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The role of gender in perceptions of artificial intelligence and robotic technologies: A fear, trust, and benefit perspective

Yıl 2025, Cilt: 11 Sayı: 3, 315 - 326, 27.10.2025

Dilek Uslu

https://doi.org/10.30855/gjeb.2025.11.3.008

Öz

This study examines the role of gender in individuals’ perceptions of artificial intelligence and robotic technologies in healthcare, focusing on fear, trust, and perceived benefits. The research was conducted with 427 participants across Türkiye using an online survey, and the data were analyzed with SPSS. The findings indicate that women reported higher levels of fear and lower levels of trust and perceived benefits toward artificial intelligence and robotic technologies compared to men. Women expressed greater concerns particularly about ethical violations, privacy issues, the transfer of healthcare services to private companies, and the replacement of human roles with machines. Men, on the other hand, demonstrated more positive attitudes regarding the potential benefits of these technologies, such as reducing workload, increasing process efficiency, and enhancing service quality. These results underscore the importance of developing inclusive and ethically-oriented strategies that account for gender differences in the digitalization of healthcare services.

Anahtar Kelimeler

Artificial intelligence Robotic technologies Gender Differences

Kaynakça

  • Abel, M., Giese, M. A. ve Vuong, Q. C. (2024). Perception of robotic actions and the influence of gender. Frontiers in Psychology, 15, 1295279. Doi: https://doi.org/10.3389/fpsyg.2024.1295279
  • Afonso, C. M., Roldán, J. L., Sánchez-Franco, M. J. ve González, M. de la O. (2012, May 19–22). The moderator role of gender in the Unified Theory of Acceptance and Use of Technology (UTAUT): A study on users of electronic document management systems. In Proceedings of the 7th International Conference on Partial Least Squares and Related Methods (PLS-2012). Houston, USA.
  • Aldasoro, I., Armantier, O., Doerr, S., Gambacorta, L. ve Oliviero, T. (2024). The gen AI gender gap. Economics Letters, 241, 111814. Doi: https://doi.org/10.1016/j.econlet.2024.111814
  • Babalola, G. T., Gaston, J.-M., Trombetta, J. ve Tulk Jesso, S. (2024). A systematic review of collaborative robots for nurses: Where are we now, and where is the evidence? Frontiers in Robotics and AI, 11, 1398140. Doi: https://doi.org/10.3389/frobt.2024.1398140
  • Choudrie, J., Junior, C. O., McKenna, B. ve Richter, S. (2018). Understanding and conceptualising the adoption, use and diffusion of mobile banking in older adults: A research agenda and conceptual framework. Journal of Business Research, 88, 449–465. Doi: https://doi.org/10.1016/j.jbusres.2017.11.029
  • Davenport, T. ve Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Doi: https://doi.org/10.2307/249008
  • de Graaf, M. M. A. ve Allouch, S. B. (2013). Exploring influencing variables for the acceptance of social robots. Robotics and Autonomous Systems, 61(12), 1476–1486. Doi: https://doi.org/10.1016/j.robot.2013.07.007
  • Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. Doi: https://doi.org/10.1016/j.ijinfomgt.2019.08.002
  • Enginyurt, E. (2025). Sağlık çalışanlarının yapay zekâya yönelik tutum ve kaygıları. Güncel Sağlık Yönetimi, 3(1), 50–65. https://dergipark.org.tr/tr/download/article-file/4658296
  • Floridi, L. ve Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). Doi: https://doi.org/10.1162/99608f92.8cd550d1
  • Gefen, D. ve Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389–400. Doi: https://doi.org/10.2307/249720
  • Hoşgör, H. ve Bozkurt, Ş. A. (2023). Sağlıkta yapay zekâ ve robotlar hakkında kimler ne düşünüyor? Kuşaklar üzerine bir araştırma. Sosyal Bilimler Araştırma Dergisi, 12(1), 13–25.
  • Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H. ve Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. Doi: https://doi.org/10.1136/svn-2017-000101
  • Jobin, A., Ienca, M. ve Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. Doi: https://doi.org/10.1038/s42256-019-0088-2
  • Jöhnk, J., Weißert, M. ve Wyrtki, K. (2021). Ready or not, AI comes: An interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5–20. Doi: https://doi.org/10.1007/s12599-020-00676-7
  • Karasar, N. (2012). Bilimsel araştırma yöntemi (24. baskı). Nobel Yayıncılık.
  • McAfee, A. ve Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. WW Norton & Company.
  • OECD. (2025). Does healthcare deliver?: Results from the Patient-Reported Indicator Surveys (PaRIS). OECD Health Policy Studies. OECD Publishing. Doi: https://doi.org/10.1787/c8af05a5-en
  • Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, California: Sage Publications.
  • Pew Research Center. (2025, April 3). How the U.S. public and AI experts view artificial intelligence. https://www.pewresearch.org/internet/2025/04/03/how-the-us-public-and-ai-experts-view-artificial-intelligence/
  • Russo, C., Romano, L., Clemente, D., Iacovone, L., Gladwin, T. E. ve Panno, A. (2025). Gender differences in artificial intelligence: the role of artificial intelligence anxiety. Frontiers in Psychology, 16, 1559457. Doi: https://doi.org/10.3389/fpsyg.2025.1559457
  • Shevtsova, D., Ahmed, A., Boot, I. W. A., Sanges, C., Hudecek, M., Jacobs, J. J. L., Hort, S. ve Vrijhoef, H. J. M. (2024). Trust in and acceptance of AI applications in healthcare: Mixed-methods study. JMIR Human Factors, 11(1), e47031. Doi: https://doi.org/10.2196/47031
  • Topol, E. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. Doi: https://doi.org/10.1038/s41591-018-0300-7
  • Türkiye İstatistik Kurumu (TÜİK). (2024, 27 Ağustos). Hanehalkı bilişim teknolojileri kullanım araştırması 2024. https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2024-53492
  • Venkatesh, V. ve Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139. Doi: https://doi.org/10.2307/3250981
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Doi: https://doi.org/10.2307/30036540
  • World Economic Forum. (2024). Global gender gap report 2024. https://www3.weforum.org/docs/WEF_GGGR_2024.pdf
  • Yıldırım, A. ve Şimşek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri (7. baskı). Ankara: Seçkin Yayıncılık.
  • Yorgancıoğlu Tarcan, G., Yalçın Balçık, P. ve Sebik, N. B. (2024). Türkiye ve dünyada sağlık hizmetlerinde yapay zekâ. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 14(1), 50-60. Doi: https://doi.org/10.31020/mutftd.1278529

