The Digital Age of Aging: Artificial Intelligence, Ethical Boundaries, and Social Work in Elderly Care

Öz

Objective: The rapid growth of the global elderly population, termed the "silver tsunami" in the literature, is profoundly transforming health and social service systems. This study aims to examine the opportunities and ethical challenges of Internet of Things (IoT) and artificial intelligence (AI)-based technologies in elderly care within the framework of Thompson’s (2009) Freedom-Control Dilemma. Method: A qualitative systematic literature review was conducted, analyzing 53 peer-reviewed articles and two academic books published between 2020 and 2025. The review focused on studies related to elderly care, health services, social work, ethics, and technology, using databases such as Scopus, PubMed, Web of Science, and ScienceDirect. Results: The findings highlight core ethical issues in elderly care technologies, including privacy, data security, transparency, accountability, autonomy, deception-manipulation, accessibility, and technology acceptance. The analysis also emphasizes the functional layers of IoT systems and the potential of AI-supported care applications to enhance safety, health monitoring, reduce social isolation, and ease caregiver burden. Conclusion: IoT and AI-based solutions not only improve quality of life for older people but also have the potential to establish an ethically legitimate care model within the freedom-control balance. The study underscores that these technologies must be developed in line with ethical design principles and structured to empower individuals in decision-making processes. From a social work perspective, it is essential that such processes uphold human dignity, foster participation, and ensure sustainability Therefore, social workers must actively engage in the development, implementation, and evaluation of these technologies to ensure that ethical values and human rights remain central to elderly care practices.

Anahtar Kelimeler

• Elderly Care
• Internet of Things
• Artificial Intelligence
• Ethics
• Freedom-Control Dilemma

Yaşlanmanın Dijital Çağı: Yapay Zeka, Etik Sınırlar ve Yaşlı Bakımında Sosyal Hizmet

Öz

Amaç: Literatürde “gümüş tsunami” olarak adlandırılan küresel yaşlı nüfusun hızlı artışı, sağlık ve sosyal hizmet sistemlerini derinden dönüştürmektedir. Bu çalışma, Thompson’un (2009) Özgürlük-Kontrol İkilemi çerçevesinde, yaşlı bakımında Nesnelerin İnterneti (IoT) ve yapay zekâ (YZ) tabanlı teknolojilerin sunduğu fırsatları ve etik zorlukları incelemeyi amaçlamaktadır. Yöntem: 2020-2025 yılları arasında yayımlanan 53 hakemli makale ve iki akademik kitap analiz edilerek niteliksel sistematik bir derleme yapılmıştır. Derleme kapsamında yaşlı bakımı, sağlık hizmetleri, sosyal hizmet, etik ve teknoloji temalı çalışmalar incelenmiş; Scopus, PubMed, Web of Science ve ScienceDirect gibi veri tabanları kullanılmıştır. Bulgular: Bulgular, yaşlı bakımında kullanılan teknolojilerde öne çıkan temel etik sorunları ortaya koymaktadır: mahremiyet, veri güvenliği, şeffaflık, hesap verebilirlik, özerklik, aldatma-manipülasyon, erişilebilirlik ve teknoloji kabulü. Analiz ayrıca IoT sistemlerinin işlevsel katmanlarına ve yapay zekâ destekli bakım uygulamalarının güvenliği artırma, sağlık takibini kolaylaştırma, sosyal izolasyonu azaltma ve bakım veren yükünü hafifletme potansiyeline dikkat çekmektedir. Sonuç: IoT ve YZ tabanlı çözümler, yaşlı bireylerin yaşam kalitesini artırmakla kalmayıp, özgürlük-kontrol dengesi içinde etik açıdan meşru bir bakım modeli oluşturma potansiyeline de sahiptir. Çalışma, bu teknolojilerin etik tasarım ilkeleri doğrultusunda geliştirilmesi ve bireyleri karar verme süreçlerinde güçlendirecek şekilde yapılandırılması gerektiğinin altını çizmektedir. Sosyal hizmet perspektifinden bakıldığında, bu süreçlerin insan onurunu

Anahtar Kelimeler

• Yaşlı Bakım
• Nesnelerin İnterneti
• Yapay Zeka
• Etik
• Özgürlük-Kontrol İkilemi

Kaynakça

1. Abdulmalek, S., Nasir, A., Jabbar, W. A., Almuhaya, M. A., Bairagi, A. K., Khan, M. A. M., & Kee, S. H. (2022). IoT-based healthcare-monitoring system towards improving quality of life: A review. In Healthcare (Vol. 10, No. 10, p. 1993). MDPI.
2. Abeele, V. V., Schraepen, B., Huygelier, H., Gillebert, C., Gerling, K., & Van Ee, R. (2021). Immersive virtual reality for older adults: empirically grounded design guidelines. ACM Transactions on Accessible Computing (TACCESS), 14(3), 1-30.
3. Ahmed, S. B., & Jabarullah, B. M. (2020). Intelligent Healthcare Solutions. In Internet of Things (IoT) Concepts and Applications (pp. 371-389). Cham: Springer International Publishing.
4. Alam, M., & Sethi, S. (2013). Security risks & migration strategy for cloudsourcing: A government perspective. International Journal of Engineering and Innovative Technology, 2(7), 205–209.
5. Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., ... & Albekairy, A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1), 689.
6. Baldominos, A., De Rada, F., & Saez, Y. (2018). DataCare: Big data analytics solution for intellige nt healthcare management. International Journal of Interactive Multimedia & Artificial Intelligence, 4(7).
7. Banks, S. (2020). Ethics and values in social work (5th edition). London: Bloomsbury Publishing. Beauchamp, T. L. (2003). Methods and principles in biomedical ethics. Journal of Medical ethics, 29(5), 269-274.
8. Berkman, B., Gardner, D., Zodikoff, B., & Harootyan, L. (2013). Social work and aging in the emerging health care world. Fostering Social Work Gerontology Competence, 203-217.

