CALL FOR PAPERS: HICSS 54 “Collaboration with Cognitive Assistants and AI”
30. März 2020, von Prof. Dr. Eva Bittner
Wir freuen uns auf zahlreiche Einreichungen zu unserem Minitrack "Collaboration with Cognitive Assistants and AI" auf der HICSS 54.
ABOUT THE CONFERENCE
The HICSS is the longest standing scientific conference in the information systems and technology field. Since 1968, it has attracted high caliber scholars and professionals in academia, industry and government agencies around the world to present their cutting edge research. Throughout its 50 years of research HICSS authors have generated a sustained stream of innovative research ideas with 19,000+ publications, and many of them have resulted in seminal work. The 2016 impact factor was 2.4.
IMPORTANT DATES
June 15, 2020: Paper Submission Deadline (11:59 pm HST)
August 17, 2020: Notification of Acceptance/Rejection
September 4, 2020: Deadline for A-M Authors to Submit Revised Manuscript for Review
September 22, 2020: Deadline for Authors to Submit Final Manuscript for Publication
October 1, 2020: Deadline for at least one author of to register for HICSS-54
TRACK: Collaboration Systems and Technologies (Bob Briggs, Jay Nunamaker)
MINITRACK: Collaboration with Cognitive Assistants and AI
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MINITRACK DESCRIPTION
In the field of information systems, as well as in the computer science domain, artificial intelligence (AI) constitutes one of the most rapidly growing streams of research. This is mainly due to the fact that technological innovations enable the development of productive AI solutions (e.g. inherent in cognitive assistants) that provide compelling benefits in various fields of application.
However, despite the recent advances, we are still far away from a strong or general AI comparable to a human intelligence, especially when it comes to intelligence across certain domains or tasks. Therefore, the importance of the engagement of humans into the decision process of AI systems is widely acknowledged in research and practice. Although a considerable amount of exploration regarding such Human-AI-Collaboration has been conducted, the breadth and scope for dialogue and experimentation needs to be broadened. This minitrack aims to provide a place for such dialogue and support of a diverse community interested in taking the challenge further.
While all submissions should consider aspects of collaboration – the work of two or more knowledge sources (i.e. human and AI) towards a common goal -, we welcome all papers that present research in this area, independent of the centrality and strength of AI, the domain they address, and the methodology they apply.
Topics to be discussed in this minitrack include (but are not limited to) the following:
- Generalizable models, methodologies and theories to design and facilitate Human-AI-Collaboration
- Exemplary use cases in various fields of application that refer to
- collaborative work practices, in which a human actor collaborates with AI
- collaborative work practices, in which AI facilitates human collaboration
- Boundaries and Challenges of Human-AI-Collaboration
- Approaches for a new division of labor (including hand-offs) in references to the task structure and capabilities of AI and humans
- Decision models for deciding, whether, when and how to access human input
- Strategies to prevent mistakes and shortcomings of individual collaborators and the noise in the contributions of individual workers
- Effectiveness of Human-AI-Collaboration (e.g. effectiveness of different training strategies in improving the performance of workers for accomplishing complex tasks)
- Orchestration of learning (of the AI, from the AI, with the AI), e.g. human-in-the-loop learning
- Design of incentive structures for Human-AI-Collaboration
- Facilitation of continuous engagement in Human-AI-Collaboration
- User reactions when confronted with an AI collaborator
- Approaches for increasing user acceptance of collaboration systems with AI components
- Prototypes of Human-AI-Collaboration in various application domains (e.g. tutoring, service, etc.)
- Legal aspects, usability, explainability or transparency of Human-AI-Collaboration
- Ethical and philosophical examinations of the common goal in Human-AI-collaboration
MINITRACK CO-CHAIRS:
Eva Bittner (Primary Contact)
University of Hamburg
bittner@informatik.uni-hamburg.de
Philipp Alexander Ebel
University of St. Gallen
philipp.ebel@unisg.ch
Sarah Oeste-Reiß
University of Kassel
oeste-reiss@uni-kassel.de
Matthias Söllner
University of Kassel
soellner@uni-kassel.de