Alicia Chong Rodriguez is keeping wearable AI tech close to the chest

Note: Transcripts are automatically generated from episode audio, and are not fully corrected for spelling, grammar, and formatting.

ALICIA CHONG RODRIGUEZ: Amelia Bloomer. She was a dress reform advocate from the 1800s who transformed the way that women were wearing clothes at that time. Because if you think about the 1800s, women were wearing corsets that would basically be so tight that they would deform their organs, right? And they would be dying at early ages of their lives because of this.

So Amelia Bloomer led this movement against those damaging corsets towards more comfortable and useful garments for women, and that’s why the first pants that women ever wore were the bloomers.

RANA EL KALIOUBY: Amelia Bloomer is one of the many women who inspire Alicia Chong Rodriguez. In fact Alicia named her company Bloomer Tech in honor of the early garment innovator. And like Amelia Bloomer, Alicia is making clothing that can transform women’s health.

Bloomer Tech is focused on wearable technology. That includes a bra that can monitor and detect women’s cardiovascular health, preventing future cardiac issues.

RODRIGUEZ: Since our inception, we were very focused on making a difference for heart disease in women, right? Like this is an area that has been understudied, under-researched, under-recognized in so many ways. Like a lot of these diseases lead to the chronic condition of heart failure, or even worse, sudden cardiac arrest, stroke, or heart attack.

EL KALIOUBY: Bloomer Tech is on a mission to stop this from happening. This is the kind of life-saving innovation that drives my work as an AI scientist and investor. And I’m so excited to share my conversation with Alicia today. We covered a lot, from algorithmic bias and the challenges of developing wearable tech to how AI can save our humanity.

I’m Rana el Kaliouby and this is Pioneers of AI – a podcast taking you behind-the-scenes of the AI revolution.

[THEME MUSIC]

Hi Alicia. Welcome to Pioneers of AI. It is so great to have you on the show.

RODRIGUEZ: Yeah, I am so happy to be here.

EL KALIOUBY: So, first of all, I wanna give a shout out to Dr. Joy Bini because she was our very first guest on the show and she recommended that we interview you. And so I’m so excited that we’re finally making this happen.

RODRIGUEZ: That’s so cool. Thank you so much.

EL KALIOUBY: Yeah. And the three of us actually share the MIT connection and the three of us are also World Economic Forum Young Global Leaders. But I think you’re the newest YGL. How’s your experience been so far?

RODRIGUEZ: Ah, it’s been amazing. And meeting so many people worldwide has been an amazing opportunity.

Copy LinkFrom personal journey to a mission in women's heart health

EL KALIOUBY: Yeah, it’s an amazing network of people. Okay, so today we’re gonna talk about bras. So you are the co-founder of a company called Bloomer Tech, which basically builds smart bras for women’s cardiovascular health. But before we dive into all of that, I would love to hear more about your personal journey, your experience at MIT and how all that culminated in your starting Bloomer Tech.

RODRIGUEZ: To share a little bit about my experience, I came to MIT back in 2015, and it was a huge accomplishment for me because being from Costa Rica, having done my undergrad in Mexico, it was my dream to be able to come to MIT. So I had dreamed about it for a long time. And when I was here, I got access to so many researchers, right? Like world-class researchers. And I was interested in sex differences in healthcare. So I talked to many of the labs before deciding which lab to do my thesis in. My background is in electrical engineering and computer science. And the lab that I felt more connected with was the Computational Cardiovascular Research Group because they understood what I wanted to work on in terms of really understanding how sex differences would impact AI and the future of machine learning algorithms back then. And I think that led to a whole array of things, doing that work that led us to realize that we could build a company.

EL KALIOUBY: Yeah. You also, I guess, have a very personal connection to starting the company, and I guess it’s your grandmother. Can you share a little bit about that story?

