How She REVERSED Her Heart Age with Data | Oura x Dr. Juna

Oh, my heart is getting old, I need to work out. And that was a huge motivator in getting me out the door and getting me on a brisk walk and getting me back on the weight machine and getting me back on the rowing machine. September of last year, my cardiovascular age was 6.5 years, and then it climbed up to 5.5, then it climbed up to 4.5. So my heart was like catching up with my body, not being as young as it was. Was like a month ago.

Hey everyone, welcome back to the Mind Body Space Podcast. I'm Dr. Juna Bobby MD, your host. Today's guest is Jasmine Hemdani. Jasmine is a software and data engineer at Oura Rings. In this episode, we're going to explore how data can empower us to make healthy choices. I sit down with Jasmine to talk about her inspiring journey in tech and how data science can support everyday wellness. Jasmine also shares her fascinating career track, and she shares some tips on how to introduce simple, engaging data activities for our kids to boost their resilience and future-ready skills. So whether you want to make healthy changes in your life or are just data curious, this episode is for you.

Hi, Juna. Is my background okay?

It's awesome. You look great. And thanks. We're both in black, which means I love black. I stopped wearing colors because I think colors are so difficult. I tried to buy colors for a long time, and then I met this woman in medical school. She was in residency with me and she just said, my closet is just all black. Oh wow. She never had to decide what to wear.

That's so true. Like, I love black, but I also did some work with color theory just to learn what my colors are.

Uh-huh.

And so. Like the course really helped me figure out what colors I should be wearing that will make me look, my skin look glowing and pop, my features, help my features pop. Today I wore black just to kind of match you a little bit. Nice, I love it. And of course I never disappoint.

Well, you see the pop of color behind me, the little pink thing? Yeah, yeah. But see the pop of colors outside of me? I love that. And then everything else is just like black. And if I need color, I'll just throw on a scarf. Yeah. Although I have problems with scarves too, but that's a whole nother story. I wanna hear about this color theory real quick because I read about that, that people were doing this, that what, what was it, an online course?

Yeah, it was an online course. It came with a brief consultation with a woman who really knows colors and she had me send her pictures of myself in various light conditions, like bathroom light, evening light, and daytime light. And she had done a lot of Photoshopping with my pictures to show me how different colors look on my skin. It was really nice. She has an office in Boston, but you could go and do the in-person color swatching.

What? I just heard about this at an entrepreneurial conference at MIT where they were talking about this startup where they do color matching. Do you know what was the name of her company?

Yeah, it was Anna Harris, I think.

Oh, okay. Awesome.

Yeah, I loved her. I just loved the interaction. It just, and like having a really good friend give you fashion advice and they know what they're talking about.

And it wasn't AI.

Now they have AI.

Yeah. Okay. So thank you so much for being here, Jasmine. And I really appreciate you taking out the time to be on this podcast today. I loved what you talked about at the Harvard Women in Business Conference where we met.

That is true.

And yeah, and the Oura ring.

Oura. Oura. Oura.

Oura looks so fashionable on you. I love it. So I have to say I'm wearing the Whoop.

Oh, okay.

I was using the Apple Watch. My son wanted me to use it. He got it for Christmas and it just wasn't working for me for some reason. When I came to Harvard this year, I saw Will Ahmed at the Harvard Club of Boston. He was fascinating when he talked about heart rate variability, which I have been using in my classes at Juilliard over the past 10 years, teaching people their heart rate variability. I was fascinated. So I bought the Whoop band.

Yeah.

I'm gonna try the Oura. Oura Ring. Yeah. Because I have had some people actually convert me a little bit. I've seen people wearing the Oura and the Whoop also. Yeah. Because I'm like, what do you do when you're weightlifting and you have that? What are you on?

I'm all about people being aware of their health, aware of how their bodies are changing and what signals their bodies are sending them. Personally, I believe that Oura is the best out there. It works very well for me because of its form factor, and I don't wear any tech on my body that can distract me. So anything that gives me a notification, is never on me. Even my phone is hardly ever on me.

Great.

I love that. And it's a change that I've made very conscientiously over the last 3 years or so, and it has done wonders.

Wow. Tell the audience what you do at Ora and how you got there.

