Ethical review of intelligent elderly care model： risk patterns， generative factors， and regulatory pathways
10.12026/j.issn.1001-8565.2026.01.15
- VernacularTitle:智能养老模式的伦理审视：风险样态、生成因素与规制路径
- Author:
Xin SHEN
1
Author Information
1. School of Marxism， Jiangxi University of Finance and Economics， Nanchang 330013， China
- Publication Type:Journal Article
- Keywords:
scientific and technological ethical governance;
artificial intelligence;
intelligent elderly care;
science and technology towards good
- From:
Chinese Medical Ethics
2026;39(1):105-112
- CountryChina
- Language:Chinese
-
Abstract:
Driven by the internal pressure of the traditional elderly care model and the external impetus of the new technological revolution， the intelligent elderly care model is emerging. However， the rapid technological development has also triggered a series of ethical controversies. Existing ethical rules struggle to interpret， adapt to， or regulate the risks of ethical norms being out of control， alienated ethical behaviors， and unclear ethical responsibility that have emerged in the intelligent elderly care model. Specifically， these risks manifest in three aspects， including infringement of the rights and interests of the elderly， imbalance in social fairness and justice， and difficulties in defining responsibility. The analysis revealed that the generative factors of ethical risks include both internal system factors and external environmental factors. To prevent and control the ethical risks of the intelligent elderly care model， efforts should focus on three levels. At the technical level， it was necessary to promote the development of responsible intelligent elderly care technologies. In terms of regulatory level， it was essential to innovate the rules and methods of responsibility allocation. Regarding cognitive level， it was vital to strengthen users’ awareness and response capacity to ethical risks. These approaches will continuously promote the upward and virtuous development of technology and foster harmonious coexistence between humans and machines.
