Episode 15 Transcript: Exploring the Role of AI in the Fight Against Cancer
There’s a Lesson in Here Somewhere Podcast
Episode 15 Transcript
Guest: Despina Kontos, Professor and Cancer Researcher at Columbia University
There’s a Lesson in Here Somewhere is a podcast hosted by Jamie Serino and Peter Carucci that features exceptional people that have compelling stories to tell. Whether it’s a unique perspective, an act of kindness, an inspirational achievement, a hardship overcome, or bearing witness to a captivating event, these are stories that must be heard, and from which we can draw important lessons.
AI’s Role in the Fight Against Cancer
In this episode, Jamie Serino and Peter Carucci speak with Dr. Despina Kontos, a professor and cancer researcher at Columbia University, to explore how artificial intelligence is transforming cancer research and patient care. From her roots in engineering to her pioneering work in medical imaging, Dr. Kontos shares how AI is moving from simple computer vision tools to sophisticated predictive analytics that are already saving lives. The conversation dives into the real-world challenges of bringing AI into clinical settings—from legal concerns to integration into existing medical workflows. Dr. Kontos also weighs in on the role of the private sector in driving innovation, the potential of democratizing medical technology to improve access, and why personal responsibility and preventative care are more important than ever. It’s a thought-provoking look at the intersection of technology, medicine, and human decision-making in the era of AI.
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Transcript
Intro
00:02
Welcome to there's a Lesson in here Somewhere conversations with interesting people with fascinating stories to tell and from which we can draw important lessons. Here are your hosts, Jamie Serino and Peter Carucci.
Jamie Serino
00:17
Hello and welcome to. There's a Lesson in here Somewhere. I'm Jamie Serino.
Peter Carucci
00:22
And I'm Peter Carucci.
Jamie Serino
00:23
And we're here today with Despina Kontos, a professor and cancer researcher at Columbia University, and we're going to talk with her about her research combining artificial intelligence and medical imaging. It's really fascinating, Despina, welcome.
Despina Kontos
00:39
It's a pleasure to be here. Thank you for having me.
Jamie Serino
00:42
Yeah, thanks for joining us, Despina. Why don't you start off by just telling us a little bit more about yourself?
Despina Kontos
00:49
Sure. So, as you said, I'm a professor at Columbia University. I have a background in computer science. You may be wondering what a computer scientist is doing in a medical center. I'm trying to basically combine computer science with medicine and, especially in this time, use artificial initiatives for the medical center at Columbia University more broadly. And yeah, it's exciting, it's fun, it's been a great career so far and been doing this for many years now. I was at the University of Pennsylvania before joining Columbia in 2004, and now I'm here in New York.
Jamie Serino
01:46
Great. So you've been sort of at this for a little while and in some ways ahead of the curve, but I guess in some ways with the curve, because we heard about artificial intelligence and then we sort of stopped hearing about it and now of course it's everywhere. Yeah, it's everywhere, right, and so maybe you could tell us a little bit about you know some of the history and you know how you got into it, what excited you about computer science and then how you got into AI, how you got into the medical field as well.
Despina Kontos
02:15
Sure, sure. So I grew up sort of like with a screwdriver in my hand, so to speak. I was one of those kids who liked to figure out how everything works and fix everything in the house. And you know, if anything broke in the house my mom would first ask me to see if I can fix it, and if I couldn't fix it then she would call the plumber or the electrician or whoever right. So I always had a knack for engineering. I was also always fascinated by medicine and biology and I just always had like a natural curiosity to figure out how things work, you know, in the physical level and the mechanical level, like since I was sort of very little Influenced.
02:54
I guess both my parents. My dad was a mathematician, computer scientist, who you know started I grew up in Greece, a company there, so a little bit of an entrepreneur as well. My mom is a medical doctor and neonatologist. You know I was always influenced by her as well. But I could never see myself dealing with little kids as my profession. I'd like I am not becoming a pediatrician, that is not happening you know, but I was equally fascinated by both.
03:20
You know, I grew up in the dinner table hearing stories about, you know, medicine and little kids who were in the NICU and what it took for doctors to revive kids who were, you know, at danger, and also innovative technologies from my dad and being, you know, naturally inclined and curious about how things work. I was kind of always torn between the two and at some point and you know, when you, yeah, we'll get to the point that we decide what we actually want to do with our lives. In college, you know, and things like that, I thought to myself, well, if I go to medicine, that's going to take forever, right, Like I have to go to regular school, then medical school, then residency, then fellowship Dude. It's going to be like such a long time until I'm out of school and I have a regular life, Right, and I have like a job and a salary.
04:07
So I said, if I go to engineering, I think life's going to be quicker.
