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

[sunyq at whu.edu.cn]

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 


Yongqiang Sun
School of Information Management
Wuhan University


sunyq at whu.edu.cn