How AI is redefining health & wellness

AI is already in your life — from your maps to your movies — but its quiet revolution is happening inside our bodies. Most of us think of health in terms of diet, exercise, or willpower, yet the truth is that our data often knows more than we do. When interpreted well, it can reveal metabolic blind spots, stress patterns, sleep disruptions, and food triggers we’d never catch on our own.

Most people think of AI as something technical, robotic, or detached — but in reality, it’s becoming one of the most personal tools in health. In this episode of The Wellness Algorithm, we’re joined by Amandeep Khurana, an Entrepreneur, Product Leader and Health Enthusiast who used data to uncover what years of guesswork and even medical guidance had missed. Together, we explore how AI can connect the dots between sleep, food, stress, metabolism and recovery, and why the goal isn’t replacing doctors — it’s creating clarity. From glucose spikes at night to hidden reactions to food and unexplained fatigue, AI can surface patterns our minds simply don’t track, giving us a kinder, more personalised way to understand our bodies.

Health isn’t about collecting more data — it’s about translating it into small, doable shifts. Whether you’re just curious about AI or already using trackers and apps, this conversation shows how technology can simplify wellbeing instead of complicating it.

Here is a list of blood tests that are helpful:

1. CBC
2. CMP
3. Lipid Panel
4. Lipid Fractionation
5. HgbA1C
6. Homocysteine 
7. Magnesium
8. Vitamin D
9. Uric Acid
10. Apolipoprotein B
11. Lipoprotein (A)
12. hs-CRP
13. IGF-1, LC/MS
14. DHEA Sulfate
15. Estradiol
16. FSH
17. LH
18. PSA Total
19. Testosterone, Free and Total
20. TSH 

For a transcript of this show, go to https://wellnesscurated.life/how-ai-is-redefining-health-wellness-2/

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Transcript

Anshu Bahanda: AI is already in your life. From the way Netflix recommends your next show to how Google Maps shows you where to go, AI is everywhere. But what is fascinating is the way that AI is being used for health and wellness. From sleep tracking to personalized food guidance, helping us to see patterns in our body which we would never have noticed otherwise. Things that the human brain would miss. AI seems to be picking up and it's life changing for some people. And we have one such guest today. So join us for this incredible conversation. This is Anshu Bahanda from Wellness Curated.

Welcome to the Wellness Algorithm. Here we go beyond quick fixes and hype and explore what really works in health and wellness. Before we proceed, can I please request you to subscribe to this page? Subscribe so we can carry on getting you these life changing conversations and speakers without charging you a penny. AI can feel like a buzzword. It can be intimidating, it can be overwhelming. But in health, it's moving us into a new era from this one size fits all advice to truly personalized, accurate wellness. And the story we're diving into today makes it real. Amandeep, my guest today, is passionate about health and wellness and his day job is in AI at AWS. He sold an AI business in the past and he's also very, very passionate about health. So his two interests are, AI and health. We're going to delve into how he combined the two to help himself and how it was life changing for him. Welcome to the chat, Amandeep, and thank you for taking the time to be here with us today.

Amandeep Khurana: Thank you. I'm excited to have this conversation.

AB: I want to ask you, Amandeep, for listeners who are new to this, what do we mean when we say AI in health and wellness? Because the word AI can overwhelm and intimidate people.

AK: That's a good point. It can overwhelm people for sure. So I'll give you my definition of how I think about it. What AI is how we can think about AI in the context of health and wellness. There's multiple layers to it. We can think about AI in the context of drug discovery. We can think about AI in the context of backend operations, or clinic efficiency. We can think about AI in the context of, more on the clinical side with patients. So all of that exists. But for most of your listeners and for people like you and I who are trying to be as healthy as possible, live our best lives, AI is a powerful tool or set of technologies available to us to make sense of our own health data to make sense of, protocols to come up with, ideas to help with diagnosis and so on and so forth. It's essentially empowering us as consumers with more information and more intelligence, so that we can be better about our own health and wellness. That's how I think about it.

AB: So you explain it in a very user friendly, simple way, which is good.

AK: Yeah. Technology is only as good as what the users are able to get out of it, right?

