AI is moving quickly, but medical devices cannot afford to treat every new model like an ordinary software update.
In this episode of the Med Device Cyber Podcast, Christian Espinosa speaks with Tyler Harmon, CEO and co-founder of IASO Automated Medical Systems, about the risks and responsibilities surrounding AI as a medical device.
Tyler explains why consumer tools such as ChatGPT and Claude should not be treated as clinical diagnostic systems, even when a doctor remains involved in the final decision. He also explores why a human in the loop does not automatically make an AI system safe when the underlying model was never designed or cleared for that medical use.
The conversation examines how predetermined change control plans can support safer AI updates, why developers must understand the difference between frontier models and AI harnesses, and what can go wrong when a medical-device company builds on top of a third-party model.
In This Episode
- 00:48 Tyler Harmon and IASO Automated Medical Systems
- 03:34 What qualifies as AI as a medical device?
- 04:44 Predetermined change control plans
- 06:08 When should an AI medical device be updated?
- 09:00 Why medical AI is not new
- 11:32 Why medical AI still needs human oversight
- 17:40 Doctors using ChatGPT to interpret X-rays
- 20:09 Frontier models and AI harnesses
- 24:16 The challenge of developing proprietary AI
- 29:21 Why medical AI can take years to reach the market
- 34:28 Using consumer LLMs outside their intended licence
- 39:25 Licensing third-party AI for medical-device use
- 40:41 Final lessons for medical-AI developers
Check out Tyler Harmon’s LinkedIn here: https://www.linkedin.com/in/tyler-h-938bbb43/
The Med Device Cyber Podcast is brought to you by Blue Goat Cyber, cybersecurity experts providing essential security solutions for the medical device industry. Learn more by visitinghttps://bluegoatcyber.com.
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Christian Espinosa is the CEO and founder of Blue Goat Cyber.
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