-------- Forwarded Message --------
CALL FOR PAPERS AMCIS 2021
Minneapolis, MN, August 10-14, 2022
Paper submission deadline: March 1 (5:00pm Eastern Standard Time,
US)
Submission System Link:
https://new.precisionconference.com/user/login
Track: AI and Semantic Technologies for Intelligent Information
Systems
Sponsoring SIG: SIGODIS
Track Description:
The purpose of this track is to provide a forum for academics and
practitioners to identify and explore the issues, opportunities,
and
solutions using Artificial Intelligence, computational ontologies,
data
driven IS, and intelligence related to business and systems
including the
social web, intelligent systems design, implementation,
integration and
deployment. An increasing number of artificial intelligence-based
systems
are being developed in different application domains employing a
variety of
tools and technologies. This track is intended to increase
cross-fertilization of ideas from these areas, share lessons
learned and
stimulate areas for further research.
Best papers from this Track will be fast tracked for publication
in a
special issue of International Journal of Intelligent Information
Technologies (
http://www.idea-group.com/IJIIT).
Track Chair:
Don Heath, University of Wisconsin Oshkosh,
drheath2@gmail.com
<mailto:drheath2@gmail.com>
Mini-tracks:
Mini-Track I: Social, Ethical, & Practical Impacts of AI for
Organizations
and Individuals
AI is an important and increasingly pervasive tool of industry
whose
widespread adoption has given rise to several criticisms, such as
lack of
transparency of analytical models, lack of explainability of
results,
workforce disruption, and the potential to introduce or perpetuate
implicit
biases. The aim of this mini-track is to provide a forum for
addressing the
social, ethical, and practical aspects of AI and ML. Particularly,
papers
exploring the impact of AI/ML through various analytic lenses
including
societal, organizational, and individual perspectives are welcome.
Mini-Track Co-Chairs:
Vijayan Sugumaran,
sugumara@oakland.edu
<mailto:sugumara@oakland.edu>
Stefan Kirn,
stefan.kirn@uni-hohenheim.de
<mailto:stefan.kirn@uni-hohenheim.de>
Mini-Track II: Innovative Technologies for Managing Data-intensive
Systems
Evoked by recent trends, such as big data, data science or cloud
computing,
the planning and engineering of IS in today's data-driven world is
getting
progressively more complex. In many cases, sophisticated
approaches are
required to overcome the data-intensive nature of such endeavors.
At this
point, established technologies, as they have been used for many
years, are
reaching their limits. However, innovative technologies and
concepts, such
as artificial intelligence, automation, cloud computing,
composable
architectures, continuous integration, micro services, domain
specific
ontologies or decision support systems appear to be promising
"enablers" to
meet the current demands. To overcome their realization
shortcomings, a
plethora of facets must be handled. Hence, in this mini-track, we
welcome a
variety of research approaches including, but not limited to,
theoretical
articles, reviews and use case studies that are related to the use
of
innovative technologies for planning, engineering, deploying,
testing and
operating data-intensive systems.
Mini-Track Co-Chairs:
Matthias Volk,
matthias.volk@ovgu.de
<mailto:matthias.volk@ovgu.de>
Daniel Staegemann,
daniel.staegemann@ovgu.de
<mailto:daniel.staegemann@ovgu.de>
Mini-Track III: Promises and Perils of Artificial Intelligence and
Machine
Learning: Disruption, Adoption, Dehumanisation, Governance, Risk
and
Compliance
In the last decade, Artificial Intelligence (AI) and Machine
Learning (ML)
have developed from peripheral technologies to dominant drivers of
innovation. They are routinely used to recognize images; parse
speech;
respond to questions; make decisions; and replace humans. Given
that AI and
ML tools are becoming a part of our everyday lives, it is critical
that
researchers and practitioners understand their state of art,
adoption and
influence. Improperly deployed AI and ML tools can violate
privacy, threaten
safety, and take questionable decisions that can affect
individuals,
organizations and ultimately society. This minitrack will focus on
the
promises and perils of AI and ML with a particular focus on (a)
adoption,
(b) disruption, (c) potential dehumanisation, and (c) governance,
risk,
compliance and ethical mechanisms required to protect and enhance
human
wellbeing. We welcome wide-ranging papers with qualitative and
quantitative
orientations; with theoretical and practical contributions; from
personal,
organizational and societal perspectives.
