综述与译文

数智技术何以应对老龄社会?

闫萍 郑璐颖 陈知知
2025年第4期
53 1542
摘要

全球老龄化与数智技术革新相互交织,为改善老年健康状况带来了严峻挑战与全新机遇。 本文从监测预警、医疗干预、治疗范式、社会心理支持四个维度,系统梳理了国外数智技术重塑老年健康领域新生态的实践探索,探讨了数智技术赋能老年健康领域的风险图谱,分析了数据主权蚀风险、数字鸿沟固化风险、技术适配缺陷风险、自主性消解风险,这些风险反映了技术理性与人文价值的深层矛盾。 最后,本文从如下四个方面,探讨了国外研究和实践给中国老年健康领域数智技术创新带来的启示:构建“制度—技术—能力”三位一体的数据安全防护体系,筑牢数据安全防线;聚焦设计伦理、情感适配、伦理监管,赋予技术人文温度;协同能力提升、资源下沉、政策激励,弥合数字鸿沟;激活年龄多样性,实现代际共创。

关键词
数智技术 老年健康 数据安全 数字鸿沟
正文
参考文献
  • 安宝洋、翁建定,2015,《大数据时代网络信息的伦理缺失及应对策略》,《自然辩证法研究》第12期。
  • 高婷婷,2022,《“共鸣”之三重误解———基于哈特穆特·罗萨“共鸣”理论的探讨》,《视听》第11期。
  • 林陶玉、方鹏骞,2025,《人口老龄化背景下老年慢性病区域医疗服务模式与对策研究》,《中国医院》第4期。
  • 王伟进、陆杰华,2025,《老龄社会及其治理面临的认知挑战与应对》,《北京行政学院学报》第2期。
  • 向运华、王晓慧,2019,《人工智能时代老年健康管理研究》,《新疆师范大学学报(哲学社会科学版)》第4期。
  • 解保军,2004,《安德瑞·高兹的“技术法西斯主义”理论析评》,《自然辩证法研究》第7期。
  • 张佳欣,2024,《机器人成为老年生活好帮手》,http://finance.people.com.cn/BIG5/n1/2024/0718/c1004-40280197.html。
  • Benge, J. & M. Scullin 2025, “A Meta-Analysis of Technology Use and Cognitive Aging. ” https://doi.org/10.1038/s41562-025-02159-9.
  • Benge, J. et al. 2023, “Technology Use and Subjective Cognitive Concerns in Older Adults. ” https://doi.org/10.1016/j.archger.2022.104877.
  • Bernal, M. et al. 2024, “Artificial Intelligence for the Study of Human Ageing: A Systematic Literature Review. ” https://doi.org/10.1007/s10489-024-05817-z.
  • Chu, C. et al. 2022, “Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults. ” https:/ / doi. org/10. 1093 / geront/ gnab167.
  • Hu, M. et al. 2024, “Healthy Aging in Place with the Aid of Smart Technologies: A Systematic Review. ” https://doi.org/10.3390/encyclopedia4040125.
  • Karches, K. 2018, “ Against the iDoctor: Why Artificial Intelligence Should Not Replace Physician Judgment. ” https://doi.org/10.1007/s11017-018-9442-3.
  • Lee, J. et al. 2019, “Current Status of Elderly Hypertensives in Korea, Insights from Nation-Wide Big Data Analysis. ” https://doi.org/10.1097/01.hjh 0000571292.62633.1c.
  • Li, J. et al. 2023, “The Smart Medicine Delivery Using UAV for Elderly Center. ” https://doi.org/10.22937/IJCSNS.2023.23.1.11.
  • Lu, X. et al. 2023, “Data Collection Methods and Predictive Analysis for Fall Prevention in Elderly Populations. ” https://ieeexplore.ieee.org/abstract/document/10487294.
  • Majumder, S. et al. 2017, “ Smart Homes for Elderly Healthcare: Recent Advances and Research Challenges. ” https://doi.org/10.3390/s17112496.
  • Menezes, P. & R. Rocha 2021, “Promotion of Active Ageing Through Interactive Artificial Agents in a Smart Environment. ” https://doi.org/10.1007/s42452-021-04567-8.
  • Oliver, D. 2019, “ David Oliver: Lessons from the Babylon Health Saga. ” https://doi.org/10.1136/bmj.l2387.
  • Pradhan, B. et al. 2021, “Internet of Things and Robotics in Transforming Current-Day Healthcare Services. ” https://doi.org/10.1155/2021/9999504.
  • Ryu, H. et al. 2020, “Simple and Steady Interactions Win the Healthy Mentality: Designing a Chatbot Service for the Elderly. ” https://doi.org/10.1145/3415223.
  • Stypinska, J. 2023, “AI Ageism: A Critical Roadmap for Studying Age Discrimination and Exclusion in Digitalized Societies. ” https://doi.org/10.1007/s00146-022-01553-5.
  • WHO 2022, “Ageism in Artificial Intelligence for Health: WHO Policy Brief. ” https://www.who.int/publications/i/item/9789240040793.
  • Zhavoronkov, A. et al. 2019, “Artificial Intelligence for Aging and Longevity Research: Recent Advances and Perspectives. ” https://doi. org/10.1016/j.arr.2018.11.003.
  • Zhu, S. et al. 2021, “Effects of Virtual Reality Intervention on Cognition and Motor Function in Older Adults With Mild Cognitive Impairment or Dementia: A Systematic Review and Meta-Analysis. ” https://doi.org/10.3389/fnagi.2021.586999.
Loading...