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CfP Special Issue on "The Dark Sides of AI"
Submission Deadline: October 31, 2020
Guest Editors
Lin Xiao, Nanjing University of Aeronautics and Astronautics,
China, xiaolin(at)nuaa.edu.cn
Xiao-Liang Shen, Wuhan University, China, xlshen(at)whu.edu.cn
Xusen Cheng, Renmin University of China, China,
xusen.cheng(at)ruc.edu.cn
Jian Mou, Xidian University & University of Ottawa, China,
jian.mou(at)xidian.edu.cn
Alex Zarifis, Loughborough University, UK,
a.zarifis(at)lboro.ac.uk Theme
Artificial intelligent (AI) is believed to bring about significant
changes to networked digital business, and it facilitates smart
services and digital transformation. In particular, AI is regarded
among the current top five emerging technologies when
organizations execute the digital first strategy. The Gartner
survey showed that 59% of organizations are gathering information
to build their AI strategies, while the remainder have already
made progress in piloting or adopting AI solutions (Panetta,
2018), indicating that we are facing a new era of AI, which brings
both unprecedented opportunities and emerging challenges.
Academically, AI has attracted some initial attention in business
research with respect to its possible applications in the field of
information systems (e.g., Gursoy et al., 2019), tourism and
hospitality (e.g., Li et al., 2019), marketing (e.g., Syam and
Sharma, 2018), and financial management (e.g., Culkin and Das,
2017), to change the interaction between organizations and
customers, gain new insights and obtain greater business values
(e.g., increasing efficiency and effectiveness).
Regardless of the numerous opportunities that AI offers, there are
undoubtedly plentiful dark sides of AI that present enormous risks
for individuals, organizations and society, which are considered
as three most important dimensions for digitalization (Alt, 2018).
From an individual perspective, the issues of AI discrimination
have been reported by consumers in content recommendation and
product recommendation in electronic markets. From an
organizational perspective, the introduction of AI based
technologies is likely to influence the profitability of
companies, but in electronic markets the negative side of
high-frequency trading has also been reported on. Organizations
also face significant issues where the lack of a strategy relating
to implications of AI could affect critical business areas and
fail to address concerns from human workforce. From a societal
perspective, AI could potentially widen the gap amongst emerging
and developed markets as well as the rich and poor. The issue of
potential job losses due to AI technologies has also received
widespread attention.
Therefore, considering the ubiquitous use of AI in digital
business today, the significant negative or detrimental
consequences of AI to individuals, organizations and society
remain to be examined and are worthy of further research
attention. We thus organize this special issue and encourage the
potential authors to address this important but so far largely
neglected topic – the dark sides of AI in the electronic markets
contexts, including social networks, electronic commerce, digital
platforms, customer relationship management, etc.
Central issues and topics
The goal of this special issue is to create a platform to address
the “dark sides of AI” in digital networked business. Submissions
adopting qualitative or quantitative research approaches, and from
individual, organizational, and/or societal perspective are
welcome. Possible contributions may include, but are not limited
to, the following topics:
The potential harms resulted from the widespread use of AI in
electronic markets
The detrimental effect of benefits and the costs of using AI in
electronic markets
Understanding how individuals, organizations and societies can
minimize, prevent or respond to the dark side of AI in the digital
business worlds
Examining dark side outcomes, behaviors and practices that
accidently or unintentionally emerge by using AI in electronic
markets
The ethics of using AI in electronic markets
Approaches to lobbying, regulating and controlling dark side
behaviors and practices associated with AI usage in electronic
markets
The trust, security and privacy issues in using AI in electronic
markets
The antecedents and consequences of dark side using AI in
electronic markets
Case studies of dark side of AI in electronic markets
Behavioral, psychological, ethical, social and cultural issues
related to the dark sides of AI in electronic markets
Submission
Electronic Markets is a Social Science Citation Index
(SSCI)-listed journal (IF 3.553 in 2018) in the area of
information systems. We encourage original contributions with a
broad range of methodological approaches, including conceptual,
qualitative and quantitative research. Please also consider
position papers and case studies for this special issue. All
papers should fit the journal scope (for more information, see
www.electronicmarkets.org/about-em/scope/) and will undergo a
double-blind peer-review process. Submissions must be made via the
journal’s submission system and comply with the journal's
formatting standards. The preferred average article length is
approximately 8,000 words, excluding references. If you would like
to discuss any aspect of this special issue, you may either
contact the guest editors or the Editorial Office.
References
Alt, R. (2018). Electronic Markets and current general research.
Electronic Markets, 28 (2), 123-128.
Culkin, R. & Das, S. R. (2017). Machine learning in finance:
The case of deep learning for option pricing. Journal of
Investment Management, 15 (4), 92-100.
Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers
acceptance of artificially intelligent (AI) device use in service
delivery. International Journal of Information Management, 49,
157-169.
Li, J., Bonn, M. A. & Ye, B. H. (2019). Hotel employee's
artificial intelligence and robotics awareness and its impact on
turnover intention: The moderating roles of perceived
organizational support and competitive psychological climate.
Tourism Management, 73, 172-181.
Panetta, K. (2018). Gartner top 10 strategic technology trends for
2018. Accessed September 2019. Retrieved from:
https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2018/.
Syam, N. & Sharma, A. (2018). Waiting for a sales renaissance
in the fourth industrial revolution: Machine learning and
artificial intelligence in sales research and practice. Industrial
Marketing Management, 69, 135-146.
You may find the call for paper from the official website:
http://www.electronicmarkets.org/call-for-papers/single-view-for-cfp/datum/2020/02/12/cfp-special-issue-on-the-dark-sides-of-ai/
If you have any questions, please do not hesitate to contact me.
Best regards
Jian Mou
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