Call for Papers

The proliferation of Generative Artificial Intelligence (GAI) tools such as ChatGPT and Midjourney is affecting a wide range of organizational processes and outcomes, including not only more “algorithmic” ones such as the assembly of work teams, the dynamic reconfiguration of roles and workflows, and quality control, but also more “heuristic” ones such as producing advice and generating the building blocks of innovation in various fields (Faraj et al., 2018; Newton, 2019; Popova et al., 2018; von Krogh, 2018). Indeed, creative tasks and activities that were once considered to be uniquely human, such as the production and revision of visual, auditory, and textual ideas and products, are seeing an increasing involvement of AI in the creative process.
 
Although reflections on the role of AI in creativity have been discussed for several decades (see Boden, 1998), recent advancements underscore the necessity for updating and building theory, as well as for phenomenon-based inquiries. Pioneering organizational research has started addressing the intersection of creativity and (G)AI by investigating topics such as the potential for augmentation of human creativity through human-AI interaction (Amabile, 2020; Krakowski et al., 2022), the impact of collaborating with AI on creative processes and employee performance (Jia et al., 2023; Magni & Jeong, 2023; Vardanyan, 2022), human-AI cocreation (Wingström et al., 2023), and how creativity is assessed differently depending on the involvement of AI in the creative process (Magni et al., 2023; Schweitzer & De Cremer, 2023).
 
However, many questions on the impact of (G)AI proliferation on creativity remain unanswered. Specifically, it remains unclear whether the creativity generated by or with the help of AI can be creativity that makes-to-last, or whether it is just a rather random recombination of existing items that “reproduce superficial aspects of fleeting reality” – in the words of Plato. In other words, can AI help generate creativity that makes-to-last and, if so, how? And how does AI generated creativity change how we evaluate and assess creative ideas and products? More fundamentally, how is the involvement of AI in creative processes changing our very definition and conceptualization of creativity?
 
We invite quantitative, qualitative, and conceptual contributions that advance our understanding on the impact of (G)AI on various facets of creativity in organizations, including (but not limited to) the following areas and related research questions:
 
The effect of (G)AI integration on human creativity:

• How does (G)AI help and/or hinder human creativity?

• What creativity aspects cannot or should not be automated with the use of (G)AI?

 
Human-AI co-creation:

• How does the integration of (G)AI in work processes change the creative process?

• How does H-AI co-creation affect the management of creativity in organizations?

 
The evaluation of (G)AI creativity:

• How can humans assess AI-generated creativity without falling prey to cognitive biases?

• Should AI-generated creativity be evaluated with different criteria than human creativity?

• Is (G)AI better at a specific creativity subdimension (novelty, usefulness)? When and why?

• What ethical considerations should be considered when assessing (G)AI creativity?

 
The changing nature of creativity conceptualizations:

• How is the proliferation of (G)AI changing how we define and assess creativity?

 
The impact of AI on creative industries:

• How is (G)AI affecting the work of creative professionals and in what ways are those occupations responding?

• How is (G)AI affecting existing evaluation schemes in creative industries? What are the implications for how creative work is valued and remunerated?

References

• Amabile, Teresa M. (2020). Creativity, Artificial Intelligence, and a World of Surprises. Academy of Management Discoveries, 6(3), 351–354.

• Boden, Margaret A. (1998). Creativity and artificial intelligence. Artificial Intelligence, 103(1–2), 347–356.
• Faraj, S., Pachidi, S., & Sayegh, K. 2018. Working and organizing in the age of the learning algorithm. Information and Organization, 28(1): 62–70.
• Jia, Nan, Luo, Xueming, Fang, Zheng, & Liao, Chengcheng. (2023). When and How Artificial Intelligence Augments Employee Creativity. Academy of Management Journal.
• Krakowski, Sebastian, Luger, Johannes, & Raisch, Sebastian. (2022). Artificial intelligence and the changing sources of competitive advantage. Strategic Management Journal, 44(6), 1425-1452.
• Magni, Federico, & Jeong, Martha. (2023). The behavioral consequences for organizational creativity of being evaluated by AI. In Academy of Management Proceedings (Vol. 2023, No. 1, p12940). Briarcliff Manor, NY 10510: Academy of Management.
• Magni, Federico, Park, Jiyoung, & Chao, Melody Manchi. (2023). Humans as creativity gatekeepers: Are we biased against AI creativity? Journal of Business and Psychology, 1-14. https://doi.org/10.1007/s10869-023-09910-x.
• Newton, D. (2019). Generative deep learning in architectural design. Technology| Architecture+ Design, 3(2), 176-189.
• Popova, M., Isayev, O., & Tropsha, A. (2018). Deep reinforcement learning for de novo drug design. Science advances, 4(7), eaap7885. 10.1126/sciadv.aap7885.
• Schweitzer, Shane, & De Cremer, David. (2023). When Being Managed by Technology: Does Algorithmic Management Affect Perceptions of Workers’ Creative Capacities? Academy of Management Discoveries. https://doi.org/10.5465/amd.2022.0115.
• Vardanyan, A. (2022). Employee-AI Augmented Collaboration: A Qualitative Study of Fashion Designers and Stylists. In Academy of Management Proceedings (Vol. 2022, No. 1, p. 18240). Briarcliff Manor, NY 10510: Academy of Management.
• von Krogh, G. (2018). Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing. Academy of Management Discoveries, 4(4), 404-409.
• Wingström, Roosa, Hautala, Johanna, & Lundman, Riina. (2023). Redefining creativity in the era of AI? Perspectives of computer scientists and new media artists. Creativity Research Journal, 1–17.
•