TY - JOUR T1 - EXAMINING THE AI ANXIETY LEVELS OF AVIATION EMPLOYEES BASED ON DEMOGRAPHIC VARIABLES TT - HAVACILIK ÇALIŞANLARININ YAPAY ZEKA KAYGI DÜZEYLERİNİN DEMOGRAFİK DEĞİŞKENLERE GÖRE İNCELENMESİ AU - Tuncal, Arif PY - 2025 DA - June Y2 - 2025 DO - 10.16953/deusosbil.1524579 JF - Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi JO - DEU Journal of GSSS PB - Dokuz Eylul University WT - DergiPark SN - 1308-0911 SP - 518 EP - 546 VL - 27 IS - 2 LA - en AB - The accelerated advancements in Artificial Intelligence (AI) give rise to anxieties regarding workplace tasks, job security, privacy, and ethics, which significantly impact employees in the technology-intensive aviation sector. The aim of the study was to examine the level of AI anxiety among professionals in the aviation sector and to investigate whether it varies based on factors such as gender, education, age, experience, and sub-sector. A survey methodology was employed. An online questionnaire was used to collect data from 345 aviation sector employees. The AI Anxiety Scale, a 5-point Likert-based instrument, was used as the measurement tool. The analysis results indicated that AI anxiety levels among aviation sector employees were moderate (M=2.8047). AI anxiety levels were highest in the sociotechnical/blindness sub-dimension (M=3.3775) and lowest in the AI learning sub-dimension (M=2.1055). No statistically significant differences in anxiety levels were found based on age, experience, or sub-sector, whereas education level showed significant differences. Although general AI anxiety did not significantly vary by gender, a notable difference was observed in AI configuration. As AI evolves in the aviation sector, addressing employee anxieties across sub-dimensions is essential for effective integration. Given the rapid advancements in AI technology, future studies should adopt a more detailed approach, focusing on sector-specific variations and analyzing the unique structures and requirements of each aviation sub-sector. KW - Artificial Intelligence KW - Artificial Intelligence Anxiety KW - Aviation KW - Employment KW - Technology N2 - Yapay zekanın (YZ) hızlı gelişimi işyerindeki görevler, iş devamlılığı, gizlilik ve etik sorunlar gibi konularda kaygılara yol açmaktadır. Yoğun teknolojinin kullanıldığı havacılık sektöründeki çalışanlar da bu kaygılardan etkilenebilir. Bu çalışmanın amacı, havacılık sektöründeki YZ kaygı düzeylerini incelemek ve bu durumun cinsiyet, eğitim, yaş, tecrübe ve alt sektör gibi faktörlere göre değişip değişmediğini araştırmaktır. Çalışmada tarama yöntemi kullanılmış ve çevrimiçi anket yoluyla havacılık sektöründe çalışan 345 katılımcıdan veri toplanmıştır. Ölçme aracı olarak 5’li Likert derecelendirmesine dayalı YZ kaygı ölçeği kullanılmıştır. Bulgular havacılık sektörü çalışanları arasında orta düzeyde bir kaygı olduğunu (M=2.8047) göstermiştir. YZ sosyoteknik/körlük alt boyutunda kaygı seviyesi (M=3.3775) daha yüksek iken, YZ öğrenme alt boyutunda kaygı seviyesi (M=2.1055) daha düşüktür. Yaş, tecrübe ve alt sektörler arasında kaygı seviyelerinde anlamlı bir istatistiksel farklılık bulunmamıştır; ancak eğitim düzeyine bağlı farklılıklar tespit edilmiştir. Cinsiyet açısından genel olarak YZ kaygısında anlamlı bir farklılık bulunmamakla birlikte, YZ yapılandırma boyutunda anlamlı bir fark gözlemlenmiştir. Havacılık sektöründe YZ’nin gelişimiyle birlikte, çalışanların farklı boyutlardaki kaygılarının ele alınması etkin entegrasyon için önem taşımaktadır. Hızla gelişen YZ teknolojisi göz önüne alındığında, gelecekteki araştırmaların daha detaylı bir yaklaşım benimsemesi ve sektöre özgü varyasyonlar ile her bir havacılık alt sektörünün benzersiz yapı ve ihtiyaçlarını incelemesi önerilmektedir. CR - Abubakar, M., EriOluwa, O., Teyei, M., & Al-Turjman, F. (2022). AI Application in the Aviation Sector. In 2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs) (pp. 52-55). IEEE. http://dx.doi.org/10.1109/AIoTCs58181.2022.00015 CR - Akkaya, B., Özkan, A., & Özkan, H. (2021). Artificial Intelligence Anxiety (AIA) Scale: Adaptation to Turkish, Validity and Reliability Study. Alanya Academic Review Journal, 5(2), 1125-1146. https://doi.org/10.29023/alanyaakademik.833668 CR - Antonio, A., & Tuffley, D. (2014). The Gender Digital Divide in Developing Countries. Future Internet, 6, 673-687. https://doi.org/10.3390/fi6040673 CR - Arnaldo Valdes, R. M., Burmaoglu, S., Tucci, V., Braga da Costa Campos, L. M., Mattera, L., & Gomez Comendador, V. F. (2019). Flight path 2050 and ACARE goals for maintaining and extending industrial leadership in aviation: A map of the aviation technology space. Sustainability, 11 (7), 2065. https://doi.org/10.3390/SU11072065 CR - Belber, B. G., & Özmen, M. H. (2024). Future Concerns Of Service Sector Employees About Artificial Intelligence. Electronic Journal of Social Sciences, 23(91), 1085-1101. https://doi.org/10.17755/esosder.1437531 CR - Bjelland, I., Krokstad, S., Mykletun, A., Dahl, A., Tell, G., & Tambs, K. (2008). Does a higher educational level protect against anxiety and depression? The HUNT study. Social science & medicine, 66 (6), 1334-45. https://doi.org/10.1016/j.socscimed.2007.12.019 CR - Boddington, P., Millican, P., & Wooldridge, M. (2017). Minds and machines special issue: Ethics and artificial intelligence. Minds and Machines, 27(4), 569-574. https://doi.org/10.1007/s11023-017-9449-y CR - Broos, A. (2005). Gender and Information and Communication Technologies (ICT) Anxiety: Male Self-Assurance and Female Hesitation. Cyberpsychology & behavior : the impact of the Internet, multimedia and virtual reality on behavior and society, 8(1), 21-31 . https://doi.org/10.1089/cpb.2005.8.21 CR - Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute, 4(1). CR - Çetiner, N., & Çetinkaya, F. Ö. (2023). The Relationship between Artificial Intelligence Anxiety and Motivation Levels of Employees: A Research on Tourism Employees. Alanya Academic Review Journal, 8(1), 159-173. https://doi.org/10.29023/alanyaakademik.1297394 CR - Cheruvu, R. (2022). Unconventional Concerns for Human-Centered Artificial Intelligence. Computer, 55, 46-55. https://doi.org/10.1109/MC.2022.3170423 CR - Çobanoğlu, A., & Oğuzhan, H. (2023). Artificial Intelligence Anxiety of Nurses and Related Factors. Gümüşhane University Journal of Health Sciences, 12 (4), 1846-1854. https://doi.org/10.37989/gumussagbil.1274522 CR - Comrey, A. L., & Lee, H. B. (1992). A First Course in Factor Analysis. Lawrence Erlbaum Associates. CR - Daqar, M., & Smoudy, A. (2019). The Role Of Artificial Intelligence On Enhancing Customer Experience. International Review of Management and Marketing, 9(4), 22. https://doi.org/10.32479/IRMM.8166 CR - Dean, S., Gilbert, T., Lambert, N., & Zick, T. (2021). Axes for Sociotechnical Inquiry in AI Research. IEEE Transactions on Technology and Society, 2, 62-70. https://doi.org/10.1109/TTS.2021.3074097 CR - Dignam, A. (2020). Artificial intelligence, tech corporate governance and the public interest regulatory response. Cambridge Journal of Regions, Economy and Society, 13, 37-54. https://doi.org/10.1093/cjres/rsaa002 CR - Directorate General of Civil Aviation. (n.d.). 2023 Annual Report. Available online at: https://web.shgm.gov.tr/documents/sivilhavacilik/files/kurumsal/faaliyet/2023_v2.pdf (Accessed on 21.01.2025). CR - Elliott, D., & Soifer, E. (2022). AI Technologies, Privacy, and Security. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.826737 CR - Enholm, I., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2021). Artificial Intelligence and Business Value: a Literature Review. Information Systems Frontiers, 24, 1709-1734. https://doi.org/10.1007/s10796-021-10186-w CR - Esgin, E., Elibol, M., & Daglı, M. (2016). Gender differences in computer-related achievement, anxiety and attitude: A meta-analysis in Turkey sample. Global Journal of Computer Sciences: Theory and Research, 6(1), 02-09. CR - Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4. CR - European Union Aviation Safety Agency [EASA]. (2023). Artificial Intelligence Roadmap 2.0- Human-centric approach to AI in aviation. Available online at: https://www.easa.europa.eu/en/document-library/general-publications/easa-artificial-intelligence-roadmap-20 (Accessed on 26.07.2024) CR - Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior research methods, 39(2), 175-191. CR - Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). Sage Publications. CR - Filiz, E., Güzel, Ş. & Şengül, A. (2022). Examination of Artificial Intelligence Concerns of Health Professionals. Journal of Academic Value Studies, 8(1), 47-55. http://dx.doi.org/10.29228/javs.57808 CR - George, D. & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Boston: Allyn & Bacon, 2003. CR - Goodman, L. (1972). A General Model for the Analysis of Surveys. American Journal of Sociology, 77, 1035 - 1086. https://doi.org/10.1086/225258 CR - Green, B. (2018). Ethical Reflections on Artificial Intelligence. Scientia et Fides, 6 (2), 9-31. https://doi.org/10.12775/SETF.2018.015 CR - Haşıloğlu, S. B., Baran, T., & Aydın, O. (2015). Pazarlama araştırmalarındaki potansiyel problemlere yönelik bir araştırma: Kolayda örnekleme ve sıklık ifadeli ölçek maddeleri. Pamukkale İşletme ve Bilişim Yönetimi Dergisi, 2 (1), 19-28. CR - He, J., Baxter, S., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019). The practical implementation of artificial intelligence technologies in medicine. Nature Medicine, 25, 30 - 36. https://doi.org/10.1038/s41591-018-0307-0 CR - Huang, M., & Rust, R. (2018). Artificial Intelligence in Service. Journal of Service Research, 21, 155 - 172. https://doi.org/10.1177/1094670517752459 CR - Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68 (9), 2267-2270. https://doi.org/10.1002/asi.23867 CR - Khan, A., Badshah, S., Liang, P., Khan, B., Waseem, M., Niazi, M., & Akbar, M. (2021). Ethics of AI: A Systematic Literature Review of Principles and Challenges. Proceedings of the 26th International Conference on Evaluation and Assessment in Software Engineering. https://doi.org/10.1145/3530019.3531329 CR - Kistan, T., Gardi, A., & Sabatini, R. (2018). Machine learning and cognitive ergonomics in air traffic management: Recent developments and considerations for certification. Aerospace, 5 (4), 103. https://doi.org/10.3390/AEROSPACE5040103 CR - Kronemann, B., Kizgin, H., Rana, N., & K. Dwivedi, Y. (2023). How AI encourages consumers to share their secrets? The role of anthropomorphism, personalisation, and privacy concerns and avenues for future research. Spanish Journal of Marketing-ESIC, 27 (1), 3-19. https://doi.org/10.1108/sjme-10-2022-0213 CR - Lemay, D., Basnet, R., & Doleck, T. (2020). Fearing the Robot Apocalypse: Correlates of AI Anxiety. International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI), 2 (2), 24–33. https://doi.org/10.3991/ijai.v2i2.16759 CR - Liu, J., Gardi, A., Ramasamy, S., Lim, Y., & Sabatini, R. (2016). Cognitive pilot-aircraft interface for single-pilot operations. Knowledge-based systems, 112, 37-53. https://doi.org/10.1016/j.knosys.2016.08.031 CR - Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2017). Brain Intelligence: Go beyond Artificial Intelligence. Mobile Networks and Applications, 23, 368 - 375. https://doi.org/10.1007/s11036-017-0932-8 CR - Majeed, A., & Hwang, S. (2023). When AI Meets Information Privacy: The Adversarial Role of AI in Data Sharing Scenario. IEEE Access, 11, 76177-76195. https://doi.org/10.1109/ACCESS.2023.3297646 CR - Manyika, J., Lund, S., Chui, M., Bughin, J., Woetzel, J., Batra, P., ... & Sanghvi, S. (2017). Jobs lost, jobs gained: Workforce transitions in a time of automation. McKinsey Global Institute, 150 (1), 1-148. CR - McClure, P. K. (2018). “You’re fired,” says the robot: the rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36 (2), 139-156. https://doi.org/10.1177/0894439317698637 CR - Meyer, J. (2007). Older Workers and the Adoption of New Technologies. ZEW - Centre for European Economic Research Discussion Paper No. 07-050. European Economics: Labor & Social Conditions eJournal. https://doi.org/10.2139/ssrn.1010288 CR - Minaskan, N., Pagani, A., Dormoy, C. A., Andre, J. M., & Stricker, D. (2021). A study of human-machine teaming for single pilot operation with augmented reality. In 2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (pp. 397-402). IEEE. https://doi.org/10.1109/ISMAR-Adjunct54149.2021.00091 CR - Moore, P. V. (2019). OSH and the future of work: benefits and risks of artificial intelligence tools in workplaces. In Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Body and Motion: 10th International Conference, DHM 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings, Part I 21 (pp. 292-315). Springer International Publishing. https://doi.org/10.1007/978-3-030-22216-1_22 CR - Nomura, T., Suzuki, T., Kanda, T., & Kato, K. (2006, September). Measurement of anxiety toward robots. In ROMAN 2006-The 15th IEEE International Symposium on Robot and Human Interactive Communication (pp. 372-377). IEEE. https://doi.org/10.1109/ROMAN.2006.314462 CR - Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., Kompatsiaris, I., Kinder-Kurlanda, K., Wagner, C., Karimi, F., Fernández, M., Alani, H., Berendt, B., Kruegel, T., Heinze, C., Broelemann, K., Kasneci, G., Tiropanis, T., & Staab, S. (2020). Bias in data‐driven artificial intelligence systems—An introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10. https://doi.org/10.1002/widm.1356 CR - Orhunbilge, N. (2000). Örnekleme Yöntemleri ve Hipotez testleri. İstanbul: Avcıol. CR - Otuokwu, D., & Chikwanda, H. (2022). The Future of Civil Aviation Industry: Technology Management. In 3rd African International Conference on Industrial Engineering and Operations Management, https://doi.org/10.46254/AF03.20220191 CR - Piera, M., Muñoz, J., Gil, D., Martin, G., & Manzano, J. (2022). A Socio-Technical Simulation Model for the Design of the Future Single Pilot Cockpit: An Opportunity to Improve Pilot Performance. IEEE Access, 10, 22330-22343. https://doi.org/10.1109/ACCESS.2022.3153490 CR - Rhee, T., & Jin, X. (2021). The Effect of Job Anxiety of Replacement by Artificial Intelligence on Organizational Members' Job Satisfaction in the 4th Industrial Revolution Era: The Moderating Effect of Job Uncertainty. Journal of Digital Convergence, 19, 1-9. https://doi.org/10.14400/JDC.2021.19.7.001 CR - Schuster, C., & Martiny, S. (2017). Not Feeling Good in STEM: Effects of Stereotype Activation and Anticipated Affect on Women’s Career Aspirations. Sex Roles, 76, 40-55. https://doi.org/10.1007/S11199-016-0665-3 CR - Sharma, J., & Devi, A. (2011). Individual Differences and Stress at Workplace. Asia Pacific Business Review, 7, 198 - 207. https://doi.org/10.1177/097324701100700318 CR - Siau, K., & Wang, W. (2020). Artificial intelligence (AI) ethics: ethics of AI and ethical AI. Journal of Database Management (JDM), 31(2), 74-87. https://doi.org/10.4018/jdm.2020040105 CR - Suebvises, P. (2018). Social capital, citizen participation in public administration, and public sector performance in Thailand. World Development, 109, 236-248. CR - Tabachnick, B.G. & Fidell, L.S. (2019). Using Multivariate Statistics (Seventh Edition). New Jersey: Pearson. CR - Takıl, N., Erden, N. K., & Sarı, A. B. (2022). Investigating artificial intelligence anxiety levels of candidates in different occupational groups. BAUNSOBED, 25(48), 343-353. https://doi.org/10.31795/baunsobed.1165386 CR - Tang, P. M., Koopman, J., Mai, K. M., De Cremer, D., Zhang, J. H., Reynders, P., Ng, C. T. S., & Chen, I-H. (2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. Journal of Applied Psychology, 108(11), 1766–1789. https://doi.org/10.1037/apl0001103 CR - Terzi, R. (2020). An adaptation of artificial intelligence anxiety scale into Turkish: Reliability and validity study. International Online Journal of Education and Teaching, 7(4), 1501-1515. CR - Torija, A. J., & Clark, C. (2021). A psychoacoustic approach to building knowledge about human response to noise of unmanned aerial vehicles. International Journal of Environmental Research and Public Health, 18(2), 682. https://doi.org/10.3390/ijerph18020682 CR - Wamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business process management journal, 26(7), 1893-1924. https://doi.org/10.1108/bpmj-10-2019-0411 CR - 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, 30(1), 61-79. http://dx.doi.org/10.4018/JDM.2019010104 CR - Wang, Y. Y. & Wang, Y. S. (2019). Development and validation of an artificial intelligence anxiety scale: an initial application in predicting motivated learning behavior. Interactive Learning Environments, 30 (4), 619-634. https://doi.org/10.1080/10494820.2019.1674887 CR - Weger, M., & Sandi, C. (2018). High anxiety trait: A vulnerable phenotype for stress-induced depression. Neuroscience & Biobehavioral Reviews, 87, 27-37. https://doi.org/10.1016/j.neubiorev.2018.01.012 CR - Whitley, B. (1996). Gender Differences in Computer-Related Attitudes: It Depends on What You Ask.. Computers in Human Behavior, 12, 275-289. https://doi.org/10.1016/0747-5632(96)00007-6 CR - Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019). Artificial intelligence and the public sector- applications and challenges. International Journal of Public Administration, 42 (7), 596-615. CR - Yalçın, A. (2024). Türkiye'de Kamu Kurumlarinin Toplum İçin Geliştirdiği Yapay Zekâ Uygulamalari. İstanbul Aydın Üniversitesi Sosyal Bilimler Dergisi, 16(2), 185-215. CR - Zhang, C., & Chu, H. (2020). Preprocessing method of structured big data in human resource archives database. In Proceedings of the 2020 IEEE International Conference on Industrial Informatics. CR - Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224 CR - Zou, T., & Sun, K. (2021). Application and Prospect of Artificial Intelligence in Aircraft Design. 2021 International Conference on Networking Systems of AI (INSAI), 201-205. https://doi.org/10.1109/INSAI54028.2021.00045 UR - https://doi.org/10.16953/deusosbil.1524579 L1 - https://dergipark.org.tr/en/download/article-file/4107411 ER -