04:09
You know, I can just like plow through, be done and be good. So I went to engineering with the intent to kind of work with my dad at the time who was having a business in Greece where I grew up, in Greece. Where I grew up, and one thing led to another and I pursued sort of graduate work in the US, at which point during my PhD I had a fellowship and in order to keep the fellowship and the financial assistance that came to it, I had to be involved with research. I had to help my professor who I was doing my PhD with, you know, in his research lab and still my plan was to go back and do the business and the whole Greek thing and everything. But it was.
04:51
You know, when I started getting involved with research, it was the sort of first time in my life that I kind of felt on my own, without sort of third-party influences that. You know, this is what I want to do when I grow up and the research that my professor was doing was related to medical imaging. So the fact that it brought in medicine that I was always fascinated by and I didn't really have to go to medical school to do it. Well, I could still follow my natural kind of tendencies in engineering and my you know natural curiosities around those lines. I really felt like this is what I want to be when I grow up, so to speak.
05:30
One thing led to another. You know kind of opportunities came up. I finished my PhD at Temple University in Philadelphia, went to University of Pennsylvania to do postdoctoral training you know here where I was not wanting to go to med school because I've been in like school forever and I kind of maxed out like everything you know like in terms of being in school. And and then I joined the faculty at Penn and started my career there as an independent investigator.
Jamie Serino
06:02
That's a really cool path. It was cool that you were able to combine the two things, or that you were pursuing one thing and the pull of the medical piece of it kept drawing you in.
Peter Carucci
06:16
Yes, yeah, no go ahead, Peter. No, it's just. I'm really fascinated by how okay I see how both sides came together in your formation. Now, how did we land on AI? How did that become your focus?
Despina Kontos
06:34
I studied computer science that's my undergrad computer engineering and informatics in Greece. I did my undergrad there and then when I came here the PhD was in computer and information systems. So I was a computer scientist by training and you know there are different directions one could take in that field. There's more of a hardware kind of expertise, there's more of a you know, all kinds of different aspects. But the work that my professor was doing and I was kind of attracted to had to do more with software and image processing, medical image processing, and so we call it AI now.
07:11
But really this field has been around for a very long time and in the field of medical imaging, you know we used to call this like computer vision, pattern recognition, medical image analysis. But a lot of the fundamentals of what we call now ai used to be there. Like my first book around neural networks was in fact in my undergrad in greece and it was written in greek. So it's been around for a long time. So when you're in this discipline you kind of choose a direction. You want to be more hardware focused. So I was thinking like, do I want to be making computers, you know, and things like that, like hands-on, as a computer scientist. There was a big direction at that time was the beginning of the internet, you know, and all that stuff was like network. You know network protocols. How does you know what gave rise to internet and bandwidth? Do I want to, you know, be the kind of person who puts together wires and things about network architecture like man?
08:03
not really so I like this was a little bit more um, at least for me. Oh, I could totally see myself going in the hands-on direction because I really, really love the screwdriver. You know, experience, um, uh, this was kind of that combined, the sort of more scientific uh pursuit, so to speak. You know, you know there's engineering and there's science and there's an overlap, right, engineering is a little different than science. I think this allowed me to also pursue scientific inquiry in addition to engineering, and I always had that as a person. I was driven by figuring out how things work.
Peter Carucci
08:45
And now you're taking data points right. As a person, I was driven by figuring out how things work. And now you're taking data points right systemically and also from medical imaging, and you're making predictions, and so the software you've developed makes these predictions.
Despina Kontos
08:58
Yes. So basically I do a whole bit of different things. So my fundamental expertise as a computer scientist working in imaging and medical imaging is to take medical imaging data so CAT scans, mris, x-rays, you name it everything and develop the computer science algorithms, the techniques to analyze this data, to extract information from this data, information that's not routinely assessed by the clinician, right, so we can quantify things, we can measure how big is your hippocampus you know in this field, you know me and cancer. We can identify where is a cancer, what type of cancer it is, how big is the tumor, the volume, whatever, all kinds of other properties, and develop the algorithm so that the computers can do that automatically. That's like my fundamental bread and butter expertise. Now, beyond that, what I became fascinated, what do we do with this information? Right, you can calculate all kinds of things from the data. I'm excited to kind of try to predict what will happen in the future. So I'm not as focused about, like the now, the diagnostic piece. I mean that we have radiologists, we have doctors, they do that pretty well. I want to be able to like predict what will happen in the future and use that information to better tailor your care now.
10:22
So, if you are a healthy individual, are you at high risk of developing a certain cancer? What are the implications of that? You know. How do you? What can we do to prevent, to reduce your risk? What can we? How should we screen you if there's a cancer, that screening is available? If there's a cancer that screening is not available, can we use this information to say maybe this is a good opportunity to start thinking about how do we screen these individuals that are at high risk, for example, ovarian cancer, which is an area I'm working on right More recently, there's no screening for women for ovarian cancer. Why is that? Okay, there are a lot of reasons why, but can we use some of these technologies to maybe enable that? There are some questions, right.
