Call for Papers

CfP special issue on "The dark sides of AI"

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, Pusan National University, South Korea, jian.mou(at)pusan.ac.kr
• 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.

Special Note – AMCIS 2020

The guest-editors organized a conference mini-track “The dark sides of AI” in Americas Conference on Information Systems (AMCIS) 2020 (https://amcis2020.aisconferences.org/track-descriptions/#toggle-id-4). Authors interested in this special issue are encouraged to submit papers to this mini-track first, and this provides the potential authors an opportunity to receive developmental feedback and suggestions. However, authors who are unable to attend AMCIS will not be disadvantaged, and all papers will go through a full peer review process to decide which papers to include in this special issue.

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.

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