AB: Yes, absolutely. Now tell me, for most of us, where do we encounter AI on a daily basis? Apps, wearable trackers. Where would it be familiar if you told people, okay, so you know, your Oura ring has AI, you know, things that would.

AK: Again, there's multiple layers to AI, right? So all your wearable devices that collect data, at some level they have some intelligence built into them. It may not be the most sophisticated intelligence when they give you reports and tell you something about your resting heart rate or how you slept or your readiness score and so on and so forth. It may not be the most sophisticated intelligence, but there is still some algorithm that's built into it. Right. So one could call that AI. Because the definition of AI is, it's a spectrum of things. Right? So I would say all your variables, all your apps, trackers and even things that your doctors use to give you different kinds of reports. There's some technology, some intelligence technology built into almost all, these things. So as individual consumers, all the apps that we use have something with the other.

AB: So now I want to ask you other things. You know, life can be very complex, but you can break it down to fairly simple stuff. We all need sleep, we all need food, and we all need ways of dealing with stress in the world that we live in.

AK: Yeah.

AB: So if someone wants small wins, how can AI actually help them with these three things?

AK: Yeah. It's a funny thing that you're asking. If someone wants small wins, how can AI help? The biggest win that you can get on those things that you just talked about is making sure your sleep is in order. And that has nothing to do with AI, that you're sleeping well and you have a good consistent sleep schedule. And AI has nothing to do with that. In fact, quite the opposite. You want technology out of your bedroom and get the best sleep possible. So I don't think you need AI to help with just the basics. Getting the basics right now as we get more advanced, as we try to figure out, you know, I try to optimize things, try to figure out why something is not working. Some of the data tracking and the intelligence becomes useful. But to get the basics right, I don't think we need to over complicate it in most cases.

AB: Okay, so just coming back to sleep, right? You're saying technology should be out of the bedroom, but I have. There's so many people, and I don't wear an Oura ring, by the way. So you know where this question is leading to. I don't wear technology and myself especially when I'm sleeping. Yeah, but people are swearing by this Oura ring because they're saying it tells us the sort of day we had and therefore the sleep it leads to.

AK: Yeah,

AB: Technology. That's AI

AK: For sure. I think this gets into the conversation of what data and how much data is useful and what do you do with data. So I think we should talk about that because it's not just the intelligence. The intelligence is interesting, but the underpinnings is the data and what's useful to track, how much is useful to track, and what's the sweet spot there about the Oura ring? I'll tell you an experiment that I'm running right now. I have not concluded yet that this is true. Anecdotal evidence tells me that my HRV had dropped over the last several months. And I had a bunch of hypotheses for why this might be happening. Then I heard somebody, or came across somebody making the claim that, some of these devices caused HRVs to drop. So I said, okay, cool, I'll run an experiment. It's pretty easy. For three months I didn't. For two months I didn't use the Oura ring. And then I bought it back. No other changes. So everything else is the same, lifestyle is the same, no other changes, minor changes here and there. And my HRV almost doubled.

AB: Oh, wow.

AK: So again, this is very early data. I'm not convinced that there is a relationship. There's a causal relationship here, but it seems to point in a certain direction where now I, I'm more curious and I want to go look into this further. So sure.

AB: Just for people who don't know, Amandeep, can we explain HRV just so people are very clear?

AK: Yeah. Heart rate variability. Right. HRV stands for heart rate variability. And so it's also not just the heart rate variability, it's also my resting heart rate, at night. So I've seen that go down a little bit. That could just be statistical error in the data. But heart rate variability is a better sign of recovery and my heart rate variability has improved over the last couple of months. And it looks like there might be a relationship to the technology.

AB: Interesting.

AK: Yeah.

AB: Okay, go ahead.

AK: Embedding the technology and collecting the data. Useful. Yes. But there might be some side effects of this thing that we are just not aware of.

AB: Of this Or

AK: Constant use or any. Yeah, exactly.

AB: Constant use of any technology. I very often worry because I always have a phone on me as a lot of people do.

AK: The phone is probably going to have the same effect.

AB: Yeah. And it's literally stuck to my hand because I use it for everything.

AK: Yeah.

AB: And it does worry me because isn't HRV the higher the HRV, the higher the stress? No, sorry. The lower the HRV, the higher the stress. It's kind of inversely related to stress.