Absolutely. I'm a data and software engineer here at Ora. I have been here since June of 2023, so that's coming up on 2 years. At Ora, I work with the research operations team. What my team does is when we are launching new studies. We do a lot of studies, like Oura invests so much in science, in figuring out what else can we decipher from the signals that our body sends us. And my team is at the forefront of these studies. We are contracting with universities, developing protocols, getting the participants, ensuring we have a proper spread of candidates across demographics and body types. As a data engineer, I built the electronic infrastructure that transports this data from candidates from university campuses to the Aura system. And we do— part of my job is to make sure it happens effectively, efficiently, and also safely, that we are protecting—

privacy-wise.

So protecting people's identity, ensuring that we are only taking the data that folks have given consent for, ensuring that the governance is proper, all while building these cool algorithms that we develop from the data that we collect.

Amazing. Tell us about one of the algorithms that you can talk about.

Yeah, we'll talk about cardiovascular age. Do you know how old your heart is? I do. Yeah, and that number might not be the same, right? Mm-hmm. Your chronological age may or may not match your heart's biological age. And that's a very important metric to track is heart health. Like heart diseases are, I think, the second or the third most chronic condition that Americans face. So anyway, so cardi—

And women. Yeah. Specifically women specifically. People don't know about women's heart health.

Yeah. Oh my gosh. Women's health is such a, it's such a huge topic in itself that we can talk about all day. But zeroing in on the cardiovascular age algorithm that I was talking about. So this is an algorithm that has been sort of under development for like 5 or 6 years. I'm talking about cardiovascular age, CVA.

Okay.

Yeah.

Are you using HRV to analyze that? Heart rate variability or using something different?

HRV is part of what goes into your cardiovascular age. Resting heart rate goes into cardiovascular age, breathing rate goes into cardiovascular age. So cardiovascular age is the holistic number that is made up of all the different smaller metrics. All of that gives you this beautiful number that's called CVA. It tells you whether your heart is older than your body, like whether your heart is performing at the same capacity that it should be at your biological age.

Yeah. So compared to people your same age, how well are you doing above or below? And your biological age can differ.

Yeah.

Actual age, wear and tear.

Specifically for your heart.

Yes.

So cardiovascular age is your heart. Yes. Right? When we talk about something called biological age, you, you're talking about like a bigger picture, even bigger than CVA.

Yes. Like your genomics and all of that.

There's lots in that goes in. So my CVA is 5.5 years younger than my age. So I am 35. I'm turning 35 this year.

Congrats.

Thank you. Feels like a big milestone. And my heart is 5 and a half years younger, so my heart is performing at 29 and a half, which is great. Awesome. And that makes me so happy.

And this is all like on the app. HRV is such an old technology, but it's really, I have used the EM-Wave with my students to train the HRV, which is the heart rate variability or your heart being able to react to different conditions. It really means that your heart is changing its rhythm with your breath, with your activity, with sleep, all of that. And it measures that. That's a pretty good indicator of your cardiovascular health. I love that Oura has that. So yeah, I'm definitely going to be buying one of those Oura rings, but I'm just worried if I lose weight because I'm trying to lose some menopausal weight or something. How do you like— can you change out the bands or do you have to buy a new one? How does it work?

So you have 5 fingers on your hands, right?

I have.

So you have like 5 different sizes. So I'm currently wearing my Oura Ring on my index finger, which is like a little commando finger.

Oh, okay.

But you can swap it to ring finger or pinky finger. So as your weight changes, you can move them around. You can move it around a little bit. It'll still work.

Oh my gosh. I didn't even think about that cuz I've been thinking about my engagement ring. So tell us about your journey. When did you find out that you were 5 and a half years younger than your biological age and did you change? Yeah.

So yes. It's a metric that changes slowly. It's not a metric that changes every day, right? Your CVA changes slowly. I did have a bout of, like, sickness and not being very active, and my HRV went from being 5.5 to 4. And that was a really big motivator in getting me moving. I had overcome sickness, and then I was still feeling very lazy and my body was ready for the next, like, getting back into working out. I was feeling, I was not feeling motivated enough. And then my CVA updated to 5 years. I was like, maybe I should try. And then my CVA updated again to 4 years. I was like, oh, my heart is getting old. I need to work out. And that was a huge motivator in getting me out the door and getting me on a brisk walk and getting me back on the weight machine and getting me back on the rowing machine.