9. Boch, A., Ryan, S., Kriebitz, A., Amugongo, L. M., & Lütge, C. (2023). Beyond the metal flesh: understanding the intersection between bio-and AI ethics for robotics in healthcare. Robotics, 12(4), 110.
10. Bouaziz, G., Brulin, D., & Campo, E. (2022). Technological solutions for social isolation monitoring of the elderly: a survey of selected projects from academia and industry. Sensors, 22(22), 8802.
11. Boulahia, M. A., Benharzallah, S., Titouna, F., & Dilekh, T. (2024). Human Activity Recognition in Enhancing Healthcare for Aging Populations: Challenges, Innovations, and Future Directions. In 2024 1st International Conference on Innovative and Intelligent Information Technologies (IC3IT) (pp. 1-6). IEEE.
12. Browne, J. D., Boland, D. M., Baum, J. T., Ikemiya, K., Goldman, P., & Dolezal, B. A. (2021). Lifestyle modification using a wearable biometric ring and guided feedback improve sleep and exercise behaviors: a 12-month randomized, placebo-controlled study. Frontiers in Physiology, 12, 777874.
13. Calasanti, T. (2020). Brown slime, the silver tsunami, and apocalyptic demography: The importance of ageism and age relations. Social Currents, 7(3), 195-211.
14. Calvo, R. A., Peters, D., Vold, K., & Ryan, R. M. (2020). Supporting human autonomy in AI systems: A framework for ethical enquiry. Ethics of digital well-being: A multidisciplinary approach, 31-54.
15. Choi, J. Y., Lee, S. H., & Yu, S. (2024). Exploring factors influencing caregiver burden: A systematic review of family caregivers of older adults with chronic illness in local communities. In Healthcare (Vol. 12, No. 10, p. 1002). MDPI.
16. Chung, J., Brakey, H. R., Reeder, B., Myers, O., & Demiris, G. (2023). Community‐dwelling older adults' acceptance of smartwatches for health and location tracking. International Journal of Older People Nursing, 18(1), e12490.
17. Costanzo, M., Smeriglio, R., & Di Nuovo, S. (2024). New technologies and assistive robotics for elderly: A review on psychological variables. Archives of Gerontology and Geriatrics Plus, 100056.
18. Coeckelbergh, M. (2012). Care robots, virtual virtue, and the best possible life. In The good life in a technological age (pp. 281-292). Routledge.
19. Cresswell, K., Callaghan, M., Khan, S., Sheikh, Z., Mozaffar, H., & Sheikh, A. (2020). Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: a systematic review. Health Informatics Journal, 26(3), 2138-2147.
20. CRO Forum. (2022). The internet of things (IoT): Risks from an insurance perspective. Retrieved from https://www.thecroforum.org/wp-content/uploads/2022/05/CRO-IoT-risks-1.pdf
21. Dahiya, E. S., Kalra, A. M., Lowe, A., & Anand, G. (2024). Wearable technology for monitoring electrocardiograms (ECGs) in adults: a scoping review. Sensors, 24(4), 1318.
22. Göransson, C., Wengström, Y., Hälleberg-Nyman, M., Langius-Eklöf, A., Ziegert, K., & Blomberg, K. (2020). An app for supporting older people receiving home care–usage, aspects of health and health literacy: a quasi-experimental study. BMC Medical Informatics and Decision Making, 20, 1-10.
23. He, X., Feng, Y., Xu, F., Chen, F. F., & Yu, Y. (2022). Smart fire alarm systems for rapid early fire warning: Advances and challenges. Chemical Engineering Journal, 450, 137927.
24. Huang, C., Zhang, Z., Mao, B., & Yao, X. (2022). An overview of artificial intelligence ethics. IEEE Transactions on Artificial Intelligence, 4(4), 799-819.
25. Huang, X., Wicaksana, J., Li, S., & Cheng, K. T. (2022). Automated vision-based wellness analysis for elderly care centers. In Multimodal AI in healthcare: A paradigm shift in health intelligence (pp. 321-333). Cham: Springer International Publishing.
26. Jones, V. K., Yan, C., Shade, M. Y., Boron, J. B., Yan, Z., Heselton, H. J., ... & Dube, V. (2024). Reducing loneliness and improving social support among older adults through different modalities of personal voice assistants. Geriatrics, 9(2), 22.
27. Kazim, E., & Koshiyama, A. S. (2021). A high-level overview of AI ethics. Patterns, 2(9)
28. Kim, D., Bian, H., Chang, C. K., Dong, L., & Margrett, J. (2022). In-home monitoring technology for aging in place: Scoping review. Interactive Journal of Medical Research, 11(2), e39005.
29. Kosuva Öztürk, Z. ve Şahin, S. (2021). Yaşlılarda sık görülen sağlık sorunları. Türkiye Klinikleri Halk Sağlığı-Özel Konular, 1, 7-22.
30. Latikka, R., Rubio-Hernández, R., Lohan, E. S., Rantala, J., Nieto Fernández, F., Laitinen, A., & Oksanen, A. (2021). Older adults’ loneliness, social isolation, and physical information and communication technology in the era of ambient assisted living: A systematic literature review. Journal of Medical Internet Research, 23(12), e28022.
31. Lauritsen, S. M., Kristensen, M., Olsen, M. V., Larsen, M. S., Lauritsen, K. M., Jørgensen, M. J., ... & Thiesson, B. (2020). Explainable artificial intelligence model to predict acute critical illness from electronic health records. Nature Communications, 11(1), 3852.
32. Lin, J. H., Lu, C. H., & Tang, S. T. (2025). Self-Capacitance Sensor for Smart Diaper. IEEE Access. Li, M., Xiong, W., & Li, Y. (2020). Wearable measurement of ECG signals based on smart clothing. International Journal of Telemedicine and Applications, 2020(1), 6329360.
33. Lombardi, M., Pascale, F., & Santaniello, D. (2021). Internet of things: A general overview between architectures, protocols and applications. Information, 12(2), 87.
34. Lučan, J., Pokmajević, M., & Kunčič, U. (2024). Impact of Technology on the Quality of Life of Elderly People in Smart Villages: Literature Review. IFAC-Papers OnLine, 58(3), 262-267.
