Skip to main content
SpringerLink
Log in

Persuasive Robots in the Field

  • Conference paper
  • First Online:
Persuasive Technology (PERSUASIVE 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13832))

Included in the following conference series:

Abstract

In this paper, we investigate the effectiveness of a persuasive social robot in the field. The service robot drives around a public space and offers water to people using a persuasive message. The persuasive utterances used evoke either scientific expertise (e.g. “Research shows that it is important to drink enough water during the day”) or a reference to other people’s choices (“Most people/men/women actually do take something to drink”), hence exploring the principle of social proof. Our study makes three contributions: First, we show how persuasive utterances that are successful in the lab are not necessarily persuasive in the field. Second, we show that context factors influence the effectiveness of a persuasive message, as well as the sequential placement of the persuasive message. Lastly, the extent to which people construe the human-robot interaction situation as social influences the effectiveness of the robot as a persuasive technology in general.

This research was partially supported by the Danish Innovations fonden in the framework of the Smooth project.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    An informal Danish greeting.

  2. 2.

    Abbreviations in the transcripts: R = robot/W = woman The Danish interactions are translated into English.

References

  1. Andriella, A., Torras, C., Alenya, G.: Short-term human–robot interaction adaptability in real-world environments. Int. J. Soc. Robot. 12(3), 639–657 (2020)

    Article  Google Scholar 

  2. Andrist, S., Spannan, E., Mutlu, B.: Rhetorical robots: making robots more effective speakers using linguistic cues of expertise. In: 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI). pp. 341–348. IEEE (2013)

    Google Scholar 

  3. Belpaeme, T.: Advice to new human-robot interaction researchers. In: Human-Robot Interaction. pp. 355–369. Springer (2020)

    Google Scholar 

  4. Broadbent, E., et al.: Benefits and problems of health-care robots in aged care settings: a comparison trial. Australas. J. Ageing 35(1), 23–29 (2016)

    Article  MathSciNet  Google Scholar 

  5. Chidambaram, V., Chiang, Y.H., Mutlu, B.: Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues. In: Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction, pp. 293–300 (2012)

    Google Scholar 

  6. Chun, B., Knight, H.: The robot makers: an ethnography of anthropomorphism at a robotics company. ACM Trans. Human-Robot Inter. (THRI) 9(3), 1–36 (2020)

    Article  Google Scholar 

  7. Cialdini, R.B.: Influence, vol. 3. A. Michel Port Harcourt (1987)

    Google Scholar 

  8. Clark, H.H., Fischer, K.: Social robots as depictions of social agents. Behavioral and Brain Sciences, pp. 1–33 (2022)

    Google Scholar 

  9. Epley, N., Waytz, A., Cacioppo, J.T.: On seeing human: a three-factor theory of anthropomorphism. Psychol. Rev. 114(4), 864 (2007)

    Article  Google Scholar 

  10. Feng, Y., Perugia, G., Yu, S., Barakova, E.I., Hu, J., Rauterberg, G.: Context- enhanced human-robot interaction: Exploring the role of system interactivity and multimodal stimuli on the engagement of people with dementia. Int. J. Soc. Robot. 14(3), 807–826 (2022)

    Article  Google Scholar 

  11. Fischer, K.: Interpersonal variation in understanding robots as social actors. In: 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 53–60. IEEE (2011)

    Google Scholar 

  12. Fischer, K.: Tracking anthropomorphizing behavior in human-robot interaction. ACM Trans. Hum.-Robot Inter. (THRI) 11(1), 1–28 (2021)

    Google Scholar 

  13. Fischer, K., Langedijk, R.M., Nissen, L.D., Ramirez, E.R., Palinko, O.: Gaze-speech coordination influences the persuasiveness of human-robot dialog in the wild. In: International Conference on Social Robotics, pp. 157–169. Springer, Cham (2020). Doi: https://doi.org/10.1007/978-3-030-62056-1_14

  14. Fischer, K., Niebuhr, O., Jensen, L.C., Bodenhagen, L.: Speech melody matters—how robots profit from using charismatic speech. ACM Trans. Hum.-Robot Inter. (THRI) 9(1), 1–21 (2019)

