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Cognitive Digital Twins: bridging minds and machine – V: Personal CDTs

Graphic representation of the multiple data sets that may be embedded in a personal digital twin. The Cognitive Digital Twin includes knowledge representation data/ability data and may include Personality/Thinking information, as well as psychological/behavioural data and social data. Image credit: Takao Nakamura, NTT

The area of Personal Cognitive Digital Twins is very recent and is evolving rapidly. The Digital Reality Initiative was one of the first to study the aspect of representing knowledge owned by a person (and a company) in a digital form mapping it onto the IEEE knowledge ontology (some 14,000 knowledge items).

Several researchers have been working in this area in the last 3 years refining and “expanding” the concept of P-CDT. An interesting paper by Takao Nakamura, NTT, from which I took this post opening image, is extending the Personal CDT in interesting ways to take into account more than knowledge and skills, tracking aspects like personality, way of thinking, psychological and behavioural characteristics. I find the paper very stimulating because of the extension to the core concept of CDT, that is the focus on knowledge. Differently from machines, at lest for now, human knowledge is not executed in a pre-deterministic way (the knowledge embedded in a robot gets executed according to the software using that knowledge), its execution is also dependent on the specific moment, on the mood of the person, of his personality (apt to take risk, more cautious…). Notice that these “ancillary” characteristics are highly valuable when selecting a person for a specific role, sometimes they might be even more important than the knowledge owned by that person. Quite often, in choosing people to work on a project I have weighted more their capability to learn new things, to dare exploring alternatives than what these people knew at time zero.

This growing “latitude” of characteristics that can (have to) be embedded in a P-CDT makes this area particularly fascinating from a research perspective, merging  a broad range of disciplines from technology to societal aspects, from human interactions to psychology…

As noticed in precious posts, many players today are creating, most of the time below our perception thresholds, a representation of our knowledge space. The HR department of most companies is doing that, information service providers are doing that to profile their customers interests. Interestingly, schools (and universities) are lagging behind, at least in terms of creating and managing their students knowledge space. Also interesting and obvious, they publish a list of “knowledge” that comes as pre-requisite to enrol and the target set of knowledge that needs to be acquired in order to “graduate” and exams are designed to check the effective acquisition of that knowledge. In the past the exams were based on the teacher judgement, more and more these are today run through a machine on a pre-determined set of questions. In the future we might see exams being run by a machine (AI chatbot) that can engage the student in conversation. What is interesting in this evolution is the requirement to “formalise” the knowledge (here we have the CDT) and the fact that the same AI chatbot might be used as a teacher to support the acquisition of knowledge.

What we are totally missing, as far as I know, is personal CDTs created, managed and used by individuals. Part is due to the relatively new area, part to the lack of easy to use tools to create and maintain and partly because there will be little use for that. In the end why should I need to create a CDT to know what I know? I have my brain always available… Well there is from time to time a need to let someone know what I know: when I look for a job. For that I create (update) a cv. Actually the cv, today, is the closest thing we have, as individual, that could be associated to the idea of personal CDT.

In the coming years, surely by the end of this decade, I am betting on a variety of tools (possibly embedded in our smartphones) that will support the creation of P-CDT from the individual standpoint. Part of this construction might happen automatically, part via interaction with the person.

The question is: who will be developing this kind of software to create P-CDT and why? Well, these are my pick:

  • Companies are transitioning to the cyberspace (Digital Transformation) and are requiring tools to support their operation in that space. AI is playing a growing role in supporting operation in the cyberspace and I expect HR departments (Google, to name but one is already doing this) to turn to AI tools to assess (pre-screen at least) potential hires. As today we have sort of standardised CVs (like the European CV) we are going to have a demand for more and more structured CVs and universities will start releasing them at graduation.
  • Companies will be facing knowledge shortage and will look for tools to manage their knowledge resources as well as to seek for needed ones. Formalisation of knowledge will become normal both to search and to offer knowledge resources. Hence the demand for tools to support search/offer.
  • Organisations, like IEEE, that are thriving on knowledge assets are looking for more effective way to turn this knowledge into an executable asset. CDTs are an obvious tool to turn their assets into value.
  • Events, conferences, training courses organisations that are providing today a “certificate of attendance” will likely to go with the flow and start delivering formalised knowledge assessment packages that can be embedded into a P-CDT.
  • Individuals, starting with those that are studying today, will see the value in developing a structured presentation of their knowledge, the same way that business today sees an advantage in creating a web page/site to provide a window on its offer and value.

As I see it, by the end of this decade P-CDP may become that standardised “coin” to code knowledge ownership and more and more people will be both supporting them and using them creating a “knowledge business ecosystem”. This will open up many opportunities, as well as issues.

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.