• FUTURE-AI: The New Framework for Medical AI

  • 2025/04/11
  • 再生時間: 7 分
  • ポッドキャスト

FUTURE-AI: The New Framework for Medical AI

  • サマリー

  • In this episode, we explore FUTURE-AI, a groundbreaking global framework designed to ensure that medical AI is not just innovative—but also ethical, transparent, and worthy of our trust. With input from 117 experts across 50 countries, this initiative aims to set the first internationally agreed-upon standards for responsible AI in healthcare.


    Topics Covered:

    • What FUTURE-AI stands for—and why it matters

    • The six core principles: Fairness, Universality, Traceability, Usability, Robustness, Explainability

    • How the Delphi method shaped a global consensus on AI standards

    • The difference between research AI tools and those ready for clinical use

    • Why this framework could shape the future of ethical AI in medicine


    Credits:
    Production: MedShake Studio
    Host: Anca Petre


    Stay connected and learn more:

    • LinkedIn: linkedin.com/in/ancapetre

    • Website: www.ancapetre.com & www.medshake-studio.com

    • Email: anca@medshakestudio.com


    More about the podcast:
    Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


    Hosted by Ausha. See ausha.co/privacy-policy for more information.

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あらすじ・解説

In this episode, we explore FUTURE-AI, a groundbreaking global framework designed to ensure that medical AI is not just innovative—but also ethical, transparent, and worthy of our trust. With input from 117 experts across 50 countries, this initiative aims to set the first internationally agreed-upon standards for responsible AI in healthcare.


Topics Covered:

  • What FUTURE-AI stands for—and why it matters

  • The six core principles: Fairness, Universality, Traceability, Usability, Robustness, Explainability

  • How the Delphi method shaped a global consensus on AI standards

  • The difference between research AI tools and those ready for clinical use

  • Why this framework could shape the future of ethical AI in medicine


Credits:
Production: MedShake Studio
Host: Anca Petre


Stay connected and learn more:

  • LinkedIn: linkedin.com/in/ancapetre

  • Website: www.ancapetre.com & www.medshake-studio.com

  • Email: anca@medshakestudio.com


More about the podcast:
Every week, I dive into the most transformative trends at the intersection of technology and healthcare. From AI-driven breakthroughs in diagnostics to the role of blockchain in securing health data, from decentralized science (DeSci) to NFT-powered health innovation, and from gamified fitness to the potential of digital twins, I’m here to make complex topics simple, accessible, and exciting.


Hosted by Ausha. See ausha.co/privacy-policy for more information.

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