[AISWorld] CFP AMCIS 2023 - Track: Artificial Intelligence and Semantic Technologies for Intelligent Information Systems

[Vijayan Sugumaran]

CALL FOR PAPERS AMCIS 2023

Panama City, Panama, August 10-12, 2023

Paper submission deadline: March 1 (10:00am 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 Chairs:

Vijayan Sugumaran, Oakland University, sugumara at oakland.edu
<mailto:sugumara at oakland.edu>  

Don Heath, University of Wisconsin Oshkosh, drheath2 at gmail.com
<mailto:drheath2 at 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.

 

Potential topics (but not limited to):

     * Behavioral and organizational aspects of AI and ML

     * Automation of work through AI and ML

     * Legal, ethical, governance issues and biased use of AI/ML

     * Effectiveness, business performance, job displacement, and dark side
of AI/ML

     * Standards and frameworks for AI/ML modeling and implementation

     * Explainable AI

     * AI Adoption diffusion

     * Ethical AI

     * Self-regulation across industries

     * Implicit and explicit bias in AI application

     * Social justice and social inclusion

 

Mini-Track Co-Chairs:

Vijayan Sugumaran, Oakland University,  sugumara at oakland.edu
<mailto:sugumara at oakland.edu> 

Stefan Kirn, Universität Hohenheim, stefan.kirn at uni-hohenheim.de
<mailto:stefan.kirn at uni-hohenheim.de> 

 

Mini-Track II: 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 mini-track 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, University of Auckland, valeriasadovykh at gmail.com
<mailto:valeriasadovykh at gmail.com> 

David Sundaram, University of Auckland, d.sundaram at auckland.ac.nz
<mailto:d.sundaram at auckland.ac.nz> 

Kevin Craig, Auburn University, kevin at kevincraig.net
<mailto:kevin at kevincraig.net> 

 

Mini-Track III: Interplay and Acceptance of Intelligent Information Systems

In recent years, digital transformation has not only led to increased
acceptance of the use of information technologies but also great challenges.
As a result, new topics and trends emerged to address the steadily
increasing amount of data and its efficient and innovative exploration.
Apart from the main drivers such as artificial intelligence and cloud
computing, concepts like edge computing, big data, microservices, deep
learning, distributed systems as well as composable architectures came into
play both in the application and in the implementation of corresponding
systems. Although these topics are widely recognized today, their interplay
provides new potentials and reveals novel challenges. To overcome these, a
plethora of facets must be handled. Hence, in this mini-track, we welcome a
variety of research approaches related to the investigation of related
topics, their application, behavioral aspects, managerial viewpoints as well
as the engineering of the corresponding systems.

 

Mini-Track Co-Chairs:

Matthias Volk, Otto-von-Guericke University Magdeburg, matthias.volk at ovgu.de
<mailto:matthias.volk at ovgu.de> 

Daniel Staegemann, Otto-von-Guericke University Magdeburg,
daniel.staegemann at ovgu.de <mailto:daniel.staegemann at ovgu.de> 

 

Mini-Track IV: Unintended Consequences of AI

The widespread adoption of artificial intelligence (AI) applications is
having a definitive effect on organizations and society. AI applications are
developed with goals of increased revenue and efficiency in business
processes. Yet, there have been numerous cases that have shown AI can have
unintended consequences. Notable examples include Uber’s fatal autonomous
vehicle accident and failure of Watson for Oncology due to biased results.
Application of AI-technologies by organizations and government have the
potential to affect (sometimes adversely) large portions of the populations,
possibly containing vulnerable societal groups. These unintended
consequences of AI can be a source of legal, financial, and reputational
risk to organizations. For this mini-track, we welcome wide-ranging papers
with qualitative and quantitative orientations; with theoretical and
practical contributions; from personal, organizational and societal
perspectives that explore causes, risks, and mitigation strategies for AI
applications that can cause legal, financial, and reputational damage to
organizations and social harm.

 

Mini-Track Co-Chairs:

Madhav Sharma, Kansas State University, madhavsharma at ksu.edu

David Biros, Oklahoma State University, david.biros at okstate.edu
<mailto:david.biros at okstate.edu> 

 

Mini-Track V: Intelligent Systems based on Multi-Modal Data

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. The contribution can be new
models, algorithms, innovative applications, but also can be practical
solutions that particularly focus on how to apply generic techniques to
specific applications. Multi modal data catering to needs of solving complex
challenging problems in education, health care, agriculture, logistics,
smart city, transportation and many more.

 

Mini-Track Co-Chair:

Amudha J., Amrita Vishwa Vidyapeetham, j_amudha at blr.amrita.edu
<mailto:j_amudha at blr.amrita.edu> 

 

Mini-Track VI: Artificial Intelligence and Machine Learning- Applications,
Solutions 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-Chair:

Annie Uthra, SRM Institute of Science and Technology, annieu at srmist.edu.in
<mailto:annieu at srmist.edu.in>  

 

Submission Information:

URL for submission: https://new.precisionconference.com/user/login 

URL for types of submission & instructions:
https://amcis2023.aisconferences.org/submissions/types-of-submissions/ 

 

Important dates:

*	January 6, 2023: Manuscript submissions begin
*	March 1, 2023: Completed research and ERF submissions are due at
10:00 a.m. EST
*	May 9, 2023: TREOs, PDS and Workshops, and Panels submissions are
due at 10 a.m. EST

 

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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 at oakland.edu <mailto:sugumara at oakland.edu> 

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