11:03
If you have a cancer, how likely is it to come back? How likely is it to recur? What's the timeline? Based on that information, how aggressive do we need to go with treatment? And if you are in treatment, are you responding? Will this drug help you fully respond or not? And if not, what could be other drugs that we could add in the equation, right?
11:24
So I'm interested in predicting the future and in doing that, you know we use computer algorithms and artificial intelligence now to get information from the imaging data, but also plug in other data, because think about it right, when you go to a doctor, oh, you know. Good morning Jamie. What's going on today. I have this. I have that. I have this heart in here. Whatever I did an x-ray, I did this.
11:44
So the doctor will take this information. They're going to look at the x-ray. They're going to ask you a question about how you feel about things. They're going to look at your family history. They're going to look at what medications you take. They're going to look how old you are. It's going to be a different thing if there are a bunch of comorbidities they have to think about. So I use artificial intelligence to basically do that collect all the data, weigh the pros and cons and come up with a prediction that is tailored to your individual needs. How do we need to treat jamie today based on who jamie is today, versus how do we need to treat Peter today based on who Peter is, even if they have the same exact thing? You know what I mean.
Jamie Serino
12:28
Yeah, and so right now, a lot of the information exists in silos. Yes, there are portals now. One doctor sees a test from another doctor and that's helping. But what you're trying to do is have AI begin to process all this information, yes, and then always have it there. It could be in the portal or in some report or whatever, and then better action could be taken.
Despina Kontos
12:54
Yes, and make it better for them. Make it easier, you know, because really, in this day and age, how much time does a doctor have when you go see them, right? Not that much. So I want to do the uh, I want to do the laundry for them, have everything ready, right? So when you go there, all this information is on their fingertips and they can better make decisions, uh, for you when you are at the point of care. That's the goal, you know.
Peter Carucci
13:18
That's what we aspire to do with this research you know, I, I my my brain is like coming up with a bazillion questions for you, but the one that I'm very fascinated to know is without you don't necessarily have to reveal too much, but have there been certain circumstances where this data has been really, and your use of AI and the data has been really instrumental in saving lives? And are you willing maybe you want to share a story or two without going too much? Or is it more a general overarching thing that's happening?
Despina Kontos
13:58
Yes and no. You know we're in the early days, right. We have not yet materialized the impact that could be done for a host of reasons, not necessarily because we don't have the technology for legal implications, for workflow implications, for cost implications, for insurance implications, all kinds of things. I could talk about that forever. But there are circumstances where AI is helping today to make things better.
14:24
Where AI is helping today to make things better, for example, there are tools that a neurosurgeon can use to visualize the tract of the brain when they're doing a surgery, for example, to extract a glioblastoma or another type of tumor in the brain. There's one thing to do the extraction, but the thing is what's the collateral damage when you do that in the brain? There's one thing to do the extraction, but the thing is what's the collateral damage when you do that? So, by trying to extract a tumor, are you going to you know damage, like language, you know are you going to damage other function based on where the tumor is Cause you have to go in there and cut things to get tumors out Right. So you can use AI to take pictures of the brain, you know, before the surgery, map the tracks of the brain, label them for their different functionality and live process during the time of the surgery, guide the surgeon on how to do the surgery as best as possible, minimizing the potential damage right.
15:19
There's AI that can, for example, in one of the areas I've been working on is predicting the risk of developing breast cancer using information from images such as mammographic density and family history and genetics. Combining that information and that can help inform women to seek screening more frequent screening, for example, for high-risk women, supplemental screening with additional imaging techniques such as MRI or breast ultrasound and so forth. So in radiation treatment, you know, ai and computer guided techniques are helping focus the radiation treatment as much as possible in the area of the tumor where sparing other organs from the collateral damage of radiation, because you know, so there's a lot of applications that are being used.
16:07
We can predict which patients in emergency care or in the ICU may develop sepsis and how to monitor these patients more closely. There's a lot of applications and I think more and more applications will be coming out in that aspect.
Jamie Serino
16:23
I think more and more applications will be coming out in that aspect, and so to what degree are you working also, then, with the hospital? Very closely and any of your work, is that starting to make its way into use?
Despina Kontos
16:39
Absolutely very closely and that's why sometimes a lot of my colleagues ask me. Sometimes a lot of my colleagues ask me I'm a computer scientist and my employer is a radiology department. I work for a radiology department. I'm not in engineering. I don't teach classes. I don't teach computer science. I don't do any of that stuff that a traditional computer science professor would do.
