Full Transcript 0:00 AI diagnosing diseases after a patient sees 17 other doctors. 0:05 AI creating personalized treatment plans. 0:08 Ai comic strips explaining medical procedures to kids. 0:12 No secret, AI could totally revolutionize healthcare, but wow, it's a lot to process, right? 0:18 It really is, yeah. 0:19 It's about way more than just having the coolest, newest technology. 0:23 We need to look at the real challenges and opportunities too. 0:25 Right, exactly. 0:26 And thankfully, there was this roundtable of experts. 0:30 They really dug into this whole complex topic, gave us all a lot to think about. 0:34 OK, perfect. 0:34 So that's what we're diving into today. 0:36 Sounds good. 0:37 One of the biggest things that jumped out, at least for me, from what these experts were saying, was just how much AI could speed up diagnoses. 0:44 They were talking about this one patient, right? 0:46 This patient saw 17 doctors, 17 over years, and they were struggling to get the right diagnosis. 0:52 But then AI comes into the picture. 0:54 Wow. 0:54 And AI pinpointed the issue almost immediately. 0:57 It's incredible, isn't it? 0:58 It is, it's really groundbreaking if you think about it. 1:02 I mean the time, the money, and I think most importantly the emotional toll that could be saved. 1:07 Oh absolutely. 1:08 If you can even imagine a future where those difficult to diagnose cases are resolved like that faster and more effectively, 1:15 that's the hope. 1:16 That's a promise AI holds. 1:17 It's like AI could be the thing that helps us solve some of health care's biggest mysteries. 1:23 And the things is, it goes beyond just diagnosis too. 1:26 The experts were also talking about personalized treatment plans, which seems kind of crazy. 1:31 What does that look like in real terms? 1:33 I mean, imagine a world where cancer treatment isn't one size fits all, you know, but it's tailored to your specific genetic makeup, 1:41 the cancer's characteristics, all of that. 1:43 Or think about chronic conditions, something like diabetes, right? 1:47 Where AI could be analyzing your data and personalizing your diet and your medication in, like, real time. 1:53 Wow. 1:55 That's amazing. 1:55 It's like having a personalized medical team, but they're available 24-7. 1:59 But okay, with all this talk about how great and amazing AI could be, you know, all of this potential, we can't forget about the practical side of things, 2:08 because implementing these technologies on a large scale, that is going to be a huge, huge undertaking. 2:14 What were the experts' thoughts on that? 2:16 Were they really daunted by this? 2:18 I think they were very aware of the hurdles, let's say. 2:21 One of their biggest challenges is going to be ensuring these technologies are developed responsibly. 2:25 You know what I mean? 2:26 It's not just about building the AI itself, it's about making sure it is accurate, reliable, and accessible to everyone. 2:34 Oh, it's about building trust in these systems before they're just widely adopted everywhere. 2:39 We need to be sure they are not just a flashy new gadget. 2:42 They're actually something that improves people's lives. 2:45 Absolutely. 2:46 And I think that requires everyone working together. 2:49 Doctors, researchers, policymakers, tech experts. 2:52 All of those people need work together to make this vision a reality. 2:56 It's like, how do we make sure this technology is actually used to benefit everyone, not a select few? 3:02 Right and that's a huge concern a lot of the experts brought up for sure and it kind of ties into this whole idea of like an AI IQ. 3:10 I think you touched on that earlier. 3:11 Yeah yeah definitely. 3:13 So what does that actually mean though in the context of health care like how does It's interesting. 3:21 Right. 3:22 It essentially means like we all need a basic understanding of what AI is, how it works and what it can't do. 3:29 Its limitations. 3:30 OK. 3:31 And that doesn't just mean doctors and scientists either. 3:34 Patients need this AI IQ too. 3:36 So they can understand what's happening. 3:38 Exactly. 3:39 They can advocate for themselves, understand their treatment options and just like feel comfortable asking their doctor questions. 3:46 So it's about empowering patients to be active participants in their own health care. 3:51 Exactly. 3:52 Even when AI is part of the picture. 3:55 Which it will be more and more, it sounds like. 3:57 Absolutely. 3:57 And it is crucial for providers, too. 4:00 I mean, imagine if doctors can confidently explain an AI-driven diagnosis to a patient or treatment recommendations. 4:07 They have to bridge that gap, right? 4:09 Between like the complex algorithm right and understandable care right. 4:13 It makes me think of those scenes in medical dramas you know where they're all huddled around an x-ray trying to make sense of it. 4:19 Oh yeah. 4:19 Are we going to get to a point where it's like that but it is an AI generated report. 4:24 It's an interesting way to think about it, for sure. 4:27 But the key difference is that AI should be a tool to help doctors not replace them. 4:32 OK. 4:33 It is about combining the best of human expertise, intuition, empathy, that human connection, with the analytical power of AI. 4:42 Is it like having, what's the word, like a really, really skilled consultant, right, by their side? 4:49 Someone who can provide insights and recommendations, but at the end of the day, the final decisions are made by the doctor and patient. 4:55 Exactly. 4:56 And you know, the experts, they emphasize this a lot, developing this AI IQ. 5:00 It's ongoing. 5:01 it's not like a one-time thing. 5:03 Because as AI changes healthcare, we all need to keep learning, keep adapting. 5:08 Keep up. 5:09 Yeah, and refining our understanding of what AI can and cannot do. 5:12 Stuff like learning a new language then, kind of. 5:14 In a way, yeah. 5:15 I like that. 5:16 You don't become fluent overnight. 