Yapay zekâ ve robotik teknolojilere yönelik algılarda toplumsal cinsiyetin rolü: Korku, güven ve fayda perspektifi

Yıl 2025, Cilt: 11 Sayı: 3, 315 - 326, 27.10.2025

Dilek Uslu

https://doi.org/10.30855/gjeb.2025.11.3.008

Öz

Bu çalışma, bireylerin sağlık hizmetlerinde yapay zekâ ve robotik teknolojilere yönelik korku, güven ve fayda algılarında toplumsal cinsiyetin rolünü incelemektedir. Türkiye genelinde 427 katılımcıyla çevrim içi anket yoluyla yürütülen araştırmada veriler SPSS programı ile analiz edilmiştir. Bulgular, kadınların yapay zekâ ve robotik teknolojilere karşı erkeklere kıyasla daha yüksek düzeyde korku duyduğunu ve daha düşük güven ile fayda algısına sahip olduğunu göstermektedir. Kadınların özellikle etik ihlaller, mahremiyet kaygıları, sağlık hizmetlerinin özel şirketlere devredilmesi ve insan unsurunun makinelerle ikame edilmesi konularında daha fazla endişe duydukları belirlenmiştir. Erkekler ise bu teknolojilerin iş yükünü azaltma, süreç verimliliğini artırma ve hizmet kalitesine katkıda bulunma gibi potansiyel faydalarına ilişkin daha olumlu tutum sergilemiştir. Bu sonuçlar, sağlıkta dijitalleşme süreçlerinde toplumsal cinsiyet farklılıklarını gözeten kapsayıcı ve etik odaklı stratejilerin geliştirilmesinin önemini ortaya koymaktadır.

Anahtar Kelimeler

Yapay Zeka Robotik Teknolojiler Toplumsal Cinsiyet

Etik Beyan

Ankara Hacı Bayram Veli Üniversitesi Etik Kurulu’nun 27.11.2024 tarihli ve 2024/415 sayılı onayı ile yürütülmüştür.

