IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-49528-y.html
   My bibliography  Save this article

Simple autonomous agents can enhance creative semantic discovery by human groups

Author

Listed:
  • Atsushi Ueshima

    (Yale University
    Yale University
    Japan Society for the Promotion of Science
    Keio University)

  • Matthew I. Jones

    (Yale University
    Yale University
    Sunwater Institute)

  • Nicholas A. Christakis

    (Yale University
    Yale University
    Yale University)

Abstract

Innovation is challenging, and theory and experiments indicate that groups may be better able to identify and preserve innovations than individuals. But innovation within groups faces its own challenges, including groupthink and truncated diffusion. We performed experiments involving a game in which people search for ideas in various conditions: alone, in networked social groups, or in networked groups featuring autonomous agents (bots). The objective was to search a semantic space of 20,000 nouns with defined similarities for an arbitrary noun with the highest point value. Participants (N = 1875) were embedded in networks (n = 125) of 15 nodes to which we sometimes added 2 bots. The bots had 3 possible strategies: they shared a random noun generated by their immediate neighbors, or a noun most similar from among those identified, or a noun least similar. We first confirm that groups are better able to explore a semantic space than isolated individuals. Then we show that when bots that share the most similar noun operate in groups facing a semantic space that is relatively easy to navigate, group performance is superior. Simple autonomous agents with interpretable behavior can affect the capacity for creative discovery of human groups.

Suggested Citation

  • Atsushi Ueshima & Matthew I. Jones & Nicholas A. Christakis, 2024. "Simple autonomous agents can enhance creative semantic discovery by human groups," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49528-y
    DOI: 10.1038/s41467-024-49528-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-49528-y
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-49528-y?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
    ---><---

    References listed on IDEAS

    as
    1. Benoit, Kenneth & Conway, Drew & Lauderdale, Benjamin E. & Laver, Michael & Mikhaylov, Slava, 2016. "Crowd-sourced Text Analysis: Reproducible and Agile Production of Political Data," American Political Science Review, Cambridge University Press, vol. 110(2), pages 278-295, May.
    2. Kevin R. McKee & Andrea Tacchetti & Michiel A. Bakker & Jan Balaguer & Lucy Campbell-Gillingham & Richard Everett & Matthew Botvinick, 2023. "Scaffolding cooperation in human groups with deep reinforcement learning," Nature Human Behaviour, Nature, vol. 7(10), pages 1787-1796, October.
    3. Hirokazu Shirado & Nicholas A. Christakis, 2017. "Locally noisy autonomous agents improve global human coordination in network experiments," Nature, Nature, vol. 545(7654), pages 370-374, May.
    4. Daniel Barkoczi & Mirta Galesic, 2016. "Social learning strategies modify the effect of network structure on group performance," Nature Communications, Nature, vol. 7(1), pages 1-8, December.
    5. Devon Brackbill & Damon Centola, 2020. "Impact of network structure on collective learning: An experimental study in a data science competition," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-13, September.
    6. Charley M. Wu & Eric Schulz & Maarten Speekenbrink & Jonathan D. Nelson & Björn Meder, 2018. "Generalization guides human exploration in vast decision spaces," Nature Human Behaviour, Nature, vol. 2(12), pages 915-924, December.
    7. Wataru Toyokawa & Andrew Whalen & Kevin N. Laland, 2019. "Social learning strategies regulate the wisdom and madness of interactive crowds," Nature Human Behaviour, Nature, vol. 3(2), pages 183-193, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Dennie & Funk, Russell & Zaheer, Aks, 2020. "Structure in Context: A Morphological View of Whole Network Performance," SocArXiv x6q7g, Center for Open Science.
    2. Niccolo Pescetelli, 2021. "A Brief Taxonomy of Hybrid Intelligence," Forecasting, MDPI, vol. 3(3), pages 1-11, September.
    3. Theiss Bendixen, 2020. "How cultural evolution can inform the science of science communication—and vice versa," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-10, December.
    4. Olschewski, Sebastian & Diao, Linan & Rieskamp, Jörg, 2021. "Reinforcement learning about asset variability and correlation in repeated portfolio decisions," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    5. Lei Xu & Ronggui Ding & Lei Wang, 2022. "How to facilitate knowledge diffusion in collaborative innovation projects by adjusting network density and project roles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1353-1379, March.
    6. Martin Haselmayer & Marcelo Jenny, 2017. "Sentiment analysis of political communication: combining a dictionary approach with crowdcoding," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2623-2646, November.
    7. Cindy Cheng & Joan Barceló & Allison Spencer Hartnett & Robert Kubinec & Luca Messerschmidt, 2020. "COVID-19 Government Response Event Dataset (CoronaNet v.1.0)," Nature Human Behaviour, Nature, vol. 4(7), pages 756-768, July.
    8. Brent Simpson & Bradley Montgomery & David Melamed, 2023. "Reputations for treatment of outgroup members can prevent the emergence of political segregation in cooperative networks," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    9. Khraisha, Tamer, 2020. "Complex economic problems and fitness landscapes: Assessment and methodological perspectives," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 390-407.
    10. Arno Riedl & Ingrid M. T. Rohde & Martin Strobel, 2021. "Free Neighborhood Choice Boosts Socially Optimal Outcomes in Stag-Hunt Coordination Problem," CESifo Working Paper Series 9012, CESifo.
    11. Agnieszka Kowalska-Styczeń & Krzysztof Malarz, 2020. "Noise induced unanimity and disorder in opinion formation," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-22, July.
    12. Füller, Johann & Hutter, Katja & Wahl, Julian & Bilgram, Volker & Tekic, Zeljko, 2022. "How AI revolutionizes innovation management – Perceptions and implementation preferences of AI-based innovators," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    13. Soojong Kim, 2019. "Directionality of information flow and echoes without chambers," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-22, May.
    14. Robin Watson & Thomas J. H. Morgan & Rachel L. Kendal & Julie Van de Vyver & Jeremy Kendal, 2021. "Social Learning Strategies and Cooperative Behaviour: Evidence of Payoff Bias, but Not Prestige or Conformity, in a Social Dilemma Game," Games, MDPI, vol. 12(4), pages 1-26, November.
    15. Magda Dubois & Tobias U. Hauser, 2022. "Value-free random exploration is linked to impulsivity," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    16. Darío Blanco-Fernández & Stephan Leitner & Alexandra Rausch, 2023. "Interactions between the individual and the group level in organizations: The case of learning and group turnover," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1087-1128, December.
    17. Tang, Ming & Liao, Huchang, 2024. "Group efficiency and individual fairness tradeoff in making wise decisions," Omega, Elsevier, vol. 124(C).
    18. Naudé, Wim & Bray, Amy & Lee, Celina, 2021. "Crowdsourcing Artificial Intelligence in Africa: Findings from a Machine Learning Contest," IZA Discussion Papers 14545, Institute of Labor Economics (IZA).
    19. Keren Weinshall & Lee Epstein, 2020. "Developing High‐Quality Data Infrastructure for Legal Analytics: Introducing the Israeli Supreme Court Database," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(2), pages 416-434, June.
    20. Elio Amicarelli & Jessica Di Salvatore, 2021. "Introducing the PeaceKeeping Operations Corpus (PKOC)," Journal of Peace Research, Peace Research Institute Oslo, vol. 58(5), pages 1137-1148, September.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49528-y. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.