5:17 It takes time, practice, and a willingness to embrace these new concepts. 5:23 Sure. 5:23 And speaking of embracing new concept, I feel like another major theme that came up in that roundtable was transparency. 5:30 Oh yeah, big time. 5:31 Can you elaborate on that a bit? 5:33 What did they mean by that? 5:34 So transparency is, it's essential when it comes to building trust in this AI-driven healthcare, right? 5:43 It's not enough to just have these systems spitting out recommendations. 5:46 We have to understand why. 5:47 The why? 5:48 Yes. 5:49 And how it got those recommendations? 5:50 So it is not just about getting an answer from the AI. 5:52 It is about understanding the thought process. 5:54 Exactly. 5:55 And doctors need to be able to interpret AI recommendations. 5:58 They need understand the reasoning behind it. 6:01 Yeah. 6:01 Then they need be to able communicate that clearly to their patients. 6:04 So the patients in the loop too. 6:06 Absolutely. 6:07 Patients, they needed to feel comfortable asking questions. 6:13 Okay, so it's like a two-way street then. 6:15 Yes. 6:15 The transparency helps ensure everyone's on the same page. 6:19 Right. 6:19 And comfortable with the decisions that are being made. 6:22 Exactly. 6:23 But transparency on its own, I mean, it is not enough, right? 6:26 No. 6:27 We also need to make sure that these AI systems are held accountable. 6:31 Like how do we make that they are functioning the way they're supposed to be functioning. 6:35 What did the experts have to say about that? 6:38 They were very, very clear that AI and healthcare, it's not a set it and forget it kind of thing. 6:43 It requires ongoing monitoring, evaluation. 6:47 We have to make adjustments along the way to ensure accuracy, fairness, make sure it is effective. 6:54 So it's like releasing a new medication. 6:56 You don't just like put it out there and hope for the best, you have to keep a close eye on it, make sure it is actually doing what it supposed to do, 7:03 that it isn't causing crazy side effects. 7:06 So how do we even go about monitoring these systems, these AI systems in a way that actually makes people feel confident? 7:14 That's a great question and something the experts definitely dove into. 7:19 They kept coming back to the importance of real-world data. 7:24 Like how do we actually evaluate these systems? 7:26 And they were saying, you know, it's one thing to have an AI that's doing great in the lab somewhere, but it is totally different when you put it out in 7:34 real world with all these different patients, different medical cases, everything. 7:39 Absolutely. 7:39 And that's what really matters, right? 7:40 It's about constantly testing, getting feedback, making changes as you go. 7:44 It is the only way to build AI that is effective and also can adapt. 7:48 Because things change in healthcare all the time. 7:50 They do. 7:50 New treatments, new research, it never stops. 7:53 So the AI has to be able to keep up with that. 7:56 Any new tool, really you've got to learn how to use it in all kinds of situations and be willing to adjust. 8:02 Exactly. 8:02 And that actually brings up something else the experts were talking about, which is guidelines. 8:08 We need clear guidelines and regulations for all of this. 8:10 Because it's such new territory. 8:12 It is. 8:13 As AI gets more integrated into health care, it has got to be done responsibly. 8:17 So having a framework, like some rules, that ensures that. 8:22 That's going to crucial. 8:23 It's like we're establishing the rules of the road, but for, you know, a brand new kind of vehicle. 8:28 Yes. 8:29 But we got to make sure everyone's driving safely, ethically, all that. 8:32 And the thing is those rules, they can't just come from one place. 8:36 It can just be tech people making those decisions. 8:38 That has to be patients, providers, researchers, policymakers, like all of them. 8:43 all the stakeholders yes they've got to work together because the goal is to create a system where this potential all this amazing AI potential it's used 8:54 for good right and we're avoiding as many of the risks possible so it finding that sweet spot right where this innovation can happen but it's not like 9:05 compromising patient safety or making people lose trust in the whole healthcare system. 9:09 It's a tough line to walk for sure but like you said that's why we need everybody at the table. 9:14 It's a conversation that's just getting started, really. 9:16 100%. And as we keep having these conversations, we have to remember, AI is a tool. 9:22 That's all it is. 9:23 And we get to decide how we use it, what our values are, and what kind of future we're trying to build. 9:28 It is big responsibility. 9:32 So to bring it all home here, We've covered a lot of ground, as always. 9:37 As we wrap up this deep dive, What's the key takeaway you hope people listening are walking away with? 9:45 That's a great question. 9:47 If I had to boil it all down, I'd say AI has the potential to completely change health care, but only if we approach it thoughtfully. 9:55 We're thinking about ethics and never losing sight of the human beings who are going to be impacted by it. 10:01 It can't just be about the technology itself. 10:03 We got to be using these tools to help patients to, help providers, you know, to actually improve people's health and create a healthcare system that's 10:11 more effective, more equitable for everyone, and frankly, just more compassionate. 10:16 Couldn't have said it better myself. 10:17 It's definitely something worth striving for. 10:19 And on that note, I want to thank you for joining us on this deep dive into the world of AI and healthcare. 10:25 It's a fascinating topic, always changing, so much to talk about. 10:29 Keep those great questions coming and we'll keep digging into them. 10:33 Until next time.
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