1887
Volume 26, Issue 3
  • ISSN 1572-0373
  • E-ISSN: 1572-0381
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Abstract

Abstract

This study investigates whether the opinions of robotic agents are more likely to influence human decision-making when the robots are perceived as value-aware (i.e., when they display an understanding of human principles). We designed an experiment in which participants interacted with two Furhat robots — one programmed to be Value-Aware and the other Non-Value-Aware — during a labeling task for images representing human values. Results indicate that participants distinguished the Value-Aware robot from the Non-Value-Aware one. Although their explicit choices did not indicate a clear preference for one robot over the other, participants directed their gaze more toward the Value-Aware robot. Additionally, the Value-Aware robot was perceived as more loyal, suggesting that value awareness in a social robot may enhance its perceived commitment to the group. Finally, when both robots disagreed with the participant, conformity occurred in about one out of four trials, and participants took longer to confirm their responses, suggesting that two robots expressing dissent may introduce hesitation in decision-making. On one hand, this highlights the potential risk that robots, if misused, could manipulate users for unethical purposes. On the other hand, it reinforces the idea that social robots might encourage reflection in ambiguous situations and help users avoid scams.

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2026-04-02
2026-04-20
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References

  1. Abate, Andrea F., Carmen Bisogni, Lucia Cascone, Aniello Castiglione, Gerardo Costabile & Ilenia Mercuri
    2020 Social robot interactions for social engineering: Opportunities and open issues. In2020 ieee intl conf on dependable, autonomic and secure computing, intl conf on pervasive intelligence and computing, intl conf on cloud and big data computing, intl conf on cyber science and technology congress (dasc/picom/cbdcom/cyberscitech), 539–547. IEEE. 10.1109/DASC‑PICom‑CBDCom‑CyberSciTech49142.2020.00097
    https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00097 [Google Scholar]
  2. Abbo, Giulio Antonio & Tony Belpaeme
    2023 Users’ perspectives on value awareness in social robots. InHri 2023, the 18th acm/ieee international conference on human-robot interaction, 1–5.
    [Google Scholar]
  3. Abbo, Giulio Antonio, Tony Belpaeme & Micol Spitale
    2025 Concerns and values in humanrobot interactions: A focus on social robotics. arXiv preprint arXiv:2501.05628.
    [Google Scholar]
  4. Alves-Oliveira, Patricia, Pedro Sequeira & Ana Paiva
    2016 The role that an educational robot plays. In2016 25th ieee international symposium on robot and human interactive communication (ro-man), 817–822. IEEE. 10.1109/ROMAN.2016.7745213
    https://doi.org/10.1109/ROMAN.2016.7745213 [Google Scholar]
  5. Andtfolk, Malin, Linda Nyholm, Hilde Eide & Lisbeth Fagerström
    2022 Humanoid robots in the care of older persons: A scoping review. Assistive Technology34(5). 518–526. 10.1080/10400435.2021.1880493
    https://doi.org/10.1080/10400435.2021.1880493 [Google Scholar]
  6. Aroyo, Alexander Mois, Francesco Rea, Giulio Sandini & Alessandra Sciutti
    2018 Trust and social engineering in human robot interaction: Will a robot make you disclose sensitive information, conform to its recommendations or gamble?IEEE Robotics and Automation Letters3(4). 3701–3708. 10.1109/LRA.2018.2856272
    https://doi.org/10.1109/LRA.2018.2856272 [Google Scholar]
  7. Asch, Solomon E.
    1951 Effects of group pressure on the modification and distortion of judgments. InHarold Guetzkow (ed.), Groups, leadership and men, 177–190. Carnegie Press.