17:04
So I'm a little bit of a hybrid and a bit of an outlier in my field. It's exactly because of that reason, because I want to be in the source of the data and I want to be in daily interaction with clinicians. Otherwise my work is, you know, it will keep me going, It'll give me publications, it will give me, you know, what academics need to get promoted and whatever, but like it's not going to make a difference in anything. So that's another thing. I've always been driven as a as an individual, you know, seeing life a little bit from a more kind of philosophical perspective and try to find meaning meaning in my life. You know, for me making an impact is a very important aspect of how I find meaning in my life, and so through my work, through my, you know, online I don't like compartmentalizing my life either very much Like I don't smell it, it's like, oh, this is my work life, this is my home life, this is my this life, this is my other life.
Peter Carucci
18:01
You know my life is my home life, this is my this life, this is my other life. You know, my life is my life.
Despina Kontos
18:03
There's one life. You know I have one life and it's here and now, and my drive since again this also were some of the things I've always felt very strongly, since I was a kid has been to make a difference. Like you know, when I'm gone, is it important that this being was around or not. That's important to me.
Peter Carucci
18:27
It's a very healthy outlook. Do you see just changing gears a hair? It's strange. I want to know your predictions about what AI will be predicting for the future. Ai will be predicting for the future. How much AI will be incorporated into the medical field compared to where it is right now? Do you see it like trajectory, going like sky high everywhere, or is it still a balancing act? I'm very fascinated.
Despina Kontos
19:04
In general, in our life, in this society, AI will take over fully. It's a tsunami. It's happening and we haven't even gotten into quantum computing yet. Wait until we get there.
19:19
I don't know if our generation will fully see the fruition of that, I think our kids for sure. It's going to be nothing that you've ever imagined. I think A complete revolution, like the industrial revolution. It's going to be a completely new era. Healthcare, I think, is going to be one of the areas that's going to be most resistant. It will know it will penetrate, will take a while. I'll tell you why. Because of all the legal, insurance and workflow considerations, right? So let's say I have an AI tool, right? Let's say I have this tool, which I have it. I make it freely, publicly available for anybody to use it. You can download it, use it at your home if you wish, that can measure your mammographic density from a mammogram and can tell you some you know information about the risk of developing breast cancer. Let's say I have it. Okay. Let's say I even make it free available. Let's say we put it in the hospital.
20:10
First of all, you have the FDA approval. It's all of that. That landscape is evolving, you know all of it. But that's I'm not in that business. I'm not in the business of FDA approval. So someone has to get it, somebody has to be interested in, like a company or somebody picking it up. You know there's a caveat with FDA that if it is within our homegrown environment we can put our tools in. So I'd say, at Columbia I can put it in, but I can't put it at like other hospitals, right? Okay, let's say somebody picks it up.
20:38
Let's say we solve that problem, which is a big problem. Who's going to pick it up and actually do that kind of path to commercialization, translation, fda approvals, all that stuff, figure that out, ok. And let's say that the tool is even fully validated, because when I'm in the lab I do my discovery on a certain population, a sample size. You know I don't do it to the universe, right? So if I'm going to use it for the entire US population or Europe or Asia, who knows where it's going to go, you know we need to do more work to to make sure it works for that data as well. So let's say we solve these problems. Let's say we also solve the problem of a commercial partner being interested to pick that up and move it forward. Ok, which are all? Those two are pretty big problems, right? So let's say we solve them.
21:23
Then we get to the hospital. A health system is a financial institution, right? So there are a ton of implications. So let's say I'm the doctor and they give me this tool. This is going to take me more time to do my job because I have to do my assessment and then I have to check in what the AI tool says and I have to wait with my assessment and I have to figure it out. So if it takes me five minutes a minute I don't know how much to read a mammogram, it could be that this will double the time that I need to do my job.
21:53
Okay, what does it bring in? Does it reduce the workload that I do? Let's say it says something right or wrong. Who takes the legal liability? Who's responsible? Is it the doctor responsible or the AI tool or the hospital? How does insurance play out If I'm a doctor with AI?
22:10
Does insurance compensate me more because I use the AI and I spend more time doing my job and blah, blah, blah, or it doesn't compensate me. Does it bring more business in the hospital or less business? So there's so many questions. How much is the license? If the hospital is going to pay X money to get a license for all its doctors to use my tool, that's a lot of money. How do they make up for it? What is the return of investment for them to use these tools?
22:35
And I will say, and I say to all my colleagues, I still don't have this answer, and part of me is kind of thankful that I'm not in that business. I'm in the business of, like, the scientific discovery. So I don't, you know, I don't have to worry as much for my day job about this, but I worry existentially, like if all I do becomes a gimmick on the website that somebody can use to have some fun. Like, what are we doing here, right? So? But I keep asking my colleagues who are in the healthcare systems, who are, like you know, cfos, whatever in a health institution, like have you seen an AI tool that has made a return on investment for the institution that adopted it? I do not know yet of an AI tool that has delivered a concrete ROI.
