Finding the Hidden Rules of Society

If we collect enough data about our behaviour, can we start to make models that can begin to reveal the hidden rules of how we behave?
13 December 2011

Interview with 

Professor Steven Bishop, UCL


Kat -  
We've heard about how we can collect data, but if we collect enough data about our behaviour, we can start to make models that can begin to reveal the hidden rules of how we behave.  These models could then be used to predict important events, like changes in economic markets, and help us to work out how to react to them.  And we're joined this evening by Steven Bishop from the Department of Mathematics at University College London and he's helping to develop just such a system.  It's a project of FuturICT, so thanks for joining us, Steven.

Steven -   Pleasure.

Kat -  What I'm really interested in is this "interconnectedness of systems" and we've seen in the recent financial problems the world had that some dodgy mortgage deals in America have affected my parents' pension.  So how interconnected is the world?  How has this happened?

Steven -   Things have become very interconnected and in fact, so interconnected that we don't quite understand how they behave and respond.  So it's not just the fact that they are interconnected, that itself doesn't lead to problems, but it's the behaviour that induces somehow.  So we need to understand the hidden effects of the interconnectivity, that hidden behaviour.

Kat -   One of the problems with this is that we're in a situation we've never ever been in before and with many types of science, you can observe things over time and make predictions and do experiments.  We're in an ever changing world.  How do we gather data to help us understand and make models?

networkSteven -   Well the data would come from a variety of sources.  We we're just talking about survey data or people in a laboratory, but there's all sorts of data from the sensors of mobile devices, but also, there are plenty of citizen scientists who actually want to give their data to make better projects and to have better data.  So the whole citizen science thing is becoming much bigger.  It's a collective behaviour.

Kat -   You're involved in a project called FuturICT and one of the things you talked about is the idea of a Planetary Nervous System.  What's that and how does that work?

Steven -   We believe that there's so much data available now that almost everything is out there, and it's just a matter of trying to find it.  Firstly, to get hold of that data but secondly, trying to understand it, really understand what it means.  We call it reality mining.  So, we really understand what the real implications are of that data.  It may come from fixed sources or mobile devices, or indeed media even.  We do lots of searching of media to try and understand trends in the media.

Kat -   So to make a little comparison, we've discussed previously on the show, and a lot of people know about, how we model climate systems.  We take a lot of data, and they make models of climate systems to see how the climate might change in the future.  What sort of outcomes do you think you can predict with the kind of modelling and data gathering you're doing and what will people do with these models and the outcomes?

Steven -   Well there are three places I think that the models could be useful.  Firstly, for policy makers, they could actually help us to make better decisions.  More evidence based policy could be done  so it stops us doing this pinball policy situation that we have tended to go through in the past.  So, that's the first aim.  The second aim is for businesses who could really use data and models in different ways, and the FuturICT project would be really a platform for them to do business from.  Rather like Amazon now - it started out as book seller but now, it's actually a platform for many businesses to interact with.  But also thirdly, for the individual.  Individuals and groups could decide their collective behaviour or how they could do things collectively which nonetheless had a global implication to it.  Those are the three areas that I think could be very useful.

Kat -   I know that part of the project involves gathering data from mobile phones and social networking and Jason has talked a little about the kind of things that mobile phones can do.  But some people are getting very concerned about privacy issues, there has been some discussion about Facebook invading people's privacy.  How can you get people to give up data without invading their privacy or do people just give you all their data or don't really care?

Steven -   Sort of both, really!  Firstly, there are many people who are quite happy to give their data in these citizens science type environments.  Some colleagues from LSE did a project at the Lord Mayor's Show where people gave up their data to say where they were.  In return, they got back which bars were the best to go to with the smallest queue.  So sometimes, people give up data and get something in return for it.  It's not just a one way thing.  It should be that it goes back the other way as well.

Kat -   So this idea of constantly gathering data, building models, finding out where we are and what's happening with all these really complicated systems, I can see that that's going to be very useful in the future, but are there any examples of where this kind of technique is going on right now?

Steven -   Well in the UK, we did lots of studies, not me personally, but people trying to understand how the spread of foot and mouth disease occurred.  We also did things like the H1N1 spreading so colleagues of mine in the US did very big studies of that.  In these problems, we can see the benefits of doing scenarios - "what if?" scenarios - what would happen if we close the airports down?  We can actually run "what if?" scenarios much better on the computer than we can in real life.  This is what we should be doing I think.

Kat -   And I guess the idea would be to avert complete disasters of the future by seeing where things are starting to go wrong and pulling things back from the edge before they get too bad.

Steven -   That's correct.  Coming back to your starting phrase about connectivity, we've seen several cases where connectivity causes cascades of failures, knock on effects that we sometimes might have guessed if we'd known about them, but other times, they give really non-linear effects which we really cannot understand how they would knock on to other systems.

Kat -   We are all connected.  Thanks very much.  That's Professor Steven Bishop from UCL.


Add a comment