First Workshop on AI utilization to increase resilience in society and economy (RSE-2022)

Aims and Scope 

Current events have clearly uncovered the fragility of society and economy. Once again, the importance of resilient structures and countermeasures has been demonstrated. Artificial Intelligence (AI) can be an important tool to enable and improve resilience, for example with respect to the healthcare system [Quelle] or supply chains of critical products [Quelle]. Within this workshop we aim at approaches that intend to increase the resilience in society and the economy with the help of AI technologies. 

 

Call for Papers 

The usual and established processes in society and economy are subject to the constant risk of being disrupted by events that occur. Increasing resilience in this context means being able to deal with these events in the best possible way. Approaches can fall into three categories: Preparation to, handling of, and learning from events. Being well prepared, e.g., through planning and forecasting approaches, can help to deal with upcoming events and therefore increase the overall resilience. But not all events allow for a suitable preparation. Then, methods for processing large amounts of data to establish a precise situation awareness are especially important. Also, decision support systems can help to empower people to decide and act accurately and within a short response time. Finally, insights can also be gained from the documented data in the post-processing of an event. This results in a wide range of topics that can be addressed in this workshop. We welcome success as well as failure stories and especially submissions with a practical but also a more theoretical focus. 

We welcome papers on the following and any related topics: 

  • Resilience in crisis situations: Prevention, treatment, aftercare 

  • Adversarial Attacks: https://de.wikipedia.org/wiki/Adversarial_Attack  

  • Barriers and gaps between research and practice – what prevents the application of AI research in practice or which AI-related topics must be studied and addressed in order to make AI methods applicable and improve resilience in society and business 

  • AI for assuring the resilience of applications or other technical systems 

  • Assuring the resilience of AI systems (internal and from external influences) 

  • Dealing with fuzziness – dealing with information sources of different trustworthiness 

  • Demands of flexibility in the execution of knowledge-intensive situations and processes 

  • Decision support systems to increase resilience 

  • Prediction 

  • Explainability of AI - Semantic Technologies - Knowledge Representation - Human-Machine Collaboration 

  • Hybrid AI approaches 

 

Names and affiliations 

Eric Rietzke - German Research Center for Artificial Intelligence 

Eric Rietzke is a senior researcher at the German Research Center for Artificial Intelligence (DFKI) in the department Smart Data & Knowledge Services / Experience-based Learning Systems at the outpost in Trier. He received his Ph.D. from the University of Trier on his research about semantic technologies and their utilization for knowledge-intensive processes. Within the DFKI he is in charge of research projects like the SPELL project, which he supervises as project manager. SPELL as a research project aims to improve the resilience of our society by providing a Semantic Platform for Control Centers and Situation Centers to support the joint coordination of complex events. 

 

Thomas Hoppe - Fraunhofer FOKUS 

Thomas Hoppe is a senior researcher and project manager at the Fraunhofer Institute for Open Communication Systems (FOKUS) in the Data Analytical Center (DANA), in Berlin. He received his doctoral degree from the Technical University Dortmund in the area of logic programming for an innovative approach for incremental partial deduction. Currently, he is in charge of several application-oriented research projects at DANA and leads the project consortium ResKriVer. The ResKriVer project aims to improve the communication and information distributed supply chain networks in order to improve their resilience in crisis situations and during catastrophes. 

 

Melanie Reuter-Oppermann - TU Darmstadt 

Melanie Reuter-Oppermann is a postdoctoral researcher in the Information Systems group at the Technical University of Darmstadt. In 2017, she received her PhD in Operations Research from the Karlsruhe Institute of Technology (KIT) on the analysis and optimization of Emergency Medical Services (EMS) systems. At KIT, she established the HealthCareLab at the Karlsruhe Service Research Institute. She is a joint coordinator of the European Working Group on Operational Research Applied to Health Services (ORAHS). In her research, she applies Information Systems and Operations Research methods to support decision making in healthcare. Besides EMS, her recent research interest is in primary care services, hospital and blood logistics as well as crisis management. She recently received the Julius von Haast Fellowship from the Royal Society of New Zealand. Within the SPELL project, she works on the design of AI-based EMS and first responder services as well as the development of the SPELL business model. 

 

Submission Details 

Papers should be formatted according to the Springer LNCS format. The length of each paper should not exceed 6 pages for a short paper and 12 pages for a long paper. All papers must be written in English and submitted in PDF format via the EasyChair system. 

 

Important Dates

  • Submission Deadline: July 15, 2022
  • Notification of Authors: August 10, 2022
  • Camera-ready Paper: August 31, 2022
  • Workshop: September 19 or 20, 2022

 

Preliminary Agenda

  • Ante meridiem

    • Keynote by 2 speakers about ongoing research projects with a focus to resilience (SPELL, ResKriVer) 

    • Presentation – 15 min per Paper + 5 min Q/A 

  • Post meridiem 

    • Poster presentation – Open discussions