    [Google Scholar]
  8. Belpaeme, Tony, James Kennedy, Aditi Ramachandran, Brian Scassellati & Fumihide Tanaka
    2018 Social robots for education: A review. Science robotics3(21). 10.1126/scirobotics.aat5954
    https://doi.org/10.1126/scirobotics.aat5954 [Google Scholar]
  9. Belpaeme, Tony & Fumihide Tanaka
    2021 Social robots as educators. InOECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots, 1431. OECD Publishing Paris. 10.1787/589b283f‑en
    https://doi.org/10.1787/589b283f-en [Google Scholar]
  10. Bhat, Shreyas, Joseph B. Lyons, Cong Shi & X Jessie Yang
    2024 Evaluating the impact of personalized value alignment in human-robot interaction: Insights into trust and team performance outcomes. InProceedings of the 2024 acm/ieee international conference on human-robot interaction, 32–41. 10.1145/3610977.3634921
    https://doi.org/10.1145/3610977.3634921 [Google Scholar]
  11. Brandstetter, Jurgen, Péter Rácz, Clay Beckner, Eduardo B. Sandoval, Jennifer Hay & Christoph Bartneck
    2014 A peer pressure experiment: Recreation of the asch conformity experiment with robots. In2014 ieee/rsj international conference on intelligent robots and systems, 1335–1340. IEEE. 10.1109/IROS.2014.6942730
    https://doi.org/10.1109/IROS.2014.6942730 [Google Scholar]
  12. Chevalier, Pauline, Bob R. Schadenberg, Amir Aly, Angelo Cangelosi & Adriana Tapus
    2022 Context-awareness in human-robot interaction: Approaches and challenges. In2022 17th ACM/IEEE international conference on human-robot interaction (hri), 1241–1243. IEEE. 10.1109/HRI53351.2022.9889584
    https://doi.org/10.1109/HRI53351.2022.9889584 [Google Scholar]
  13. Chyung, Seung Youn, Katherine Roberts, Ieva Swanson & Andrea Hankinson
    2017 Evidencebased survey design: The use of a midpoint on the likert scale. Performance improvement56(10). 15–23. 10.1002/pfi.21727
    https://doi.org/10.1002/pfi.21727 [Google Scholar]
  14. Cialdini, Robert B. & Noah J. Goldstein
    2004 Social influence: Compliance and conformity. Annu. Rev. Psychol. 55(1). 591–621. 10.1146/annurev.psych.55.090902.142015
    https://doi.org/10.1146/annurev.psych.55.090902.142015 [Google Scholar]
  15. Cifuentes, Carlos A., Maria J. Pinto, Nathalia Céspedes & Marcela Múnera
    2020 Social robots in therapy and care. Current Robotics Reports11. 59–74. 10.1007/s43154‑020‑00009‑2
    https://doi.org/10.1007/s43154-020-00009-2 [Google Scholar]
  16. Ciupinska, Kinga, Serena Marchesi, Giulio Antonio Abbo, Tony Belpaeme & Agnieszka Wykowska
    2024a Awareprompt : using diffusion models to create methods for measuring value-aware ai architectures. InAna Paula Rocha, Luc Steels & Jaap van den Herik (eds.), Proceedings of the 16th international conference on agents and artificial intelligence : volume 3, 1436–1443. SCITEPRESS. 10.5220/0012596400003636
    https://doi.org/10.5220/0012596400003636 [Google Scholar]
  17. 2024b Stimuli from: Awareprompt: Using diffusion models to create methods for measuring value-aware ai architectures. 10.5281/zenodo.10516945
    https://doi.org/10.5281/zenodo.10516945 [Google Scholar]
  18. Ciupińska, Kinga, Agnieszka Wykowska & Davide De Tommaso
    2024 From labs to living rooms: Evaluating humans’ perception of value-laden decisions made by humanoid robot. Preprint. 10.31219/osf.io/6asb7
    https://doi.org/10.31219/osf.io/6asb7 [Google Scholar]
  19. Cocchella, Francesca, Giulia Pusceddu, Giulia Belgiovine, Michela Bogliolo, Linda Lastrico, Maura Casadio, Francesco Rea & Alessandra Sciutti
    2023 At school with a robot: Italian students’ perception of robotics during an educational program. In2023 32nd ieee international conference on robot and human interactive communication (ro-man), 1413–1419. IEEE. 10.1109/RO‑MAN57019.2023.10309379
    https://doi.org/10.1109/RO-MAN57019.2023.10309379 [Google Scholar]
  20. Foddy, Margaret
    1978 Patterns of gaze in cooperative and competitive negotiation. Human relations31(11). 925–938. 10.1177/001872677803101101
    https://doi.org/10.1177/001872677803101101 [Google Scholar]
  21. Graham, Jesse, Jonathan Haidt, Sena Koleva, Matt Motyl, Ravi Iyer, Sean P. Wojcik & Peter H. Ditto
    2013 Moral foundations theory: The pragmatic validity of moral pluralism. InAdvances in experimental social psychology, vol.471, 55–130. Elsevier.