23:24
And I think there's a lot of effort right now, all these companies that are trying to commercialize these things, to kind of measure the impact of these tools within a healthcare system, on patients, on the logistics of healthcare, right, and so until we work that out, I think there's going to be a lot of resistance from healthcare institutions. The appetite is there, but the implementation is just tough, and so eventually there's going to be a lot of pressure in the system because non-traditional I think healthcare systems are going to invade this space. So you know, like Amazon, google, all of these folks like, they see the value and they're structuring healthcare models that are very different than a traditional healthcare system in a hospital and that is going to take away a lot of care from the conventional healthcare systems, I think, because of the AI. So they see the value, because the way the traditional healthcare system is built now it's like a complex, archaic institution. To go there and inject this technology is so disruptive.
24:35
But if you're starting from scratch and you're going with this from the beginning, you say I'm going to use this from the beginning, I'm going to have fewer doctors, I'm going to streamline all the patient communication through it. If you build it from the beginning with that in mind, that's a whole different story. Right, you can make it used to your advantage and you can have, I think, a substantial return on investment from the get-go. And so I think eventually there's going to be enough pressure built up in the system that they will have to go that way to also absorb some of the cost of healthcare that is increasing. There's going to be a lot of changes right now in healthcare insurance reimbursements, and health systems are going to be under immense pressure to become sustainable and viable, and so I think that's where AI is going to come in and catalyze a lot of aspects, and that's where we're going to start seeing the adoption of these tools becoming more broad.
Jamie Serino
25:35
Yeah, that was going to be my follow-up was that what role would the private sector play? And it could just be in upending it completely, you know, democratizing it, so to speak, or, you know, taking an industry that's ripe for change, for disruption, and yeah, if they start from scratch, then they don't have any of those issues to deal with. Going outside of the insurance system, you know, came to mind as well. So, yeah, a lot of different scenarios, so it's interesting that you brought that up.
Peter Carucci
26:05
It's already begun in a way with, like, a lot of online virtual care.
Despina Kontos
26:10
Yes, exactly.
Peter Carucci
26:12
You know, it's cheaper for them rather than you know, and the liabilities are different.
Despina Kontos
26:16
Absolutely.
Peter Carucci
26:17
And it's interesting you mentioned, like if there was a company or an organization that began with this model in mind, it would change the game.
Despina Kontos
26:29
Completely. It would change the game. Yes, what?
Peter Carucci
26:31
about the international approach. I know many countries, like in Europe or around the world, don't have our for lack of a better term capitalist, insurance-based health care. They have health care. Do you see any difference between, let's say, you know European countries adopting this kind of AI or other countries around the world, or are we the leader here and it has been coming out of this area?
Despina Kontos
27:02
I think Europe, specifically from what I hear, the regulatory framework is even more complicated than here, I'm not seeing it coming out of Europe.
27:10
I don't know about Asia, though I think there's a good chance they could be more innovative than we are in that sense because they need it, and there's also they don't have as many doctors as we do, and so they look up to some of these technologies to help alleviate some of the problem the fact that they don't have enough physicians to take care of everybody. So I'm not sure, but I'm not seeing it coming out of Europe, in my view.
Peter Carucci
27:38
I think here will happen eventually.
Despina Kontos
27:41
Here will happen, you know, within the next like five to ten years, and then I think when that starts happening, we're going to see some more advancements from quantum computing and then everything we know will be different. I mean, that is going to be the real revolution. If I was a student now, that's what I would be doing my PhD.
Peter Carucci
28:06
What makes that so special, I guess, compared to where we are, everything you know will be different.
Despina Kontos
28:12
Everything you know, everything we have known about computers will collapse and change. So quantum computers are based on the principles of quantum physics, and I'm not going to go into all the details of it. But basically what quantum physics is telling us is that not more than one states are possible to exist at the same time between matter and energy. Regular computers are based on the binary logic.
28:46
You know whatever we do in the computers, programming however you want to call, when you go down, down, down, down, down, down to the chip level, it's all zero and one. That's it on or off. Zero and one. In your interconnection of hardware, whatever all the software, we do everything. When it boils down, when it breaks down to the hardware level, it's all all zero and one. But that's not going to be the case anymore, right? And that is the fundamental limit of how much computers can compute, because at the end of the day, it's all zero and one. You can be both zero and one at the same time, but now at the hardware level. But now at the hardware level, you know, zero and one can coexist at the same time and multiple calculations can be happening at the same time. So you know, things that would be computationally not even possible could happen in minutes or seconds, you know.
Jamie Serino
29:44
So this is going to blow up everything as we know, completely blow up everything as we know.
Despina Kontos
29:46
I wish I was around to see it.
Jamie Serino
29:47
I don't think we'll be around to see it, but I wish I mean it definitely is discussed a lot, but I guess separating the hype or the sort of future outlook of it versus the reality of it. But I know a lot of companies are preparing for it and working on it and they keep saying it's going to happen soon. But then to your point, how long would it then become more mainstream? Et cetera, et cetera. But then I just read an article where there would be a concern even about the electrical grid.