AK: Correct. It's correct. It is. Stress and recovery overall. Yes, is inversely related.

AB: Now tell me. So we've kind of talked a little bit about sleep and stress. Talk to me about food. Yeah. About how AI can help people with food or how they can use it to help with their diet.

AK: I think, Yeah, I think the more important thing here is to understand what data is useful and then think about.

AB: Sorry to interrupt, but I was gently leading people into the data thing because people seem to be so worried about data. That's the one thing which just, you know, so many people are so intimidated by it. So I was gently leading them into data.

AK: Right.

AB: But go ahead.

AK: Yeah. Again, food or exercise? I think the key thing here is what data are you collecting and then what intelligence do you want on top of the data? Right. So the way I would think about AI is if I have a set of data about my sleep, food, stress, exercise, overall health, I'm going to give it to a human being that's going to, let's say a coach or a doctor that's going to make sense of it and then tell me, you know, you should eat this, you should not eat that. So it's a nutritionist that's going to give me some plans. It's an exercise physiologist that's going to give me exercise, plans and so forth. I'm going to go to a professional that's going to give me some of this information and AI can potentially replace some of the things that that professional can, can do. Right. So that's the way I think about AI. The Question is what data do I need to collect to make this useful? And that goes to the health goals, and that then tells you what data is relevant and useful for those health goals. Now there are some basic things that I would consider are, you know, appropriate for pretty much everybody that is trying to take a data driven approach to their own health.

We can go down the food, sleep, exercise, and just general blood markers. So on the food front, I find it very, very useful to start to track food. Everything that I'm eating, like I'll wait, I'll put it in a tracker like a MyFitnessPal or thermometer. What I'm looking to track for the most part is my macros saturated with fats, and total caloric intake. And then not just through the day, but per meal as well as to the week. Right. So that's what I'm looking to track and the reason I track that.

AB: I'm going to interrupt you again. Before we start getting into what data to collect for these different areas, can I ask you to best explain to the listeners who feel overwhelmed by data or privacy, because that's a fear. Before we get into actually talking about the data, explain to them what should be their starting point and what should they worry about and what shouldn't they worry about and then we'll get into what data they should.

AK: Sure. You brought up privacy. That's an interesting topic. I've heard, people are pretty concerned about privacy and I've also heard people take a completely different stance on privacy and saying, you know, none of this is that important that I need to keep private. I generally take the stance that none of the things that I'm going to use or none of the data that I'm going to put in these apps is that important from a privacy perspective. So did I eat eggs in the morning or did I have a smoothie? Who cares, right? So generally, I take a much more open stance on it. I think about privacy as a trade off conversation. If you're online, you're using Facebook and Google and any of the social media things, you probably have much less privacy than you think you do. These tech products and companies know much more about you, than you think they do. So there's that. Now do I want to put some of my super private information onto an app that, you know, just somebody just built, around the corner.

Maybe not, but I generally take a much more liberal stance on using technology here from a privacy standpoint. So, again, that's my personal stance. Now, for people who are just starting out, I think getting the basics right on, let's just track what you're eating. Let's just track how many times a week you are exercising and what type of exercises we are doing. And just getting started with that is actually very, very helpful. And then, having your blood markers, tracking those, and then tracking your sleep. You know, the interesting thing about sleep tracking is you could just be using a simple paper form, to track sleep quality and sleep quantity. And that's what sleep specialists use, by the way. Sleep specialists do not use it. Oura. And whoop. They use a simple paper form. And, you can look it up. Yeah, I work with CP specialists, and that's what they do. I said, hey, I have my Oura. I'll give you the. Give you access to my Oura. And they said, no, we don't want that. That's for you. You can keep doing whatever you don't want to do with the Oura. We want to know how you're feeling. So write it in the form. There's something about using a paper and pen to fill up a form and then take a picture of it at the end of the week and send it to us. Okay. Yeah. So there are forms you don't need technology for. This was pretty basic stuff there.

AB: Okay, so you're saying just keep track of how you're sleeping, what you're eating, and put that into the likes of My Fitness Pal or something. Yeah, those two things. And how much you're exercising, what kind of exercise are you doing?

AK: Yep, yep.

