IDEAS home Printed from https://ideas.repec.org/p/pie/dsedps/2024-314.html
   My bibliography  Save this paper

Teaming Up with Artificial Agents in Non-routine Analytical Tasks

Author

Listed:
  • Lorenzo Cominelli
  • Federico Galatolo
  • Caterina Giannetti
  • Cristiano Ciaccio
  • Felice Dell’Orletta
  • Philipp Chaposkvi
  • Giulia Venturi

Abstract

Using a real-life escape room scenario, we investigate how different levels of embodiment in artificial agents influence team performance and conversational dynamics in non-routine analytical tasks. Teams composed of either three humans or two humans and an artificial agent (a Box, an Avatar, and a hyper-realistic Humanoid) worked together to escape the room within a time limit. Our findings reveal that while human-only teams tend to complete all tasks more frequently, they also tend to be slower and make more errors. Additionally, we observe a non-linear relationship between the degree of agent embodiment and team performance, with a significant effect on conversational dynamics. Teams with agents exhibiting higher levels of embodiment display conversational patterns more similar to those occurring among humans. These results highlight the complex role that embodied AI plays in human-agent interactions, offering new insights into how artificial agents can be designed to support team collaboration in problem-solving environments.

Suggested Citation

  • Lorenzo Cominelli & Federico Galatolo & Caterina Giannetti & Cristiano Ciaccio & Felice Dell’Orletta & Philipp Chaposkvi & Giulia Venturi, 2024. "Teaming Up with Artificial Agents in Non-routine Analytical Tasks," Discussion Papers 2024/314, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    • Handle: RePEc:pie:dsedps:2024/314
    Note: ISSN 2039-1854
    as

    Download full text from publisher

    File URL: https://www.ec.unipi.it/documents/Ricerca/papers/2024-314.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Levin Brinkmann & Fabian Baumann & Jean-François Bonnefon & Maxime Derex & Thomas F. Müller & Anne-Marie Nussberger & Agnieszka Czaplicka & Alberto Acerbi & Thomas L. Griffiths & Joseph Henrich & Joel, 2023. "Machine culture," Nature Human Behaviour, Nature, vol. 7(11), pages 1855-1868, November.
    2. Corgnet, Brice & Hernán-González, Roberto & Mateo, Ricardo, 2023. "Peer effects in an automated world," Labour Economics, Elsevier, vol. 85(C).
    3. Chugunova, Marina & Sele, Daniela, 2022. "We and It: An interdisciplinary review of the experimental evidence on how humans interact with machines," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    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. Fabian Dvorak & Regina Stumpf & Sebastian Fehrler & Urs Fischbacher, 2024. "Generative AI Triggers Welfare-Reducing Decisions in Humans," Papers 2401.12773, arXiv.org.
    2. Dreyfuss, Bnaya & Heffetz, Ori & Hoffman, Guy & Ishai, Guy & Kshirsagar, Alap, 2024. "Additive vs. subtractive earning in shared human-robot work environments," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 692-704.
    3. Ivan Ðula & Tabea Berberena & Ksenia Keplinger & Maria Wirzberger, 2024. "From challenges to opportunities: navigating the human response to automated agents in the workplace," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    4. Liu, Fanjue & Lee, Yu-Hao, 2024. "Virtually responsible? Attribution of responsibility toward human vs. virtual influencers and the mediating role of mind perception," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    5. Gorny, Paul M. & Groos, Eva & Strobel, Christina, 2024. "Do Personalized AI Predictions Change Subsequent Decision-Outcomes? The Impact of Human Oversight," MPRA Paper 121065, University Library of Munich, Germany.
    6. Daniela Sele & Marina Chugunova, 2023. "Putting a Human in the Loop: Increasing Uptake, but Decreasing Accuracy of Automated Decision-Making," Rationality and Competition Discussion Paper Series 438, CRC TRR 190 Rationality and Competition.
    7. Vomberg, Arnd & Schauerte, Nico & Krakowski, Sebastian & Ingram Bogusz, Claire & Gijsenberg, Maarten J. & Bleier, Alexander, 2023. "The cold-start problem in nascent AI strategy: Kickstarting data network effects," Journal of Business Research, Elsevier, vol. 168(C).
    8. Maggioni, Mario A. & Rossignoli, Domenico, 2023. "If it looks like a human and speaks like a human ... Communication and cooperation in strategic Human–Robot interactions," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 104(C).
    9. Mathieu Chevrier & Brice Corgnet & Eric Guerci & Julie Rosaz, 2024. "Algorithm Credulity: Human and Algorithmic Advice in Prediction Experiments," GREDEG Working Papers 2024-03, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France, revised Dec 2024.
    10. Wei, Xiahai & Xu, Jiawei & Cao, Hui, 2024. "Production automation upgrades and the mystery of workers' overwork: Evidence from a manufacturing employer-employee matching survey in China," Journal of Asian Economics, Elsevier, vol. 91(C).

    More about this item

    Keywords

    complex tasks; artificial agents; teamwork;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pie:dsedps:2024/314. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/dspisit.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.