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Rethinking technological acceptance in the age of emotional AI: Surveying Gen Z (Zoomer) attitudes toward non-conscious data collection

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  • Ho, Manh-Tung
  • Mantello, Peter
  • Ghotbi, Nader
  • Nguyen, Minh-Hoang
  • Nguyen, Hong-Kong T.
  • Vuong, Quan-Hoang

Abstract

This paper examines technological acceptance for automated emotion-sensing devices and non-conscious data collection (NCDC). We argue that conventional 20th century scholarship of human-machine relations is ill-equipped in the age of intelligent machines that sense, monitor, and tracks human sentiment, emotion, and feeling. We conduct a regression analysis on a dataset of 1015 Generation Z student respondents (age 18–27) from 48 countries and 8 regions worldwide using the Bayesian Hamiltonian Monte Carlo approach. The empirical results highlight the significance of sociocultural factors that influence technological acceptance by this specific generational demographic. Our findings also demonstrate the advantage but also the inherent limitation of traditional theories such as Davis's “Technological Acceptance Model” in accounting for of cross-cultural factors such as religions and regions, given the transfer of new technologies across borders. Moreover, our findings highlight important governance and design implications that need to be addressed to ensure that emotional AI systems and devices serve the best interests of individuals and societies.

Suggested Citation

  • Ho, Manh-Tung & Mantello, Peter & Ghotbi, Nader & Nguyen, Minh-Hoang & Nguyen, Hong-Kong T. & Vuong, Quan-Hoang, 2022. "Rethinking technological acceptance in the age of emotional AI: Surveying Gen Z (Zoomer) attitudes toward non-conscious data collection," Technology in Society, Elsevier, vol. 70(C).
  • Handle: RePEc:eee:teinso:v:70:y:2022:i:c:s0160791x2200152x
    DOI: 10.1016/j.techsoc.2022.102011
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    Cited by:

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    2. Le, Tam-Tri & Nguyen, Minh-Hoang, 2022. "A journey of SM3D: looking back at notable studies," OSF Preprints a8pju, Center for Open Science.
    3. Ho, Manh-Tung & Le, Ngoc-Thang B. & Mantello, Peter & Ho, Manh-Toan & Ghotbi, Nader, 2023. "Understanding the acceptance of emotional artificial intelligence in Japanese healthcare system: A cross-sectional survey of clinic visitors’ attitude," Technology in Society, Elsevier, vol. 72(C).
    4. Sayed Fayaz Ahmad & Heesup Han & Muhammad Mansoor Alam & Mohd. Khairul Rehmat & Muhammad Irshad & Marcelo Arraño-Muñoz & Antonio Ariza-Montes, 2023. "Impact of artificial intelligence on human loss in decision making, laziness and safety in education," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    5. Deng, Shichang & Zhang, Jingjing & Lin, Zhengnan & Li, Xiangqian, 2024. "Service staff makes me nervous: Exploring the impact of insecure attachment on AI service preference," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    6. Behn, Oliver & Leyer, Michael & Iren, Deniz, 2024. "Employees’ acceptance of AI-based emotion analytics from speech on a group level in virtual meetings," Technology in Society, Elsevier, vol. 76(C).
    7. Nguyen, Minh-Hoang & Mindsponge, AISDL, 2022. "Study on emotional AI and gen Z in the news," OSF Preprints yj9a7, Center for Open Science.
    8. Nguyen, Minh-Hoang, 2023. "Investigating urban residents' involvement in biodiversity conservation in protected areas: Empirical evidence from Vietnam," Thesis Commons z2hjv, Center for Open Science.
    9. Mindsponge, AISDL, 2022. "Release of guide for bayesvl version 1.0," OSF Preprints rs3zb, Center for Open Science.

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