AB: Those are your suggestions. You tracked for years, right? What kind of data did you collect? And why did you do it?

AK: All the tracking that I'm. I'm talking about? You could just use this. Use a journal, paper, and pen to do all of this. You don't need apps. Now, of course, apps make it easier in a lot of cases. For example, just calculating your macros. You put it in My Fitness Pal. It's much easier than if you put it on paper and then you go Google. You know, how much does that egg have? So, yes, these things make it easier for sure, but you don't need the apps to get started on my own. Tracking. So I've had chronic metabolic challenges since my teenage years and I've dealt with obesity since the age of 15. And about 10, 12 years ago at this point I started to just get into details of studies and different kinds of protocols and just got curious about metabolic health and started reading and learning from there. Then I started tracking my own data. And it started with just a simple set of blood tests to then get body composition through DEXA's to then sure, I was tracking my food to where I was tracking my sleep at the time? I don't remember.

I probably didn't start with sleep tracking at the time. But later on I did actually track it. So over time I am probably collecting much more data than useful in, in most cases. But I am a data geek so it doesn't overwhelm me, I actually enjoy it. That's not true for everybody. If you look at it like if I just talk to my wife about this, she says I don't need to track all this. I'm gonna sleep, I feel fine, I'm okay. I don't need an Oura ring, which is totally okay.

AB: Probably a reaction to you. Maybe she's. That's a reaction.

AK: It's very much possible. Yeah, she's over-correct. She's correcting me. Yes. So I generally take a much more data driven stance and I've also found that there are diminishing returns. So the more I know about my blood markers over, let's say three month intervals, as compared to six month intervals. It's not that I can act on it or there is anything to act on. But I still collect the data because I just like data. That's what I do. That's my day job generally.

AB: So tell me, when you analyzed all the data that you tracked with AI, what specific health issues did it reveal to you which had escaped the human eye? Because I remember you and I chatting about it and you were just blowing you away.

AK: Yeah. So, the context of the data that I'm collecting, let's talk about that a little bit and then I'll talk about some of the challenges I was working on and then how I used AI to uncover some interesting, interesting things that made a difference. So over the last, let's say 10 years, which is the last decade, I've got blood tests every few months, let's say every six months, all in a spreadsheet. It used to be in a spreadsheet. Now and then DEXA scans every six to 12 months. I've got those are the two big ones then sleep tracking with Oura, et cetera. For the last few years, I've got my genetics done. I've got a couple of different kinds of genetic testing done. So that's the basic data that I'm working with. And then of course I track my weight regularly. I already said sleep and body comp. So those are the things now, I've now started tracking. Over the last six months I've started tracking my blood pressure with a continuous blood pressure monitor. So now last year I was working on, and I'm still working on the metabolic fitness side of things.

So this is about a year ago. And what I was, I was having a hard time even with the caloric intake where I was in a deficit, I was having a very, very hard time losing weight and or losing fat. So my goal is not to lose weight, it's to lose fat. So it's a body composition goal. And as I again my blood test showed elevated insulin levels which, but my glucose levels are fine, but insulin levels were elevated and that's how it's been for quite some time. But this time I saw them much more elevated, elevated than usual. And I had again done my genetics and I'd done all these blood tests. I put it all into chat GPT at the time and I said let me just see if I can do anything interesting. We're just going to play around and see if I can find something useful. I had no idea what I'm going to discover. I had no idea what I was, what I was doing. This was just playing around with it. At the time what ChatGPT gave me, and there was a couple of genetic reports as well was said that, you know, I have a couple of genetic snips, because of which there is a high correlation or those have high correlation with high amount of saturated fats will cause or can cause insulin resistance and high amount of branch in amino acids can cause insulin resistance.

