Birks, D orcid.org/0000-0003-3055-7398, Heppenstall, A orcid.org/0000-0002-0663-3437 and Malleson, N orcid.org/0000-0002-6977-0615 (2020) Towards the development of societal twins. In: Frontiers in Artificial Intelligence and Applications. 24th European Conference on Artificial Intelligence (ECAI 2020), 29 Aug - 08 Sep 2020, Santiago de Compostela, Spain. , pp. 2883-2884. ISBN 9781643681009
Abstract
A digital twin is a virtual data-driven replica of a real-world system. Recently, digital twins have become popular in engineering and infrastructure planning where they provide insights into complex physical systems or processes. Yet, to date, considerably less research has explored how digital replicas of social systems - representing the decisions, behaviors and interactions of individual people, and, in turn, their emergent outcomes - might be developed and integrated with those of physical systems. In this position paper we discuss the need for such societal twins, what they might look like, and set out key challenges that will need to be overcome if these benefits are to be realised.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Education, Social Sciences and Law (Leeds) > School of Law (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Funding Information: | Funder Grant number Alan Turing Institute No ref given |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Oct 2020 11:27 |
Last Modified: | 15 Oct 2020 11:27 |
Status: | Published |
Identification Number: | 10.3233/FAIA200435 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166596 |
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