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The many faces of Digital Transformation – Societal Scenarios XVIII

Graphic exemplifying the impact of AI on learning and using the personal knowledge. On the left hand side the time it takes to accrue a specific knowledge and on the right hand side the decrease of value of that specific knowledge over time. AI can help in acquiring knowledge faster and in keeping that knowledge valuabe/usable for a longer period of time.

3. Increased knowledge/intelligence

Although the evolution through enhanced energy, materials and tools is happening, the most important and possibly radical evolution in this century is rooted in the exponential growth of knowledge and ability to tap onto this knowledge. This is different from genome evolution but it is closely tied to the cultural evolution that brought the homo sapiens into the homo sapiens sapiens. In other words, it is something that has already happened and that is about to happen again with similar -huge- game changing effects.

Thinking about the shift from the neolithic stone-age human to the human based on societies, with distribution of work, new value creation/perception, the rise of a societal ethics, the rise of economy, one can see the type of revolution on the making we are starting in these decades as culture/intelligence becomes shared through and with the cyberspace.

The Digital Transformation by mirroring the physical world into the cyberspace and moving many activities to the cyberspace is creating an explosion of data. These data are fuelling artificial intelligence that in turns create meta-data and knowledge. It is a virtuous spiral where more begets even more.

Humans, through their smartphone, are already in touch with a knowledge base that was unthinkable just 20 years ago. Having access to knowledge does not imply that this knowledge is understood. Actually, only a tiny fraction of the existing knowledge is likely to be understood by anyone person. Different persons will have different capability to understand but collectively it is a sure thing that humans have created a digital infrastructure that is transforming their perception of knowledge. 

More than that. It is not just that an individual may be prepared to understand only a certain knowledge space. It’s  is also about the fact that understanding takes time and knowledge is growing at such speed that  it gets more and more difficult for a single person to grasp it in a reasonable time. “Reasonable” here reflects the ratio between the time it takes to acquire a given knowledge and the time such knowledge will remain usable. Basically, the time it takes to learn something has not changed significantly over the last millennia, although education has become a bit more efficient. This time is constrained by the brain’s ability to absorb, and make sense, of new knowledge. However, the life time of knowledge, particularly in certain areas, has decreased significantly thus making the ratio Use/Learn smaller and smaller to the point that the cost of learning may exceed the benefit.

This, together with the fact that the knowledge space has become too broad to be grasped by a single person/company, is pressing to find an alternative approach to knowledge and intelligence (understanding when and how to apply the knowledge).

The availability of AI assistants is a first (tiny) step in the direction of using AI to flank people’s knowledge. These assistants, today, are very limited in their performance, they act as reminders or as smart web browsers. They are basically operating at a syntactical level, i.e. they don’t understand what they say. However, within this decade one can expect:

  • availability of intelligent assistants that understand a subject matter and can work together with the person to provide knowledge just in time;
  • availability of a personal digital twin that can understand what the needs of its physical twin are and independently browse the web looking for knowledge that can matter to its physical twin;
  • availability of cognitive digital twins that can work at semantic level, adsorbing knowledge and delivering it in a customised form at the appropriate time.

These advances can both shorten the learning time (because learning can be simplified and highly customised taking into account both the needs to accrue a specific knowledge and the capability of that specific person shaping the knowledge to fit that person’s learning “style”) and at the same time can extend the useful life of a person knowledge by flanking it with the required addendum. Augmented reality can play a significant role in the delivery of just in time knowledge by integrating it into the physical world (one technician will not need to be taken up to speed of new television models to repair it since AI and AR will guide her to the diagnoses and to the subsequent fixing). Virtual Reality can provide an immersive environment sustaining more effective learning. However, the shortening of the learning time cannot lead to a zero learning time and likewise the obsolescence of knowledge in certain fields cannot be overcome completely by “knowledge patches”.

The real solution has to be found in an extended paradigm of distributed knowledge and intelligence, “extended” because society and industry have been using this paradigm for centuries: by pulling together people with different/complementary knowledge it is possible to operate as a single entity that is fully knowledgeable in a target domain. The “extended” refers to the inclusion of machines and machine intelligence in the pool of distributed knowledge. This is something new that is made possible through the advances of these last years in artificial intelligence and that will continue in the coming ones. Differently from human learning, machine learning can be speed up to result in an exponential increase of knowledge, basically unconstrained.

Notice how this extension results in a real augmentation of a person knowledge space, hence, in general in a human augmentation/evolution. Human 2.0 extends beyond the current human capabilities by accessing, seamlessly, artificial intelligence.

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.

One comment

  1. Important points. Digital Transformation depends on our ability to convert Big into Smart Data; Information into Knowledge.