So let's talk about what those things are. Saturated fats, types of fats that are found in full fat, dairy or red meat, coconut oil and so forth. On the other hand, unsaturated fats are in the likes of nuts and olive oil and, and so forth. So my diet did include saturated fats. We would use ghee and coconut oil for cooking and I would use butter. And when it was yogurt, I enjoyed full fat yogurt as opposed to unfat. Now so that was that. And then branch. Amino acids are amino acids that are typically found in most protein sources, especially animal protein sources. Now I have generally taken a stance of more protein, less carbs. And so I would take protein shakes as an example. So let's say, I need to get to 150 grams of protein in a day. I would easily take one or two scoops of whey protein and make a little smoothie out of it. Again, I keep it pretty low starch, low, low sugar. But I would consume protein shakes. Okay, so now branch in amino acids. I'm consuming them through the protein shake and saturated fats. I'm consuming them through dairy and meats. I don't like red meat much. So that was not a problem. But it was mostly the dairy and the butter, where the saturated fats are going in. Now that piece of information, it didn't say that this is causing it.

We don't know if this is a causal relationship. It said that there is a tendency, there's a chance, there's a higher risk of insulin resistance. Find an experiment for me. Yeah, because I have those snips. So, and so said okay, why don't, why don't I run an experiment? I'm going to keep my calories the same and I'm going to cut out saturated fats and replace them with unsaturated fats. I'm going to cut out protein shakes and I'm going to try to get the same amount of protein through each chicken breast. And so that's what I did. I'm going to do this for a couple of months and see what happens. And I start and in about 10 to 15 days I drop 10 pounds and my insulin comes down from 16 to 9. And that was just mind boggling. I said okay, I don't believe this. This doesn't make any sense. Again, I'd been tracking all my food so I know my calories were the same. Or maybe the calories had gone down a little bit because, you know, eating that much chicken, this was just hard. So they've probably gone down a little bit, but not nothing. Not by 3,500 calories a day. Right. That is what would explain 10 pounds of weight loss in 10 days. I certainly didn't drop my calories by 3,500. I wasn't even eating 3,500 a day. So.

Okay, so now this doesn't make any sense. Now keep in mind I'm doing DEXA scans so I know that this is fat loss. I know this is not water loss. So I continue the thing and I go for another couple of weeks, three weeks, and I drop another 10 pounds and my insulin levels stay below 10.

AB: Oh my God,

AK: This is fascinating. This is, this is really, really fascinating. So I've, since then, changed my dietary pattern entirely. Entirely. As in I've cut out saturated fats. I don't take saturated fats on a day to day regular basis. It's all monounsaturated fats or polyunsaturated fats. And I've stopped consuming protein shakes. I still hit my protein targets.

AB: This is so fascinating.

AK: Yeah, yeah. Now or

AB: Did it just help with weight loss? Did it also help with energy levels and other long term effects? You said insulin levels came down.

AK: Came down. Yeah, I mean of course just having 20 pounds of fat less in the body helps with everything. Right? So my blood pressure dropped a little bit. I was more active. I could keep, I can go for two hour walks and hikes and so yeah, from that perspective, yes. And energy levels were better.

AB: Fascinating. And this is something that no doctor picked up for you. This is something Chatgpt,

AK: Correct.

AB: Because I know that you've had a team of doctors that you work with who help you with your health issues.

AK: Right, yes I do. But yeah, nobody picked up on this thing. And there have been other cases where I've used AI for analysis of a bunch of things. And my doctors have generally said that that level of analysis and data crunching is just not possible, it's not practical for them to do it. And they generally have found those analyses to be useful in coming up with protocols for me.

AB: Fascinating. And tell me, besides changing your food patterns, what else did you change based on the analysis done by AI? for you on your data.

AK: I think this was the primary one from a data perspective. In that example it was food, exercise and sleep stuff. I have not yet, at least not at the time. I did not get much out because that's what's not what I was looking at. Now there are other examples of me using AI for diagnosing some other issues, which I can talk about. But in that instance, it was full.

AB: Okay. Fascinating. And did you ever or how can AI be used with sleep? Help with sleep and stress? Those are really big ones globally.