    [Google Scholar]
  22. Graham, Jesse, Brian A. Nosek, Jonathan Haidt, Ravi Iyer, Koleva Spassena & Peter H. Ditto
    2008 Moral foundations questionnaire. Journal of Personality and Social Psychology.
    [Google Scholar]
  23. Grishchenko, Ivan, Geng Yan, Eduard Gabriel Bazavan, Andrei Zanfir, Nikolai Chinaev, Karthik Raveendran, Matthias Grundmann & Cristian Sminchisescu
    2023 Blendshapes ghum: Realtime monocular facial blendshape prediction. arXiv preprint arXiv:2309.05782.
    [Google Scholar]
  24. Hancock, Peter A., Deborah R. Billings, Kristin E. Schaefer, Jessie Y. C. Chen, Ewart J De Visser & Raja Parasuraman
    2011 A meta-analysis of factors affecting trust in human-robot interaction. Human factors53(5). 517–527. 10.1177/0018720811417254
    https://doi.org/10.1177/0018720811417254 [Google Scholar]
  25. Hertz, Nicholas, Tyler Shaw, Ewart J de Visser & Eva Wiese
    2019 Mixing it up: how mixed groups of humans and machines modulate conformity. Journal of Cognitive Engineering and Decision Making13(4). 242–257. 10.1177/1555343419869465
    https://doi.org/10.1177/1555343419869465 [Google Scholar]
  26. Hou, Yoyo Tsung-Yu, Wen-Ying Lee & Malte Jung
    2023 “should i follow the human, or follow the robot?” — robots in power can have more influence than humans on decision-making. InProceedings of the 2023 chi conference on human factors in computing systems, 1–13. 10.1145/3544548.3581066
    https://doi.org/10.1145/3544548.3581066 [Google Scholar]
  27. Leiner, Dominik J.
    2024 Sosci survey (version 3.5.01). Computer software. https://www.soscisurvey.de
    [Google Scholar]
  28. Normoyle, Aline, Jeremy B. Badler, Teresa Fan, Norman I. Badler, Vinicius J. Cassol & Soraia R. Musse
    2013 Evaluating perceived trust from procedurally animated gaze. InProceedings of motion on games, 141–148. 10.1145/2522628.2522630
    https://doi.org/10.1145/2522628.2522630 [Google Scholar]
  29. Pasquali, Dario, Austin Kothig, Alexander Mois Aroyo, John Edison Munoz Cadorna, Kerstin Dautenhahn, Stefano Bencetti, Rea Francesco & Alessandra Sciutti
    2023 That’s not a good idea: A robot changes your behavior against social engineering. InProceedings of the 11th international conference on human-agent interaction, 63–71. 10.1145/3623809.3623879
    https://doi.org/10.1145/3623809.3623879 [Google Scholar]
