IDEAS home Printed from https://ideas.repec.org/a/kap/jbuset/v178y2022i4d10.1007_s10551-022-05059-4.html
   My bibliography  Save this article

Sex Robots: Are We Ready for Them? An Exploration of the Psychological Mechanisms Underlying People’s Receptiveness of Sex Robots

Author

Listed:
  • Junzhao Ma

    (Monash University)

  • Dewi Tojib

    (Monash University)

  • Yelena Tsarenko

    (Monash University)

Abstract

Artificial Intelligence (AI)-powered products have started to permeate various spheres of our lives. One of the most controversial of such products is the sex robot, an application of the AI-integrated robotic technology in the domain of human sexual gratification. The aim of this research is to understand the general public’s receptiveness towards this controversial new invention. Drawing upon the social intuitionist model, we find that the fear of AI, emblematic of the broader anxiety of technology’s encroachment on the human sphere, shapes the public’s receptiveness to sex robots. Perceived substitutability of sex robots for human-to-human sexual interactions mediates this relationship. Religiosity is found to moderate this mediated relationship. Our findings are first established with a cross-sectional study. A “big data” field study further validates them. The present research is one of the first empirical studies to examine the underlying psychology of the public’s receptiveness to sex robots. By doing so, we aim to provide relevant government and industry bodies with a better understanding of this important topic for more informed policy making, and to raise awareness of the significant social and ethical implications should sex robots become widely accepted and adopted.

Suggested Citation

  • Junzhao Ma & Dewi Tojib & Yelena Tsarenko, 2022. "Sex Robots: Are We Ready for Them? An Exploration of the Psychological Mechanisms Underlying People’s Receptiveness of Sex Robots," Journal of Business Ethics, Springer, vol. 178(4), pages 1091-1107, July.
    • Handle: RePEc:kap:jbuset:v:178:y:2022:i:4:d:10.1007_s10551-022-05059-4
    DOI: 10.1007/s10551-022-05059-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10551-022-05059-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10551-022-05059-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stephens-Davidowitz, Seth, 2014. "The cost of racial animus on a black candidate: Evidence using Google search data," Journal of Public Economics, Elsevier, vol. 118(C), pages 26-40.
    2. Ivar Krumpal, 2013. "Determinants of social desirability bias in sensitive surveys: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2025-2047, June.
    3. Paschen, Ulrich & Pitt, Christine & Kietzmann, Jan, 2020. "Artificial intelligence: Building blocks and an innovation typology," Business Horizons, Elsevier, vol. 63(2), pages 147-155.
    4. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    5. John Hulland & Jeff Miller, 2018. "“Keep on Turkin’”?," Journal of the Academy of Marketing Science, Springer, vol. 46(5), pages 789-794, September.
    6. Joseph K. Goodman & Gabriele Paolacci, 2017. "Crowdsourcing Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(1), pages 196-210.
    7. Kirk Doran & Joseph Price, 2014. "Pornography and Marriage," Journal of Family and Economic Issues, Springer, vol. 35(4), pages 489-498, December.
    8. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    9. Kaplan, Andreas & Haenlein, Michael, 2020. "Rulers of the world, unite! The challenges and opportunities of artificial intelligence," Business Horizons, Elsevier, vol. 63(1), pages 37-50.
    10. J. Barnett & H. Cooper & V. Senior, 2007. "Belief in Public Efficacy, Trust, and Attitudes Toward Modern Genetic Science," Risk Analysis, John Wiley & Sons, vol. 27(4), pages 921-933, August.
    11. Melissa S. Kearney & Phillip B. Levine, 2015. "Media Influences on Social Outcomes: The Impact of MTV's 16 and Pregnant on Teen Childbearing," American Economic Review, American Economic Association, vol. 105(12), pages 3597-3632, December.
    12. Juma, Calestous, 2016. "Innovation and Its Enemies: Why People Resist New Technologies," OUP Catalogue, Oxford University Press, number 9780190467036, Decembrie.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christian Goglin, 2023. "The Ethics of Artificial Intelligence: Review of Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI by R. Blackman; Ethics of Artificial Intelligence: Case Studie," Journal of Business Ethics, Springer, vol. 188(3), pages 623-627, December.
    2. Michael Haenlein & Ming-Hui Huang & Andreas Kaplan, 2022. "Guest Editorial: Business Ethics in the Era of Artificial Intelligence," Journal of Business Ethics, Springer, vol. 178(4), pages 867-869, July.