RODRIGUEZ: So right before coming to MIT, and this is why I focused on cardiovascular so much, I was talking with a group of friends and we all had a relative that had had breast cancer in the past. And all of our relatives fortunately survived. They got diagnosed on time and we were all talking about it, and we were thinking what’s the biggest threat to women’s health right now?

And that’s when for the first time I learned about heart disease being a threat to women. And I was curious about my family because my sister had had breast cancer. Now my mom has had breast cancer. But we never talk about heart disease.

Who in our family has had heart disease?

And I’m the youngest of six and I’m the grandchild that is named after my grandma. So I’ve always been very proud of my grandma because she was a pioneer of her times. Like she graduated as an OB-GYN in a time when women were rarely allowed to obtain medical degrees. So I always looked up to her when I went to a class of engineering and I was one or two women in a class of 40. This is what I think about, because I’m named after my grandma.

EL KALIOUBY: Getting goosebumps. That’s amazing.

RODRIGUEZ: So for me it was shocking when I asked my mom, hey, has someone in our family had heart disease? And she was like, oh, your grandma died from a heart attack. She died when I was 12 years old. I just never knew it was from heart disease. And then talking to other people, they have stories like that. It’s a story more common than we can imagine, that it suddenly takes a loved one away. And that’s when it was all very shocking, and we were very curious about that.

Copy LinkWhy heart disease in women remains dangerously overlooked

EL KALIOUBY: Yeah. One of the things that I’m really passionate about is women’s health and AI, and in particular, how can we combine this trifecta of sensors, data and AI — both predictive AI, but also generative AI — to really understand and get to kind of the underlying causes of, and also diagnosis of, women’s health.

And I just wanna share some statistics. So 44% of women in the US have some form of heart disease, yet women have a harder time getting diagnosed than men. And to your point, we don’t even talk about it. And in fact, women are twice as likely to die after heart failure than men. This is very upsetting, obviously, and you have a kind of personal experience with this too. How has this gap inspired your work?

RODRIGUEZ: Yeah, and when you add to those statistics across any age, right? Because sometimes people hear this statistic of how women are having worse outcomes and they think, oh, they get heart disease when they’re older, but it’s across any life stage that it happens. So women are just having worse outcomes. And when you look at the research that has been done in sex differences, you realize that it has not been until very recently that there’s been an accumulation of evidence in terms of what’s really going on between men and women. And it’s because women were excluded from clinical trials for a long time, especially from cardiovascular research. It was only until 1993 that the NIH mandated inclusion of women in their clinical studies.

EL KALIOUBY: That is crazy, by the way. That is crazy that before 1993, the inclusion of women in these clinical trials was overlooked. Right.

RODRIGUEZ: Yeah, so we’ve never had that much data from women in general, right? Like I think that can perpetuate a lot of problems that we see in the field, but there is growing evidence on sex differences, which is what’s exciting in the last 30 years. Pioneers that understood early on that women’s hearts, just because they’re smaller, doesn’t mean that they’re just smaller-sized hearts of men. Like they’re not just little men, as some doctors call it. And it’s not only bikini medicine, right? Talking about reproductive health — women’s health is way more than that.

And I think that has led to an opening of an opportunity where AI could either perpetuate problems or fix them. If we move forward and collect more data from women that is missing, because that’s the reality: women’s data is missing in many areas.

Copy LinkHow missing data creates algorithmic bias in healthcare

EL KALIOUBY: Yeah. And for folks who are listening to us who are not immersed in the AI and machine learning space, how does this data and potentially algorithmic bias become quite hurtful?

RODRIGUEZ: Yeah, I think the under-diagnosis that we see today, right, like if you think about it from a clinical standpoint, we’ve been using a lot of data sets for clinical decision making for a long time. Either people are at high risk, middle risk, or low risk, and that way you decide what therapy they’re going to get and what’s the next stage for their process.