AK: Yeah, so I tried this where I take a screenshot of my Oura day to day, right? Take the graphs and I take those screenshots and I put it into chat GPT and ask it questions, right? So, for instance, I've, I've taken screenshots of that and my CGM and there was a continuous glucose monitor. So I'm tracking my glucose levels again. That's another certain taker that I track. I've taken that, put it into ChatGPT at one point because I was finding that my sleep was not very restful, and my heart rate was going up middle of the night. So I fed all of that information into ChatGPT and pointed to my liver producing glycogen or dumping glycogen into the bloodstream in the middle of the night. And the reasoning it gave was that, it's either a stress response, which I'm sleeping. It shouldn't be a stress response. It's not that I'm having nightmares every night. Or it could be that I didn't eat enough carbs throughout the day, in which case the body is trying to compensate, or the liver is trying to compensate by producing more or releasing more glycogen into the blood. So one of the things it said was at dinner time, add about 30, 40 grams of carbs and see what happens. And I tried that again. This is something that a nutritionist will also be able to pinpoint. But again, if. If I went to them and said I'm not sleeping very well, they wouldn't. That's it. That's not where they would go.

AB: They won't associate it with carbs. They won't necessarily associate.

AK: Yeah. Correct. Yeah, the mechanism. Of course, they understand the mechanism, but they wouldn't have connected the dots that easily. And also, I wouldn't have taken my sleep issues to a nutritionist. Right. So there's that. So I tried that. And, yes, I stopped having the glucose secretion in the middle of the night and my heart rate didn't go up.

AB: Wow, that's fascinating. That's where you come. Also, it's looking at you holistically, right? It's looking at you as the holistic organism that functions. It's not just, obviously the prompts You've given it are important and you obviously gave it a very clever prompt. What tends to happen very often is that we focus on one issue. So it's like when not sleeping, we're not sleeping. We're not sleeping. This is just a look at. Look at you.

AK: Yeah.

AB: On the whole. And said what could be wrong where in his body? And that's what it found.

AK: Which is generally hard for doctors to do. So you asked a question about my team of doctors missing things. I would not go to my nutritionist and tell them about sleep issues. I would not go to the sleep specialist and tell them about my diet. And they're not going to help me optimize my diet. So it's just, they're specialized in those topics. But for them to take a complete picture and connect the dots is just hard,

AB: You know. Amandeep, I would love you to share some other sort of aha moments with people just to give them an idea of what can help them with AI in their health.

AK: Yeah, I'll give you another example. This is relatively recent. And again I've actually written about a lot of this on my substack and you can put a link to that, in the show notes.

AB: We'll put a link in the.

AK: Yeah. So a recent one where I was on one Sunday morning, just doing my workout. And this particular instance I was trying to do some squats. I started doing my warm up. I was in the second set of my warm up, not picking up any heavy weights. It was just kind of getting moving and halfway through the set I felt something snap in my back. Now I've had injuries in the past so I know when something doesn't feel right in the lower back because I've had lower back injuries and this one just didn't feel right. So I left everything, I left the weights, I left everything. And I just lie down, you know, half an hour later, you know, I kind of just move around and say, okay, what's going on? This doesn't feel right. I shouldn't be injuring myself during a warm up. It's a very slow set. I'm easing into it. What's going on? So a couple of days later, again, this was, this was a pretty bad injury. I was barely able to move a couple of days later as I was able to move and do some things.

Let me figure it out again. Let's try if I can get something interesting out of AI on this one. So I have my own tracker app. Now that I've built, which tracks a lot of data, for me. And so I plug that, and that is now integrated into AI. So I go and ask the LLM some questions. And I'm using Claude in this case, and I ask it some questions. I say I've been feeling low energy, which is true at the time. I also injured myself doing this workout. And so, can you help me think through what might be going on? Go analyze all my data. So it has access to my continuous group of smarter data. It has access to my sleep data from Oura. It has access to all my blood markers and supplements and meds, and it has all of that, and it also has access to my exercise data from Whoop. So it crunches through the last six months of six, to nine months of data, and comes back and actually surfaces up that, oh, you know, you've had low ferritin, which is true. I'd had low ferritin for some time. And there is this change that has happened in your sleep architecture over the last six months.

Plus you've had low ferritin and the hormonal shift over the last six months. Again, I knew about the hormonal shift. All of this would point to this phenomena with the muscles pushing on strength training may not be a good idea. Your risk injury because of. Because of these things. And this might explain why you're feeling low energy and less strength. And to me, again, I knew about low ferritin, I knew about the hormonal shifts, so that was not surprising. But connecting the dots of that to how I should be changing my workout planning.

AB: Yeah.

