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Скачать или смотреть First, We Must Listen: Reimagining Healthcare in the Age of AI with Sheila Phicil

  • Building AI Boston
  • 2026-03-02
  • 7
First, We Must Listen: Reimagining Healthcare in the Age of AI with Sheila Phicil
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Описание к видео First, We Must Listen: Reimagining Healthcare in the Age of AI with Sheila Phicil

What happens when we introduce powerful new technology into a system that was already failing the people it was built to serve? That is the question at the heart of this conversation. In this episode of Building AI Boston, we sit down with Sheila Phicil, social change futurist, founder of Phicil-itate Change™, and author of the forthcoming book Remembering How to Care: Reimagining Healthcare in the Age of AI, to explore what it will truly take to redesign healthcare from the bottom up.

Sheila's journey began in Port-au-Prince, Haiti, where a volunteer medical mission taught her that even the best-intentioned care can miss the mark entirely. That lesson, listen first and design second, has driven nearly two decades of work inside institutions like Dana-Farber Cancer Institute and Boston Medical Center, and now sits at the core of everything she builds.

We dive into:
Why the U.S. spends the most on healthcare yet ranks last in life expectancy among developed nations and what structural forces are really driving that gap
How the SEEDS of Innovation™ Framework helps health systems get to the root of the problem instead of repeating the same costly mistakes
The Listen Phirst™ platform: using voice AI to collect lived experience at scale and center the voices of the most vulnerable in innovation decisions
Why digital health fails at a 98% rate and what that tells us about introducing AI into already strained systems
The coming collision of rising unemployment, shrinking healthcare coverage, and burnt-out providers
Data sovereignty and why your health data is an extension of your identity, belongs to you, and should be treated as the asset it is
Why the people experiencing the most pain are the ones best positioned to drive the innovation

Sheila also shares her open letter to the CEO of Anthropic on how current AI models risk undermining human sovereignty and makes the case that the most urgent question of our time is not how to build smarter AI, but who gets to decide what health, safety, and care actually mean.

This is a conversation about listening, equity, and what it looks like to walk up to the top of the river and ask why people are falling in. The future of healthcare will not be designed by the system. It will be built by listening to the people living it.
____________________________________________________________________________
 
Sheila Phicil, MPH, MS, PMP, FACHE | Social Change Futurist ™ | 4x Founder 
Phicil-itate Change: https://phicil-itatechange.com
Listen Phirst™ Platform: https://listenphirst.com
Sheila's Open Letter to the CEO of Anthropic: https://helpthisbook.com/sheila-phici...

Guest Bio 

Sheila Phicil is a Social Change Futurist™ with nearly two decades of experience shaping healthcare innovation. She is the founder of Phicil-itate Change™, an innovation studio helping startups, investors, and health systems implement ethical, patient-centered solutions. She’s held leadership roles at Brigham and Women’s Hospital, Dana-Farber Cancer Institute, and Boston Medical Center, where she served as Director of Innovation for the Health Equity Accelerator. She developed the SEEDS of Innovation™ Framework and launched Listen Phirst™, a platform translating patient stories into actionable insights, while advancing data sovereignty through consent and compensation. A first-generation Haitian American, Sheila launched her first nonprofit at age 14. She holds dual master’s degrees from Boston University, is a PMP and FACHE, and has received multiple leadership honors. She is a sought-after speaker and a published contributor to journals including JAMA Oncology. Her forthcoming book, Remembering How to Care: Reimagining Healthcare in the Age of AI, explores reimagining healthcare in the age of AI.

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