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2025 Outlook: Workforce III

Cognitive Digital Twins are used to encapsulate knowledge and transform it into an executable one. The can be used to represent the knowledge space of a single person or the one of an organization. IN the graphic the architecture of KaaS, the tool created by DRI to support the creation and use of Cognitive Digital Twins. Image credit: Digital Reality Initiative

Among the points I discussed in the previous point there is the one of seeing the workforce, and the individual employee, as a service provider. What matters is the delivery of tthe service, not “what” is used to deliver it, whether a physical person or a machine/software.

What a company is expecting from an employee is the execution of some task, and that involves knowledge and skill. Machines have skill (very specific to each machine) but their knowledge is very narrow and defined by the “cogs” and the way they are arranged. Software, of course is more flexible in terms of embedding and representing knowledge and can turn that knowledge into an executable one.

The embedding of AI in software applications (and in machines, like robots) is both extending the knowledge and enabling the machine (the application) to turn it into an executable one (i.e. to pick up the knowledge needed at that particular time for that particular task). As more activities are being performed in the cyberspace more and more they can be executed using digital knowledge.

This representation of knowledge along with the capability of picking up what is needed and transform it into an executable one, can be captured by the Cognitive Digital Twin technology, basically an extension of Digital Twins to the realm of digital knowledge.

Cognitive digital twins have been proposed some 3 years ago by IBM as a way to make machines (robots) smarter. At about the same time Cognitive Digital Twins – CDT- have been proposed by the Digital Reality Initiative group as a way to capture knowledge of a person / organisation that has resulted in the creation of a tools based on CDT to access the IEEE knowledge space and create your own CDT, the Knowledge as a Service platform.

An individual can create her own CDT and use it in her professional life. It can embed its “cv” and expands to include the various working experiences. Since a CDT can be used to execute knowledge that person could, at least in principle, delegate to her CDT some knowledge tasks. Since the CDT operates in the cyberspace it can be used in parallel to perform concurrently a variety of tasks, like a knowledge alter ego of the person.

As a person works from remote it might be impossible to tel if the interactions are actually managed by the person or by her CDT (this assumes that the Turing test is “passed” if the interaction is with another person, but in general just a subset of the Turing requirements have to be satisfied – you are using the CDT for a specific task, not for generic interaction…).

From an employee, rather a freelance professional, the use of her CDT is a great advantage: it frees time by taking up part of the tasks and it can serve multiple “clients” at the same time. The CDT keeps learning, and it can actually learn faster than its physical (human) counterpart so that it becomes, over time, a cognitive augmentation of the person.

The other side of the coin is that a company may start using CDTs as service providers but over time it can adsorb the knowledge into the own company’s CDT. At that point it would no longer need the services of an external CDT! Your CDT may get “fired”…

This clearly opens up new scenario. However, it is not short term and as long as a CDT is strongly coupled with the person and becomes an augmentation of that person (i.e. the person is still required) we could consider it as any other tool. It is however a very slippery slope with many question marks on the future of the workforce.

By 2025 we can for sure expect that knowledge will become a manageable and managed entity that can be traded in the cyberspace by companies and that will have an impact on the workforce.

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.