AK: Because it's gonna. I. I'm not gonna feel that strong. So pushing it might be, you know, risking injury, which is exactly what happened. Connecting the dots was super helpful. Now, my doctors were working on both those problems, but they hadn't connected the dots into my exercise programming.

AB: Fascinating. That's absolutely fascinating. Now, tell me another thing. With so much data that you collect. Right. Yeah. And you get AI to analyze this data for you. More often than not, it must be giving you an action plan and telling you that something may not be right because we're human, do you. Does it ever make you anxious or obsessed about oh, my God. Or what's happening to me? How do you set these boundaries for yourself? That.

AK: Yeah, that's a great question. Yeah, that's a great question. Anxious? No, it doesn't make me anxious. Obsessed. This is a bit of an obsession for me. So, yes, but again, it's more of, my mindset and my temperament is one of taking a different approach. I want to know things. Not knowing gives me more anxiety than knowing. Which is not true for everybody. Some people prefer not knowing, right? I prefer knowing.

AB: So you always want to know.

AK: Correct. This is not the only topic where that happens.

AB: Do you think you would tell people, people who it could make you anxious, that, okay, you track it for a certain amount of time and then go take a break and come back to it every week or every Tuesday.

AK: For sure, I think the data is only as good as what it empowers you to do. If it does the opposite and overwhelms you, it's not serving its purpose. But lack of awareness is also not helpful. Right. So if you are trying to accomplish some health goal, whether it's weight loss or better sleep or, you know, whatever it might be, if you use data, you can get there faster, more efficiently, and just have a better plan.

AB: Are there any situations where you would say, please don't bother with AI now you need to go to a doctor straight away, someone who's listening to this, who's assimilating all this information you're giving.

AK: Oh, sure. Well, AI is not a replacement for a doctor. So everything that I do, I run it by my doctors. So this example of the ferritin, low ferritin causing issues, I did the analysis and sent it to both my doctors and they looked at it and they said, yeah, we agree, we agree. And your plan needs to change. This makes sense. I wouldn't have changed my plan or my medical medicine dosage or anything like supplement dosage without running it by the doctors. So it's not a replacement for doctors. It's empowering you with information. It gives you ideas. It actually makes it easier to go and have those conversations with doctors because you are more informed. In my case, I'm more informed and they are more informed now, so they like it too.

AB: Okay, so you're saying this is not replacing human beings.

AK: Not at all.

AB: To guide you. This shouldn't be your only guiding light.

AK: That's absolutely right. Yeah. Because we have the hallucination problem with AI so it can give you things that are not accurate.

AB: So, yes, that's an important point that everyone needs to note is use this data and use the information you're given and take it to your doctor. Okay. I want you to talk to me about the future, what is it about? What is the future of AI? What really excites you about health and wellness by 2030?

AK: Oh, wow, you know, in the world of AI, even 18 months is very far away. Everything that I say might not be true in six months. Things are moving very, very fast. I think the empowering of the individual with more intelligence is actually very exciting. And then there will be a point where we will be able to trust AI based solutions as our first line of defense. From a medical perspective. Right. So you can take pictures of things and ChatGPT will tell you it does it today, that this is what it looks like. So the tech is getting there. I think by 2030 I'm fairly certain we'll have some AI doctored solution available as a first line of defense. And it's not just going to be the first line of defense, even for optimization. I think the optimization piece is way sooner than that. I do it already.

AB: Anything that you think by 2030 is five years away. Anything you think in four and a half, five years, which is going to be drastically different from today in the context.

AK: Yeah, it's so hard to predict. I think we're mostly talking about health optimization for individuals. We haven't talked about drug discovery and things like that. So I think there's a lot of promising things that can happen on that front. On just drug discovery, for example. But we're mostly focused on the individual, I think on that front. More and more information. We already have the ability to track a lot of information. There's probably some other things that I'd like to be able to track which are just not available right now. But it's not that far out, in the next five years. I think just synthesizing all of this and having our own little longevity apps, it's probably going to happen in the next two years. I know a few people that are working on this. Drastically different. The interesting thing about this is human beings are not going to be drastically different in the next five years. It's not the technology, it's our inability to change our own behavior that comes in the way.

AB: Are you sure we're not going because things are moving so rapidly?

