Johannes Gutenberg University Mainz
Institutional description
The Johannes Gutenberg University was founded in 1477 and is located in the capital of the federal state of Rhineland-Palatinate, where Johannes Gutenberg invented printing more than 500 years ago. Today, some 32.500 students, 10 percent from abroad, study at JGU (www.uni-mainz.de), making it one of Germany’s largest universities. With 75 fields of study and more than 260 degree courses, JGU offers an extraordinarily broad range of courses. JGU enjoys global eminence as a researchdriven university and regularly achieves solid positions in international research rankings. Successes in the Excellence Initiative of the German federal and state governments have confirmed JGU’s academic status. Annually, about 700 PhD students complete their studies at JGU. Another attribute of JGU is its research-oriented teaching – which incorporates research-based topics in the curricula early on. Similar emphasis is placed on promoting and mentoring young research talents. JGU also considers the exchange of knowledge with society as one of its key duties. As an open university, JGU offers the populace a unique portfolio of information dissemination concepts that extend far beyond the scope of standard popular academic formats. Through its system of university governance, JGU makes sure that its members participate in the strategic planning and that outstanding academics get involved.
Research expertise related to AI FORA
Based in the Institute of Sociology is the Chair of Sociology of Technology and Innovation. With its attached Social Simulation infrastructure (TISSS Lab) it is engaged in the investigation of complex social systems. Analysing social phenomena around the production, the structures and the consequences of social innovations, helps to understand, describe and explain the complex dynamics and long-term effects of innovative change. For research, these complexity aspects require a computer-based lab research infrastructure, which supports a mix of quantitative and qualitative empirical methods combined with innovative methodological approaches from Computational Social Science such as social simulation. Especially, long term impact assessment of changes in interactional behaviour between stakeholders can be valuably addressed and investigated by such methodology.
Publications of institution
- Ahrweiler, P., Frank, D., & Gilbert, N. (2019). Co-Designing Social Simulation Models For Policy Advice. In 2019 Spring Simulation Conference (SpringSim) (pp. 1–12). Tucson, AZ, USA, USA: IEEE. https://doi.org/10.23919/SpringSim.2019.8732901 (peer-reviewed publication published in July 2019)
- Ahrweiler, P., Frank, D., & Gilbert, N. (2019). Co-Designing Social Simulation Models For Policy Advice. 2019 Spring Simulation Conference (SpringSim) Tucson, AZ, USA (peer-reviewed accepted conference paper)
- Frank, D., Juranyi, Z., Ahrweiler, P. & Kampis, G. (2019). Artificial Intelligence for Assessment: Prototyping responsible Technology Production for future Societies. Social Simulation Conference (SSC 2019), Annual Conference of the European Social Simulation Conference ESSA. Mainz, Germany (peerreviewed accepted conference paper; expected to appear in Springer Proceedings of SSC 2019 in 2020)
Principal Investigator: Prof. Dr. Petra Ahrweiler
Professor of Sociology, Johannes Gutenberg University, 55128 Mainz, Germany
Petra Ahrweiler is Full Professor of Sociology of Technology and Innovation, Social Simulation at Johannes Gutenberg University Mainz, Germany. Her appointment at JGU started in 2013 with getting leave for obtaining the position of Director and CEO at the EA European Academy of Technology and Innovation Assessment in Bad Neuenahr-Ahrweiler, Germany, until 2017. Before 2013, she had been Full Professor of Technology and Innovation Management at Michael Smurfit School of Business, University College Dublin, Ireland, and Director of its Innovation Research Unit IRU. Furthermore, she was Research Fellow of the Engineering Systems Division at Massachusetts Institute of Technology (MIT), Cambridge/USA. She started her professional career with studying Social Sciences at the University of Hamburg, Germany. At Free University Berlin, Germany, she received her PhD for a study on Artificial Intelligence, and got her habilitation at the University of Bielefeld, Germany, for a study on simulation in Science and Technology Studies. Her main interests in research and teaching are the mutual relationship of new technologies and society, inter-organisational innovation networks, and agent-based models as methodological innovation in the Social Sciences. Petra Ahrweiler won various research prizes, has long experience in coordinating and completing international, mostly European research projects, publishes inter-disciplinarily in international journals, and has been awarded with fellowships of various scientific societies such as the German Academy of Technical Sciences acatech or AcademiaNet, the network of excellent female scientists in Germany.
University of Surrey / CRESS
Institutional description
The University of Surrey has excellent academics whose mission is to lead pioneering research and innovation to create new thinking around, and to provide practical solutions for, some of the world’s main technological challenges. It works in partnership with international academia, industry, policy makers and commerce. Innovative and dynamic, and with around 15,000 students, SURREY is the Times and Sunday Times University of the Year 2016. It also ranks fourth in the Guardian University Guide 2016 and eighth in the Complete University Guide 2016. In the 2015/2016 QS World University Rankings, it is awarded five stars, the highest rating achievable, and is placed within the top one per cent of global higher education institutions. Involved in EC projects for more than 25 years, including around 190 funded from the FP7 and ongoing Horizon2020 programmes, SURREY has extensive experience of acting as both coordinator and beneficiary. It excels at multidisciplinary and cross border research and benefits from excellent professional and administrative support. The Centre for Research in Social Simulation CRESS, headed by Professor Nigel Gilbert, is involved in a number of research projects applying simulation to areas such as environmental management, understanding value chains, the governance of science, web-based social networks, and basic research on modelling the evolution of social structure. It has a strong reputation in the methodology of and application of agent-based modelling. Its work has been supported by the European Commission through sixteen project grants over the past 14 years and also by grants from the UK Research Councils.
