Yapay Zekâ Kaygısının Gelecek Kaygısı ve Yenilikçi Davranışlar Üzerindeki Etkisi: Üniversite Öğrencileri Üzerine Bir Uygulama

Öz

Çalışmanın amacı üniversite öğrencilerinin yapay zekâ kaygılarının yenilikçi davranışları üzerindeki etkisini gelecek kaygısı aracılığında incelemektir. Çalışmada yapay zekâ konusundaki gelişimlerin genç nesilleri nasıl etkilediği ve potansiyel iş gücünün yenilikçi davranışlarının bu gelişmelerden nasıl etkilendiği araştırılmıştır. Bireylerin sosyolojik, ekonomik ve siyasi gelişmeler sonucunda gelecek kaygısı yaşamaları ve gelecek kaygısının yapay zekâ kaygısı ve yenilikçi davranışlar etkileşimindeki rolü incelenmiştir. Araştırma evrenini Tokat Gaziosmanpaşa Üniversitesi öğrencileri oluşturmaktadır. Veriler, anket tekniği ile 384 öğrenciden yüz yüze ve çevrim içi şekilde toplanmıştır. Araştırma bulgularına göre üniversite öğrencilerindeki yapay zekâ kaygısının, yenilikçi davranışları pozitif etkilediği ve gelecek kaygısının bu etkileşimde aracı rolü olduğu tespit edilmiştir. Üniversite öğrencilerin toplumun gelişiminde ve kalkınmasında önemli rolü bulunmaktadır. Yapay zekâ kaygısının yenilikçi davranışları olumlu yönde etkilemesinde akademisyenlere ve uygulayıcılara önemli görevler düşmektedir. Çalışma kapsamında, araştırma değişkenleri özelinde kaygıların optimum düzeyde tutulması ve yeni nesillerin yenilikçi/yaratıcı davranışlara teşvik edilmesi açısından önerilerde bulunulmuştur.

Anahtar Kelimeler

• Yapay Zekâ Kaygısı
• Gelecek Kaygısı
• Yenilikçi Davranış

The Effect of Fear of Artificial Intelligence on Future Anxiety and Innovative Behaviors: An Application on University Students

Öz

The study aims to examine the effect of university students' fear of artificial intelligence on their innovative behaviors by mediating future concerns. It was investigated how developments in artificial intelligence affect young generations and how the innovative behaviors of the potential workforce are affected by these developments. Individuals' future anxiety as a result of sociological, economic, and political developments and the role of future anxiety in the interaction of fear of artificial intelligence and innovative behaviors were examined. The research population consists of Tokat Gaziosmanpaşa University students. Data were collected from 384 students via survey technique, face-to-face and online. According to the research findings, it has been determined that fear of artificial intelligence in university students positively affects innovative behaviors and future anxiety, which has a mediating role in this interaction. University students have an essential role in the development and progress of society. Academicians and practitioners have important roles in ensuring that fear of artificial intelligence positively affects innovative behaviors. Within the scope of the study, suggestions were made to keep the concerns specific to the research variables at an optimum level and to encourage new generations to have innovative/creative behaviors.

Anahtar Kelimeler

• Fear of Artificial Intelligence
• Future Anxiety
• Innovative Behavior

Kaynakça

1. Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188-2244.
2. Akkaya, B., Özkan, A., & Özkan, H. (2021). Yapay zekâ kaygı (YZK) ölçeği: Türkçeye uyarlama, geçerlik ve güvenirlik çalışması. Alanya Akademik Bakış, 5(2), 1125-1146.
3. Al Khoury, G., Hallit, R., Malaeb, D., Sakr, F., Dabbous, M., Merdad, N., ... & Obeid, S. (2024). The relationship between optimism-pessimism and fear of Artificial Intelligence in young adults from four Arab countries: The mediating effect of seeing a dark future, 18 July 2024, PREPRINT (Version 1)
4. Allison, P. D. (1999). Multiple regression: A primer. Pine Forge Press.
5. Alotaibi, N. S., & Alshehri, A. H. (2023). Prospers and obstacles in using artificial intelligence in Saudi Arabia higher education institutions—The potential of AI-based learning outcomes. Sustainability, 15(13), 10723.
6. Altunışık, R., Gegez, E., Koç, E., Sığrı, Ü., Yüksel, A., Boz, H., & Yıldız, E. (2022). Sosyal bilimlerde araştırma yöntemleri: Yeni perspektifler. Seçkin Yayıncılık.
7. Aşantuğrul, N. (2024). Üniversite öğrencilerinin gelecek kaygıları üzerine nitel bir araştırma: Üniversite öğrencilerinde gelecek kaygısı. Ases Ulusal Sosyal Bilimler Dergisi, 4(1), 62-68.
8. Bawuro, F. A., Shamsuddin, A., Wahab, E., Adenuga, K. I., & Ndaghu, J. T. (2019). Motivational mechanisms on teachers’ innovative behaviour-a systematic review approach. Journal of Critical Reviews, 7(6), 239-245.

