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Social Media Use and Attitudes toward AI: The Mediating Roles of Perceived AI Fairness and Threat

Li, Wenbo, Zheng, Xia·2024·Human Behavior and Emerging Technologies
DOI 10.1155/2024/3448083
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Abstract

This study investigates the association between social media use and attitudes toward AI technologies. A nationally representative two-wave longitudinal survey (N=5110) examined the mediating roles of perceived AI fairness and threat concerning three AI technologies: algorithms, facial recognition technology, and driverless passenger vehicles. Hypotheses were derived from media effect theories and the heuristic and systematic model of human-AI adoption. The results showed that social media use predicted more positive attitudes toward the three AI technologies indirectly through increased perceived AI fairness and reduced perceived AI threat. The findings contribute to our understanding of social media effects on attitudes toward AI and the underlying psychological mechanisms, providing valuable theoretical insights and practical implications.

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Figure 1 Hypothesized serial mediation models predicting the associations between social media use and attitudes toward (a) algorithms, (b) facial recognition technologies, and (c) driverless passenger vehicles. ∗ p < 05 ; ∗∗ p < 01 ; ∗∗∗ p < 001 .
Figure 1 Hypothesized serial mediation models predicting the associations between social media use and attitudes toward (a) algorithms, (b) facial recognition technologies, and (c) driverless passenger vehicles. ∗ p < 05 ; ∗∗ p < 01 ; ∗∗∗ p < 001 .CC-BY · From the PDF

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Citations

Cites

Research works printed but not linked: 52

  1. 10.1177/00936502231191832 · DOI
  2. K. Schwab, 2017, The fourth industrial revolution (first U.S. edition)
  3. IBM, 2022, Global Data from IBM Shows Steady Ai Adoption as Organizations Look to Address Skills Shortages, Automate Processes and Encourage Sustainable Operations
  4. 10.1016/j.chbr.2020.100014 · DOI · Paper page
  5. 10.1371/journal.pone.0257732 · DOI
  6. 10.1093/scipol/scac056 · DOI
  7. 10.1016/S2589-7500(21)00132-1 · DOI · Paper page
  8. 10.1177/09636625221113957 · DOI
  9. 10.3389/fpubh.2022.856571 · DOI
  10. 10.1111/j.1460-2466.1976.tb01397.x · DOI · Paper page
  11. 10.1177/14614448231180257 · DOI
  12. 10.1080/19312458.2012.732626 · DOI
  13. 10.1007/s00146-023-01854-3 · DOI
  14. 10.1080/08838151.2020.1843357 · DOI
  15. 10.1201/b23083 · DOI
  16. 10.1109/ICDM51629.2021.00100 · DOI
  17. 10.1108/JBS-12-2018-0204 · DOI · Paper page
  18. N. E. Sanders, 2023, Opinion|How Chatgpt Hijacks Democracy
  19. 10.1016/j.jbusres.2020.12.012 · DOI
  20. 10.1080/0144929X.2021.1884288 · DOI
  21. 10.1007/s12369-020-00734-w · DOI
  22. 10.1016/j.tele.2021.101694 · DOI
  23. 10.1016/j.giq.2023.101803 · DOI
  24. 10.1016/j.chb.2021.106894 · DOI
  25. 10.1177/14614448221108112 · DOI
  26. 10.1109/MSP.2018.2701166 · DOI · Paper page
  27. 10.1016/j.jbef.2020.100352 · DOI
  28. 10.1080/1369118X.2016.1154086 · DOI
  29. 10.1177/01634437221119021 · DOI · Paper page
  30. 10.1093/ijpor/edl003 · DOI
  31. 10.1007/978-3-030-87626-5_19 · DOI
  32. 10.1038/s41558-022-01377-7 · DOI · Paper page
  33. 10.1007/s12369-020-00640-1 · DOI
  34. 10.1007/978-3-030-81907-1_3 · DOI
  35. 10.1177/0894439317698637 · DOI · Paper page
  36. 10.1016/j.tele.2015.08.007 · DOI
  37. 10.1017/s0140525x1300263x · DOI
  38. 10.1037/0022-3514.76.5.839 · DOI · Paper page
  39. 10.1038/s41562-019-0670-y · DOI
  40. 10.1146/annurev-psych-122414-033608 · DOI · Paper page
  41. 10.1145/3375959.3375968 · DOI
  42. 10.1177/10946705221103538 · DOI
  43. 10.1108/JBS-11-2021-0182 · DOI
  44. Pew Research Center, .., The American Trends Panel
  45. 10.1177/0963662520917339 · DOI
  46. 10.1016/j.sleh.2022.01.001 · DOI
  47. 10.1016/j.ssmph.2020.100717 · DOI
  48. A. F. Hayes, 2017, Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach
  49. 10.1016/j.ausmj.2017.02.001 · DOI
  50. 10.1111/j.1745-9125.1998.tb01268.x · DOI
  51. 10.1007/s00146-021-01148-6 · DOI
  52. 10.1177/10755470241232352 · DOI

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Metadata

Authors
Li, W., & Zheng, X.
Venue
Human Behavior and Emerging Technologies
Publisher
Wiley
Published
2024-04-02
Volume
2024
Pages
1-11
ISSN
2578-1863
DOI
10.1155/2024/3448083
Cited by
15
References
15
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (unspecified)

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