Category:	Science and Technology
Domain:	Social Sciences, Computer Science
Keywords:	Computer Science - sociology, psychology, methodology, causality, simulation, Monte Carlo optimisation
Outlook:	Simulations that take advantage of vastly increased computing power could be used more heavily in the social sciences, eventually becoming the more dominant means of analysis as a method of predicting human behaviour.
Summary Analysis:	Quantitative analysis methods in social sciences that use statistical and numerical rather than verbal data, have traditionally been limited by the amount of information and data that can be processed. Researchers have typically relied on smaller sets of variable data and as a result, have tended to use the same information in many different circumstances. Computer simulations that borrow methods from applied physics and business decision make it much easier to use a greater range of information and throughly evaluate each alternative. Increased computing power and storage capacity means that there are potentially no limits to the size of datasets and the number of variables that can be analysed and the variables can also be measured across time repeatedly. Social scientists are expected to increasingly use simulation, as they learn to rely on computers and an aleatory (random) approach to knowledge that takes into account the vastness of available data. The big challenge however will be to develop statistical techniques for finding patterns in these huge datasets.

	Implications:	Better understanding of social behavior as it occurs in reality Increased ability to study humans in their networks and contexts, and to study their behaviour as it is affected by sequences of events
	Early Indicators:	Use of simulation by sociologists to contrast global network structures with the local patterning that generates the network Use of agent-based modeling by consumer researchers to study shopping behaviour Use of simulation by social scientists to explore discovery and diffusion of knowledge in an endogenous social network Use of agent-based modeling of dynamic parties to study electoral behaviour New Zealand developing a simulator for validation of interventions
	What to Watch:	Sociology and psychology departments at major universities offer required courses in using simulation for quantitative analysis.
	Parallels/Precedents:	Use of simulation in business to reach optimal business decisions and understand individual airline routes
	Enablers/drivers:	Increased computing power Availability of large datasets and merging of data
	Leaders:	Institutions: University of Manchester - National Centre for e-Social Science [link] University of Chicago University of Melbourne Johns Hopkins University Swiss Federal Institute of Technology University of Balearic Islands (Palma de Mallorca, Spain) University of Buenos Aires Blaise Pascal University Clermont-Ferrand, France Ecole des Hautes Etudes en Sciences Sociales, Paris Cornell University Stanford University University of Michigan Manchester Metropolitan University University of Wisconsin-Madison University of California, Berkeley University of Warwick, Systems Modelling and Simulation Group [link] University of Surrey, Centre for Research in Social Simulation [link] University of Bradford, School of Informatics [link] Institute of Cognitive Sciences and Technologies, Italy [link] European Social Simulation Association [link]
	Figures:
	Sources:	Abbott, Andrew. 2001. Time Matters: On Theory and Method. Interview with Andrew Abbott, Professor, Department of Sociology, University of Chicago Robins, Garry, Philipa Pattison and Jodie Woolock. 2005. Small and Other Worlds: Global Network structures from Local Processes. American Journal of Sociology. Volume 110, Number 4: 894-936 Fowler, James H and Oleg Smirnov. 2005. Dynamic parties and social turnout: An Agent-based Model. American Journal of Sociology. Volume 110, Number 4: 1070-94 C W Johnson, Lesons from the Evacuation of the World Trade Centre, September 11th 2001, for the development of computer-based simulations [link] Tuncer Oren, Rationale for a code of professional ethics for simulationists [link] Duncan Graham-Rowe, Mission to build a simulated brain begins, New Scientist 1 June 2005 [link] Paul K Davis, Military Applications of Simulation, in Applied Systems Simulation: Methodologies and Applications, Kluwer 2003 [link] M Carter, A Canadian Network for modelling and simulation in healthcare, Clin Invest Med, 2005, 28, 6, 318-319 [link] Foresight Project Report: Data Mining, Data Fusion and Information Management [link] Foresight Project Report - Brain Science, Addiction & Drugs: Drugs Futures 2025 [link]

	At A Glance:	When:	21–50 years +
		Where:	Global
		How Fast:	Years
		Likelihood:	High
		Impact:	Unknown
		Controversy:	Medium

Related Outlooks: