YAPAY ZEKÂ'NIN GÖRÜNMEZ ELİ: TEKNOLOJİNİN ETKİSİNİ ANLAMAK

Öz

Bu çalışma, özellikle Türkiye bağlamında, yapay zekâ ve aile dinamikleri arasındaki karmaşık ilişkileri, teknolojinin hem avantajlarını hem de dezavantajlarını göz önünde bulundurarak incelemektedir. 2025 yılına kadar, iletişim, rutinler ve aile finansmanı dahil olmak üzere günlük yaşamın her unsuru yapay zekanın etkisinde kalacaktır. Yapay zekâ, ev işlerini azaltarak, uzaktan çalışma ve eğitime olanak tanıyarak ve kişiselleştirilmiş öğrenme ve sağlık desteği sunarak aile üretkenliğini artırır ve daha yüksek aile geliri ve daha kaliteli zaman geçirilmesini sağlayabilir. Ancak yapay zekâ ile ilgili bir dizi sorun da bulunmaktadır. Bunlar arasında aşırı ekran süresine bağlı sosyal izolasyon olasılığı, aile seçimlerini etkileyen algoritmik önyargılar, veri toplama kaynaklı gizlilik endişeleri ve yüksek maliyetlerin neden olduğu dijital eşitsizlik sayılabilir. Türkiye'deki yüksek enflasyon, yapay zekânın benimsenmesini teşvik ederken, gelir eşitsizliği dijital uçurumu daha da derinleştiriyor. Çalışmaya göre, eşit erişimi, sağlam veri güvenliğini ve sorumlu yapay zekâ kullanımını teşvik eden politikalar çok önemlidir. Yapay zekâ çağında sürdürülebilir refahı sağlamak ve aile birliğini korumak için, gelecekteki araştırmalar Türkiye'deki uzun vadeli, kültürel açıdan duyarlı sonuçlara odaklanmalıdır.

Anahtar Kelimeler

• Aile Dinamikleri
• Dijital Dönüşüm
• Türkiye
• Yapay Zeka

THE INVISIBLE HAND OF ARTIFICIAL INTELLIGENCE: UNDERSTANDİNG THE IMPACT OF TECHNOLOGY

Öz

This study examines the intricate relationships between artificial intelligence (AI) and family dynamics, considering both the technology's benefits and drawbacks, particularly in the context of Turkey. Every element of daily life will be impacted by AI by 2025, including communication, routines, and family finances. Artificial intelligence (AI) enhances family productivity and may result in higher family income and more quality time by reducing household chores, enabling remote employment and education, and offering individualised learning and healthcare support. However, there are many problems with AI, including the possibility of social isolation due to excessive screen time, algorithmic biases that affect family choices, privacy concerns arising from data collection, and digital inequality caused by high costs. High inflation in Turkey is driving the adoption of AI, while income inequality exacerbates the digital gap. According to the study, policies that promote equitable access, robust data security, and responsible AI use are crucial. To ensure sustained prosperity in the AI era while preserving family unity, future research should focus on the long-term, culturally sensitive consequences in Turkey.

Anahtar Kelimeler

• Artificial Intelligence
• Family Dynamics
• Digital Transformation
• Turkey

Kaynakça

1. Abreu, M.P., Del-Vecchio, R.R., & Grassi, R. (2020). Analysis of productive structure applying network theory: The Brazilian case, Structural Change and Economic Dynamics, 53, 281-291. https://doi.org/10.1016/j.strueco.2020.03.005
2. Aggar, C., Sorwar, G., Seton, C., Penman, O., & Ward, A. (2023). Smart home technology to support older people's quality of life: A longitudinal pilot study. International journal of older people nursing, 18(1), e12489. https://doi.org/10.1111/opn.12489
3. Akter, S., Motamarri, S., Hani, U., Shams, R., Fernando, M., Babu, M.M., et al. (2020). Building dynamic service analytics capabilities for the digital marketplace. Journal of Business Research, 118: 177–188. https://doi.org/10.1016/j.jbusres.2020.06.016
4. Alfeir, N.M. (2024). Dimensions of artificial intelligence on family communication. Front. Artif. Intell. 7:1398960. https://doi.org/10.3389/frai.2024.1398960
5. Allhoff, F. & Henschke, A. (2018). The Internet of Things: Foundational ethical issues, Internet of Things, 1–2: 55-66. https://doi.org/10.1016/j.iot.2018.08.005
6. Allioui, H., & Mourdi, Y. (2023). Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey. Sensors, 23(19), 8015. https://doi.org/10.3390/s23198015
7. Almusaed, A., Yitmen, I., & Almssad, A. (2023). Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review. Energies, 16(6), 2636. https://doi.org/10.3390/en16062636
8. AlQudah, A. A., Al-Emran, M., & Shaalan, K. (2021). Technology Acceptance in Healthcare: A Systematic Review. Applied Sciences, 11(22), 10537. https://doi.org/10.3390/app112210537

9. Arees, Z. A. (2023). The Social Impact of Artificial Intelligence. In J. Wang (Ed.), Encyclopedia of Data Science and Machine Learning (pp. 834-847). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-7998-9220-5.ch048
10. Bertolazzi, A., Quaglia V., & Bongelli, R. (2024). Barriers and facilitators to health technology adoption by older adults with chronic diseases: an integrative systematic review. BMC Public Health, 24(1):506. https://doi.org/10.1186/s12889-024-18036-5
11. Bezcioglu-Goktolga, I., & Yagmur, K. (2022). Intergenerational differences in family language policy of Turkish families in the Netherlands. Journal of Multilingual and Multicultural Development, 43(9), 891–906. https://doi.org/10.1080/01434632.2022.2036746
12. Cugurullo, F., Caprotti, F., Cook, M., Karvonen, A., McGuirk, P., & Marvin, S. (Eds.). (2023). Artificial Intelligence and the City: Urbanistic Perspectives on AI (1st ed.). Routledge. https://doi.org/10.4324/9781003365877
13. Çolak, O. (2023). The Impact of Artificial Intelligence on the Employment Structure of the Tourism Industry: An Interview with ChatGPT. İktisadi İdari Ve Siyasal Araştırmalar Dergisi, 8(22), 919-939. https://doi.org/10.25204/iktisad.1347642
14. Dalgıç-Tetikol, D. E., Köksal, E., & Güloğlu, B. (2023). The Evaluation of the Digital Divide in Turkey. Journal of Research in Economics, 7(1), 65-83.
15. DesJardine, M. R., Shi, W., & Cheng, X. (2023). The New Invisible Hand: How Common Owners Use the Media as a Strategic Tool. Administrative Science Quarterly, 68(4), 956-1007. https://doi.org/10.1177/00018392231192863
16. Duanmu, X., Yu, J., Yuan, X., & Zhang, X. (2025). How Does Digital Infrastructure Mitigate Urban–Rural Disparities? Sustainability, 17(4), 1561. https://doi.org/10.3390/su17041561
17. Druga S., Christoph F. L., & Ko A. J. (2022). Family as a third space for AI literacies: how do children and parents learn about AI together? In: Proceedings of the 2022 CHI conference on human factors in computing systems, pp. 1–17.
18. Efe, A. (2022). The Impact of Artificial Intelligence on Social Problems and Solutions: An Analysis of The Context of Digital Divide and Exploitation. Yeni Medya, (13): 247-264. https://doi.org/10.55609/yenimedya.1146586
19. Eloundou, T., Manning, S., Mishkin, P. & Rock, D. (2023). GPTs are GPTs: An Early Look at the Labour Market Impact Potential of Large Language Models, Papers: 2303.10130. https://ideas.repec.org/p/arx/papers/2303.10130.html
20. Güven, G., & Yumugan, S. (2025). Artificial intelligence in preschool education: Personalised assessment and evaluation with artificial intelligence. Uluslararası Sosyal Bilimler ve Eğitim Dergisi – USBED 7(12).
21. Hanna, M.G., Pantanowitz, L., Jackson, B., Palmer, O. Visweswaran, S. Pantanowitz, J. Deebajah, M., Rashidi, H.H (2025).Ethical and Bias Considerations in Artificial Intelligence/Machine Learning, Modern Pathology, 38(3): 100686
22. Hu, D., Lan, Y., Yan, H. & Chen, C.W. (2025). What makes you attached to social companion AI? A two-stage exploratory mixed-method study, International Journal of Information Management, 83, 102890.
23. Hur, H., & Abner, G. (2024). What makes public employees want to leave their jobs? A meta-analysis of turnover intention predictors among public sector employees. Public Adm. Rev. 84, 115–142. https://doi.org/10.1111/puar.13601
24. İbrahimi, A. (2025). The Impact of Artificial Intelligence on University Education and Social Behaviour in Kosovo. (2025). Journal of Educational and Social Research, 15(3), 407. https://doi.org/10.36941/jesr-2025-0107
25. İlhan, Ü.D., Güler, B.K., Turgut, D. & Duran, C. (2025). Unique challenges in the Turkish workforce: examining the impact of job demands and resources on work-related outcomes of blue- and white-collar workers. Front. Psychol. 16:1588266. https://doi.org/10.3389/fpsyg.2025.1588266
26. Jorgensen W, Bjornsen M, Carlsen R. (2025). Ethical considerations for using artificial intelligence in digital technologies, Int J Ethics Soc., 7(1): 10-17. https://doi.org/10.22034/ijethics.7.1.10
27. Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, 15(16), 12451. https://doi.org/10.3390/su151612451
28. Karaş, Z. (2024). Effects of AI-Generated Misinformation and Disinformation on the Economy. Duzce University Journal of Science and Technology, 12(4), 2349-2360. https://doi.org/10.29130/dubited.1537268
29. Kaya, I. & Mutlu-Bayraktar, D. (2021). Digital parenting research in Turkey: A content analysis study. Inonu University Journal of the Faculty of Education, 22(2), 1046-1082. https://doi.org/10.17679/inuefd.928805
30. Khan, M.S., Umer, H. & Faruqe, F. (2024). Artificial intelligence for low-income countries. Humanit Soc Sci Commun 11, 1422. https://doi.org/10.1057/s41599-024-03947-w
31. Kim, J., & Ryu, S. J. (2023). Enhancing Sustainable Design Thinking Education Efficiency: A Comparative Study of Synchronous Online and Offline Classes. Sustainability, 15(18), 13293.
32. Kim, I., Lee, S., Yang, S. J., Kim, D., Kim, H., & Shin, Y. (2023). Effects of Screen Time on Problematic Behaviour in Children During the COVID-19 Pandemic in South Korea. Journal of the Korean Academy of Child and Adolescent Psychiatry, 34(3), 175–180. https://doi.org/10.5765/jkacap.230014
33. Klimczuk, A. (Ed.). (2024). Intergenerational Relations: Contemporary Theories, Studies, and Policies. London: IntechOpen. https://doi.org/10.5772/intechopen.111170
34. Koseoglu, G., Wasti, S. A., and Terzi, H. (2021). Employee Turnover in Turkey. In Global Talent Retention: Understanding Employee Turnover Around the World, eds. D. G. Allen and J. M. Vardaman (Leeds: Emerald Publishing Limited), 167–189.
35. Kumar, V., Ashraf, R.A. & Nadeem, W. (2024). AI-powered marketing: What, where, and how? International Journal of Information Management, 77: 102783. https://doi.org/10.1016/j.ijinfomgt.2024.102783
36. Lainjo, B. (2023). The Global Social Dynamics and Inequalities of AI. International Journal of Innovation, Scientific Research and Review, 5 (8).4966-4974.
37. Laestadius, L., Bishop, A., Gonzalez, M., Illenčík, D., & Campos-Castillo, C. (2024). Too human and not human enough: A grounded theory analysis of mental health harms from emotional dependence on the social chatbot Replika. New Media & Society, 26(10), 5923-5941. https://doi.org/10.1177/14614448221142007
38. Lee, C.-F., & Tang, S.-M. (2024). Can AI Robot Teaching Improve Children’s Performance in Housework? A Quasi-Experimental Study. Children, 11(11), 1330. https://doi.org/10.3390/children11111330
39. Malarvizhi, C.A.N., Al Mamun, A., Reza, M.N.H. et al. (2025). Seniors’ attitudes and intentions toward IoT-enabled healthcare devices in emerging economies. Sci Rep 15, 13320. https://doi.org/10.1038/s41598-025-97507-0
40. Mazarakis, A., Bernhard-Skala, C., Braun, M., & Peters, I. (2023). What is critical for human-centred AI at work? –Toward an interdisciplinary theory. Frontiers in Artificial Intelligence, 6, 1257057.
41. Meng, J. & Dai, N. (2021). Emotional support from AI chatbots: should a supportive partner self-disclose or not? Journal of Computer-Mediated Communication 26(4): zmab005.
42. Mhlanga, D. (2021). Artificial Intelligence in the Industry 4.0, and Its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies? Sustainability, 13(11), 5788. https://doi.org/10.3390/su13115788
43. Mittermaier, M., Raza, M.M., & Kvedar, J.C. (2023). Bias in AI-based models for medical applications: challenges and mitigation strategies. npj Digit. Med. 6, 113 https://doi.org/10.1038/s41746-023-00858-z
44. Naghib, A., Jafari Navimipour, N., Hosseinzadeh, M., & Sharifi, A. (2023). A comprehensive and systematic literature review on the big data management techniques in the Internet of Things. Wireless. Netw. 29, 1085–1144.
45. Pimenow, S., Pimenowa, O., Prus, P., & Niklas, A. (2025). The Impact of Artificial Intelligence on the Sustainability of Regional Ecosystems: Current Challenges and Future Prospects. Sustainability, 17(11), 4795. https://doi.org/10.3390/su17114795
46. Pinto, G. P., & Prazeres, C. (2025). Data Privacy in the Internet of Things: A Perspective of Personal Data Store-Based Approaches. Journal of Cybersecurity and Privacy, 5(2), 25. https://doi.org/10.3390/jcp5020025
47. Pirzada, P., Wilde, A., Doherty, G. H., & Harris-Birtill, D. (2021). Ethics and acceptance of smart homes for older adults. Informatics for Health and Social Care, 47(1), 10–37. https://doi.org/10.1080/17538157.2021.1923500
48. Popoola, O., Rodrigues, M., Marchang, J., Shenfield, A., Ikpehai, A. & Popoola, J. (2024). A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, challenges and solutions, Blockchain: Research and Applications, 5(2):100178
49. Ranaa, M., Siddiqeeb, M.S., Sakiba, N. & Ahamedb, R. (2024). Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework, Heliyon, 10(18): e37569.
50. Rashid, A.B. & Kausik, M.D.A.K. (2024). AI revolutionising industries worldwide: A comprehensive overview of its diverse applications, Hybrid Advances, 7, 100277.
51. Revak, B., & Csiszarik-Kocsir, A. (2024). The Future Impact of Artificial Intelligence according to the Opinions of Hungarian and Turkish Youth in the Sight of a National Competitiveness. The Eurasia Proceedings of Educational and Social Sciences, 38, 103–112. https://doi.org/10.55549/epess.851
52. Sajja, R., Sermet, Y., Cikmaz, M., Cwiertny, D., & Demir, I. (2024). Artificial Intelligence-Enabled Intelligent Assistant for Personalised and Adaptive Learning in Higher Education. Information, 15(10), 596. https://doi.org/10.3390/info15100596
53. Salmani, A. (2023). An AI-Based Human-Centred Approach to Support Multidisciplinary Requirements Engineering.
54. Savaş, S. (2021). Artificial Intelligence and Innovative Applications in Education: The Case of Turkey, Journal of Information Systems and Management Research, 3 (1):14-26
55. Shum, N.Y.E. & Bobo Lau, H.P. (2024). Perils, power and promises: Latent profile analysis on the attitudes towards artificial intelligence (AI) among middle-aged and older adults in Hong Kong, Computers in Human Behaviour: Artificial Humans, 2(2): 100091
56. Szondy, M. B., & Magyary, Á. (2025). Artificial Intelligence (AI) in the Family System: Possible Positive and Detrimental Effects on Parenting, Communication and Family Dynamics. European Journal of Mental Health, 20, e0038, 1–8. https://doi.org/10.5708/EJMH.20.2025.0038
57. Tai, M. C. (2020). The impact of artificial intelligence on human society and bioethics. Tzu chi medical journal, 32(4), 339–343. https://doi.org/10.4103/tcmj.tcmj_71_20
58. Taniguchi, H. & Yamada, K. (2022). ICTCapital-SkillComplementarity and Wage Inequality: Evidence from OECD Countries, Labour Economics, 76: 102151.
59. Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502–517. https://doi.org/10.1016/j.jbusres.2020.09.009
60. Tuncalp, D. (2025). Directing the future: artificial intelligence integration in family businesses, Journal of Family Business Management, 15(2): 254-277.
61. Uyan, U., & Gültekin, S. U. (2024). Yapay zekâ öz yeterlilik ölçeğinin Türkçe’ye uyarlanması: geçerlilik ve güvenilirlik çalışması. Journal of Research in Business, 9(1), 135-148. https://doi.org/10.54452/jrb.1415212
62. Vardakis, G., Hatzivasilis, G., Koutsaki, E., & Papadakis, N. (2024). Review of Smart-Home Security Using the Internet of Things. Electronics, 13(16), 3343. https://doi.org/10.3390/electronics13163343
63. Varriale, V., Cammarano, A., Michelino, F. et al. (2025). Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems. J Intell Manuf, 36: 61–93. https://doi.org/10.1007/s10845-023-02244-8
64. Wang, W. & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and humanity: A review and research agenda. Journal of Database Management, 30(1):61-79. https://doi.org/10.4018/JDM.2019010104 58
65. Wen, H., Shang, J. & Nghi, X-H. (2025). Does artificial intelligence matter for the population ageing-inclusive growth nexus? International evidence, Telecommunications Policy, 49(4):102932.
66. West, M., Rice, S., & Vella-Brodrick, D. (2024). Adolescent Social Media Use through a Self-Determination Theory Lens: A Systematic Scoping Review. International Journal of Environmental Research and Public Health, 21(7), 862. https://doi.org/10.3390/ijerph21070862
67. Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation, Computers and Education: Artificial Intelligence, 3: 100061
68. Yılmaz, İ. (2025). The Right to be Forgotten Regarding Artificial Intelligence Data Collection in the European Union and Taiwan, Kişisel Verileri Koruma Dergisi. 7(1), 53-61.