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Megatrends for this decade – XLIII

From Digital Manufacturing to Digital Society. The various layers composing a Digital Society. At the bottom, as enabling infrastructure, distributed computing and Robotic Swarms, Internet of everything to include Things and People, Digital Ecosystems whose players interact with one another via Agents, a reference model for data (ontology and semantics), organisation through theory of complex systems giving rise to an emerging global intelligence and a the top a self organising management. Image credit: P. Skobelev and Borovik S. Yu.

Working in a smart environment

It is well known that human societies progress through a continuous interaction among minds (people) and resources. Increasing one or the other, or both, without an effective interaction leads nowhere.

Hence humans are more than used to exploit distributed intelligence, the one present in other humans in the group. Actually, some people were/are used to “harvest” intelligence from animals, as an example: by looking at their behaviour they could infer a possible danger ahead.

Over the past century we have learnt to get information from a variety of sensors and by processing the data we have been able to be smarter. As these sensors became more sophisticated they both provided better data (covering more and more aspects of the real world) but they have also become more and more difficult to interpret (think about the data provided by sensors in a car, or in an airplane: it would be impossible to make use of the data they provide in real time, we have to rely on a computer to harvest and process them). This has opened the door to interaction with computers to retrieve and make sense of information/knowledge. We have been moving to use computers because they are fast and can react in real time, to using computer because they can correlate huge quantity of data and make sense of that and we are progressively rely on computers (AI) because they can make sense out of data and evaluate the best course of action in a given situation, in other words because they have become “intelligent”. More and more computers (devices embedding computers) are becoming autonomous and take decisions based on their perception of the context (context aware) and on the goals that have been defined.

Now, the point is that when you have several autonomous systems each of them context aware, you have a situation where the action of one system affects the context and therefore influence the actions of the other systems in that context not by direct interaction but through an influence on the context. We, humans, are autonomous systems and as such we use context awareness (quite often) to tune our behaviour. I would say that most of our life is based on context awareness and adaptation, only a minimal part is based on explicit interactions.

People walking in a crowd automatically adjust their movement based on the context. Most people will tend to occupy the central space so that in a station, as shown in this photo, people getting out of the train will walk in the central part of the corridor forcing people moving to trains to walk on the sides. It is an example of a swarm behaviour/intelligence. Image credit: DNYUZ

Think about walking on a pedestrian road. You are among hundreds of other people, moving in a seemingly random directions (at least this is what I feel sometimes…). You never stop asking the other person what are his plans so that you can avoid bumping on him. Nor is he asking you. And yet, seamlessly, we manage to go our way without hitting anybody (well, most of the time…). This is what is known as the swarm intelligence. The behaviour of each participant in the swarm affects the behaviours of he others and in turns this creates an emergent behaviour (intelligence) of the swarm. This also applies to knowledge (and culture): by living in a certain environment you absorb the knowledge and culture that is at the core of that environment societal behaviour (by living side to side with a mathematician you are not going to “learn” differential equation by proximity, but over time you learn to “think” in a certain way…). This is also one of the reasons why remote working is not the same as working in the same space and both companies and workers pointed this out during the lockdown we have experienced in the Covid-19 pandemic. The smart of the crowd, of the swarm, is lost when proximity is lost.

In this decade workers are going to make higher use of telework but companies will need to find ways to restore the swarm intelligence. The evolution of collaborative tools has increased rapidly in response to the pandemic and quite a few have tried virtual spaces. So far nothing has emerged as being capable of restoring the benefits of proximity but we should get closer by the end of this decade. VR could potentially play a significant role providing more credible virtual presence in a community but we are definitely no there yet.

The Baxter co-bot has been designed with some anthropomorphic traits, a screen is used as a head to convey a sense of attention, emotion…. . Image credit: Rethink Robotics

This seamless influence in a crowd/team is not available among people and machines, so far. People today experience a gap between themselves and machines. Co-bots are being designed to operate seamlessly with workers, some are even given some anthropomorphic traits to robots, like Baxter, see figure. The use of voice interaction is surely going to increase the effectiveness of interactions. The use of artificial intelligence and NLP (Natural Language Processing) along with the capability of distinguishing various streams of speech (as humans do, focussing on a specific conversation out of many) will further improve seamless interactions.

The availability of a pervasive, high-bandwidth, communication infrastructure is making possible to connect, in a seamless way, local intelligence (both machines and humans) creating a swarm in the cyberspace and letting local intelligence to become augmented by accessing the emerging intelligence of the swarm. The crucial point here, for an effective smart ambient, is “seamless”: people should not perceive an interface, they should just “live and act” in a context and the smartness of the context is actually increasing intelligence to each person (and machine). An example of this “swarm intelligence” is provided by Unanimous AI. Through software (including AI) Unanimous AI leverages the distributed intelligence of a crowd complementing it with the intelligence of machines.

A screenshot of the Swarm Intelligence interface. Each participant contributes to the total intelligence, including the one generated by machines or autonomously by the system. Image credit: Unanimous AI

As an examples practitioner medical doctors can interact (via voice or through a screen) with Unanimous AI Swarm Intelligence (customised to fit the needs of healthcare practitioners) and share experience or formulate questions. The long term view would be to have a presence of tendrils of this swarm in the studio of the doctor to pick up all conversation, record all exams and their results, pick up the voice of the patient…. (all of this is not done at the moment, connection to the system requires an explicit action by the doctor -this, by the way addresses also privacy issues…). The Swarms collects and cross checks all these data and autonomously peruses the thousands of medical articles in medical journals, cross references drugs and their effect as tested in the labs and experienced in the field. This knowledge, and intelligence, is made available to doctors.

The approach to emerging intelligence via a swarm can be applied to a variety of context and I feel we are going to see plenty of it in many areas, transforming the working place and the way of working by the end of this decade.

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.