How long of a period did you lose that year and a half off your heart?

Let me grab my phone real quick and I'll give you actual data.

Oh, sure.

Of course.

Yes. I love data.

So let's get some real data.

So I have to say that I like that the cardiovascular age is over time because sometimes when you get real data, you can really get obsessed with checking. 'Cause just for fun, I had a continuous glucose monitor on and I was constantly checking my levels and driving everybody crazy.

I've considered getting a CGM, which is a continuous glucose monitor. Sorry, I'm fake used to using all the acronyms.

I— Oh no, it's fine. You know, I'm a physician, right? Oh, I have no idea. But my audience is not, so it's great that you're spelling everything out.

All right. Well, okay, so in September of last year, my cardiovascular age was 6.5 years, and then it climbed up to 5.5, then it climbed up to 4.5. So my heart was like catching up with my body not being as young as it was like a month ago. So by October, I was at 4.5 years. So that's a year and a half. So you lost like, yeah, it took a whole month for that metric to update. And that was when I had caught the flu or something was going on. And then I was like, I'm not working out, whatever. And then I started working out, and then it went to 5 years in November. And then by mid-November, I had gone down to 6 and a half years.

Up? Yeah. Oh, down. Yes, down. So your age was younger. Your light age was 6 and a half years younger.

Yes. So you want more gap, right? If you're 4 years, 6 and a half years is better. Yes. Than 4 years.

Got it. That's amazing. So over a few months, you were able to lower your cardiovascular age. Yeah. Just by exercising.

By exercising. Exactly. Like getting my heart pumping.

Mm-hmm. Does Oura show the actual live heart rate and things like that?

You— we do have a heart rate.

So you can see that.

Awesome. What more you can see, your heart rate is how much physiological stress you're under. You can also see how much time you've spent in a restored state, which stress is a part of our lives. We live busy, productive lives and we're all go-getters.

I always tell everybody you need cortisol, that cortisol in the morning to get you out of bed.

Exactly.

But that's also why heart attacks happen at dawn because a lot, you know, that sort of change, that circadian rhythm change can cause people to have heart attacks.

But what you also need is some restorative time. Yes.. And like Oura visualizes that for you. So today, I— it's only noon, so I've had 30 minutes of stress, but I've also managed to squeeze in 30 minutes of restorative time. That was probably the morning yoga that I did.

Nice.

I had 4.5 hours of stress throughout the day, but I did squeeze in an hour and 45 minutes of restorative time. So that gets—

and what is the data that it's using to measure the stress?

So it's physiological stress, it's not psychological stress, and it is your heart rate, your breathing rate, body temperature, things like that. Mm-hmm.

Oh, it measures temperature. Okay. It does. Yes. So does my Whoop actually. But as a mind-body clinician, I have to say that the physiological stress is related to your mental stress as well.

It is.

I think that it's so powerful to see outside of yourself and like have that feedback. You know, so every time I had the CGM, the continuous glucose monitor on, and I would eat a big meal and then I would actually just go walk on the treadmill, not even fast or anything, I would see that, that sugar dipping, which I would just get so controlled. And so even if you walk that like 5, 10 minutes right after a meal and you can see that line, it's so powerful.

Absolutely.

Yeah. So I wanna talk to you about what inspired you to enter data science and Was this something you were attracted to as a kid? As a woman in STEM, I wanna know about how you got interested in this.

It was, I'll tell you my journey and you can decide why and how I got into it. I'll tell you why I think, 'cause it was accidental. My bachelor's is in electrical engineering, so I've always been about devices and taking things apart and figuring out how they work. And I worked at a chemical plant in Texas. They're part of Bayer, Bayer Material Sciences, the folks who make aspirin.

Yes.

So, I worked there for a couple of years and it was such an awesome opportunity. I got to work with hardware, I got to work with software, I got to work with the design of the user interface that the chemical plant was using. And that just kind of opened my mind to being like, oh, I have a degree in electrical engineering. That doesn't mean I can only use it for electronics and hardware stuff. I can apply it to all these other cool features. And that's sort of where I got the inspiration to be like, okay, what can I do with all the data that's coming off of these sensors? We installed like 700 sensors in this chemical factory.

Yeah, it was awesome. Give me an example. What do you mean by sensor? Like humidity sensor, that kind of thing, or?

