IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-02625-1.html
   My bibliography  Save this article

Looking towards an automated future: U.S. attitudes towards future artificial intelligence instantiations and their effect

Author

Listed:
  • Ekaterina Novozhilova

    (College of Communication, Boston University)

  • Kate Mays

    (College of Agriculture and Life Sciences, University of Vermont)

  • James E. Katz

    (College of Communication, Boston University)

Abstract

The present study explores people’s attitudes towards an assortment of occupations on high and low-likelihood of automation probability. An omnibus survey (N = 1150) was conducted to measure attitudes about various emerging technologies, as well as demographic and individual traits. The results showed that respondents were not very comfortable with AI’s management across domains. To some degree, levels of comfort corresponded with the likelihood of automation probability, though some domains diverged from this pattern. Demographic traits explained the most variance in comfort with AI revealing that men and those with higher perceived technology competence were more comfortable with AI management in every domain. With the exception of personal assistance, those with lower internal locus of control were more comfortable with AI managing in almost every domain. Age, education, and employment showed little influence on comfort levels. The present study demonstrates a more holistic approach of assessing attitudes toward AI management at work. By incorporating demographic and self-efficacy variables, our research revealed that AI systems are perceived differently compared to other recent technological innovations.

Suggested Citation

  • Ekaterina Novozhilova & Kate Mays & James E. Katz, 2024. "Looking towards an automated future: U.S. attitudes towards future artificial intelligence instantiations and their effect," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02625-1
    DOI: 10.1057/s41599-024-02625-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-02625-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-024-02625-1?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. Igbaria, M. & Iivari, J., 1995. "The effects of self-efficacy on computer usage," Omega, Elsevier, vol. 23(6), pages 587-605, December.
    2. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    3. Viswanath Venkatesh & Hillol Bala, 2012. "Adoption and Impacts of Interorganizational Business Process Standards: Role of Partnering Synergy," Information Systems Research, INFORMS, vol. 23(4), pages 1131-1157, December.
    4. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    5. Nazir Ullah & Waleed S. Alnumay & Waleed Mugahed Al-Rahmi & Ahmed Ibrahim Alzahrani & Hosam Al-Samarraie, 2020. "Modeling Cost Saving and Innovativeness for Blockchain Technology Adoption by Energy Management," Energies, MDPI, vol. 13(18), pages 1-22, September.
    6. Rebitschek, Felix G. & Gigerenzer, Gerd & Wagner, Gert G., 2021. "People underestimate the errors made by algorithms for credit scoring and recidivism prediction but accept even fewer errors," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11, pages 1-11.
    7. Xu, Yingzi & Shieh, Chih-Hui & van Esch, Patrick & Ling, I-Ling, 2020. "AI customer service: Task complexity, problem-solving ability, and usage intention," Australasian marketing journal, Elsevier, vol. 28(4), pages 189-199.
    8. Maja Rožman & Polona Tominc & Borut Milfelner, 2023. "Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships," Cogent Business & Management, Taylor & Francis Journals, vol. 10(2), pages 2248732-224, December.
    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. Sharath Sasidharan & Radhika Santhanam & Daniel J. Brass & Vallabh Sambamurthy, 2012. "The Effects of Social Network Structure on Enterprise Systems Success: A Longitudinal Multilevel Analysis," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 658-678, September.
    2. Irfan Bashir & C. Madhavaiah, 2014. "Determinants of Young Consumers’ Intention to Use Internet Banking Services in India," Vision, , vol. 18(3), pages 153-163, September.
    3. Kerstin Pezoldt & Jana Schliewe, 2012. "Akzeptanz von Self-Service-Technologien: State of the Art," Schmalenbach Journal of Business Research, Springer, vol. 64(2), pages 205-253, March.
    4. Hsiao, Chun Hua & Yang, Chyan, 2011. "The intellectual development of the technology acceptance model: A co-citation analysis," International Journal of Information Management, Elsevier, vol. 31(2), pages 128-136.
    5. Kim, Miyea & Oh, Joohyun & Kim, Beomsoo, 2021. "Experience of digital music services and digital self-efficacy among older adults: Enjoyment and anxiety as mediators," Technology in Society, Elsevier, vol. 67(C).
    6. Martínez-Torres, M.R. & Díaz-Fernández, M.C. & Toral, S.L. & Barrero, F., 2015. "The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 146-160.
    7. Martínez-Caro, Eva & Cegarra-Navarro, Juan Gabriel & García-Pérez, Alexeis & Fait, Monica, 2018. "Healthcare service evolution towards the Internet of Things: An end-user perspective," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 268-276.
    8. Neill, William D. & Richard, James E., 2012. "Intranet portals: Marketing and managing individuals’ acceptance and use," Australasian marketing journal, Elsevier, vol. 20(2), pages 147-157.
    9. Raf Buyle & Mathias Van Compernolle & Eveline Vlassenroot & Ziggy Vanlishout & Peter Mechant & Erik Mannens, 2018. "“Technology Readiness and Acceptance Model” as a Predictor for the Use Intention of Data Standards in Smart Cities," Media and Communication, Cogitatio Press, vol. 6(4), pages 127-139.
    10. Ozturk, Ahmet Bulent & Bilgihan, Anil & Nusair, Khaldoon & Okumus, Fevzi, 2016. "What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience," International Journal of Information Management, Elsevier, vol. 36(6), pages 1350-1359.
    11. Wu, Kewen & Zhao, Yuxiang & Zhu, Qinghua & Tan, Xiaojie & Zheng, Hua, 2011. "A meta-analysis of the impact of trust on technology acceptance model: Investigation of moderating influence of subject and context type," International Journal of Information Management, Elsevier, vol. 31(6), pages 572-581.
    12. Andrei OGREZEANU, 2015. "Models Of Technology Adoption: An Integrative Approach," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 55-67, June.
    13. Ammar AL-Ashmori & Shuib Bin Basri & P. D. D. Dominic & Luiz Fernando Capretz & Amgad Muneer & Abdullateef Oluwagbemiga Balogun & Abdul Rehman Gilal & Rao Faizan Ali, 2022. "Classifications of Sustainable Factors in Blockchain Adoption: A Literature Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    14. King Hang Lam & Wai Ming To & Peter K.C. Lee, 2022. "Smart Building Management System (SBMS) for Commercial Buildings—Key Attributes and Usage Intentions from Building Professionals’ Perspective," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    15. Lee, Kyootai & Yan, Aihua & Joshi, Kailash, 2011. "Understanding the dynamics of users’ belief in software application adoption," International Journal of Information Management, Elsevier, vol. 31(2), pages 160-170.
    16. Wenzel, Stefan, 2014. "App'ification of Enterprise Software - Evaluating Mobile App Characteristics Enabling Online Purchase And Their Portability To Enterprise Application Software," EconStor Preprints 146785, ZBW - Leibniz Information Centre for Economics.
    17. Sarv Devaraj & Robert F. Easley & J. Michael Crant, 2008. "Research Note ---How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use," Information Systems Research, INFORMS, vol. 19(1), pages 93-105, March.
    18. Irina Heimbach & Oliver Hinz, 2018. "The Impact of Sharing Mechanism Design on Content Sharing in Online Social Networks," Information Systems Research, INFORMS, vol. 29(3), pages 592-611, September.
    19. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    20. Bilgihan, Anil & Barreda, Albert & Okumus, Fevzi & Nusair, Khaldoon, 2016. "Consumer perception of knowledge-sharing in travel-related Online Social Networks," Tourism Management, Elsevier, vol. 52(C), pages 287-296.

    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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02625-1. 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: https://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.