Home / Blog / Disruptive Technologies in extreme automation impacting beyond 2040 I

Disruptive Technologies in extreme automation impacting beyond 2040 I

In the technologies that, according to the Imperial College foresight study, will have a disruptive impact beyond 2040 let’s now consider the one related to extreme automation: Swarm robotics, Battlefield robots and AI board members and politicians.

Swarm Robotics

What’s a (photoshopped) bee doing on Mars? It is announcing a NASA research project to use robotic swarms -bee like- to explore Mars. Credit: NASA

Robots are becoming more and more autonomous. At the same time they are becoming more flexible and are equipped with a variety of “tools” increasing their usability in many areas. Bringing these robots to the market is an exercise of balancing performances with cost. It is obvious that the simpler the robot the easier it is to manufacture (and maintain) and the lower its cost. At the same time, increasing its complexity would extend its capability and possibility of use. An intermediate approach is to use several simpler robots cooperating to perform more complex tasks.

We can see this approach at work in natural systems: ants and bees are clear examples, but they are not alone. We, human being, are also another example: when we work, as we do, as a community we can do much more than what any single individual can do, and that goes both in creating artefacts (like a car or a city!) and in creating knowledge. The total is greater then the sum of its parts.

Probably we are the first species that has become so good in harvesting the intellectual capacity of individuals to create a higher intellectual capacity. Till some time ago this increased capacity was created by one human exposed to knowledge created by other humans, now it is starting to happen in machines able to leverage on our knowledge to create new knowledge – through deep learning / artificial intelligence.

Cooperation, in general, does not come for free. So if you want to have simpler entities communicating to create a more valuable output you need to “invest” in communications. However, there are examples where communication is not explicit, it does not require effort. Rather it is implicit (see the discussion on implicit communications in the SAS initiative White Paper) and as such does not require an extra effort. Welcome to Swarms!

Bees and ants invest very little in “communications”, by far they use implicit communications. By flapping its wings (not sure if bees do flap their wings….but you get the point) the bee temperature increases and this increase is perceived by other nearby bees that change their behaviour. Ants leave a trail of odorous molecules and this trail affect the behaviour of other ants. The evolution did the trick of transforming these implicit messages in higher level community behaviour.

Scientists are trying to do the same with robots: swarm robotics.

They are foreseeing a broad variety of applications, from Mars exploration to characterising a geographical area, from sensing in the sea to a future health care.

Multiple robots are already applied in agriculture coordinating among them the various activities. They are not a swarm though. To make a swarm you would need many more and communications would have to be implicit. Credit: Xaver Robots

The basic principle is common to all applications: use a multitude, from ten to ten thousands simple robots each one behaving according to simple rules that connect its behaviour to the environment leading to a self orchestrating behaviour, just like bees … and humans!

In the coming decades these “simple” robots will become more sophisticated and the relations among them will also become more sophisticated (as is the one orchestrating neurones in our brain) giving rise to the emergence of intelligent behaviour. It is therefore reasonable to expect in the 2040 timeframe a disruption from swarm robotics in several areas, from the inside of our bodies to the environment to the planetary exploration.

Notice that in swarms there is no single control point and that as single participants in the swam (robot) are self influencing one another in a dynamically evolving way, as we are expecting to happen in the future when robots will be able to learn and evolve based on experience, it will become difficult to predict the behaviour and this raises legal and ethical issues (who is in charge in the setting up of the framework of evolution and who will be responsible for unplanned -undesired- behaviour?).


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.