    Google Scholar 

  15. Fischer, K., et al.: Integrative social robotics hands-on. Interaction Studies 21(1), 145–185 (2020)

    Google Scholar 

  16. Forlizzi, J.: How robotic products become social products: an ethnographic study of cleaning in the home. In: 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 129–136. IEEE (2007)

    Google Scholar 

  17. Fountoukidou, S., Ham, J., Matzat, U., Midden, C.: Persuasive design principles and user models for people with motor disabilities. In: Signal Processing to Drive Human-Computer Interaction: EEG and eye-controlled interfaces, pp. 49–79. Institution of Engineering and Technology (IET) (2020)

    Google Scholar 

  18. Ghazali, A.S., Ham, J., Barakova, E.I., Markopoulos, P.: Effects of robot facial characteristics and gender in persuasive human-robot interaction. Front. Robot. AI 5, 73 (2018)

    Article  Google Scholar 

  19. Goldstein, N.J., Cialdini, R.B., Griskevicius, V.: A room with a viewpoint: using social norms to motivate environmental conservation in hotels. J. Consumer Res. 35(3), 472–482 (2008)

    Article  Google Scholar 

  20. Ham, J., Bokhorst, R., Cuijpers, R., Pol, D.v.d., Cabibihan, J.J.: Making robots persuasive: the influence of combining persuasive strategies (gazing and gestures) by a storytelling robot on its persuasive power. In: International conference on social robotics, pp. 71–83. Springer (2011)

    Google Scholar 

  21. Ham, J., Cuijpers, R.H., Cabibihan, J.J.: Combining robotic persuasive strategies: the persuasive power of a storytelling robot that uses gazing and gestures. Int. J. Soc. Robot. 7(4), 479–487 (2015)

    Article  Google Scholar 

  22. Hashemian, M., Couto, M., Mascarenhas, S., Paiva, A., Santos, P.A., Prada, R.: Persuasive social robot using reward power over repeated instances of persuasion. In: International Conference on Persuasive Technology, pp. 63–70. Springer, Cham (2021). Doi: https://doi.org/10.1007/978-3-030-79460-6_6

  23. Johnstone, B.: Discourse Analysis. John Wiley & Sons (2017)

    Google Scholar 

  24. Jung, M., Hinds, P.: Robots in the wild: A time for more robust theories of human- robot interaction (2018)

    Google Scholar 

  25. Kaptein, M., Markopoulos, P., De Ruyter, B., Aarts, E.: Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles. Int. J. Hum Comput Stud. 77, 38–51 (2015)

    Article  Google Scholar 

  26. Kru¨ger, N., et al.: The smooth-robot: a modular, interactive service robot. Front. Robot. AI 8 (2021)

    Google Scholar 

  27. Langedijk, R.M., Fischer, K.: Appeals to expertise make robots persuasive in human-robot healthcare interaction. In: Manipulation, Influence, and Deception: The Changing Landscape of Persuasive Language. Cambridge University Press (submitted)

    Google Scholar 

  28. Langedijk, R.M., Jensen, L.C., Fischer, K.: Persuasive effects of social proof in human-robot interactive dialog. Int. J. Soc. Robot. (Submitted)

    Google Scholar 

  29. Langedijk, R.M., Odabasi, C., Fischer, K., Graf, B.: Studying drink-serving service robots in the real world. In: 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 788–793. IEEE (2020)

    Google Scholar 

  30. Lee, H.R., Cheon, E., Lim, C., Fischer, K.: Configuring humans: what roles humans play in hri research. In: 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 478–492. IEEE (2022)

    Google Scholar 

  31. Liu, B., Tetteroo, D., Markopoulos, P.: A systematic review of experimental work on persuasive social robots. International J. Soc. Robot., 1–40 (2022)

    Google Scholar 

  32. Melkas, H., Hennala, L., Pekkarinen, S., Kyrki, V.: Impacts of robot implementation on care personnel and clients in elderly-care institutions. Int. J. Med. Informatics 134, 104041 (2020)

    Article  Google Scholar 

  33. Mutlu, B., Forlizzi, J.: Robots in organizations: the role of workflow, social, and environmental factors in human-robot interaction. In: 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 287–294. IEEE (2008)