In some of the cases, for example, the Chava score, which is a score to measure the risk of cryptogenic stroke — being male or female is one of the things used to calculate whether you are at higher risk. So just being female puts you at higher risk, right? But that’s how little we know about these conditions. They had to put it as part of the calculation.

EL KALIOUBY: And presumably the more data we have, the better these algorithms and these decision trees become. Are you focused on a particular piece of clothing, which is the bra? Why go with the bra design?

RODRIGUEZ: Yeah, well, for us, following her legacy in this technological era, it was important to think about how clothing can do so much more for women’s health. The bra is a garment that women wear every day of their lives when they go outside their houses in many cultures. So we saw it as something that if we were able to collect data, because it’s also in a very good location of the body to collect very reliable and important signals from the body, right? Like we have the heart and we have the lungs right there where we have the bra. And opposed to other wearable devices that are making their technology smaller and have to sacrifice a lot of things for comfort, right?

Like, let’s think about a ring or a wristband, or even the medical patch monitors that have made technology smaller. The trade-off is their performance and capabilities. We don’t have to do that with a bra. We just need to ensure that it looks and feels like any other bra, that it’s comfortable, but you can use flexible technology to make it a seamless experience, and there’s a lot of real estate in that chest area, so you can collect huge amounts of signals.

Copy LinkWhy the bra is a powerful platform for medical sensing

EL KALIOUBY: So I wanna use this framework of the trifecta of sensors, data and AI to really understand how Bloomer Tech and how your smart bras work. So let’s start with the sensing technology. What kind of sensors do you have in there and what are you measuring?

RODRIGUEZ: Yeah, so we have our patented textile-based sensors that collect huge amounts of data from that location of the body. So we’ve included things like multi-lead ECG, temperature, activity, posture, movement.

EL KALIOUBY: Take us through like what exactly is ECG measuring?

RODRIGUEZ: Yes. So ECG measures the difference of potential between two points of your body. So it’s an electrical measurement of how your heart is working at different angles, right? So there’s hundreds of years of evidence on how at different angles you can interpret the data from the ECG. And now there’s more coming thanks to AI, in terms of how it can be used for interpreting other things.

So it’s a very valuable parameter and you can see all of the different angles of the heart — your atrium, your ventricle — to see how it performs from an electrical standpoint.

EL KALIOUBY: Amazing. So that’s one. And then you said temperature.

RODRIGUEZ: Yes, so temperature — we have it in the right location, and for many years we’ve done ovulation tracking right under the armpit so that you can get those trends. But it can also give you information about your metabolism. It can give you different information in terms of inflammation parameters if you correlate it with the right data. But this is talking more big-picture multimodal.

EL KALIOUBY: But how is BloomerTech’s bra different than the array of other wearables out there? We’ll get to that after a short break. Stay with us.

[AD BREAK]

Copy LinkWhat makes smart bra data different from consumer wearables

EL KALIOUBY: I wear a Whoop sensor. You kind of started to allude to that. How is the data collected from Bloomer Tech different than just say a Whoop or an Oura ring?

RODRIGUEZ: I think it’s very complementary, but we’re just using it for different applications because the physiological signals that we’re getting from our device are meant to be used for medical-grade capabilities. So the resolution of the signal is higher because of the location, right? Like when you have sensors too close to each other, the measurement is really of that point of the body. When you have them a little bit farther away, you can get better resolution of what you’re reading. So it’s complementary because our goal is to go more into the diagnostics and clinical side for women that are at risk or have already been diagnosed with heart disease.

EL KALIOUBY: Interesting. What are some of the limitations of what this bra can collect today?

RODRIGUEZ: For us we’ve designed it in a way where we can collect data in a dynamic format, and the limitations come with the battery, right? Like the higher sampling rates, the more you reduce the battery capabilities. So finding that sweet spot of what — especially when we run clinical trials — what’s the sweet spot of sampling data that you want to get that will get you to the algorithm that you want to develop? I think those trade-offs are the ones that you have to make good decisions on.

