Computation, be it based on statistical modeling or newest techniques of predictive analytics, holds the promise to be able to anticipate and act infallibly on futures and uncertain situations more generally. That the future is an object of governmental knowledge and action is nothing new though. What is the characteristic of today’s relationship with futures in policy making and action? To what extent do the means of computation, from statistical models to learning algorithms employed in predictive analytics change this relationship, and the
collective capacity and legitimacy to engage with future, uncertain situations? How do technologies of prediction change policies? Who predicts, how, and with what effects on decisions and administration and on their politics? More generally, how do ways of predicting institutionalize, fail to do so or change?

This international event concludes the ANR-funded INNOX research project. It will take place at the Musée des Arts et Métiers on 11-13 September 2017. Keynote lectures will be given by :
Claudia Aradau (King’s College London)
Paul Edwards (Stanford University and University of Michigan)
Steve Hilgartner (Cornell University)

Contributions on modelling and prediction in matters of health, environment, climate, agriculture, security, crime and urban management, will be offered by :
Stefan Aykut (Hamburg University)
Silke Beck (Helmholtz Centre for Environmental Research)
Bilel Benbouzid (UPEM, LISIS)
Henri Boullier (IFRIS, CERMES3)
Dominique Cardon (Sciences Po., Medialab)
Christophe Cassen (CIRED)
Béatrice Cointe (CIRED)
François Dedieu (INRA, LISIS)
David Demortain (INRA, LISIS)
Bruno Dorin (CIRED)
Céline Granjou (IRSTEA)
David Guéranger (Ponts Paris Tech, LATTS)
Pierre-Benoit Joly (INRA, LISIS)
Francis Lee (Uppsala University)
Adrian Mackenzie (Lancaster University)
Martin Mahony (Nottingham University)
Grégoire Mallard (IHEID)
Alain Nadai (CIRED)
Sylvain Parasie (UPEM, LISIS)
Dirk Scheer (Karlsruhe Institute of Technology)

Free registration: www.innox.fr