Research on the Regulation of Intelligent Elderly Service Laws in the Age of Artificial Intelligence

Abstract

Abstract The artificial intelligence senior care model brings about work efficiency improvement and human resource cost saving to old care service enterprises and government departments. Taking Maslow’s hierarchy of needs theory as an entry point, the article systematically combs through the needs, legal source relations, and potential risks of intelligent senior care services. To accurately assess the relevant influencing factors of the legal regulation of innovative senior care services, linear regression and seemingly uncorrelated regression models are introduced. The model parameters are estimated by Bayesian estimation method, and the empirical analysis is conducted based on the baseline regression and seemingly uncorrelated regression models. When the local government pension policy decreases by every 1 percentage point, the degree of legal regulation of innovative pension services will decrease by 0.598 percentage points. In addition, in the likelihood uncorrelated regression model, the influence coefficient of education level is −0.372, which is 38.81% lower than the benchmark regression model. To better guide the standardized development of innovative senior care services, the central and local governments must actively introduce relevant policies to help the public better understand and accept the advantages of intelligent senior care services.