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The economics of the Digital Transformation – XXV

UBS Chief Economist Daniel Kalt at a meeting with clients. Actually Daniel may be playing golf at this time, his digital twin is in charge. Image Credit: UBS and FaceMe

Decoupling of CDT knowledge from the physical person

The decoupling of a CDT from its physical twin can be leveraged in two opposite ways, as a proxy. and as an augmentation of the physical twin (it makes most sense when applied to a person)

Both generate economic value and biz opportunity.


A person activity (as well as a machine) is limited in time and space. By moving a mirror image into the cyberspace these limits fade away. It becomes possible for a person to interact with any other system independently of its location and with as many systems as needed at the same time as long as it is / they are connected to the cyberspace.

The mirror copy is instantiated and each instance can take care of the interactions with a given system.

A CDT can share its knowledge (and execute that knowledge through interaction) with an unlimited number of systems independently of their location. More than that. The feedback from those interactions can be analysed in real time and can increase the CDT knowledge thus affecting subsequent interactions.

There are several examples of knowledge based applications that work in this way. When accessing a website like Booking, Expedia, airline website, the application managing it gets the feeling of the interest for a specific location from the frequency of interactions and revise the price accordingly. In other words, the knowledge acquired shows that many people (or that a specific person) are interested in a specific service and the price of that service increases… It is becoming usual to change the access device to fool the system and avoid the price increase.

A CDT operating at stage IV can instantiate itself and interact with several parties at the same time on behalf of its physical twin. As an example, UBS has been using a CDT of their Chief Economist to make interactions with many investors possible at any time and at the same time.

As already noticed the big issue is how to manage the drift in knowledge occurring as a CDT interacts in the cyberspace and how to synchronise it with its physical twin. Specific (new breed of) knowledge management applications may be needed to abstract the knowledge gap being created and made the physical twin aware of that.

A complementary approach would see an integration of the CDT with the physical twin resulting in an augmentation of the latter so that as a matter of fact the drift is only an internal aspect whilst at system level (the CDT together with its physical twin) just improve its knowledge set.


In the short term, within this decade, a CDT can become a cognitive extension of a person, as well as a cognitive extension of a machine.  However in the machine case the architecture can be quite different since it would be possible to “change the software” of the machine to actually transfer any additional knowledge in the machine itself, something that –at least for the foreseeable horizon is not possible in the case of a person, i.e. no brain upload. For this reason here only the augmentation of human is considered.

Humans have been able to create various forms of cognitive augmentation, the oldest one is called specialisation. A person, through learning, training and experience becomes expert in a specific field and offer that expertise to others, effectively augmenting the societal prowess. This is what is meant by saying the education hubs foster economic development, that investing in education generates widespread wealth increase.

More recently, a blink of an eye in human history, the use of computers and AI has increased the capability of people that are finding in the cyberspace (and in the access tools like the smartphone) a cognitive prosthetic.

A CDT is just another tool becoming available to booster a person’s knowledge and most importantly the executable knowledge since the CDT can contextualise the knowledge to make it useful.

The challenge is to make this augmentation seamless. AR tools can be instrumental in this. One problem, of course, is to evaluate the level of understanding associated to this augmented knowledge. The risk is that the human counterpart becomes a pure executor of knowledge, like a robot being told by the CDT turn that screw!

Notice, however, that this is already an issue. Most of the time when using tools, including a simple calculator, people just trust the result and apply it  (who would ever stop in recalculating by hand an excel spreadsheet?!).

By using more and more sophisticated tools people delegate to them not just the menial task but, also, the understanding task. This is just going to increase more and more as tools become more “intelligent” and “knowledgeable”.

It is obvious the economic value and competitive advantage provided by cognitive augmentation. Such as advantage will become so strong that companies may start to require employees and suppliers to have CDTs and will expect to be able to interact with them, through them and in association with them.

At personal level the availability of a cognitive augmentation will be considered as important as a degree. This will motivate few companies to start offering CDTs as a service and Intelligence agencies will start delivering knowledge in shape of CDTs. This will be an interesting evolution in line with the concept of network of CDTs previously explained.

The societal implications have yet to be studied but they are obviously very significant. The more so as the connection to, the augmentation through, the CDT becomes seamless.

The increase in value of CDT goes hand in hand with the increased capabilities of AI (and the development of its underpinning: processing power and data access) and it may turn out that CDT seen as an integral part of a person knowledge space can become a bridge between human intelligence capability and artificial intelligence capability, addressing the potential clash of the two by integrating them.

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 Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. 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.