35. Mahmoudi Asl, A., Molinari Ulate, M., Franco Martin, M., & van der Roest, H. (2022). Methodologies used to study the feasibility, usability, efficacy, and effectiveness of social robots for elderly adults: scoping review. Journal of Medical Internet Research, 24(8), e37434.
36. Mallinson, D. J., & Shafi, S. (2022). Smart home technology: Challenges and opportunities for collaborative governance and policy research. Review of Policy Research, 39(3), 330-352.
37. Nath, R. K., & Thapliyal, H. (2021). Wearable health monitoring system for older adults in a smart home environment. In 2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) (pp. 390-395). IEEE.
38. Neves, F., Souza, R., Sousa, J., Bonfim, M., & Garcia, V. (2023). Data privacy in the Internet of Things based on anonymization: A review. Journal of Computer Security, 31(3), 261-291.
39. Oyibo, K., Wang, K., & Morita, P. P. (2023). Using smart home technologies to promote physical activity among the general and aging populations: scoping review. Journal of Medical Internet Research, 25, e41942.
40. Pfeifer-Chomiczewska, K. (2023). Intelligent service robots for elderly or disabled people and human dignity: legal point of view. AI & SOCIETY, 38(2), 789-800.
41. Piau, A., Steinmeyer, Z., Charlon, Y., Courbet, L., Rialle, V., Lepage, B., ... & Nourhashemi, F. (2021). A smart shoe insole to monitor frail older adults’ walking speed: results of two evaluation phases completed in a living lab and through a 12-week pilot study. JMIR mHealth and uHealth, 9(7), e15641.
42. Philip, N. Y., Rodrigues, J. J., Wang, H., Fong, S. J., & Chen, J. (2021). Internet of Things for in-home health monitoring systems: Current advances, challenges and future directions. IEEE Journal on Selected Areas in Communications, 39(2), 300-310.
43. Pressman, S. M., Borna, S., Gomez-Cabello, C. A., Haider, S. A., Haider, C., & Forte, A. J. (2024). AI and ethics: a systematic review of the ethical considerations of large language model use in surgery research. In Healthcare (Vol. 12, No. 8, p. 825). MDPI.
44. Rayes, A., Salam, S., Rayes, A., & Salam, S. (2017). Internet of things (iot) overview. Internet of Things From Hype to Reality: The Road to Digitization, 1-34.
45. Roumaissa, B., & Rachid, B. (2022). An IoT-based pill management system for elderly. Informatica, 46(4).
46. Santhanaraj, K. K., & MM, R. (2021). A survey of assistive robots and systems for elderly care. Journal of Enabling Technologies, 15(1), 66-72.
47. Sharkey, A., & Sharkey, N. (2012). Granny and the robots: ethical issues in robot care for the elderly. Ethics and Information Technology, 14, 27-40.
48. Sivakanthan, S., Blaauw, E., Greenhalgh, M., Koontz, A. M., Vegter, R., & Cooper, R. A. (2021). Person transfer assist systems: a literature review. Disability and Rehabilitation: Assistive Technology, 16(3), 270-279.
49. Sparrow, R., & Sparrow, L. (2006). In the hands of machines? The future of aged care. Minds and Machines, 16, 141-161.
50. Sridevi, U. K., Sudhir, S., & Palaniappan, S. (2020). Elderly behavior prediction using a deep learning model in smart homes. In Applications of Deep Learning and Big IoT on Personalized Healthcare Services (pp. 115-131). IGI Global.
51. Tak, S. H., Choi, H., Lee, D., Song, Y. A., & Park, J. (2023). Nurses' perceptions about smart beds in hospitals. CIN: Computers, Informatics, Nursing, 41(6), 394-401.
52. Tan, K. C. K. (2024). Use of Senior Technology Acceptance Model (STAM) for Social Robots Studies.
53. Thompson, N. (2009). Understanding social work: Preparing for practice (3th ed.). Macmillan Press: New York.
54. Tun, S. Y. Y., Madanian, S., & Mirza, F. (2021). Internet of things (IoT) applications for elderly care: a reflective review. Aging Clinical and Experimental Research, 33, 855-867.
55. Turner, S. G., Pillemer, K., Demetres, M., Heaney, K., Joshi, S., Luebke, M., ... & Reid, M. C. (2024). Physical pain among family caregivers to older adults: A scoping review of the literature. Journal of the American Geriatrics Society, 72(9), 2853-2865. Türkiye İstatistik Kurumu (TÜİK). (2025). İstatistiklerle yaşlılar, 2024. https://data.tuik.gov.tr/Bulten/Index?p=Istatistiklerle-Yaslilar-2024-54079
56. United Nations, Department of Economic and Social Affairs, Population Division. (2024). World population prospects 2024: Summary of results. https://population.un.org/wpp/assets/Files/WPP2024_Summary-of-Results.pdf
57. United Nations Population Fund. (2024). Ageing. https://www.unfpa.org/ageing Valera Román, A., Pato Martínez, D., Lozano Murciego, Á., Jiménez-Bravo, D. M., & de Paz, J. F. (2021). Voice assistant application for avoiding sedentarism in elderly people based on IoT technologies. Electronics, 10(8), 980.
58. Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13.
59. Wang, Z., Ramamoorthy, V., Gal, U., & Guez, A. (2020). Possible life saver: A review on human fall detection technology. Robotics, 9(3), 55.
60. Yamazaki, Y., Ishii, M., Ito, T., & Hashimoto, T. (2021). Frailty care robot for elderly and its application for physical and psychological support. Journal of Advanced Computational Intelligence and Intelligent Informatics, 25(6), 944-952.
61. Yew, G. C. K. (2021). Trust in and ethical design of carebots: the case for ethics of care. International Journal of Social Robotics, 13(4), 629-645.
62. Zanella, A., Mason, F., Pluchino, P., Cisotto, G., Orso, V., & Gamberini, L. (2020). Internet of things for elderly and fragile people. Arxiv Preprint Arxiv:2006.05709.
63. Zhang, Q., Varnfield, M., Higgins, L., Smallbon, V., Bomke, J., O'Dwyer, J., ... & Karunanithi, M. (2022). The smarter safer homes solution to support older people living in their own homes through enhanced care models: Protocol for a stratified randomized controlled trial. JMIR Research Protocols, 11(1), e31970.