Yeah, humidity sensor, pressure sensor. We had a lot of chemical flowing from one tank to another tank, so we had a lot of sensors that would detect how much which liquid was flowing, chemical was flowing from one tank to another tank, at what rate, at what temperature.

And you had tons of data coming in.

So much data coming in.

And you had to kind of decipher that, make sense of it.

Make sense of it, show it to the technicians in a way that would make their jobs easier in troubleshooting issues and monitoring that the chemical processes were happening as expected.

Wait, but you're an electrical engineer, so how did you get hired into this job?

Right, so this job was called a process control engineer. Process control engineering is part of electrical engineering, directly ties into that. And this job was automating an entire process. So, the process was completely manual when we got there, me and my team, as part of a 3-person team. And by the end, after several years, it was a fully automated process. So, I got to work on all sorts of things.

Hardware, software. So, you said it was an accident, like sort of parallel.

Yeah, I started to teach myself. I started by learning Python. I started by learning data engineering practices.

Wow.

Took a few courses, and I was just so curious about—

So where did you learn about Python? Was it CS50 or something?

It was just an online course, to be honest. And a lot of—

See, this is what I'm talking about. I love that. So you self-taught Python on online— Yeah. Did you use Coursera or edX or one of those platforms or just—

Oh gosh, I don't even remember anymore, but it was not Coursera. It was the other one that was big during that time. This is like 2016, right?

That's edX that did Harvard, MIT.

It was probably that one. I've taken so many courses in my—

I'm with you. That's why I came back to school for my master's degree in education, but I spent the whole semester now at MIT, which you can cross-register. So I've been learning everything about AI. And I just thought it was a great time to learn about AI, but I love your story in the sense that you just followed your curiosity.

I did.

Right? You just get curious. Anybody can learn anything online. That's what I'm finding out here.

Yes.

You actually don't have to come back to school.

It's an— hey, I love being a student at school specifically. I absolutely love it too. My life just hasn't gone that way yet. I haven't ruled it out. I love folks who go back to school after a break, and I feel like that positions them in a really awesome space to learn meaningful things.

It definitely recharged my brain. How did you end up at Aura?

So after my job at Bayer, I worked in healthcare data analytics for humans. Then I worked on DNA analytics for dogs, different companies. And I always kind of just like gravitated more and more towards like using data to make lives better. It was first, it was for humans, then I was like, take a break, go make dogs' lives better. And that just happened to be like somebody from Aura reached out. They're like, hey, we loved your profile on LinkedIn. Do you wanna come talk to us? I had seen them pop up online and I had seen them like pop up in my ads. I was like curious and I got to know the team and the work they were doing and it was, I was just sold. I was like, yes, I wanna be part of this.

I love it. And I love making lives better with data. That sounds like a tagline.

I just thought of that. So maybe I'll make that my tagline now.

Well, for all those listening who wonder what they're gonna do with their lives, a lot of students and, you know, parents of students listen to this. So how did Ora reach out to you? What was on your LinkedIn profile? And also, how did you get that first initial, like, job outside of your electrical engineering after the chemical factory?

Okay, so two-part question. I'll answer the first one first. Okay. So getting out of the electrical engineering space and making that move into the data analytics space was the challenging bit, right? I had the same resume, but I sort of talked more about the projects that I was passionate about. And a lot of the data projects made it onto that list. I talked a lot about my skills, my Python skills and my data engineering skills and how I had learned all these cool things. I also did quite a few of like personal projects on, on like GitHub, which were not part of my job to demonstrate that I'm more than a process engineer.

Wow. So you had links to your GitHub repo. So you had links to whatever you coded on GitHub.

I think it's called like a portfolio. A well-rounded portfolio is what I was trying to make. Yeah. And I was also not afraid to move away from home. This was in Texas. My first data analytics job was in Boston. So I chased where I saw my opportunity. I went there.

And the first two jobs with the human and the dogs, Did you find those jobs or did they find you?

The first one I found because I was transitioning away from process engineering. And then COVID happened. I didn't want to work. I wanted to spend time with my mom and dad during COVID I was dating my then boyfriend, now husband, long distance. So I wanted to go live closer to him, so I quit my job. I moved to Louisiana for a few months to be with my parents. Then I moved to San Diego to live with my boyfriend for a few months. We ended up getting married and—

Congrats.