Kaynakça

  • Abel, M., Giese, M. A. ve Vuong, Q. C. (2024). Perception of robotic actions and the influence of gender. Frontiers in Psychology, 15, 1295279. Doi: https://doi.org/10.3389/fpsyg.2024.1295279
  • Afonso, C. M., Roldán, J. L., Sánchez-Franco, M. J. ve González, M. de la O. (2012, May 19–22). The moderator role of gender in the Unified Theory of Acceptance and Use of Technology (UTAUT): A study on users of electronic document management systems. In Proceedings of the 7th International Conference on Partial Least Squares and Related Methods (PLS-2012). Houston, USA.
  • Aldasoro, I., Armantier, O., Doerr, S., Gambacorta, L. ve Oliviero, T. (2024). The gen AI gender gap. Economics Letters, 241, 111814. Doi: https://doi.org/10.1016/j.econlet.2024.111814
  • Babalola, G. T., Gaston, J.-M., Trombetta, J. ve Tulk Jesso, S. (2024). A systematic review of collaborative robots for nurses: Where are we now, and where is the evidence? Frontiers in Robotics and AI, 11, 1398140. Doi: https://doi.org/10.3389/frobt.2024.1398140
  • Choudrie, J., Junior, C. O., McKenna, B. ve Richter, S. (2018). Understanding and conceptualising the adoption, use and diffusion of mobile banking in older adults: A research agenda and conceptual framework. Journal of Business Research, 88, 449–465. Doi: https://doi.org/10.1016/j.jbusres.2017.11.029
  • Davenport, T. ve Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Doi: https://doi.org/10.2307/249008
  • de Graaf, M. M. A. ve Allouch, S. B. (2013). Exploring influencing variables for the acceptance of social robots. Robotics and Autonomous Systems, 61(12), 1476–1486. Doi: https://doi.org/10.1016/j.robot.2013.07.007
  • Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. Doi: https://doi.org/10.1016/j.ijinfomgt.2019.08.002
  • Enginyurt, E. (2025). Sağlık çalışanlarının yapay zekâya yönelik tutum ve kaygıları. Güncel Sağlık Yönetimi, 3(1), 50–65. https://dergipark.org.tr/tr/download/article-file/4658296
  • Floridi, L. ve Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). Doi: https://doi.org/10.1162/99608f92.8cd550d1
  • Gefen, D. ve Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389–400. Doi: https://doi.org/10.2307/249720
  • Hoşgör, H. ve Bozkurt, Ş. A. (2023). Sağlıkta yapay zekâ ve robotlar hakkında kimler ne düşünüyor? Kuşaklar üzerine bir araştırma. Sosyal Bilimler Araştırma Dergisi, 12(1), 13–25.
  • Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H. ve Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230–243. Doi: https://doi.org/10.1136/svn-2017-000101
  • Jobin, A., Ienca, M. ve Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. Doi: https://doi.org/10.1038/s42256-019-0088-2
  • Jöhnk, J., Weißert, M. ve Wyrtki, K. (2021). Ready or not, AI comes: An interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5–20. Doi: https://doi.org/10.1007/s12599-020-00676-7
  • Karasar, N. (2012). Bilimsel araştırma yöntemi (24. baskı). Nobel Yayıncılık.
  • McAfee, A. ve Brynjolfsson, E. (2017). Machine, platform, crowd: Harnessing our digital future. WW Norton & Company.
  • OECD. (2025). Does healthcare deliver?: Results from the Patient-Reported Indicator Surveys (PaRIS). OECD Health Policy Studies. OECD Publishing. Doi: https://doi.org/10.1787/c8af05a5-en
  • Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, California: Sage Publications.
  • Pew Research Center. (2025, April 3). How the U.S. public and AI experts view artificial intelligence. https://www.pewresearch.org/internet/2025/04/03/how-the-us-public-and-ai-experts-view-artificial-intelligence/
  • Russo, C., Romano, L., Clemente, D., Iacovone, L., Gladwin, T. E. ve Panno, A. (2025). Gender differences in artificial intelligence: the role of artificial intelligence anxiety. Frontiers in Psychology, 16, 1559457. Doi: https://doi.org/10.3389/fpsyg.2025.1559457
  • Shevtsova, D., Ahmed, A., Boot, I. W. A., Sanges, C., Hudecek, M., Jacobs, J. J. L., Hort, S. ve Vrijhoef, H. J. M. (2024). Trust in and acceptance of AI applications in healthcare: Mixed-methods study. JMIR Human Factors, 11(1), e47031. Doi: https://doi.org/10.2196/47031
  • Topol, E. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. Doi: https://doi.org/10.1038/s41591-018-0300-7
  • Türkiye İstatistik Kurumu (TÜİK). (2024, 27 Ağustos). Hanehalkı bilişim teknolojileri kullanım araştırması 2024. https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2024-53492
  • Venkatesh, V. ve Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139. Doi: https://doi.org/10.2307/3250981
  • Venkatesh, V., Morris, M. G., Davis, G. B. ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Doi: https://doi.org/10.2307/30036540
  • World Economic Forum. (2024). Global gender gap report 2024. https://www3.weforum.org/docs/WEF_GGGR_2024.pdf
  • Yıldırım, A. ve Şimşek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri (7. baskı). Ankara: Seçkin Yayıncılık.
  • Yorgancıoğlu Tarcan, G., Yalçın Balçık, P. ve Sebik, N. B. (2024). Türkiye ve dünyada sağlık hizmetlerinde yapay zekâ. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 14(1), 50-60. Doi: https://doi.org/10.31020/mutftd.1278529
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Hastane İşletmeciliği, İnovasyon Yönetimi
Bölüm Makaleler
Yazarlar

Dilek Uslu 0009-0007-9072-2881

Erken Görünüm Tarihi 27 Ekim 2025
Yayımlanma Tarihi 27 Ekim 2025
Gönderilme Tarihi 17 Temmuz 2025
Kabul Tarihi 12 Eylül 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 11 Sayı: 3

Kaynak Göster

APA Uslu, D. (2025). Yapay zekâ ve robotik teknolojilere yönelik algılarda toplumsal cinsiyetin rolü: Korku, güven ve fayda perspektifi. Gazi İktisat ve İşletme Dergisi, 11(3), 315-326. https://doi.org/10.30855/gjeb.2025.11.3.008
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