Despina Kontos
30:15
It's going to be the same.
Jamie Serino
30:16
Do we have the electrical grid to actually support all that?
Despina Kontos
30:21
Well, things will change. Once upon a time, a computer was an entire room and now it's in your pocket, right, so we will evolve. You know it's going to be disruptive, everything you know. It's just.
Jamie Serino
30:33
That's the nature of human evolution you know, not the first time, not the last time that something like that happened yeah, and and do you see, like even some of the medical technology making its way into the home? Like, I definitely see the cons and the danger of this, but could someone you know give themselves an X-ray or give themselves some sort of scan? Right, it's a part of maybe a household piece of equipment or something.
Despina Kontos
30:59
I think, so I'm all for it. You know, don't tell me there's no danger of being in the hospital. You go with one type of thing and you come out with five others, right. So there are dangers in both. Wherever there's human nature involved, there are risks, because, in my view, we're the ones who always mess up everything. But yeah, I think all these things will happen, absolutely. I'm excited for it.
Jamie Serino
31:27
Yeah, I mean cause that's really. It's like democratization. You see, this access to things and you know, down to the individual level, um is just what has been happening over and over and over again. Um, so you, you brought up um scanning and trying to predict. So we talked a little bit about using the AI to sort of draw all this information together, doing the laundry for the doctor, you know, as you you were saying how about, like, scanning and using, you know, predictive metrics and doing some sort of preventative treatment? Like I do not have a tumor today, but chances are because of my family history. Maybe there are genetic tests also and then maybe now ai is picking up something because of my age or something they have an inflammation in my body or whatever it is. Um, and then all of a sudden, red flag, you, you might develop a tumor somewhere. Like, are you also doing that sort of predictive?
Despina Kontos
32:26
Yes, absolutely Absolutely, and I think it's important to have this discussion, you know, because through interventions, lifestyle interventions, you know, I'm not saying we're going to like totally prevent cancer or whatever, but you know the impact we could have on healthcare by lifestyle interventions. Battling obesity, you know. You know wellbeing, you know, and so forth, hypertension, you know all of these factors that are water, based on lifestyle and some genetics. I'm not like saying just all like lifestyle, but you know, we can have a you know impact on public health.
33:01
That is, could have more impact than you know, for example, all cancer therapists combined right. So, and so I think it's important to have these discussions around prevention and and and, for people to be open to the idea of if, if they want that in their lives, to have that information.
33:26
Like you know I have a lot of discussions with friends or colleagues. I'm like you know, I'm the person who likes to know, right? You know I want to do genetic testing. I want to know what's going on and they're like why do you want to know if you're going to have, like, alzheimer's? Well, I want to know because I want to be on the lookout. For example, right Like there's a whole bunch of therapies now in development. You know preventative things. You know lifestyle interventions. If nothing else, I want to prepare myself. I think it's important to have that information and have these conversations.
Peter Carucci
34:01
You know, as you're saying, that I'm just thinking about a family member I had, who he's since passed, but he had a certain condition and he got a scan back and the doctor said to him hey, I've got good news.
34:18
This measurement did not go down anymore in the last month, and so he celebrated by going out to have the biggest dinner and eating everything he shouldn't have eaten in his celebratory meal. And I said to him what are you doing? The doctor said this isn't in your diet. This isn't in your diet. You're not supposed to eat this. You got to have more broccoli. What are you doing? And he goes hey, I got great news. The prediction came back that I haven't lost any more of that thing. And this is great and it's funny. You can lead the horse to water with a lot of this information, but you can't make that horse make the water. So with humanity, it's interesting that AI can make these predictions and then we may just go in and mess it right up. We might just go in and you know. So do you find that? I mean, do you see that battle playing out?
Despina Kontos
35:13
I see it I don't know if I see it as a battle. You know I'm a huge believer in personal choice and personal responsibility and personal responsibility. You know there's a very good argument of you know the extending life okay, as a concept. You know, I want you to prevent these things and that because I want you to live longer. Okay, how much value does that have to the individual? Maybe, if some person wants to live a certain way, it'll be shorter you know, I respect that, you know or they want to eat this all day.
35:45
They eat all this all day. Like, what can I tell you? I'm just going to give you the information. You do what you feel is appropriate for you to do. I'm not going to tell you, I'm not going to force you to do anything. I'm very against like forcing in that sense. But I do think it's important to have the information and aware, well-informed choices and then if your strategy is an exit strategy, that's on you yeah, I, I think you know there's it, it is, it is on you and, and, I think, different people.
Jamie Serino
36:21
I've heard people say, like you know, the mental health community, that there's actually an overwhelming amount of information now about our health. And you have these sort of biohackers, influencers that you know spend almost every minute of their day doing something that is extending their life, you know, or fighting against your life, you know, and that's that's great. That's one extreme. But then you know, some people that you know maybe have anxiety issues are beginning. You know, am I drinking enough water? Am I exercising enough? Am I getting enough hours of sleep? Am I meditating? Is my cortisol levels too high? Are my cortisol levels too high?
