[AISWorld] [CFP] Data and Information Management Special Issue: Human-AI Interaction

[Kem]

Calls for Papers
Data and Information Management
Special Issue on Human-AI interaction

Submission Deadline: September 30, 2022
Submission website: https://www.editorialmanager.com/dim/

Special Issue Guest Co-Editors:
Yongqiang Sun, Wuhan University (sunyq at whu.edu.cn)
Xiao-Liang Shen, Wuhan University (xlshen at whu.edu.cn)
Kem Z.K. Zhang, Lakehead University (zzhang54 at lakeheadu.ca)

Introduction:
In this special issue, we are calling for papers that advance the existing
research on human-AI interaction. In the current wave of technological
evolution, the human-like capabilities possessed by AI challenge the
assumptions that researchers have held about how humans interact with IT
artifacts (Schuetz et al., 2020). AI, along with its ever-growing
capabilities to perceive, understand, react, and learn, is entering domains
that used to be exclusive to humans. This change greatly blurs the boundary
between humans and technology. In this regard, human-AI interaction remains
an open challenge in both industry and scientific communities. Unlike
interactions with traditional IT artifacts, new research questions arise
from human interactions with AI.

Interdisciplinary research has already shown that people tend to treat AI
as a human when interacting with AI. Therefore, AI should be viewed as an
autonomous and intelligent machine that interacts with humans, not simply
as an IT artifact. Due to the rapid iteration of AI, humans can interact
with AI in a more human-like way to an unprecedented degree. As a result,
the development of AI has led the changes in the research focus of
human-machine interaction. Some important questions need to be considered:
How does AI differ from previous IT artifacts? What role does the unique
anthropomorphic capability of AI play in human-AI interaction? Are there
unprecedented and unexpected problems in this new type of interaction?

However, research on human-AI interaction is still in the early stages. We
currently lack a deep understanding of the conceptualization, the
theorization, and the evolution of human-AI interaction, as well as both
positive and negative outcomes generated by such a new type of interaction.
Such understanding is necessary if scholars want to employ the work of
human-AI interaction to deepen their understanding of IT. We believe that
interdisciplinary research can take advantage of this opportunity to make
additional discoveries that will guide human-AI interaction. Based on the
above concerns, we aim to advance the discussions on the future of human-AI
interaction and contribute to the development of current and future
human-AI research.

This special issue aims to extend our current understanding of human-AI
interaction by leveraging various theoretical perspectives and methodological
approaches. The special issue welcomes submissions from all disciplines
with a special emphasis on data and information generated in human-AI
interaction. Units of analysis could be individuals, groups, organizations,
or society. Data could potentially be extracted from multiple sources and can
be subjective and/or objective. The methodology can be conceptual,
empirical, or computational.

Research topics may include, but are not limited to:
1. Literature review and meta-analysis of human-AI interaction research
2. Conceptual and theoretical framework of human-AI interaction
3. New theories and methodologies on human-AI interaction
4. Anthropomorphic features of AI
5. Human-AI interaction design
6. Human-AI symbiosis and harmony
7. Human-AI collaboration
8. Hybrid intelligence augmentation
9. Human-AI interaction in organizations
10. Subjective well-being in human-AI interaction
11. The dark sides of human-AI interaction
12. Misbehavior in human-AI interaction
13. Negative impacts of human-AI interaction
14. Trust and distrust in human-AI interaction
15. Privacy and cybersecurity in human-AI interaction
16. Legal and ethical challenges in human-AI interaction

Submission, Review and Timeline
We encourage original and high-quality submissions that are not submitted
to or accepted by other journals. Significantly extended version of
conference or workshop papers (essentially 30% novel content) are welcome.
The authors are also expected to highlight the relevance, the novelty, and the
contribution of the submitted article in the cover letter.

Submitted papers must conform to the author guidelines available on the DIM
journal website at https://www.elsevier.com/journals/data-and-information
-management/2543-9251/guide-for-authors. Authors are required to submit
their manuscripts online through the DIM submission site at
https://www.editorialmanager.com/dim/, and choose the article type "SI:
Human-AI interaction".

The special issue operates on a tight timeline, and authors should expect
quick turnaround for reviews and revisions. Submissions will be evaluated
by at least two independent reviewers. The review criteria include the
relevance to the special issue, novelty, clarity, originality, the
significance of contribution, technical quality, and quality of
presentation. The accepted papers will be published online first.

Please refer to more information about the special issue at:
https://www.journals.elsevier.com/data-and-information
-management/call-for-papers/special-issue-human-ai-interaction

Author guidelines:
https://www.elsevier.com/journals/data-and-information
-management/2543-9251/guide-for-authors


Kem Zhang
Lakehead University
zzhang54 at lakeheadu.ca