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Call for Submissions: The Interplay of Machines and Humans: State
of the Art and a Research Agenda for Hybrid Intelligence
Background
Research in the field of information systems provides a long
history of discussions of who is superior in predicting certain
outcomes: statistical methods or the human brain (Meehl 1954).
This debate keeps on flaring up due to the remarkable
technological advances in the field of artificial intelligence
(AI) such as solving tasks like object and speech recognition or
achieving significant improvements in accuracy through
deep-learning algorithms (Jordan and Mitchell 2015). Consequently,
serious concerns arise whether general intelligent machines will
take over jobs of humans and solves problems that previously
required the human intellect (McAfee and Brynjolfsson 2017).
However, achieving the development of human-level, general AI in
the next decades is rather doubted (e.g. Stanford 2016). The most
likely paradigm for the division of labor between humans and
machines is thus Hybrid Intelligence. This concept aims at using
the complementary strengths of human intelligence and AI to behave
more intelligent than each of the two could be in separation
(Kamar 2016).
While machines are particularly good in consistently solving
repetitive tasks that require the fast procession of huge amount
of date, humans have superior capabilities for emphatic or
intuitive tasks. Therefore, artificial intelligence rather
augments the human judgement through providing predictive
assistance. In such setting, where AI provides the human with
input that is then evaluated to make a judgement, human and
machines act as teammates. Vice versa AI systems can benefit and
learn from human input. This approach allows to integrate human
domain knowledge in the AI to design, complement and evaluate the
capabilities of machine intelligence in settings such as medicine
or semi-autonomous driving, where humans monitor the performance
of machines.
The paradigm of Hybrid Intelligence, thus, comprises two
interrelated directions: hybrid teamwork, where AI enlarges the
intelligence of humans and the augmentation of AI through the
input of humans. Within this workshop we will describe both
directions and provide insights into the current state of research
and practical applications in various domains.
This workshop intends to facilitate the discourse amongst IS
researchers interested in hybrid intelligence. We invite those who
are interested to shape the future of the field to join us in
Portsmouth. The workshop itself serves to present, discuss, and
organize the ideas submitted. In addition to that, we encourage
researchers that are involved in practice-oriented research
projects to submit a project description and to showcase their
projects within the workshop.
Possible topics of submissions include, but are not limited to:
· Generalizable models, methodologies and theories to design and
facilitate Hybrid Intelligence
· Approaches for a new division of labor 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 different training strategies in improving the
performance of workers for accomplishing complex tasks · Design of
incentive structures for a given task · Approaches for increasing
user acceptance of systems with AI components
Submission Guidelines:
· The workshop participants will develop their ideas in a short
paper of not more than two (2) pages (ECIS paper template). · The
submissions should be e-mailed to Dominik Dellermann (
dellermann@uni-kassel.de) and Philipp Ebel
(
ph.ebel@uni-kassel.de).
In addition to that, interested researchers might participate in
the workshop without submitting a paper, but by discussing the
manuscripts of the other workshop participants.
Important Dates:
Submission Deadline: 30.04.2018
Notification to Authors: 11.05.2018
Date of the workshop: 25.06.2018
Workshop Chairs
* Philipp Ebel, University of Kassel, Germany
(corresponding chair)
* Dominik Dellermann, University of Kassel, Germany
Program Committee
Sarah Oeste-Reiß, University of Kassel, Germany
Matthias Söllner, University of St. Gallen, Switzerland
Jan Marco Leimeister, University of St. Gallen, Switzerland
Further information can be found on the ECIS 2018 workshop
website:
http://ecis2018.eu/call-for-workshops-or-tutorials/
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