IDEAS home Printed from https://ideas.repec.org/a/inm/ororsc/v35y2024i5p1589-1607.html
   My bibliography  Save this article

The Crowdless Future? Generative AI and Creative Problem-Solving

Author

Listed:
  • Léonard Boussioux

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Jacqueline N. Lane

    (Harvard Business School, Boston, Massachusetts 02163)

  • Miaomiao Zhang

    (ContinuumLab.AI, San Francisco, California 94114)

  • Vladimir Jacimovic

    (Harvard Business School, Boston, Massachusetts 02163; ContinuumLab.AI, San Francisco, California 94114)

  • Karim R. Lakhani

    (Harvard Business School, Boston, Massachusetts 02163)

Abstract

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 generated by the human crowd (HC) and collaborative human-AI efforts using two alternative forms of solution search. The challenge attracted 125 global solvers from various industries, and we used strategic prompt engineering to generate the human-AI solutions. We recruited 300 external human evaluators to judge a randomized selection of 13 out of 234 solutions, totaling 3,900 evaluator-solution pairs. Our results indicate that while human crowd solutions exhibited higher novelty—both on average and for highly novel outcomes—human-AI solutions demonstrated superior strategic viability, financial and environmental value, and overall quality. Notably, human-AI solutions cocreated through differentiated search, where human-guided prompts instructed the large language model to sequentially generate outputs distinct from previous iterations, outperformed solutions generated through independent search. By incorporating “AI in the loop” into human-centered creative problem-solving, our study demonstrates a scalable, cost-effective approach to augment the early innovation phases and lays the groundwork for investigating how integrating human-AI solution search processes can drive more impactful innovations.

Suggested Citation

  • Léonard Boussioux & Jacqueline N. Lane & Miaomiao Zhang & Vladimir Jacimovic & Karim R. Lakhani, 2024. "The Crowdless Future? Generative AI and Creative Problem-Solving," Organization Science, INFORMS, vol. 35(5), pages 1589-1607, September.
  • Handle: RePEc:inm:ororsc:v:35:y:2024:i:5:p:1589-1607
    DOI: 10.1287/orsc.2023.18430
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/orsc.2023.18430
    Download Restriction: no

    File URL: https://libkey.io/10.1287/orsc.2023.18430?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ororsc:v:35:y:2024:i:5:p:1589-1607. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.