Dirk Helbing was speaking at a session entitled “Predictability: from physical to data sciences”. This was an opportunity for participating scientists to share ways in which they have applied statistical methodologies they usually use in the physical sciences to issues which are more ‘societal’ in nature. Examples stretched from use of Twitter data to accurately predict where a person is at any moment of each day, to use of social network data in identifying the tipping point at which opinions held by a minority of committed individuals influence the majority view (essentially looking at how new social movements develop) through to reducing travel time across an entire road system by analysing mobile phone and GIS (Geographical Information Systems) data…
With their eye on the big picture, Dr Helbing and multidisciplinary colleagues are collaborating on FuturICT, a 10-year, 1 billion EUR programme which, starting in 2013, is set to explore social and economic life on earth to create a huge computer simulation intended to simulate the interactions of all aspects of social and physical processes on the planet. This open resource will be available to us all and particularly targeted at policy and decision makers. The simulation will make clear the conditions and mechanisms underpinning systemic instabilities in areas as diverse as finance, security, health, the environment and crime. It is hoped that knowing why and being able to see how global crises and social breakdown happen, will mean that we will be able to prevent or mitigate them.
Modelling so many complex matters will take time but in the future, we should be able to use tools to predict collective social phenomena as confidently as we predict physical pheno[men]a such as the weather now.
This will require a tremendous amount of data. It may also require asking for a lot more data from individual members of society in a way that has not happened yet. To this point, individuals have been willing to volunteer information in places like Facebook and Twitter but we will need much more consistent information than that to truly develop models like are suggested here. Additionally, once that minute to minute information is collected, it needs to be put in a central dataset or location to see all the possible connections. Who is going to keep and police this information? People might be convinced to participate if they could see the payoff. A social model will be able to do what exactly – limit or stop crime or wars? Help reduce discrimination? Thus, getting the data from people might be as much of a problem as knowing what to do with it once it is obtained.