Mini-Track Co-Chairs:
Valeria Sadovykh,
valeriasadovykh@gmail.com
<mailto:valeriasadovykh@gmail.com>
David Sundaram,
d.sundaram@auckland.ac.nz
<mailto:d.sundaram@auckland.ac.nz>
Kevin Craig,
kevin@kevincraig.net
<mailto:kevin@kevincraig.net>
Mini-Track IV: Artificial Intelligence, Machine Learning, and
Digital
Transformation
Artificial Intelligence (AI) and Machine Learning (ML) are
redefining
businesses and accelerating digital transformation. The areas of
artificial
intelligence, machine learning, digital transformation, analytics,
visualization, human-AI interaction, and a variety of AI and
digital
transformation topics have become critical to businesses as they
navigate
the pandemic, endemic, and new normal landscapes. The purpose of
this
mini-track is to provide a venue and forum for researchers
involved in these
bleeding-edge technologies to share research findings, explore new
research
directions, and build networks.
Mini-Track Co-Chairs:
John Erickson,
johnerickson@unomaha.edu
<mailto:johnerickson@unomaha.edu>
Keng Siau,
klsiau@cityu.edu.hk <mailto:klsiau@cityu.edu.hk>
Mini-Track V: Multi-modal Data Analytics for Intelligent Systems
In this era of data explosion, multi modal data from various
sensors have
been widely available to solve complex challenging problems in
various
application areas like automation industry, health care,
logistics, smart
city, transportation and many more. The solution to design
artificial
intelligent system has been feasible with the growth of
intelligent
techniques like deep learning, reinforcement learning which can
address the
different aspects of these challenges.
This mini track submission aims to bring cross-disciplinary
original
research and review articles with a focus on integrated concepts
and
technologies, insights from the multi-modal data, design of
intelligent
system and how to deal with these challenges under
resources-constrained
environments. The contribution can be new models, algorithms,
innovative
applications, but also practical solutions that particularly focus
on how to
apply generic techniques to specific applications.
Mini-Track Co-Chairs:
Amudha J.,
j_amudha@blr.amrita.edu
<mailto:j_amudha@blr.amrita.edu>
Tiago Falk,
tiago.falk@inrs.ca <mailto:tiago.falk@inrs.ca>
Supriya M.,
m_supriya@blr.amrita.edu
<mailto:m_supriya@blr.amrita.edu>
Rajakumar Arul,
rajakumararul@ieee.org
<mailto:rajakumararul@ieee.org>
Mini-Track VI: Intelligent Systems and Machine Learning-
Solutions,
Technologies and Techniques
The world of Artificial Intelligence and Machine Learning
continues to
accelerate at an unfathomable pace and made its foot print in
almost all the
fields. While artificial intelligence refers to the concept of
creating
intelligent machines that can mimic human cognitive abilities and
behaviors,
machine learning refers to a specific application of AI where
machines can
learn from data without being explicitly programmed. Intelligent
systems are
technologically superior machines that understand and react to
their
surroundings. Intelligent systems find their applications in a
variety of
fields, including factory automation, Assistive robotics,
Military,
Medical-care, Education, Intelligent-transportation etc. Machines
have
recently demonstrated the ability to learn and even master tasks
that were
previously thought to be extremely difficult for machines,
demonstrating
that machine learning algorithms are potentially useful elements
of
detection and decision support systems. However these intelligent
systems
have lots of potential research problems that need to be addressed
in
future.
Mini-Track Co-Chairs:
Annie Uthra R
annieu@srmist.edu.in
<mailto:annieu@srmist.edu.in>
Submission Information:
URL for submission:
https://new.precisionconference.com/user/login
URL for types of submission & instructions:
https://amcis2022.aisconferences.org/submissions/types-of-submissions/
Important dates:
* January 21, 2022: Manuscript submissions begin
* March 1, 2022: Completed research and ERF submissions are due at
5
p.m. EST
* April 15, 2022: Workshop, panel, TREO and PDS submissions are
due at
5 p.m. EST
================================================
Vijayan Sugumaran, Ph.D.
Distinguished Professor, Management Information Systems
Chair, Department of Decision and Information Sciences
Co-Director, Center for Data Science and Big Data Analytics
School of Business Administration
Oakland University
Rochester, MI 48309
Phone: 248-370-4649
Fax: 248-370-4275
Email:
sugumara@oakland.edu <mailto:sugumara@oakland.edu>
================================================
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