EL KALIOUBY: Presumably you wanna have longitudinal data, you’re tracking this data over the course of the day.

RODRIGUEZ: Yeah, exactly. But for example, for ovulation tracking, do you need to track it 24/7? Probably not. You don’t need that huge of a sample, right. For other things you might want to have continuous data. So we also have bio impedance, which is a very interesting sensor because it allows you to look at all of the layers of your body in terms of fluid — like sweat on the outer layer — all the way inwards to look at fluid retention in your lungs, right? So there’s a lot of information there too.

EL KALIOUBY: So that is interesting. When I first started at MIT and we started our company, we were measuring skin conductance as a measure of arousal off the wrist, and we experimented also measuring it off the sternum. Is this the same kind of signal that you are measuring as well?

RODRIGUEZ: Yes. I think that one was galvanic skin response. It’s similar. It’s very similar. Like the methodology of acquiring the data is definitely the same. It’s more of how much you’re measuring by inputting different currents and then how you’re doing the functions at the end to make the measurement.

Copy LinkThe engineering challenge of making wearable health tech practical

EL KALIOUBY: Fascinating. So I wanna double-click on some of the design considerations to build this into a bra. And I guess the first thing you have to figure out is how do you build flexible and washable circuits? That must have not been easy. I’m guessing this is part of your patented technology. Can you say more about that?

RODRIGUEZ: Yeah, so the interesting part of that is a combination of materials and being very clever on how you connect different technologies. So before coming to MIT, I worked for six years in the semiconductor industry. I think that gave a little bit of insight into what you can and cannot do, and how to ensure that you can combine different materials to ensure that this works optimally.

I think the flexible circuit revolution was also happening at that moment, where it was finally lower cost and more accessible to make at scale. And that was a very big thing. And then our sensors stack — the way that we build those sensors with textile fabric and ensuring that it was a combination of semiconductors and fabric — so that it could acquire good amounts of data.

But we had a lot of combinations, a lot of ideas, and then we just saw what performed better.

EL KALIOUBY: So if you’re measuring things like bio impedance for example, how does sweating and exercise and movement come into play? Like that must be another design consideration.

RODRIGUEZ: Yes, definitely. For things like electrocardiogram, sweat and all of these things — when it’s a dry sensor, it just makes the signal much better and less noisy. So it’s actually pretty good when we find people that are sweaty.

EL KALIOUBY: Huh?

RODRIGUEZ: It’s definitely better than having dry skin in that case.

EL KALIOUBY: Yeah. And then how do you design for things like varying sizes and even color, right? Like, I don’t know if you’re gonna compete with Victoria’s Secret, but how do you make this both comfortable and, yeah, something the woman would wanna wear?

RODRIGUEZ: Even though Victoria’s Secret is a huge market, we would prefer to partner with them than to compete with them.

EL KALIOUBY: If anybody’s listening from Victoria’s Secret, reach out.

RODRIGUEZ: Yeah. So definitely the way that we designed it is to be more of a medical device than to be a consumer device, right? Like our application pipeline is focused on clinical decision making.

Rather than health and wellness. So the way that we designed it is to be much better than the current patch monitors — those stickers — or better than Holter monitors.

Right. That’s kind of the thought process. Something that can be comfortable, that she can wear every day of her monitoring session because she usually has a doctor following her session, and it won’t interfere with her day-to-day activities. Right. Like she can wear it as she would any other bra. And over time in these design considerations that you’re asking, we learned a lot about different preferences in terms of bras across different ages, and we realized that we are not going to be able to build one bra that everyone likes. So we designed it in a way where you can basically connect it to any bra of her preference — a wireless bra, a tank top to sleep in, a sports bra, a surgical bra, right? And that’s why we call it the Bloomer Tag, which — “Tag” is the acronym for Tech Augmented Garment — so that we can augment the garment of her preference.