AK: Yeah, no, I'm pretty sure behavior will change for you and I will still be as hard as it is today.

AB: Okay, so lastly, before we get into the rapid fire round, I want you to give us something really interesting for people listening. I want you to share a 7 day starter kit like starter to use AI wisely and see the benefits for their health and wellness.

AK: Yeah, depending on where the individual is. If you're collecting, let's say you're using all these apps like you're using Oura to track sleep, you're using, you know, whoop for workouts, MyFitnessPal for food tracking. Let's say you're using all of this and you're tracking a lot of the information. Try to feed this into the likes of ChatGPT and ask it questions. Right, and ask it questions like, okay, given my last three months of data, what are the trends you see? Here's my focus area. What do you think I could be doing better or different? So let's see what it says and then interact with it to ask more questions and see what you can get out.

AB: What about people who haven't tracked anything?

AK: Yes, so let's go to that one next. If you're on the spectrum of I have not tracked or I'd like to track, I'd like to get started if you're there. Then just starting with, just start using some of these apps again. You don't have to buy devices, whatever devices you have are fine. You can start tracking with even just paper and pen. So I went for a one hour walk. Right back then I went for a one hour walk. And then of course if you have a device and you know what your heart rate was during that one hour walk. And so start with that, get a comprehensive set of blood tests done. If you haven't done that already, at least once a year, getting a comprehensive set of blood tests would be helpful because all of that then completes the picture. And then once you start this tracking, the interesting thing about tracking is let's say food and exercise. Let's say you say I want to be eating 2,000 calories a day to get to 100 grams of protein, whatever your macros and caloric goals are. And the moment you start tracking, you actually get better at adhering to the plan. So yeah, it's not just having a plan but tracking it makes it easier. And you get better at adhering to the plan.

AB: That's fascinating. Amandeep, because you're such a data geek. There are so many people I've had conversations with who said, we don't want to know.

AK: Yeah,

AB: We'd rather not know. 

AK: Yeah,

AB: That's interesting. They're like, no, it's too complicated. The doctors will find something. Especially as people get older, they either go more towards, oh, we want to track our data, we want to find out what's going on, or they go the other way. They say, no, thank you, we're getting older, there'll be an issue, it'll settle down.

AK: Yeah. No, totally again, that's just a temperament and a mindset thing. Some people like it, some people don't.

AB: Thank you, thank you for that very interesting conversation. Before you go, I want to do a very quick rapid fire round. So tell me if it's a myth or fact and one line. Why? Yeah. Can AI replace your doctor?

AK: Not yet. Eventually it will, but not yet.

AB: So the doctors need to start thinking of alternative jobs.

AK: Or I would say that, I'd say that they need to figure out a way to work with AI and be more effective at their job.

AB: Okay. More data always equals better health.

AK: Not true. You can have more data, not act on it. And just be overwhelmed by it. And actually could hurt more than help.

AB: Okay. Wearables are medical devices.

AK: They're not medical devices because they're not medical grade. So I won't call them medical devices. Yeah,

AB: AI can tell you exactly how many calories you burn.

AK: Not true, not true. They're all estimates. Yeah. At best. And they're mostly inaccurate data.

AB: Privacy is the biggest risk of AI.

AK: I don't think so. It is a risk, but I don't think it's a big risk.

AB: AI can predict illness with 100% accuracy. Accuracy given the right data.

AK: Not true, not true. Even doctors can't predict illness with 100% accuracy with all the data in the world. So no, there's always some error there.

AB: Okay, thank you, Amandeep. That was a great conversation. Thank you so much for being here.

AK: Thank you, thank you for having me.

AB: What I love about today's conversation is how it showed us that AI isn't just a tech toy. It can be a health companion for each one of us. Amandeep's story proves that when you use it wisely, AI can uncover blind spots, guide your choices, and even improve your well being in ways you never expected. If this episode helped you in any way, please subscribe to the Wellness Algorithm and leave a comment. We don't charge you for this podcast. Your support helps us bring you even more inspiring guests. You share it with a friend who's curious about the future of health. And remember the three Cs. Be curious, be credible, and be compassionate to yourself. I'm Anshu Bahanda from Wellness Curated, and I can't wait to see you next time.