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What if the future of AI in healthcare depends less on better models and more on whether patients can actually access their own data?
In this episode of The People’s AI, presented by the Vana Foundation, we explore why health data portability is not just a bureaucratic headache, but a foundational issue for better care, better research, and better AI. We begin with the story of Liz Salmi, who discovered just how difficult it was to access and move her own medical records after years of treatment for brain cancer. That experience became the starting point for a bigger conversation about patient rights, siloed health systems, and the real-world consequences of inaccessible data.
From there, we examine how better access to health records can help patients catch errors, ask better questions, and become more active participants in their own care. We also look at the larger implications for medicine itself: how fragmented data limits research, weakens AI models, and slows the development of more personalized treatments.
We then dig into the idea of digital twins in healthcare, with insights from Jim St.Clair, Reinhard C. Laubenbacher, Ph.D., and Dr. Matthew DeCamp. Together, they help explain how digital models of the body could eventually support more precise diagnostics, treatment planning, and preventive care, but only if the underlying data is portable, usable, and governed in ways that respect privacy and patient ownership.
It is a conversation about medical records, interoperability, digital twins, precision medicine, and the broader question of who controls health data in an AI-driven future.
Topics covered:
The People’s AI is presented by the Vana Foundation, supporting a new internet rooted in data sovereignty and user ownership, where individuals, not corporations, govern their own data and share the value it creates. Learn more at Vana.org.
No transcript available for this episode.

The People's AI: The Decentralized AI Podcast

The People's AI: The Decentralized AI Podcast

The People's AI: The Decentralized AI Podcast