Copy LinkWhy clinical validation comes before consumer scale

EL KALIOUBY: Very cool. I’m quite intrigued by your go-to-market strategy. It sounds like you are not going direct to consumer and this is more of a clinical-grade product. Did you consider going direct to consumer? And if so, tell us more about how you made decisions around what market to focus on.

RODRIGUEZ: We want to improve our outcomes and the way for us to get there is to ensure that we are clinically validated along the way, and eventually we’ll be able to open more health and wellness channels.

So some of the cardiologists that we’ve been talking to, who are experts in AI, they’ve been saying we have the models now, we just don’t have the data. So that’s kind of the piece that is missing. So we were sure that we wanted to bring good resolution, high quality data into what we’re building, and controlling the quality, making a regulated device — talking about your trifecta, AI, sensors in women’s health — we added the regulatory side to it.

EL KALIOUBY: If any of our listeners wanted to get involved in any of these studies or even potentially partner with you, what would that look like and how should they get involved?

RODRIGUEZ: Yeah, so the easiest way to connect with us is through our website at bloomertech.com. There we have a form. If you want to use our devices in your clinical studies or you want to be a subject in one of our studies — whether you have already been diagnosed with heart disease or have a family history of heart disease and you want to participate in those studies — that’s a good place to sign up.

Copy LinkHow AI turns raw cardiovascular signals into actionable insight

EL KALIOUBY: Amazing. Okay, so we talked about the sensors, the data. Let’s talk about AI. How are you incorporating machine learning in the bra, and what does that look like? Give us some examples.

RODRIGUEZ: Yes, so in the early days, one of the things that we realized, especially with ECG, is that for a long time we’ve been using unsupervised learning for a lot of things.

EL KALIOUBY: Two main approaches in machine learning. One where you have supervised, and basically you have a ground truth labeled data set that you use for training and validation. And the other approach is unsupervised, where you don’t have the labeled data.

RODRIGUEZ: Yeah. And you allow the data to gravitate towards each other to make definitions around it, right? So in digital signal processing techniques, right, like when you use things like blind source separation — if you think about right now with the microphone, there’s one source of my voice, but if I have three microphones with all of that data, I can separate what is noise from what is actually my voice very easily. So for us, in the way that we decided to use AI in our devices, it’s a combination of things, right? So there’s a thousand AI algorithms cleared by the FDA. Out of those, the majority are in radiology. Number two is cardiology, right?

EL KALIOUBY: So what are examples of these cardiology-related AI algorithms that are FDA cleared?

RODRIGUEZ: So examples include arrhythmia detection, right? So to detect a tachycardia, bradycardia, AFib, right? The newer ones I would say have to do with aortic stenosis and left ventricular ejection fraction, which is when the heart doesn’t pump enough blood to the body. So it’s an early indicator that you might develop heart failure, and you can detect that from ECG data.

And now you can detect sex from ECG data, right? Like just with the ECG, something that the eye wouldn’t recognize — it has 97% AUC, you see?

EL KALIOUBY: Which is area under the curve accuracy, basically. Score.

RODRIGUEZ: So it’s very accurate at detecting whether the ECG is from a male or a female.

EL KALIOUBY: Yeah, is the idea to create like real-time intervention? So you’re wearing this bra and say you’re about to have a heart attack. Does it detect this in real time? And does it give the user an alert? Does it alert a doctor? Tell us where the data goes and how it’s being used.

RODRIGUEZ: Well that use case, I see it more as a future scenario where we have machine-to-machine communication and the device will be able to talk to another device — to send someone to do CPR if she’s going to have sudden cardiac arrest, or something similar, right? Like I see it more on that spectrum, but the use case for our device right now —

Like we start with cardiac monitoring, which is more traditional, so that we can use the existing pathways. But we envision a world where, for women that are at risk or diagnosed with heart disease, she can have this in her closet. If she’s having symptoms, her insurance would cover her wearing it while she gets the appointment with her cardiologist.