—traveled the world for a year and a half. And then— Wow. —I was finally ready to come back to work. I was like, yes, I feel recharged. I feel like I'm ready to make a difference. I'm ready to get curious again, and I started looking at what else was happening out there. Doggy DNA was— Embark was new on the field. They were doing some groundbreaking work. The two co-founders had traveled the world sampling dogs for their DNA all over the world, and they were building this amazing database of dog genetic information that had never been built before. And that was just so fascinating. I was working with a recruiter at that time because I had taken a long break and I wanted to make sure that I had a smooth process coming back into work. I told him that, "Hey, I'm really interested in these people. They're doing some really awesome work." He was able to get me connected to the right folks and we talked and they were very appreciative of the fact that I had taken a break to recharge and was enthusiastic to come back.

I mean, most people would be afraid to take a break, I think. And I love that you just kind of said, I'm gonna do what's important to me. And I guess obviously you had means to do that. I think. Did you create a narrative that was strong around why you took that time off? Or did you even, were you concerned about it? I wasn't concerned about it.

I told them what I told you. I didn't want, the world seemed like it was ending around me. I didn't want to lose out on time with my parents. I didn't want to lose out on time with my boyfriend, now husband, who I love so much. I was like, this is important to me and I'm gonna go do this important thing. I won't say that Embark was the only interview I did. I did a lot of other interviews where some people were not appreciative of the fact that I took such a long break. And I knew that those were not the right places for me to be.

Maybe the dog lovers. Point of view of the world aligns with more of a relaxed, I don't know.

Taking time for what's important. Yes. Yeah. And when you're working, you give it your 100%, you build world-class solutions, but when it's time for family, when it's time for recharging yourself, guess what? You give that 100% too.

This is why I asked you to come on my podcast, cuz you were talking about this stuff at Harvard also, and it just resonated so much with me. I mean, you know, there are times in our lives where juggling is not actually a truthful thing. You can't juggle everything at once. So it's like you're gonna go off balance to one thing or the other. Like I've focused on my children for a very long time. Yeah. You know, and career, but there's no real balance is what I'm trying to say. It kind of does seesaw up and down depending on what time of life you're in. Absolutely. So congratulations on all the success you've had. Thank you. And more success to come, I'm sure. So when we're talking to kids about data, I talk to a lot of kids who are interested in STEM, and I think data matters now more than ever. Do you agree with that? Oh yeah, absolutely.

I've built my career on data. I think it's only going to become more important as our capacity to collect and interpret data increases. So it's both, right? You can collect a lot of data, but the next question is, now what? Or so what.

But let's get even granular than that. For people who don't even think about data in their day-to-day lives, why, what would you tell them about why it's so important for our day-to-day lives, actually?

You might not be consciously thinking about data, but everything you absorb, whether it's from your eyes or from your nose, or you eat something or you touch something or you absorb an idea, all of that is data, right? I am seeing a car pass by, that's data. If I sit here and look at how many cars pass by my window, at the end of the day, I know how busy of a street I live on. Like, you might not think of those observations as data.

And it's so important because we make decisions based on data, right?

Exactly. If you're going to buy a house, you are collecting data points. If you're buying a candy, let's say for a child, you are probably like, how do you decide what's your favorite candy? You assess different aspects of it. You assess whether you like the taste, you assess whether you like the texture, is it attractive packaging? All of those things are data points.

Yeah, when I was buying our house, we gathered so much data. I even gathered data on pollution and the radius around a highway that you should be so that you don't have that toxic pollution. And I would sit outside of the house at night, even with my husband, and we would be like, what is the nighttime like in this neighborhood? Yeah, all that was data. But now you can get that data probably just from AI, like ChatGPT, you know, like you probably don't have to sit outside of the house.

Maybe, probably not.

Although I do believe in sense data is very important, like our emotional gut. Absolutely. But yeah, tell me more about that, like how you use data from Oura to go inwards and why is that so important for our wellbeing and our, you know, ability to thrive in our lives?

