[AISWorld] AMCIS 2024 CFP: Behavioral Research in Data Analytics and Artificial Intelligence (Track: SIGDSA)

[Nima Kordzadeh]

*Mini-track: *Behavioral Research in Data Analytics and Artificial
Intelligence

*Track:* Data Science and Analytics for Decision Support (SIGDSA)


Salt Lake City, Utah -- August 15-17, 2024

https://amcis2024.aisconferences.org/track-descriptions/#toggle-id
<https://amcis2024.aisconferences.org/track-descriptions/#toggle-id-8>-8



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*Mini-track Description:*



The ability to leverage data analytics (DA) and artificial intelligence
(AI) technologies has become a crucial factor for firm success [1, 2]. With
the availability of data characterized by high velocity, volume, and
variety, many firms have invested in DA and AI technologies to improve the
quality of their decision-making. However, firms also acknowledge the
critical role of human factors, such as human cognition, emotion, judgment,
and behavior, in developing, implementing, and using such technologies. For
example, data analysts need to integrate aspects that are not captured by
analytical tools, such as ethical principles and intuition, into their
analytics processes and decisions [3, 4].

The focus of this minitrack is to explore and enhance understanding of the
behavioral aspects of implementing and using DA and AI technologies. In
particular, this minitrack focuses on perceptions, attitudes, intentions,
and behaviors related to analytics and AI systems, and their impact on
decision-making processes and outcomes in organizational and social
settings [5].

Suggested topics include, but are not limited to:

* Impact of DA and AI use on decision-making quality

* Ethical and privacy aspects of using DA and AI

* Trust in DA and AI

* Human-AI augmentation

* User-centered DA and AI

* Conversational AI

* Anthropomorphism in AI

* Algorithm aversion and appreciation

* Algorithmic bias and fairness

* Explainable AI

* Technostress effects of DA and AI use





*References: *

*1.* Chen, H., Chiang, R.H., Storey, V.C. (2012). Business Intelligence and
Analytics: from Big Data to Big Impact. MIS Quarterly.1165–1188.

*2.* Jain, H., Padmanabhan, B., Pavlou, P. A., & Raghu, T. S. (2021).
Editorial for the Special Section on Humans, Algorithms, and Augmented
Intelligence: The Future of Work, Organizations, and Society. Information
Systems Research, 32(3), 675-687.

*3.* Kordzadeh, N., & Ghasemaghaei, M. (2022). Algorithmic Bias: Review,
Synthesis, and Future Research Directions. European Journal of Information
Systems. 31(3), 388-409.

*4.* Someh, I., Davern, M., Breidbach, C. F., & Shanks, G. (2019). Ethical
Issues in Big Data Analytics: A Stakeholder Perspective. Communications of
the Association for Information Systems, 44(1), 34.

*5.* Baesens, B., Bapna, R., Marsden, J.R., Vanthienen, J., Zhao, J.L.
(2016) Transformational Issues of Big Data and Analytics in Networked
Business. MIS Quarterly, ;40(4), 807-818.

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*IMPORTANT DATES:*

   - January 5, 2024: Manuscript submissions begin
   - March 1, 2024: Submissions are due at 10 am EST
   - May 8, 2024: TREOs, PDS, Workshop, and Panel submissions are due at 10
   am EST



*Mini-track Co-chairs:*



   - Nima Kordzadeh, Worcester Polytechnic Institute, nkordzadeh at wpi.edu
   - Maryam Ghasemaghaei, McMaster University, ghasemm at mcmaster.ca



We look forward to receiving your submissions!



----

Nima Kordzadeh, Ph.D.

Assistant Professor of Information Systems & Data Science

Worcester Polytechnic Institute | Business School
<https://www.wpi.edu/academics/business>

100 Institute Rd, Worcester, MA 01609

E-mail: nkordzadeh at wpi.edu