Especially for women with chronic conditions and women that want to prevent a recurrent episode after she already had a procedure.

Right? Like you can have this in your closet, you can have it accessible and you can collect very valuable data to prevent a secondary event.

EL KALIOUBY: Amazing. So for now, it’s a data collection device to kind of enable your doctor to see what happens between doctor’s visits, and hopefully be able to provide better intervention.

RODRIGUEZ: For now, but the big picture is generating all those new digital biomarkers that are specific to women because there are heart diseases that are predominant in women that we’ve known about for a long time. And we believe that most of the devices that exist today have been designed around signal and pattern recognition around traditional diseases that affect men more. So that’s why women are having worse outcomes. Like now it’s a good time to develop this next generation of ways to detect these patterns for diseases that have been under-recognized for such a long time.

EL KALIOUBY: After a short break, Alicia and I zoom out and talk about the potential of AI and personalized medicine as a whole. We’ll be right back.

[AD BREAK]

Copy LinkThe future of personalized medicine for women

EL KALIOUBY: I just love the idea of wearables that empower people to really be the CEOs of their own health. I wear a lot of things and it helps me track my sleep and my physical fitness, and at some point I wore a continuous glucose monitor. So I kind of imagine a future version of the world where I have an AI co-pilot for my health. I don’t think we’re there yet, but it sounds like that’s kind of part of your vision as well, like this idea of personalized medicine. So talk more about that.

RODRIGUEZ: Yes. Well, I like to call it deep phenotyping, right? Like now that genomics has advanced so much and we know more or less what our genetic predispositions are, but we know that lifestyle and environments are going to be a huge factor in what gets triggered and what doesn’t in that genetic coding.

And for me, that’s how deep phenotyping comes into play, because the more you know about yourself — and to your point, personalized to you and what those signals look like and what’s doing you good, right? Like for some people, coffee is great. For some people it might not be that great and give them stomach pain.

All of these different things that make each of us unique individuals, even though there’s a baseline where we’re very similar to each other — I think that’s where we are going to be, because we’re going to have those unique data points from different stages of your life, especially in women. There are three very well-known stages of her life across her spectrum, right? Like either she’s menstruating, she might get pregnant and go through pregnancy and postpartum, which is another life stage, and she will go through menopause, right? So all of those stages require different data sets across the spectrum of your life and how your body will respond to different things. And I’m a big believer in digital therapeutics and everything that we will be able to do by understanding our data better.

EL KALIOUBY: Yeah, and I love this particular kind of spotlight on harnessing data, AI, and wearables for women’s health. One of the areas that I personally would love to have is like a hormone tracking wearable that measures my hormones longitudinally. Is this something that you’ve thought about? What other kinds of innovations do you have your eye on as it relates to AI and women’s health?

RODRIGUEZ: Well there’s a lot that we have our eye on in terms of women’s health that we believe are directly correlated to the heart. So if you think about the heart, it is very smart in how it will direct blood to your body depending on what is happening. If you get pregnant, your cardiac output will increase significantly by 30 to 40%, right? Like the heart is probably the first to know.

EL KALIOUBY: Huh.

RODRIGUEZ: More than anything else, because it starts building everything required for the baby to grow there. There are other things that we believe, right? Like if you eat something, your metabolization and your body temperature change in response to things you eat.

So in terms of hormones, there’s a lot of studies that show how in your follicular phase or your luteal phase, right — before and after ovulation — your heart rate variability changes. So there’s a lot of information that is very rich to the heart, very well connected to our cycles. Because our cycles are a pattern and not everyone has the same 28 or 21 day cycle, right? That’s a standard that has been used for a long time. But even from month to month or from age to age, you could be different. So the amount of information — I believe what we’re going to be able to do with this is going to remove a lot of invasive interventions that we have today in women’s health, because we’re going to be able to connect the dots non-invasively.