9. Bessen, J. (2019). Automation and jobs: When technology boosts employment. Economic Policy, 34(100), 589-626.
10. Bochniarz, K. T., Czerwiński, S. K., Sawicki, A., & Atroszko, P. A. (2022). Attitudes to AI among high school students: Understanding distrust towards humans will not help us understand distrust towards AI. Personality and Individual Differences, 185, 111299.
11. Boddington, P., Millican, P., & Wooldridge, M. (2017). Minds and machines special issue: Ethics and artificial intelligence. Minds and Machines, 27, 569-574.
12. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. WW Norton & company.
13. Bysted, R. (2013). Innovative employee behaviour: The moderating effects of mental involvement and job satisfaction on contextual variables. European Journal of Innovation Management, 16(3), 268–284.
14. Calo, R. (2017). Artificial intelligence policy: a primer and roadmap. UCDL Rev., 51, 399.
15. Chowdhury, S., Joel-Edgar, S., Dey, P. K., Bhattacharya, S., & Kharlamov, A. (2023). Embedding transparency in artificial intelligence machine learning models: managerial implications on predicting and explaining employee turnover. The International Journal of Human Resource Management, 34(14), 2732-2764.
16. Chuo, Y. H., Tsai, C. H., Lan, Y. L., & Tsai, C. S. (2011). The effect of organizational support, self efficacy, and computer anxiety on the usage intention of e-learning system in hospital. African Journal of Business Management, 5(14), 5518–5523.
17. Clarke, R. (2019). Why the world wants controls over Artificial Intelligence. Computer Law & Security Review, 35(4), 423-433.
18. Creswell, J. W. (2017). Nitel, Nicel Araştırma Deseni ve Karma Yöntem Yaklaşımları. (Çev. Ed. Demir, S.B.). 3. Baskı. Eğiten Kitap.
19. Çalışkan, A., Akkoç, İ., & Turunç, Ö. (2019). Yenilikçi davranış: Bir ölçek uyarlama çalışması. Uluslararası İktisadi ve İdari Bilimler Dergisi, 5(1), 94-111.
20. Çetiner, N., & Çetinkaya, F. Ö. (2024). Çalışanların yapay zekâ kaygısı ile motivasyon düzeyleri arasındaki ilişki: Turizm çalışanları üzerine bir araştırma. Alanya Akademik Bakış, 8(1), 159-173.
21. D'zurilla, T. J., & Nezu, A. M. (1990). Development and preliminary evaluation of the Social Problem-Solving Inventory. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 2(2), 156.
22. Damanpour, F. (1996). Organizational complexity and innovation: Developing and testing multiple contingency models. Management science, 42(5), 693-716.
23. De Jong, J., & Den Hartog, D. (2010). Measuring innovative work behaviour. Creativity and Innovation Management, 19(1), 23-36.
24. Deci, E. L., Olafsen, A. H., & Ryan, R. M. (2017). Self-determination theory in work organizations: The state of a science. Annual Review of Organizational Psychology and Organizational Behavior, 4(1), 19-43.
25. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71.
26. Dursun, S. & Aytaç, S. (2009). Üniversite öğrencileri arasında işsizlik kaygısı. Uludağ Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 28(1), 71-81.
27. Esmer, Y., & Arıbaş, A. N. (2023). Önlisans öğrencilerinin gelecek kaygılarına yönelik nitel bir araştırma. Karamanoğlu Mehmetbey Üniversitesi Sosyal ve Ekonomik Araştırmalar Dergisi, 25(44), 330-347.
28. Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin's Press.
29. Gedikli, E., & Akdoğan, R. (2023). Sağlık yönetimi öğrencilerinin gelecek kaygısı ile mutluluk düzeyleri arasındaki ilişkinin incelenmesi. Abant Sağlık Bilimleri ve Teknolojileri Dergisi, 3(3), 1-12.
30. Gherheş, V. (2018). Why are we afraid of artificial intelligence (AI)?. European Review of Applied Sociology, 11(17), 6-15.
31. Giallonardo, V., Sampogna, G., Del Vecchio, V., Luciano, M., Albert, U., Carmassi, C., ... & Fiorillo, A. (2020). The impact of quarantine and physical distancing following COVID-19 on mental health: study protocol of a multicentric Italian population trial. Frontiers in Psychiatry, 11, 533.