So your body, for a long time, we've looked at a body and you go to the doctor when something's wrong. And by that time, a lot has happened and you have ended up in a state of unease or disease. Looking at the signals that your body is sending you, that's more than hunger or thirst, the ones that we feel very loudly. Your body is constantly giving you all these signals, and by collecting them and by interpreting them in a scientific correct way, you now have actionable insights. I am a night owl. Personally, and having that validation come from my Oura Ring, which has looked at my sleep patterns, it has looked at my activity patterns. When is my mind in its most creative? Like, when is my mind in its most active? That has given me the reasoning and like some motivation to stand up for myself, be like, no, I am more active at night. I will be taking an hour to do my creative projects at I will not be forcing myself to wake up at 5:00 AM because my body type is not that. Interesting. And you hear in the media, morning owls are the best. And then as a society, we've like developed to think that. Yeah. Teenagers need so much more sleep than we give them the time for.

Yes. And especially in the mornings, they start to shift their circadian rhythm. But I'm also a night owl too, but I'm a different night owl because at night I like to watch TV or something and it's terrible. And like my creativeness is like very early in the morning, usually when I have more energy.

It would be so fun to put the ring on you and observe you for a few months and just see what your chronotype is. Uh-huh. Yeah.

So it gives you an actual chronotype, the app. Yeah. Amazing. So it'll probably tell me I'm very confusing. I don't think so. And I always say, I always say, cuz it was, I was born in Seoul, Korea, South Korea, and I moved to America. So I always say that's my problem. You have to adapt. I'm so mixed up. Yeah.

I'll tell you this, you'll get some very actionable insights from your ring. I've made a lot of other changes based on the data that Oura has given me.

Mm-hmm. So. Well, you said exercise, right?

Exercise is a big one. I know my deep sleep happens more in the early part of the early part of my sleep, so I make a point to wear a sleep mask and prioritize, like, when I get into bed, the first half of my sleep is very important for me. So I've made conditions right to, like, optimize that time.

So all this data, I mean, I love it because it's about self-awareness, right? Yes. Because I always talk about how our brain is encased in our cranium, in our skull, And the brain is actually not looking at itself. So that's why self-awareness is so hard. And I think things like aura and WOOP, all of these things give us some insight into ourselves where if we look at our friends, we can say right away, or our kids, for example, I'll be like, no to my daughter. Like, you have to go to sleep early. You need sleep. You've been like this since you were a baby. So you have all that awareness of other people cuz you can observe them. But you can't really observe yourself as much.

Yeah, you hit the nail on the head with that. It's a companion that observes you and gives you information in a very gentle, unbiased way. It's something you can trust, and it doesn't come with judgment. If my mom calls me and asks me if I've eaten a balanced breakfast, it's coming from a place of concern. So it removes that human tendency to perceive outside perspective as judgment.

Which is why sometimes I talk to ChatGPT, because it's not gonna judge me.

See? And it's scientifically backed. It's proven to be very, very accurate. And so you can have the peace of mind that what you're listening to is coming from a data source that is 99% accurate about what your body needs. So there's that aspect to it.

So how can parents introduce their children to data concepts and make it accessible and engaging? Can you give them, like, some day-to-day examples that they can resonate with or relate to for kids?

I would say make data a daily part of, like, conversation. But not in like an overbearing way. I was curious about all these things that were happening around me. So I'm somebody who's not interested in working in financial data. I have friends who are passionate about market trends and all of that. Okay. And then nurture that, introduce data in that field. You might find a more receptive audience. Somebody who's more willing to think about data in terms of a field that they're already interested in.

Interesting. So if they're watching a TV show that they love, you can go into the data of like how many people watch that show. Yeah. How long it took to make that show. All that stuff, right?

Where in the world are other people watching this show? Where in the world is the biggest viewership? What percentage is— you can sort of start digging into that.

Yes. So behind the scenes at Ora, you're working on features and developing things all the time, organizing datasets. Can you share some insights about that just in general? I know that's a big question, but—

Yeah. So research has so many phases, right? I think that's something I can talk about, the phases of research. Like, how does an idea go from an idea to a product?

Okay.

And research plays a huge part of it. Data plays a large part of it. So you have an idea that— somebody had an idea at Oura that, hey, could you calculate your cardiovascular age from the information on the ring? And what did we do? We theorized that perhaps we could. We did a lot of data analysis on the internal data collections, which is just where people who work at Oura contribute their data for science. And once we have a working hypothesis, we partner with universities, we partner with research facilities, and then we open up the research to people. People who are eligible can sign up through these universities. We have some studies ongoing with University of San Francisco, University of Los Angeles, and you become part of the community that's contributing data. You contribute your data with consent. There's a lot of consent that goes into it. And you offer the Oura Ring for free or?