EL KALIOUBY: Yeah, and I honestly believe that it will create new insights. Like there’s just so much confusion and lack of understanding. I’m gonna particularly focus on perimenopause, right. I feel like there’s not enough objective data out there on what to look for and how to use all this knowledge to really advance your health and wellness journey. So I’m excited to see what comes out of this space.

RODRIGUEZ: And it’s very interesting because I’m obviously not a cardiologist, right? But I have fortunately been exposed to many of the experts. And when they tell you we are at the infancy of understanding female cardiac health, it resonates, right? Because there are so many interconnections there that we really are going to be able to do a lot if we create a data set like this.

Copy LinkBuilding trustworthy AI with privacy and human care in mind

EL KALIOUBY: Yeah, you know, you are probably collecting the world’s largest longitudinal cardiovascular data set for women. One of the things we talk a lot about on the show is how to do this responsibly and how to think about trust and data privacy. So can you share a little bit more about how Bloomer Tech thinks about all these considerations?

RODRIGUEZ: Yes. I think you have to be very intentional about the type of company that you’re building and understanding the limitations of certain areas that as a company culture and value you’re going to set, right? So when you start, even from the hardware design, when you start thinking about cybersecurity —

Because of the type of product that you’re aiming to be, you have to think about what are the implications of different communication protocols that you put in, and what you allow in the firmware for others to do with this, right? Like, how can this be hacked or not? If you can hack it, then everyone else can hack it, and you have to try to hack yourself.

So I think you have to be very intentional since inception about how you’re going to get the data, how you’re going to store it. Of course, if I had all of the money in the world, I would build my own data center, because I think this is very valuable data, but we follow everything that we know is good practice, which is ensuring that since the data collection, the device only has a device ID. We never connect it to the patient name or anything, right?

Like we will not connect.

Depersonalized — it’s just data from a wearable device that doesn’t have a connection to her personal information, and that’s stored separately. We are intentionally building to get information from things like blood work and imaging, right? Because we are working with people that are already diagnosed or are at risk and have gotten many tests.

And this is very valuable for the future of what we can do with women’s health. So explaining to people what we’re doing is very important. If you want to participate, you can participate, but we’re not forcing you.

EL KALIOUBY: So, final question. I think about this question a lot because I spent my entire career really thinking about how to humanize technology before it dehumanizes us. So my question for you is, what do you think it means to be human in the age of AI?

RODRIGUEZ: You know, I think that AI is going to give us our humanity back, because I think for many years people have been following what their software says. When you think about the future of AI and the way I think about humanity, right? Like if you think about the doctor and having this release of the keyboard, because now they can spend more time with you. They don’t have to spend so much time taking notes and all of that. It brings a little bit of that humanity. I’ve even heard that because the AI takes notes for them, the AI makes them reflect on things like, you were missing this — why didn’t you ask this? So they learn a lot from the AI because it recognizes patterns and it makes each of us better, and it gives us more time for each other. I think it’ll give us more time with our loved ones, with our team members, with our families. I think it will be great to get humanity back.

EL KALIOUBY: Wonderful way to end this interview. AI will bring our humanity back. Thank you so much for joining us on this show, Alicia. It was really fun.

RODRIGUEZ: Thank you. Thank you so much for having me. I really had fun too.

EL KALIOUBY: I totally agree with Alicia: that AI will bring back our humanity. And personalized medicine is one of the strongest places where this will happen.

And in particular, I see so much potential in women’s health and AI. Women’s health is woefully underfunded. Like Alicia said, historically women were excluded from clinical studies. Sure, that’s changed, but there’s still a HUGE gender gap in healthcare.

And while women live longer than men on average, recent studies show that women have shorter healthspans – which is basically the number of years a person lives in good health.

So there’s still lots of work to do. This is where AI can come in. I believe the trifecta of new sensors, data and AI will create new solutions for women’s health. AND it presents a massive economic opportunity.

This is our first episode on AI and women’s health … but it definitely won’t be our last.