By 2025, nearly a quarter (24%) of global GDP will come from digital technologies such as AI (World Economic Forum). AI has been claimed to offer almost unlimited potential across sectors and industries, ranging from reinventing business models to redesigning the customer experience to decision-making (Duan et al., 2019) to changing the nature and the future of work (Schwartz et al., 2019).
AI in the workplace environment may affect the nature of work, replace specific roles currently performed by humans, or even better, enhance human capabilities (e.g. AI-enabled recruiting) (Dwivedi et al., 2019). It is estimated that till 2030, automation and AI will significantly impact the one third of our work activities (Manyika et al., 2017). This means that the current way we work and operate might be altered radically, which can potentially cause significant societal changes.
· Challenges of AI in decision making
- AI in society and discriminatory bias
- Ethical, policy and governance implications
- AI decision-making
- Trust and transparency of AI-based decision making
- Digital transformation via AI
- AI and its impact on the nature and future of work
- Social, behavioral, and economic implications of AI
- AI-enabled changes to business strategy, business models and ecosystems
- AI-enabled changes to innovation and value creation processes
- Challenges and implications for Information Systems research
Forms of Submission
This Special Issue will consist of invited papers that are extended or modified versions of selected papers accepted at the 20th IFIP I3E Conference on e-Business, e-Services and e-Society (www.I3E2021.com), Galway, Ireland. The submission will be a substantial revision of the conference publication, and the authors will be required to submit a letter detailing the difference between their conference paper and the new version. The invited papers will go through peer review; if an invited conference paper does not receive a satisfactory review, the paper will not be considered for the Special Issue.
Submission Instruction
Manuscripts must be submitted in PDF format to the International Journal of Information Management online submission system at https://www.evise.com/profile/#/IJIM/login.
Authors should select “SI: Decisions & Work”, from the “Choose Article Type” pull- down menu during the submission process. All contributions must not have been previously published or be under consideration for publication elsewhere.
Paper submissions must conform to the format guidelines of International Journal of Information Management available at
Important dates
- Submission deadline: 30th November 2021
- Notification of first round reviews: 31st January 2022
- Revised Manuscripts due: 31st March 2022
- Notification of second round reviews: 31st May 2022
- Final Version Due: 31st July 2022
Guest Editors
- Denis Dennehy: ( [email protected]) National University of Ireland Galway, Ireland
- Anastasia Griva: ( [email protected]) National University of Ireland Galway, Ireland
- Nancy Pouloudi: ([email protected]) Athens University of Economics and Business, Greece
- Matti Mäntymäki: ([email protected]) University of Turku, Finland
- Ilias Pappas: (Ilias Pappas <[email protected]) University of Agder, Norway
References
Davenport, T. 2018. The AI advantage: How to put the artificial intelligence revolution to work, MIT Press.
Duan, Y., Edwards, J.S. and Dwivedi, Y.K., 2019. Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, pp.63-71.
Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A. and Galanos, V., 2019. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, p.101994. DoI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., Ko, R. and Sanghvi, S., 2017. Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey Global Institute, 150 https://www.mckinsey.com/~/media/mckinsey/featured%20insights/Future%20of%20Organizations/What%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Report-December-6-2017.ashx
Schwartz, J. Hagel, J. Wool, M. and Monahan, K. 2019. “Reframing the future of work” February 19. MIT Sloan Management Review. https://sloanreview.mit.edu/article/reframing-the-future-of-work/
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