An article has been published in Evidence based HRM: "Neumann, M. (2020). From organizing to organizations: a typological scale of human relations management outside the legal world. Evidence based HRM: a global forum for empirical scholarship (online first)"
New Publication of the Unit (in Evidence based HRM)
New Publication of the Unit (in Handbuch der Methoden der Politikwissenschaft)
With participation of the unit a handbook for methods of political science has been published: "Neumann, M., Lorenz, J. (2020) Simulation in der Politiwissenschaft. In: Wagemann, C., Goerres, A., Siewers, M. (Eds.). Handbuch der Methoden der Politikwissenschaft (pp. 595-618). Cham: Springer."
New Publication of the Unit (in Quality & Quantity)
New Special Issue of the journal Quality & Quantity - International Journal of Methodology with participation of the uni published: "Voinea, C. F., Neumann M. (2020): Interdisciplinary Approaches in Political Culture Research Methodology, in: Quality & Quantity Vol. 54 / Issue 2 (Special Issue)."
New Publication of the Unit (in Kriminologie)
New article of the unit published by the journal Kriminologie - Das Online-Journal: "Neumann, M., Möhring, M. (2020): Rockerbanden: Netzwerke oder Organisationen?, in: Kriminologie - Das Online-Journal Vol. 2 / Issue 1: 63-86."
New publication of the unit: Comment from the European Social Simulation Community on the COVID 19 pandemic
Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action
The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers’ demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people’s lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research.
New Publication of the Unit (in Nature)
New article of the unit published by the journal NATURE: Squazzoni, F., Ahrweiler, P., Barros, T. Bianchi, F. et al. (2020): Unlock ways to share data on peer review. Nature, vol. 578, 512-514.
New Research Project: "AI NAVI"
The Volkswagen Foundation has funded a new project planning grant with the TISSS Lab: AI Navigation of Complex Social Landscapes (AI NAVI).
AI NAVI will explore if and how Artificial Intelligence is influencing socio-political decision making, contributing to contemporary manifestations of populism around the world. The TISSS Lab at JGU Mainz will lead and coordinate the research efforts of a consortium of interdisciplinary social, cognitive and computer scientists at the Universities of Gießen, Mainz, Newcastle, Surrey and the Deutschen Forschungszentrums für Künstliche Intelligenz to design an innovative, integrated approach to study these complex events.
Lecture "Understanding the World with AI: Training and Validating AI Systems Using Synthetic Data" – Philipp Slusallek
09.12.2019
16:00-18:00 O'clock
Room 03-134 SBII
In cooperation with KI@JGU (a working group of scientists from many faculties and other JGU institutions, founded in 2018, who either conduct research on AI or use AI for their work (e.g. in higher education)), the Department of Sociology of Technology and Innovation, Simulation Methods invites to a lecture on "Understanding the World with AI: Training and Validating AI Systems Using Synthetic Data" by Prof. Dr.-Ing. Philipp Slusallek, Scientific Director at the German Research Center for Artificial Intelligence (DFKI).
We would be very pleased about active participation, an additional registration is not necessary for this lecture.
Understanding the World with AI: Training and Validating AI Systems Using Synthetic Data
Abstract:
The world around us is highly complex but AI Systems must be able to reliably make accurate decisions that in many cases may even affect human lives. With Digital Reality we propose an approach that instead of only relying on real data, learns models of the real world
and uses synthetic sensor data generated via simulations for the training and -- even more importantly -- the validation of AI Systems. This is extended by a continuous process of validating the models against the real world for improving and adapting the models to a changing environment.
A highly relevant application of this approach is autonomous driving as well in more general term intelligent sensor systems. Using a model about the objects to be measured and the measuring process these systems are aware of what and how they are measuring and can adapt the measuring strategy and parameters accordingly, e.g. to obtain more accurate measurements or achieve higher throughput.
Phillip Slusallek:
Philipp Slusallek is Scientific Director at the German Research Center for Artificial Intelligence (DFKI), where he heads the research area on Agents and Simulated Reality. At Saarland University he has been a professor for Computer Graphics since 1999, a principle investigator at the German Excellence-Cluster on “Multimodal Computing and Interaction” since 2007, and Director for Research at the Intel Visual Computing Institute since 2009. Before coming to Saarland University, he was a Visiting Assistant Professor at Stanford University. He originally studied physics in Frankfurt and Tübingen (Diploma/M.Sc.) and got his PhD in Computer Science from Erlangen University. He is associate editor of Computer Graphics Forum, a fellow of Eurographics, a member of acatech (German National Academy of Science and Engineering), and a member of the European High-Level Expert Group on Artificial Intelligence.
His research covers a wide range of topics including artificial Intelligence, simulated/digital reality, computational sciences, real-time realistic graphics, high-performance computing, motion modeling & synthesis, novel programming models, 3D-Internet technology, and others.
Social Simulation Conference 2019
The Social Simulation Conference 2019 took place September 23 - 27, 2019 at the Johannes Gutenberg University in Mainz, Germany.
The conference is one of the key activities of the European Social Simulation Association (ESSA) to promote social simulation and computational social science in Europe and elsewhere. With over 180 attendees from 25 different countries and more than 120 paper and poster presentations, SSC19 has been greatly received by the attendees.
This year’s special theme was “Social Simulation for Social Policy” with foci on the areas of Urban Planning – Environmental, economic, demographic and social perspectives. Many great papers have been presented on these topics and especially the keynote presentations by Joshua M. Epstein, Nigel Gilbert, Erik Johnston and Gert Jan Hofstede gave interesting insights on social simulation, policy making and on how to use social simulation for policy making.
New Publication of the Unit
New article of the unit published in the edited volume The Routledge Companion to Innovation Management: "Ahrweiler, P. (2019): Innovation Management Simulations using Agent-Based Modelling, in: Chen, J., Brem, A., Viardot, E., Wong, P. K.:The Routledge Companion to Innovation Management: S. 539-559."