It's different for every study.

Every study has a different protocol.

Students at Juilliard, maybe we could do something together when they're going on stage with the Oura.

Hey, that's an awesome idea. I would pursue that. But every study has a different protocol. And it's the needs are different, compensation, if provided, is different. Okay. We do collect state-of-the-art data from participants, and we use that to develop our algorithms. Great. We collect hundreds of data points. We collect them from people who are wide demographics. We try to make sure that we have a representative percentage of people that we've collected data from, so when our models are built, they're accurate for almost everyone. They are not biased for race, identity, or genders. We take care to develop algorithms that have integrity across populations. And that is a journey for an idea to come to a product.

What would you tell kids to focus on now that AI is changing the future of work?

Oh my gosh. That's a big question. I was at the MIT Museum last night, and they have this wonderful AI Mind the Gap exhibit that's focused on AI, how it has changed from the '60s, '70s to now and what's possible. And I love the idea they presented there. It's that AI is supposed to be cooperative. We work with AI to improve our lives. AI is not a great decision maker. You are still the decision maker. You are still the person asking questions. AI helps you gather information, organize your thoughts, but we are always going to need people who can direct AI in what to do. Maybe the AI can then go do the work, but we will always need good decision makers. We will always need people who know where to look or what is important. Because AI doesn't, it can't do that. It can answer your questions. It can tell you everything about one topic, but it doesn't know what is the important topic. Hmm. Okay. So AI is a great helper. Oh, a helper.

So it will like 10x you basically.

It totally has the ability to 10x you.

I'm sure you're learning all about it because you're so curious. And do you use it every day in your work?

I use it every day. I use it every day in work. My emails are cleaner without it. Oh, nice. Because I use AI to help me write them. Gemini has been helpful in troubleshooting some like virtual environment type stuff, while ChatGPT is really good at text analysis. Nice. That's what I'm finding, but that's just my experience. It's free, so.

Yeah.

I use Gemini and I use ChatGPT more because I'm interested in which one's better. So I'll usually pose the same question to both of them and see what they say. Sometimes ChatGPT is a better performer and sometimes Gemini is a better performer.

Interesting. So Jasmine, thank you so much for being here. I love it. I would love to continue this conversation. Where can listeners learn more about your work at Oura or about Oura in general? Just at their website? I would send you to ouraring.com.

We have sections where you can learn about the ring itself. We have sections where you can read our health blog. It talks about all the cool discoveries we're making. We have a How Aura Works section if you're curious about how it works and what you can expect and what your day can look like. And you can look at what careers we have open. Amazing.

I have some grad students that have interned for me who might be very interested in applying to Aura.

Absolutely. Go to our website, and I really recommend going to our blogs that are under the Why Aura section. They're very informative. The person who writes the blogs for us, her name is Lok, and she is a gem of a person. I just love reading her writing, so I would recommend people to go to the Aura blog and learn more about Aura.

Great. And how old do you have to be to use it? Like, what's the minimum age? I don't know. I would love to know. You can—

I don't know if there is a minimum age. Yeah, let me know. Yeah, I think if you're interested in learning about your sleep— Tweens even, maybe? I know people who are using Oura Rings for their children, tweens, early teens. Wow, okay. Awesome. Teenagers. I don't know if there's a minimum ring age. I will find out and I will email you.

So go to mindbodyspace.com to the podcast page and sign up. And I always follow up with them if they have any questions about the podcast. And would you be willing to answer them if I get some questions? Oh yeah, absolutely. And where are you based? I'm based in Boston. Oh, we have to have lunch. Okay. Before I graduate and move back to New York, I'll be back here often, but I'd love to take you out for lunch.

I would love to meet with you for lunch. Let me know whenever.

Jasmine, thank you so much for being here.

I loved being here. Thank you so much for having me.

I hope you enjoyed that as much as I did. In. Head on over to mindbodyspace.com/podcast to sign up for our email list to get the latest tips and to send us your questions. While you are there, check out our courses and products on time, brain, and stress for kids and parents. Thanks for joining us.