The Crowdless Future? Generative AI and Creative Problem Solving
Open accessAbstract
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy business ideas and assessed the novelty, value, and creativity of solutions created by both the human crowd and the collaborative efforts of one human and AI. The challenge attracted 125 global solvers from various industries and the human-prompted AI solutions were generated using strategic prompt engineering. We recruited 300 evaluators to judge a randomized selection of 13 out of 234 solutions, totaling 3,900 evaluator–solution pairs. Our findings demonstrate that the solutions generated through human-AI collaboration matched the creativity of those from the human solvers. Whereas the human-AI solutions provided more value, the human-only solutions were more innovative—both on average and for highly novel outcomes. Our study explores the potential for incorporating “AI-in-the-loop” into creative problem-solving, offering a scalable and cost-efficient method for enhancing the early phases of innovation. Our research paves the way for future exploration of how AI can be integrated into creative processes to foster more effective innovation.
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Although several studies have compared AI-generated creativity against a human benchmark, a surprisingly limited amount of work has examined the creative output of human-AI dyads and the collaborative processes that undergird this.
“Furthermore, although several studies have compared AI generated creativity against a human benchmark8,16, a surprisingly limited amount of work has examined the creative output of human-AI dyads and the collaborative processes that undergird this.”
From Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence (2024) · cites this paper as [16]
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- Authors
- Boussioux, L., N. Lane, J., Zhang, M., Jacimovic, V., & Lakhani, K. R.
- Affiliations
- Harvard University (US)
- Venue
- Organization Science
- Publisher
- Elsevier BV
- Published
- 2023
- Volume
- 35
- Issue
- 5
- Pages
- 1589-1607
- ISSN
- 1047-7039 (ISSN-L)
- OpenAlex
- W4401533174
- Cited by
- 343
- References
- 97
- Citations by year
- 2026: 178 · 2025: 124 · 2024: 35 · 2023: 6
- FWCI
- 45.14
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Organization Science (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, human-AI collaboration, creative problem solving, crowdsourcing, circular economy, business idea generation, prompt engineering, large language models, solution search, novelty, early-stage innovation
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