Research Article

Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency

Volume: 22 Number: 5 September 30, 2025
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Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency

Abstract

The increasing dependence on AI-supported services raises important questions about how positive beliefs about AI can turn into privacy risks. This study tests a gender-moderated mediation model of AI attitude, AI dependence, and online privacy concern (OPC) among Turkish university students. A cross-sectional survey conducted on 478 students using validated scales (AIAS-4, AI Dependency Scale, OPC Scale) was analyzed using structural equation modeling and the PROCESS Model 59. The measurement model demonstrated excellent fit (χ²/df = 1.01, CFI = 0.999, RMSEA = 0.005) and strong reliability-validity indicators. AI attitude significantly increased AI dependency (β = .50, p < .001), which in turn strengthened OPC (β = .77, p < .001). Gender moderates both relationships and reveals a significant moderator-mediation index (−.11; 95% CI [−.21, −.01]). Overall, the model explains 28% of the variance in OPC. The findings reveal a two-way effect of positive AI attitudes: while promoting beneficial participation, they also increase dependency-based privacy concerns, particularly among female users. Organizations should integrate privacy-aware AI literacy and gender-sensitive feedback mechanisms into digital platforms to mitigate risks while maintaining trust.

Keywords

digitalization, AI attitude, AI dependence, online privacy concern

References

  1. Alakurt, T. (2017). Çevrimiçi mahremiyet kaygısı ölçeğinin Türk kültürüne uyarlanması. Pegem Eğitim ve Öğretim Dergisi, 7(4), 611-636.
  2. Barnes, S. J., & Pressey, A. D. (2012). In search of the “privacy paradox”: Privacy concerns and willingness to disclose in online social networks. Journal of Business Research, 66(9), 1528–1535. https://doi.org/10.1016/j.jbus-res.2012.02.015
  3. Bayor, L., Weinert, C., Maier, C., & Weitzel, T. (2025). Social-oriented communication with AI companions: Benefits, costs, and contextual patterns. Business & Information Systems Engineering, 67(4), 1–19. https://doi.org/10.1007/s12599-025-00955-1
  4. Buchanan, T., Paine, C., Joinson, A. N., & Reips, U. D. (2007). Development of measures of online privacy concern and protection for use on the Internet. Journal of the American Society for Information Science and Technology, 58(2), 157–165. https://doi.org/-10.1002/asi.20459
  5. Byrne, B. M. (2013). Structural equation modeling with AMOS: Basic concepts, applications, and programming (1st ed.). New York, NY: Routledge. https://doi.org/10.4324/97802-03807644
  6. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. http://doi.org/10.-1207/S15328007SEM0902_5
  7. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
  8. Degeling, M., Lentzsch, C., Nolte, A., Herrmann, T., & Loser, K. U. (2016, November). Privacy by socio-technical design: A collaborative approach for privacy friendly system design. In 2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC) (pp. 502-505). IEEE. https://doi.org/10.1109/CIC.2016.077
  9. Elliott, D., & Soifer, E. (2022). AI technologies, privacy, and security. Frontiers in Artificial Intelligence, 5, 826737. https://doi.org/10.-3389/frai.2022.826737
  10. Emon, M. M. H., Khan, T., Rahman, M. A., & Siam, S. A. J. (2024, September). Factors influencing the usage of artificial intelligence among Bangladeshi professionals: Mediating role of attitude towards the technology. In 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS) (pp. 1-7). IEEE. https://doi.org/10.-1109/COMPAS60761.2024.10796110
APA
Fidan, Ü. (2025). Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency. OPUS Journal of Society Research, 22(5), 869-881. https://doi.org/10.26466/opusjsr.1725180
AMA
1.Fidan Ü. Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency. OPUS JSR. 2025;22(5):869-881. doi:10.26466/opusjsr.1725180
Chicago
Fidan, Üzeyir. 2025. “Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency”. OPUS Journal of Society Research 22 (5): 869-81. https://doi.org/10.26466/opusjsr.1725180.
EndNote
Fidan Ü (September 1, 2025) Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency. OPUS Journal of Society Research 22 5 869–881.
IEEE
[1]Ü. Fidan, “Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency”, OPUS JSR, vol. 22, no. 5, pp. 869–881, Sept. 2025, doi: 10.26466/opusjsr.1725180.
ISNAD
Fidan, Üzeyir. “Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency”. OPUS Journal of Society Research 22/5 (September 1, 2025): 869-881. https://doi.org/10.26466/opusjsr.1725180.
JAMA
1.Fidan Ü. Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency. OPUS JSR. 2025;22:869–881.
MLA
Fidan, Üzeyir. “Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency”. OPUS Journal of Society Research, vol. 22, no. 5, Sept. 2025, pp. 869-81, doi:10.26466/opusjsr.1725180.
Vancouver
1.Üzeyir Fidan. Individual Privacy Perception in the Digital Age: The Interaction of Artificial Intelligence Attitude and Dependency. OPUS JSR. 2025 Sep. 1;22(5):869-81. doi:10.26466/opusjsr.1725180