32. Granter, S. R., Beck, A. H., & Papke Jr, D. J. (2017). AlphaGo, deep learning, and the future of the human microscopist. Archives of Pathology & Laboratory Medicine, 141(5), 619-621.
33. Guggemos, J. (2024). To fear or not to fear–Human resource development professionals’ positioning towards artificial intelligence with a focus on augmentation. Computers and Education: Artificial Intelligence, 7, 100260.
34. Ha, J. G., Page, T., & Thorsteinsson, G. (2011). A study on technophobia and mobile device design. International Journal Of Contents, 7(2), 17–25.
35. Hammad, M. A. (2016). Future anxiety and its relationship to students' attitude toward academic specialization. Journal of Education and Practice, 7(15), 54-65.
36. Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford publications.
37. Hayton, J. C., & Cholakova, M. (2012). The role of affect in the creation and intentional pursuit of entrepreneurial ideas. Entrepreneurship Theory and Practice, 36(1), 41-67.
38. Hemade, A., Hallit, R., Malaeb, D., Sakr, F., Dabbous, M., Merdad, N., ... & Obeid, S. (2024). The mediating effect of dark future between personality traits and fear of artificial İntelligence in arab young adults. PREPRINT (Version 1)
39. Henkel, A. P., Bromuri, S., Iren, D., & Urovi, V. (2020). Half human, half machine–augmenting service employees with AI for interpersonal emotion regulation. Journal of Service Management, 31(2), 247-265.
40. Jaiswal, A., Arun, C. J., & Varma, A. (2023). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. İçinde Artificial Intelligence and International HRM (pp. 114-143). Routledge.
41. Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
42. Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267-2270.
43. Kim, J. Y., Choi, D. S., Sung, C. S., & Park, J. Y. (2018). The role of problem solving ability on innovative behavior and opportunity recognition in university students. Journal of Open Innovation: Technology, Market, and Complexity, 4(1), 4.
44. Kim, J., Kadkol, S., Solomon, I., Yeh, H., Soh, J. Y., Nguyen, T. M., ... & Ajilore, O. A. (2023). AI anxiety: A comprehensive analysis of psychological factors and interventions. Available at SSRN 4573394.
45. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
46. Kula, K. Ş., & Saraç, T. (2016). Üniversite öğrencilerinin gelecek kaygısı/The future anxiety of the university students. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 13(33), 227-242.
47. Kwang, N. A., & Rodrigues, D. (2002). A Big‐Five Personality profile of the adaptor and innovator. The Journal of Creative Behavior, 36(4), 254-268.
48. Lesia Viktorivna, K., Oleksandrovych, A. V., Oleksandrivna, I. K., & Oleksandrivna, N. K. (2022). Artificial intelligence in language learning: What are we afraid of. Arab World English Journal. (8), 262-273.
49. Li, J., & Huang, J. S. (2020). Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society, 63, 101410.
50. Liang, H., Peng, Z., Xue, Y., Guo, X., & Wang, N. (2015). Employees’ exploration of complex systems: An integrative view. Journal of Management Information Systems, (1), 322–357.
51. Manev, I. M., Gyoshev, B. S., & Manolova, T. S. (2005). The role of human and social capital and entrepreneurial orientation for small business performance in a transitional economy. International Journal of Entrepreneurship and Innovation Management, 5(3-4), 298-318.
52. Menzies, R. G., & Clarke, J. C. (1995). The etiology of phobias: A nonassociative account. Clinical Psychology Review, 15(1), 23-48.
53. Milosevic, I., & McCabe, R. E. (2015). Phobias: The psychology of irrational fear. Bloomsbury Publishing.
54. Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679.
55. Müller, V. C., & Bostrom, N. (2014). Future progress in artificial intelligence: A poll among experts. AI Matters, 1(1), 9-11.
56. Öztırak, M. (2023). A study on the impact of artificial intelligence anxiety on the innovation-oriented behaviours of employees. Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 10(2), 267-286.