36:59
And so, yeah, there can be an overwhelming amount of information, but I guess then at that point, each person has to deal with it and pick and choose what they want to incorporate into their lives. You know, I guess to that this is making me think to ask the question of, like you know, does this add, you know, an even more overwhelming amount of information to the person? It's just like, hey, the information is there, each individual deals with it, you know, is that what it is, or is there some other you know thing here, anything else that you'd have to add? It is like or is there some other you know thing here, anything else that you'd have to add? To some, to something like like that, that type of future I?
Despina Kontos
37:37
can only speak for myself and my own experience. Right, and at the end of the day, I'm not even a doctor, I'm just a computer scientist and an engineer. I personally like the information. I don't feel overwhelmed by the information, but I think you know one of the things we don't do very well in our society is to teach people in our educational system whatever it's very like how to use their brain, right, we are very kind of like information focused, like you have to learn, learn, learn things, but we don't really teach people how to use their brain. In what sense? Like you know, a lot of what you're talking, just talked about, is like how you suffer from your own brain, like how you can't even untangle your own thoughts, how you let your brain drag you down in any direction, and how we live our lives in ability and the skill to pause and be the masters of our own brain, of our own emotions and, at the end of the day, in our own destiny. We are just like being dragged along, right? So I think so from my perspective. So I think so from my perspective.
39:10
I like information, I want to know. That's always been my thing. Like I always want to know. I don't care, I want to know. I don't care the cost, I want to know. But I think it's important to, as a society, to develop the skills to use our brains and our emotions in a constructive, healthy, life-sustaining way. We don't do that, you know. Most of what we suffer from is our own thoughts and our own emotions about something that doesn't even exist, like either something that has happened in the past or something that we think that will happen in the future. But we very rarely are present in the present moment.
Peter Carucci
39:53
Yeah.
Despina Kontos
39:53
So, that takes us in a very, completely different kind of direction this discussion. But the problem is how? Is not the information or the tools or whatever is how. The problem is always us, it's always it's us. You know our individual response to what is happening. That is always the problem in our existence, right, I think at least, and you know our ability to respond to what is happening. That, I think, is where we need to focus as a society and take control of our ability to respond in a conscious, aware and health sustaining manner. That is my view.
Jamie Serino
40:36
Yeah, it's well said. I think it involves a little bit of Taoism, a little bit of Buddhism. Yeah, the thought comes in, the thought leaves Right, and you know it also makes me think about going back to what you said earlier. There's a bit of like change management here that needs to happen as you introduce this new thing, and we talked about introducing it to the health system, but even introducing it to doctors, any anyone using, you know, this medical information, and then introducing it even to the people, the patients and stuff. So the the change management piece is you know how do we use this information? Um, either as a practitioner or as the patient receiving it.
41:22
Um, and that change management piece, you know that that that's where like disruption comes in, and disruption is successful when the change management part goes well. Um, when it doesn't go well, that's where like disruption comes in and disruption is successful when the change management part goes well. When it doesn't go well, that's when it gets all kind of clunky. So I mean, do you ever have those types of discussions in terms of like, okay, now we're introducing this new thing, you know what's going to be the resistance to it. How do we get over that resistance? That's the change management and organizational, that's the behavioral Exactly.
Despina Kontos
41:51
Exactly, we have these discussions all the time and again, as I said, I'm just the engineer, guys. I am making the gadgets and bringing them to the doorstep. That is my expertise, my training, my job, my calling, my thing. I make the gadgets and bring them to your doorstep. But I think the process of evaluating whether or not something should actually be used by a physician should actually be communicated to the patients. That's a whole different scientific field. Like there is what we call like implementation science, comparative effectiveness science, outcomes research.
42:25
There are actual experts about this and we kind of bypass that whole thing. We bypass that thing. We just take it from me, the engineer what do I know? And try to like shove it in the face of the health system with the hands of the physician. We bypass the whole process, folks. Like we need to engage these experts to do their job right and we need to work together. Like I'll give you the gadget. You take this gadget, see if it makes sense or not. If you have some feedback, give it back to me. I'll tweak it, I'll change it, I'll do whatever it takes you know, and then the health system needs to be communications Like.
43:02
there needs to be an understanding that, at the end of the day, we need to do this to better our society and healthcare and health patients. At the end of the day, we need to do this to better our society and health care and health patients at the end of the day, right. If this is not our goal, we will fail as a society in this, and so we need to have these kind of open communications and coordination between people like me.