    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. Ma, Junzhao & Seenivasan, Satheesh & Yan, Bingyu, 2020. "Media influences on consumption trends: Effects of the film Food, Inc. on organic food sales in the U.S," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 320-335.
    2. David H Chae & Sean Clouston & Mark L Hatzenbuehler & Michael R Kramer & Hannah L F Cooper & Sacoby M Wilson & Seth I Stephens-Davidowitz & Robert S Gold & Bruce G Link, 2015. "Association between an Internet-Based Measure of Area Racism and Black Mortality," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-12, April.
    3. Kristina Gligorić & Arnaud Chiolero & Emre Kıcıman & Ryen W. White & Robert West, 2022. "Population-scale dietary interests during the COVID-19 pandemic," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    4. Abay,Kibrom A. & Hirfrfot,Kibrom Tafere & Woldemichael,Andinet, 2020. "Winners and Losers from COVID-19 : Global Evidence from Google Search," Policy Research Working Paper Series 9268, The World Bank.
    5. Rahlff, Helen & Rinne, Ulf & Sonnabend, Hendrik, 2023. "COVID-19, School Closures and (Cyber)Bullying in Germany," IZA Discussion Papers 16650, Institute of Labor Economics (IZA).
    6. Andrew Bacher-Hicks & Joshua Goodman & Jennifer Greif Green & Melissa K. Holt, 2022. "The COVID-19 Pandemic Disrupted Both School Bullying and Cyberbullying," American Economic Review: Insights, American Economic Association, vol. 4(3), pages 353-370, September.
    7. Bacher-Hicks, Andrew & Goodman, Joshua & Mulhern, Christine, 2021. "Inequality in household adaptation to schooling shocks: Covid-induced online learning engagement in real time," Journal of Public Economics, Elsevier, vol. 193(C).
    8. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    9. Ishani Chaudhuri & Parthajit Kayal, 2022. "Predicting Power of Ticker Search Volume in Indian Stock Market," Working Papers 2022-214, Madras School of Economics,Chennai,India.
    10. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    11. Sansone, Dario, 2019. "Pink work: Same-sex marriage, employment and discrimination," Journal of Public Economics, Elsevier, vol. 180(C).
    12. Bentzen, Jeanet Sinding, 2021. "In crisis, we pray: Religiosity and the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 541-583.
    13. Jesse T. Richman & Ryan J. Roberts, 2023. "Assessing Spurious Correlations in Big Search Data," Forecasting, MDPI, vol. 5(1), pages 1-12, February.
    14. Jetter, Michael & Walker, Jay K., 2022. "News coverage and mass shootings in the US," European Economic Review, Elsevier, vol. 148(C).
    15. Aksoy, Cevat Giray & Ganslmeier, Michael & Poutvaara, Panu, 2020. "Public Attention and Policy Responses to COVID-19 Pandemic," IZA Discussion Papers 13427, Institute of Labor Economics (IZA).
    16. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    17. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    18. Breithaupt, Patrick & Kesler, Reinhold & Niebel, Thomas & Rammer, Christian, 2020. "Intangible capital indicators based on web scraping of social media," ZEW Discussion Papers 20-046, ZEW - Leibniz Centre for European Economic Research.
    19. Perroni, Carlo & Scharf, Kimberley & Talavera, Oleksandr & Vi, Linh, 2022. "Does online salience predict charitable giving? Evidence from SMS text donations," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 134-149.
    20. JooSeok Oh & Timothy Paul Connerton & Hyun-Jung Kim, 2019. "The Rediscovery of Brand Experience Dimensions with Big Data Analysis: Building for a Sustainable Brand," Sustainability, MDPI, vol. 11(19), pages 1-21, September.

    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:kap:jbuset:v:178:y:2022:i:4:d:10.1007_s10551-022-05059-4. 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.springer.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.