395- When AI Makes Healthcare Mistakes Lives Are Lost w/Sandeep Shenoy

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Philip Howard

Tech News, Technology, Business, Management, News

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🗓️ 12 February 2026

⏱️ 31 minutes

🔗️ Recording | iTunes | RSS

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Summary

Sandeep Shenoy has spent seventeen years integrating AI into medical devices at Viant Medical. He's not anti-AI. He builds it every day. But he's watched the industry rush to deploy systems trained on data sets that were never designed to be fair.The problem isn't the technology. It's the history baked into the data. "When AI makes a mistake in finance, you lose money. When it makes a mistake in healthcare, you could lose a life." Early fitness trackers failed to read female heart rate patterns because of biased training data. That already happened.We get into bias audits as continuous process, fairness by design principles, and accountability frameworks. Plus why ethics needs to move out of the compliance box and into business value.The uncomfortable truth: patients have zero say in how these devices work. They just know a doctor told them they need it. By then, discrimination might already be built in.

Transcript

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0:00.0	Hi, I'm Michael Moore hosting this podcast.
0:11.7	I'm here with Sandeep Chenoy, IT manager for Viant Medical.
0:15.8	Welcome to the program, Sandeep.
0:17.1	Thanks, Michael.
0:18.1	It's great to be here.
0:19.6	Awesome.
0:20.3	Let's talk a little bit about you and your
0:22.4	experience. And Viant Medical, so you're in healthcare. How long have you been in healthcare?
0:30.0	Yeah, so I have been in healthcare for over 17 years. I'm a digital transformation leader in
0:36.9	healthcare for 17 years, specifically in healthcare
0:39.8	and medical device manufacturing. It's tough enough to be in healthcare. You've been there for 17
0:46.1	years. And on top of that, you've been doing digital transformation. Tell us a little bit
0:51.2	about the digital transformation. Yeah, I specialize in integrating AI, blockchain and Internet of things in
0:59.0	med tech environments. So we manufacture medical devices and then our job is to make sure that all these systems are connected and we build
1:08.0	algorithms based on the data and then we secure them through
1:13.3	blockchain and everything. So it's all about innovations in medical devices. So that's what we do.
1:20.2	I know managers. So I look after a certain team members from the quality perspective and
1:25.6	the digital transformation perspective.
1:29.1	Well, let's dive in this a little bit.
1:31.1	AI in medical devices.
1:35.0	Let's break that down and figure out what that actually means.
1:35.9	Yeah.
	...

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