Peter Carucci
43:36
And coordination between people like me, people who are in the middle and people who are on the other side, to be able to successfully bring this to help us, to help us as humanity right. And you're currently using, or rather you created, this kind of system and you're working with AI to make certain predictions about specifically certain cancers and whatnot. About specifically certain cancers and whatnot, and I recall in an earlier conversation we had, you're also looking at it in terms of like, maybe predicting Alzheimer's.
Despina Kontos
43:55
Yeah, not me, my colleagues, right, I work in cancer specifically, but colleagues of mine.
Peter Carucci
44:01
I guess this is a field kind of the predictive Generally, overall, Exactly, I'd love to hear a little more about what you see that future looking like, or what that looks like.
Despina Kontos
44:12
I think there are similar considerations across the board. If it's cancer, if it's Alzheimer's, if it's cardiac disease, there's similar trends and similar work happening across the board. And we have the data, the technology, the expertise to develop these technologies and these tools that can help us personalize care. And so, again, the question becomes what are the barriers, the opportunities? And we need to decide as a society, how do we want to use these technologies? I think it's up to us to decide collectively what we want to do with it.
Peter Carucci
44:50
Do you really think it's up to us to decide collectively what we want to do with it? Do you really think it's up to us to decide, or do you think it's?
Despina Kontos
44:59
the financial impact. I know Life is complicated and there's all kinds of interests, guys, but again, from my perspective, if we don't all take personal responsibility, we are doomed. It's very easy to say it's somebody else's fault. That doesn't help anybody. It's our collective, individual responsibility that's responsible for everything. We vote, we elect the people who govern us. We buy products. We don't buy products. We invest this whole thing. I've never been a person who like, oh, it's like the. They right, they, they want to do this. They, who are they? It's us. I don't know this. They. I've never seen this they. Have you seen this? They? So I think it's. We all have to take personal responsibility. There's no other way out.
Peter Carucci
45:44
But in this polemic we're discussing the possibility of, let's say I don't want to say names but a large company Amazon or Google or any large company could just jump the shark here, take this technology and try to force its hand into healthcare for the financial benefits. Are you the end?
Despina Kontos
46:06
user of this. They all depend on us. They all depend on the end user?
Peter Carucci
46:09
Who are they depending on? Who are they going to sell it to?
Despina Kontos
46:11
It's your money and my money, and you know who's going to pay for this right, who's going to pay for it. So we don't diminish the role of personal responsibility. It is the only way out. The only way out, I think All right?
Jamie Serino
46:29
Well, Despina, as we look to wrap up here, is there anything that we didn't ask or anything that you would want to make sure to add?
Despina Kontos
46:39
You know, I think the future is bright. If we want to make it bright. The future can be very doom and gloomy if we want to make it doom and gloomy. History has shown that, you know, us humans are probably the worst kind on the planet. But it has also shown that we are probably the worst kind on the planet, but it has also shown that we're probably the best kind on the planet as well. So I think it's up to us to decide how we want to flip that coin. Yeah, and, of course, everybody in their daily lives to take personal responsibility for everything that they do, as little as or big, whatever they're doing, every moment counts, I think in this game.
Jamie Serino
47:13
Yeah, and that's a really good message because, you know, of course we didn't really touch upon this, but there's always these like end-of-the-world scenarios with AI, terminator, you know, missiles launching. And it's interesting because, you know, we talked about Asia and the Asian cultures tend not to have that mythology and the Western cultures tend to have that mythology that the robots are going to rise up and take us over, and you know, and you know, I don't know who's right there, but you're sort of saying that the individuals have the responsibility and they have the wherewithal and they have the control.
Despina Kontos
47:48
Really, in the end, Show me a time in human history where robots were not taking over Quote robots when there was peace and prosperity and that everybody was in La La Land. You know human history is, you know, continuously in turmoil, mayhem, wars, this disaster Like. Show me a time in human history where this does not exist. So I think there's a little bit of a hype there and, at the end of the day, if the robots take over and destroy us, we'll probably deserve it, you know, because we let them do it.
Jamie Serino
48:23
We were asking for it.
Despina Kontos
48:25
You know, I also have a perspective. Why are we always doom and gloom Like the robots are going to be like the worst of us. There's a fair chance that that may be the best of us, you know the best?
48:35
yeah, I think we're totally capable of destroying this planet without any help from the robots. We don't need the robots to self-destruct. I think we're doing a good job at it as it is. So, who knows, maybe the robots are going to save us because they might tap into the best of our intelligence. That's another flip side of the story. That's a scenario.
Jamie Serino
48:57
I like that A message of control, control and Despina. It's been fascinating. We learned so much here. We're probably gonna have to come back and talk to you some more because we still have, I think, a thousand questions, but I want to thank you. I want to thank everyone for watching and listening and we will see you all next time.
Despina Kontos
49:17
Thank you. Thank you for having me and let's get together again before the robots come. Okay, thank you All right.
Jamie Serino
49:24
Thank you.