    Google Scholar 

  34. Okafuji, Y., Baba, J., Nakanishi, J., Amada, J., Yoshikawa, Y., Ishiguro, H.: Persuasion strategies for social robot to keep humans accepting daily different recommendations. In: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1950–1957. IEEE (2021)

    Google Scholar 

  35. Park, C.H., Ros, R., Kwak, S.S., Huang, C.M., Lemaignan, S.: Towards real world impacts: design, development, and deployment of social robots in the wild (2020)

    Google Scholar 

  36. Riek, L.D.: Wizard of oz studies in hri: a systematic review and new reporting guidelines. J. Hum.-Robot Interact. 1(1), 119–136 (2012)

    Article  Google Scholar 

  37. Rudaz, D., Tatarian, K., Stower, R., Licoppe, C.: From inanimate object to agent: impact of pre-beginnings on the emergence of greetings with a robot (2023). https://doi.org/10.1145/3575806

  38. Sacks, H., Schegloff, E.A., Jefferson, G.: A simplest systematics for the organization of turn taking for conversation. In: Studies in the Organization of Conversational Interaction, pp. 7–55. Elsevier (1978)

    Google Scholar 

  39. Salomons, N., Van Der Linden, M., Strohkorb Sebo, S., Scassellati, B.: Humans conform to robots: Disambiguating trust, truth, and conformity. In: Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 187– 195 (2018)

    Google Scholar 

  40. Saunderson, S., Nejat, G.: How robots influence humans: a survey of nonverbal communication in social human–robot interaction. Int. J. Soc. Robot. 11(4), 575–608 (2019)

    Article  Google Scholar 

  41. Schegloff, E.A.: Sequence organization in interaction: a primer in conversation analysis I, vol. 1. Cambridge University Press (2007)

    Google Scholar 

  42. Schegloff, E.A.: Opening sequencing. Perpetual contact: mobile communication, private talk, public performance, pp. 326–385 (2002)

    Google Scholar 

  43. Siegel, M., Breazeal, C., Norton, M.I.: Persuasive robotics: the influence of robot gender on human behavior. In: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2563–2568. IEEE (2009)

    Google Scholar 

  44. Sung, J., Grinter, R.E., Christensen, H.I.: “Pimp my roomba” designing for personalization. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 193–196 (2009)

    Google Scholar 

  45. Thellman, S., et al.: He is not more persuasive than her: no gender biases toward robots giving speeches. In: Proceedings of the 18th International Conference on Intelligent Virtual Agents, pp. 327–328 (2018)

    Google Scholar 

  46. Weiss, A., Spiel, K.: Robots beyond science fiction: mutual learning in human– robot interaction on the way to participatory approaches. AI Soc. 37(2), 501–515 (2022)

    Article  Google Scholar 

  47. Winkle, K., Lemaignan, S., Caleb-Solly, P., Leonards, U., Turton, A., Bremner, P.: Effective persuasion strategies for socially assistive robots. In: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 277–285. IEEE (2019)

    Google Scholar 

Download references

Acknowledgements

We would like to thank the colleagues who have helped us during these experiments: Eduardo Ruiz Ramirez, Lotte Damsgaard Nissen, Matous Jelinek, Selina Eisenberger and Oskar Palinko.

Author information

Authors and Affiliations

  1. University of Southern Denmark, Alsion 2, 6400, Sonderborg, Denmark

    Rosalyn M. Langedijk & Kerstin Fischer

Authors
  1. Rosalyn M. Langedijk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kerstin Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rosalyn M. Langedijk .

Editor information

Editors and Affiliations

  1. University of Salzburg, Salzburg, Austria

    Alexander Meschtscherjakov

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Cees Midden

  3. Eindhoven University of Technology, Eindhoven, The Netherlands

    Jaap Ham

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Langedijk, R.M., Fischer, K. (2023). Persuasive Robots in the Field. In: Meschtscherjakov, A., Midden, C., Ham, J. (eds) Persuasive Technology. PERSUASIVE 2023. Lecture Notes in Computer Science, vol 13832. Springer, Cham. https://doi.org/10.1007/978-3-031-30933-5_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-30933-5_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30932-8

  • Online ISBN: 978-3-031-30933-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation