Context-Aware Knowledge Management for Socio-Cyber-Physical Systems: New Trends towards Human-Machine Collective Intelligence
Alexander Smirnov, SPIIRAS, Russian Federation
Managing Knowledge-intensive Business Processes: Challenges, Scenarios, Technologies
Manfred Reichert, Ulm University, Germany
Hybrid Intelligence: AI Systems That Collaborate with People Instead of Replacing Them
Frank van Harmelen, The Hybrid Intelligence Center & Vrije Universiteit Amsterdam, Netherlands
Context-Aware Knowledge Management for Socio-Cyber-Physical Systems: New Trends towards Human-Machine Collective Intelligence
Alexander Smirnov
SPIIRAS
Russian Federation
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Brief Bio
Prof. Alexander Smirnov is a Head of Computer Aided Integrated Systems Laboratory, St.Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS). He received his Ph.D from St. Petersburg State University of Electrical Engineering (1984) and Dr.habil. from SPIIRAS (1994), and became a Full Professor in 1998. Also, he is a Professor and a Head of International Laboratory on Intelligent Technologies for Socio-Cyberphysical Systems, ITMO University, St. Petersburg (from 2014), and a Founder of Joint Master Program on Business Informatics between ITMO University and Rostock University (Germany). He has been involved in projects sponsored by Ford, Nokia, Festo, US DoD, European Research Programs (Information Society Technologies, Esprit, Eureka/Factory, etc.), and Russian agencies in the areas of distributed intelligent systems, ontology management, intelligent decision support systems, etc. He is a member of technical committees of IFIP TC WG5.1 on Global Product Development for the Whole Life-Cycle, IEEE SMC TC on Cyber-Physical Cloud Systems, IEEE SMC TC on Cognitive Situation Management, IFAC TC 5.1 on Manufacturing Plant Control, and a fellow of the European Academy of Industrial Management. He is a member of Advisory Committee & Editor Boards: Journal of Intelligent Manufacturing; International Journal of Multiagent and Grid Systems; International Journal of Data Analysis Techniques and Strategies; Management and Production Engineering Review; International Journal of Product Lifecycle Management. His current research is in the areas of ontology-driven information integration, corporate knowledge management, context management, operational decision support, socio-cyber-physical systems, human-computer cloud. He published more than 350 research papers in reviewed international journals and proceedings of international conferences, books, manuals.
Abstract
The competitiveness of companies and organizations heavily depends on how they maintain and access highly decentralized up-to-date information & knowledge coming from various resources located in their Socio-Cyber-Physical Systems. Such systems tightly integrate heterogeneous resources of the physical world and IT (cyber) world together with social networking concepts. Context-Aware Knowledge Management is becoming de facto one of the required business strategies in these systems. Its goal is to facilitate knowledge transfer and sharing in the context of business structures and activities bound together with the cultural norms. This keynote presents new trends (including role-based organization, dynamic motivation mechanisms and multi-aspect ontology) in knowledge management for socio-cyber-physical systems. Such trends can facilitate creation of innovative IT & HR environments based on human-machine collective intelligence, where information & knowledge are shared between participants and across collectives of participants, who can be both people (collective intelligence as the methods used by humans to act collectively for problem solving) and software services (based on artificial intelligence models). The keynote considers examples of trends and their implementation experience in a global production company.
Managing Knowledge-intensive Business Processes: Challenges, Scenarios, Technologies
Manfred Reichert
Ulm University
Germany
Brief Bio
Manfred is Professor of Computer Science and Director of the Databases and Information Systems Institute at Ulm University, Germany. His research spans across the fields of digital services, information systems, business process management, and process flexibility. Moreover, he has been engaged in many projects related to healthcare, logistics, automotive engineering, and Industry 4.0. Currently, he collaborates with several large companies, including Daimler,BMW Uhlmann Pac Systems, and adesso. Manfred was PC co-chair of the BPM’08, CoopIS’11, and EDOC’13 conferences, and general chair of the BPM’09 and EDOC’14 conferences as well as the BPM’15 workshops. He received several best paper wards (e.g. OTM’05, EDOC’08, AIMS‘17) as well as the BPM Test of Time Award at the BPM’13 conference. Finally, he is co-founder of the AristaFlow Ltd. and co-author of a Springer book on process flexibility.
Hybrid Intelligence: AI Systems That Collaborate with People Instead of Replacing Them
Frank van Harmelen
The Hybrid Intelligence Center & Vrije Universiteit Amsterdam
Netherlands
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Brief Bio
Frank van Harmelen has a PhD in Artificial Intelligence from Edinburgh University, and has been professor of AI at the Vrije Universiteit since 2001, where he leads the research group on Knowledge Representation. He was one of the designers of the knowledge representation language OWL, which is now in use by companies such as Google, the BBC, New York Times, Amazon, Uber, Airbnb, Elsevier, Springer Nature, XMP, and Renault among others. He co-edited the standard reference work in his field (The Handbook of Knowledge Representation), and received the Semantic Web 10-year impact award ifor his work on the open source software Sesame (over 200.000 downloads). He is a Fellow of the European Association for Artificial Intelligence, member of the the Dutch Royal Academy of Sciences (KNAW), of The Royal Holland Society of Sciences and Humanities (KHWM) and of the Academia Europaea, and is adjunct professor at Wuhan University and Wuhan University of Science and Technology in China.
Abstract
Much of current AI research is implicitly aimed at building systems that replace humans: self-driving cars to replace Uber drivers, translation software replacing interpreters, image analysis software replacing radiologists. But it's becoming increasingly clear that machine intelligence will be rather different from human intelligence. It is therefore more interesting to build AI systems that collaborate in hybrid teams of people and machine, in order to combine their complementary skills. This will require that we start asking a whole set of new research questions. How to equip AI systems with a "theory of mind" to make them collaborative? How to make AI systems adaptive to changes in the team and the environment? How to instill moral values into these systems? And of course how to make them explainable? We will outline a research agenda for hybrid intelligence and present some early results from researchers worldwide into hybrid intelligence.