57. Paredes, M. R., Apaolaza, V., Fernandez-Robin, C., Hartmann, P., & Yañez-Martinez, D. (2021). The impact of the COVID-19 pandemic on subjective mental well-being: The interplay of perceived threat, future anxiety and resilience. Personality and Individual Differences, 170, 110455.
58. Pınar, G., & Bozkurt, Ö. Ç. (2022). Yenilikçi davranış yoluyla akademik başarıyı desteklemede yaratıcı öz yeterlik ve dijital okuryazarlığın rolü. Mehmet Akif Ersoy Üniversitesi Uygulamalı Bilimler Dergisi, 6(1), 1-31.
59. Pirim, H. (2006). Yapay zekâ. Journal of Yasar University, 1(1), 81-93.
60. Rachman, S. (1977). The conditioning theory of fearacquisition: A critical examination. Behaviour Research and Therapy, 15(5), 375-387.
61. Rahwan, I., Cebrian, M., Obradovich, N. et al. (2019). Machine behaviour. Nature, 568, 477–486.
62. Rayburn, S. W., Anderson, S., & Sierra, J. J. (2021). Future thinking continuity of learning in marketing: A student perspective on crisis management in higher education. Marketing Education Review, 31(3), 241-255.
63. Rogers, C. R. (2013). A theory of therapy and personality change: As developed in the client-centered framework. Perspectives in Abnormal Behavior: Pergamon General Psychology Series, 341.
64. Saruhan, Ş. C., & Özdemirci, A. (2018). Bilim, felsefe ve metodoloji. Beta yayınları.
65. Sharkey, A., & Sharkey, N. (2012). Granny and the robots: Ethical issues in robot care for the elderly. Ethics and Information Technology, 14, 27-40.
66. Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935-943.
67. Shin, D. (2021). The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI. International Journal of Human-Computer Studies, 146, 102551.
68. Spivack, G., Platt, J. J., & Shure, M. B. (1976). The problem-solving approach to adjustment. Jossey-Bass.
69. Şahin, M. (2019). Korku, kaygı ve kaygı (anksiyete) bozuklukları. Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi, 6(10), 117-135.
70. Tabachnick, B. G., & Fidell, L. S. (2014). Using multivariate statistics: Pearson new international edition, Pearson.
71. Türköz, O., Bektaş, M., & Çiçek, H. (2021). Lisansüstü eğitim alan öğrencilerde gelecek kaygısı. Bucak İşletme Fakültesi Dergisi, 4(2), 132-152.
72. Verma, S., & Singh, V. (2022). Impact of artificial intelligence-enabled job characteristics and perceived substitution crisis on innovative work behavior of employees from high-tech firms. Computers in Human Behavior, 131, 107215.
73. Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. Journal of Database Management (JDM), 30(1), 61-79.
74. Wang, Y. Y., & Wang, Y. S. (2022). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 30(4), 619-634.
75. Warwick, K. (2023). Yapay Zekâ Temel Prensipler, Çev. G. Uysal & A. Uysal, Ginko Bilim.
76. Yıldırım, M., Kaynar, Ö., Arslan, G., & Chirico, F. (2023). Fear of COVID-19, resilience, and future anxiety: Psychometric properties of the Turkish version of the dark future scale. Journal of Personalized Medicine, 13(4), 597.
77. Zaleski, Z. (1996). Future anxiety: Concept, measurement, and preliminary research. Personality and Individual Differences, 21(2), 165-174.
78. Zaleski, Z., Sobol-Kwapinska, M., Przepiorka, A., & Meisner, M. (2019). Development and validation of the Dark Future scale. Time & Society, 28(1), 107-123.
79. Zarsky, T. (2016). The trouble with algorithmic decisions: An analytic road map to examine efficiency and fairness in automated and opaque decision making. Science, Technology, & Human Values, 41(1), 118-132.
80. Zengin, Y., & Boran, O. (2019). İş güvencesizliğinin gelecek kaygısı ve çalışan performansına etkisi: Bir uygulama. Sosyal, Beşeri ve İdari Bilimler Dergisi, 2(10), 719-736.
81. Zirar, A. (2023). Can artificial intelligence’s limitations drive innovative work behaviour?. Review of Managerial Science, 17(6), 2005-2034.