Research expertise related to AI FORA
The core competence of CRESS is the use of Artificial Intelligence (AI) for computational modelling. The Centre has deep experience with the development and evaluation of AI-assisted social simulation systems. CRESS research is about what types of AI tools are of value for these systems, the infrastructure and software that will be required, and the capabilities needed to build, interpret and use them. Currently, CRESS is focusing on the application of AI algorithms, especially computational modelling, to the formulation, appraisal and evaluation of public policy, in order to achieve a step change in our understanding of whether and how computational modelling and other AI tools can be used for policy making and the risks and benefits in doing so. While CRESS’ main focus is on the use of computational models, other AI technologies, such as deep learning, reinforcement learning, image recognition etc. are also considered in its research programme.
Publications of institution
- Ahrweiler, P., Frank, D., & Gilbert, N. (2019). Co-Designing Social Simulation Models For Policy Advice: Lessons Learned From the INFSO-SKIN Study. In 2019 Spring Simulation Conference (SpringSim) (pp. 1–12). Tucson, AZ, USA, USA: IEEE. https://doi.org/10.23919/SpringSim.2019.8732901
Gilbert, N., Ahrweiler, P., Barbrook-Johnson, P., Narasimhan, K. P., & Wilkinson, H. (2018). Computational Modelling of Public Policy: Reflections on Practice. Journal of Artificial Societies and Social Simulation, 21(1), 14. https://doi.org/10.18564/jasss.3669
Calder, M., Craig, C., Culley, D., de Cani, R., Donnelly, C. A., Douglas, R., Edmonds, B., Gascoigne, J., Gilbert, N., … Wilson, A. (2018). Computational modelling for decision-making: Where, why, what, who and how. Royal Society Open Science, 5(6), 172096. https://doi.org/10.1098/rsos.172096
Barbrook-Johnson, P., Badham, J., & Gilbert, N. (2017). Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study. Health Communication, 32(8), 939–944. https://doi.org/10.1080/10410236.2016.1196414
Kolkman, D. A., Campo, P., Balke-Visser, T., & Gilbert, N. (2016). How to build models for government: criteria driving model acceptance in policymaking. Policy Sciences, 49, 1–16. https://doi.org/10.1007/s11077-016-9250-4
Rowden, J., Lloyd, D. J. B., & Gilbert, N. (2014). A model of political voting behaviours across different countries. Physica A: Statistical Mechanics and Its Applications, 413, 609–625. Gilbert, N. (2007). A generic model of collectivities. Cybernetics and Systems: An International Journal, 38(7), 695–706.
Principal Investigator: Prof. Dr. Nigel Gilbert
Director of the Centre for Research in Social Simulation, University of Surrey, Guildford, GU2 7XH, UK
He founded and is Director of the Centre for Research in Social Simulation at the University of Surrey. The Centre currently numbers 12 researchers and has contributed new knowledge in a wide range of areas at the interface between engineering, public policy and the social sciences, including inter alia, understanding processes of innovation in high-tech industrial sectors, the unanticipated consequences of fiscal policies to promote the installation of solar panels, the dynamics of extortion racket systems such as the Mafia, and the behavioural aspects of household energy demand. Professor Nigel Gilbert is a recognised expert in computational social science with a background in engineering. He was one of the first to use agent-based models in the social sciences, in the early 1990s, and has since published widely on the methodology underlying computer modelling, and on the application of simulation for applied and policy related problems such as understanding commercial innovation, managing environmental resources such as energy and water, and supporting public policy decision-making. Professor Gilbert has been the Principal Investigator of 61 research grants and contracts, receiving funding totalling over £17 million. He is currently the Director of the Centre for the Evaluation of Complexity Across the Nexus (CECAN), which brings together UK, European and US mathematicians, computer scientists, environmental scientists and social scientists to develop and test methods for the evaluation of complex public policies. A common feature of almost all the projects in which he has been involved is that they are multi-disciplinary and collaborative, bringing together, computer scientists, social scientists, public sector and civil society organisations. He has contributed to public affairs in a number of roles, including as a Specialist Advisor to the House of Commons Home Affairs Select Committee, as a member of the DECC/DEFRA Social Science Expert Panel, and of the Future and Emerging Technologies Advisory Board of the European Commission’s Horizon 2002 programme. He was a member of a panel for both the 2001 and the 2008 Research Assessment Exercise. He was appointed Commander of the Order of the British Empire (CBE) in the Queen’s Birthday Honours of 2016 for services to engineering and the social sciences. He is a Fellow of the Royal Academy of Engineering, a Chartered Engineer, and a Fellow of the Academy of the Social Sciences and of the Royal Society of Arts. He was a Pro Vice-Chancellor of the University of Surrey for eight years and now has a Distinguished Chair there. He has been on the Board of Directors of three start-up companies and has founded two successful academic journals.