twin with contextual information and data (like the contagion risk in a given area so that the person can be aware of it and take precautions or the warning of having been in proximity to a positive person so that a test can be taken).

The privacy, at this stage, is preserved since the data are “localised” but do not identify a specific person.

The “control” part can be executed through a framework of rules imposed by the Government. The personal digital twin operates within this framework and provides awareness on this framework to its physical twin (the person). It is only when the person opt to disregard the rules that a red flag is raised and the privacy broken. Notice that this is similar to what happens with speed traps: they monitor all cars but they notify the police only the ones breaking the rules.

In the pharma sector, digital twins mimicking organs and systems are starting to play a role in the design and testing of drugs. The next step (undergoing) is to use a Personal Digital Twin reflecting the characteristic of a specific person and of  the ailment (mostly experimented at this time for cancer patients) to find out, through simulation, the potential effectiveness of drugs to create a personalised treatment.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the New Initiative Committee and co-chairs the Digital Reality Initiative. He is a member of the IEEE in 2050 Ad Hoc Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.