  30. Podell, Dustin, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Muller, Joe Penna & Robin Rombach
    2023 Sdxl: Improving latent diffusion models for high-resolution image synthesis. arXiv preprint arXiv:2307.01952.
    [Google Scholar]
  31. Pusceddu, G., M. Sangineto, F. Cocchella, M. Bogliolo, G. Belgiovine, L. Lastrico, M. Casadio, F. Rea, C. Gena & S. Sciutti
    2025 Exploring children’s strategies in response to robot’s advice during a group task with icub and nao. InProceedings of the international conference on social robotics. 10.1007/978‑981‑96‑3519‑1_38
    https://doi.org/10.1007/978-981-96-3519-1_38 [Google Scholar]
  32. Qin, Xin, Chen Chen, Kai Chi Yam, Limei Cao, Wanlu Li, Jian Guan, Puchu Zhao, Xiaowei Dong & Yiqiang Lin
    2022 Adults still can’t resist: A social robot can induce normative conformity. Computers in Human Behavior1271. 107041. 10.1016/j.chb.2021.107041
    https://doi.org/10.1016/j.chb.2021.107041 [Google Scholar]
  33. Qiu, Liang, Yizhou Zhao, Jinchao Li, Pan Lu, Baolin Peng, Jianfeng Gao & Song-Chun Zhu
    2022 Valuenet: A new dataset for human value driven dialogue system. Proceedings of the AAAI Conference on Artificial Intelligence36(10). 11183–11191. 10.1609/aaai.v36i10.21368. https://ojs.aaai.org/index.php/AAAI/article/view/21368
    https://doi.org/10.1609/aaai.v36i10.21368 [Google Scholar]
  34. Rassin, Eric, Peter Muris, Ingmar Franken, Maartje Smit & Maggie Wong
    2007 Measuring general indecisiveness. Journal of Psychopathology and Behavioral Assessment291. 60–67. 10.1007/s10862‑006‑9023‑z
    https://doi.org/10.1007/s10862-006-9023-z [Google Scholar]
  35. Rokeach, Milton
    1973The nature of human values. Free press.
    [Google Scholar]
  36. Salomons, Nicole, Michael Van Der Linden, Sarah Strohkorb Sebo & Brian Scassellati
    2018 Humans conform to robots: Disambiguating trust, truth, and conformity. InProceedings of the 2018 acm/ieee international conference on human-robot interaction, 187–195. 10.1145/3171221.3171282
    https://doi.org/10.1145/3171221.3171282 [Google Scholar]
  37. Schwartz, Shalom H.
    2012 An overview of the schwartz theory of basic values. Online readings in Psychology and Culture2(1). 11. 10.9707/2307‑0919.1116
    https://doi.org/10.9707/2307-0919.1116 [Google Scholar]
  38. Sembroski, Catherine E., Marlena R. Fraune & Selma Šabanović
    2017 He said, she said, it said: Effects of robot group membership and human authority on people’s willingness to follow their instructions. In2017 26th ieee international symposium on robot and human interactive communication (ro-man), 56–61. IEEE. 10.1109/ROMAN.2017.8172280
    https://doi.org/10.1109/ROMAN.2017.8172280 [Google Scholar]
  39. Sharkey, Amanda & Noel Sharkey
    2021 We need to talk about deception in social robotics!Ethics and Information Technology231. 309–316. 10.1007/s10676‑020‑09573‑9
    https://doi.org/10.1007/s10676-020-09573-9 [Google Scholar]
  40. Shiomi, Masahiro & Norihiro Hagita
    2016 Do synchronized multiple robots exert peer pressure?InProceedings of the fourth international conference on human agent interaction, 27–33. 10.1145/2974804.2974808
    https://doi.org/10.1145/2974804.2974808 [Google Scholar]
  41. Twyman, Matt, Nigel Harvey & Clare Harries
    2008 Trust in motives, trust in competence: Separate factors determining the effectiveness of risk communication. Judgment and Decision Making3(1). 111–120. 10.1017/S1930297500000218
    https://doi.org/10.1017/S1930297500000218 [Google Scholar]
  42. Van Eecke, Paul, Lara Verheyen, Tom Willaert & Katrien Beuls
    2023 The candide model: How narratives emerge where observations meet beliefs. InThe 61st annual meeting of the association for computational linguistics, 48–57. Association for Computational Linguistics. 10.18653/v1/2023.wnu‑1.7
    https://doi.org/10.18653/v1/2023.wnu-1.7 [Google Scholar]
  43. Vollmer, AnnaLisa, Robin Read, Dries Trippas & Tony Belpaeme
    2018 Children conform, adults resist: A robot group induced peer pressure on normative social conformity. Science robotics3(21). eaat7111. 10.1126/scirobotics.aat7111
    https://doi.org/10.1126/scirobotics.aat7111 [Google Scholar]
  44. Zhang, Lixuan, Iryna Pentina & Yuhong Fan
    2021 Who do you choose? comparing perceptions of human vs robo-advisor in the context of financial services. Journal of Services Marketing35(5). 634–646. 10.1108/JSM‑05‑2020‑0162
    https://doi.org/10.1108/JSM-05-2020-0162 [Google Scholar]
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