CIM News
Exploring the Social Aspects of Driverless Cars
Workshop, Friday December 2
Co-organised by:
The Centre for Interdisciplinary Methodologies (CIM) - University of Warwick
Warwick Manufacturing Group (WMG) - University of Warwick
University of the Arts, London
Societal acceptance of driverless technology is a key objective of today’s innovation drive. Most current research in this area, however, relies on a limited set of methods, namely survey research, user studies and behaviourial analysis. Creative methods like design research and issue mapping can complement these existing approaches by bringing to light still hidden social implications of innovation in a participatory way. As driverless cars have the potential to transform society – and indeed the very relations between innovation, government and public life - it becomes crucial that we investigate these less obvious, latent social implications. To enable public understanding and facilitate societal engagement with driverless futures, we need creative methods.
This one-day event at the University of Warwick will bring to bring together a small group of social scientists, design researchers, engineers and policy makers in order to develop research agendas for public engagement and societal acceptance of driverless cars using creative methods. The workshop has been organised by Dr. Noortje Marres (CIM), Dr. Rebecca Cain (WMG) and Dr. Lucy Kimbell (Univeristy of the Arts London) with Dr. Ana Gross (CIM) and Mr. Arun Ulahannan (WMG).
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How to Map Issues? CIM ESRC DTC event
Mixing methods for the study of topical affairs - an Advanced Training Event convened by Noortje Marres
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Dr Nathaniel Tkacz will be speaking at Warwick Paytech 2016. Find out more...
New Associate Professor post at CIM/Warwick Q-Step
For more information and about the post (and to apply) please see the web link: Associate Professor Post CIM/QStep
Big Data Video - IAA Award
Big data are said to be transforming everyday life. At CIM, our researchers are currently leading and/or involved in several major data-driven projects.