Personalized Aging-in-Place Support Through Fine-Tuning of Generative AI Models

Artificial intelligence (AI) has long been proposed as an enabling technology for addressing the challenges of the impending demographic shifts in western countries. While AI tools for identifying, monitoring, and assessing adherence to best health practices have been previously proposed, recent developments in generative AI models offer unique capabilities to address compliance-related challenges. This manuscript proposes a framework for enhancing AI-assistive technology through personalization enabled by generative AI. Namely, emerging generative models are fine-tuned using training data mined from text, audio, and visual records of target individuals to produce customized user experiences which can be integrated within the technology ecosystem available to the end-user. In addition to proposing this framework, this work-in-progress manuscript also reviews recent advancements in technologies which enable its implementation.