I’ve been thinking a lot about the way our society meets technology head-on. As we approach an age of unprecedented advancements—artificial intelligence, genetic editing, life extension—the big question that keeps coming back is: Who truly benefits? This episode of the Redefining Society and Technology Podcast digs into how innovation might uplift some while leaving others behind, and what that means for our shared future.
Guest: Dr. Bruce Y Lee
Senior Contributor @Forbes | Professor | CEO | Writer/Journalist | Entrepreneur | Digital & Computational Health | #AI | bruceylee.substack.com | bruceylee.com
Bruce Y. Lee, MD, MBA is a writer, journalist, systems modeler, AI, computational and digital health expert, professor, physician, entrepreneur, and avocado-eater, not always in that order.Executive Director of PHICOR (Public Health Informatics, Computational, and Operations Research) [@PHICORteam]
On LinkedIn | https://www.linkedin.com/in/bruce-y-lee-68a6834/
On Twitter | https://twitter.com/bruce_y_lee
Website | https://www.bruceylee.com/
On Forbes | https://www.forbes.com/sites/brucelee/
On Psychology Today | https://www.psychologytoday.com/us/contributors/bruce-y-lee-md-mba
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Host: Marco Ciappelli, Co-Founder at ITSPmagazine [@ITSPmagazine] and Host of Redefining Society Podcast
Visit Marco's website 👉 https://www.marcociappelli.com
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This Episode’s Sponsors
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I’ve been thinking a lot about the way our society meets technology head-on. As we approach an age of unprecedented advancements—artificial intelligence, genetic editing, life extension—the big question that keeps coming back is: Who truly benefits? This episode of the Redefining Society and Technology Podcast digs into how innovation might uplift some while leaving others behind, and what that means for our shared future.
Shaping Technology, Shaping Society
I’ve always felt that technology doesn’t simply “happen” to us; we shape its purpose, direction, and impact. Today, we’re facing a future where AI-driven healthcare, gene editing, and other profound innovations promise to change how we live. Yet, as I sit down with Dr. Bruce Y. Lee, we confront a timeless issue: Who gets to enjoy the fruits of these breakthroughs first? The wealthiest nations? The richest individuals? Or can we find a path that lets everyone share in the benefits?
Learning from Our Past
History is filled with examples of innovation tipping the scales of power. When only a few had access to sea travel, they colonized distant lands. Control of information shaped empires. Over time, global communities realized that the well-being of one affects the well-being of all. Still, initial inequalities often last for decades, sometimes centuries, before evening out. Now we face a similar divide, but with far more at stake.
Healthcare at a Crossroads
The healthcare industry illustrates this perfectly. High-tech medications and advanced procedures often come with staggering price tags. Meanwhile, entire groups go without the basics. It’s not that technology inherently creates inequality; it’s that our complex systems—insurance companies, regulatory bodies, pharmaceutical giants—skew the playing field. Those with time, money, and influence can access cutting-edge treatments first, while others must wait or never receive them at all.
Algorithms and Old Biases
AI-driven platforms might promise equitable access to information or diagnostics, but they’re only as fair as the data behind them. If existing biases and blind spots shape that data, they’ll be amplified by the technology itself. We risk codifying age-old injustices into new, gleaming interfaces. If we don’t proactively address these issues, we’ll only replicate the past’s mistakes, dressed up in modern clothing.
Pathways to a More Equitable Future
Yet, there’s hope. Technology can just as easily be a solution if we use it thoughtfully. AI can streamline drug discovery, cutting development times and costs. Virtual clinical trials can simulate diverse populations, breaking the limitations of biased real-world testing. More nimble players can enter the market, driving prices down and access up. The tools to level the playing field are within our reach—if we choose to build and deploy them that way.
Looking Ahead: Beyond Our Human Shell
As we turn toward transhumanism, life extension, and the possibility of uploading ourselves into digital realms, the stakes grow even higher. Will advanced genetic editing or digital immortality be a luxury item, creating a new class system of enhanced humans and immortal minds? Or can these breakthroughs be democratized, ensuring that everyone can participate in the next chapter of human evolution?
Choosing Our Future
I’m not here to say technology is bad, or even inherently unequal. It’s a mirror, reflecting our collective values and choices. We have the power to push for policies that ensure AI, genetic editing, and life-extending treatments serve everyone. But it won’t happen by chance. It’ll require conscious effort, ethical frameworks, and a refusal to accept business as usual.
As we move forward, let’s remember that we’re all part of this conversation. Let’s insist that technology’s greatest achievements are not trophies for the few, but shared blessings that help everyone thrive. If we do this right, the singularity doesn’t have to be an age of winners and losers; it can be a future where we all rise together.
See You Next Time
You'll find links to connect with Bruce and explore his incredible contributions in journalism and medicine. I promise you; he's just as insightful and entertaining as he seems in the series. So, see you next time – same bar, same garlic, new topics!
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Resources/References
The Singularity Is Nearer: When We Merge with AI
by Ray Kurzweil
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[00:00:00] Marco Ciappelli: Hello, everybody. Welcome to another episode of Redefining Society. Oh, yeah. Now is N Technology podcast. I felt that I needed to be more clear, especially for the search engine, because That's all we talk about, but I decided to focus on society and apparently people always look for the word technology.
So I just implemented there. If you're looking at the video, you can see that the title is up there. If you're listening the show, it's now redefining society and technology podcast. And as you know, it's one way and then it's the other. So how society influence technology and how technology is in influence society.
I hope that society has a little bit more to say than the technology itself, but that's up for conversation. That's what we talk about. And today, of course, it's a new episode with my friend, Dr. Bruce Y. Lee and his other good friend at this point, the garlic in the background. And we're going to talk about a few things that we started To cede, let's say, on the other episode, the one before where we were talking about transhumanism Because I just finished reading The Singularity is Near by Ray Kurzweil and it raised a lot of questions so I have an outline for what they can be the next three episodes and We picked one of the three and I'll let you know which one it is after the I welcome Bruce to the show.
Welcome.
[00:01:42] Bruce Y. Lee: Thanks, Marco. Always great to be here. I am a friend over this side.
[00:01:49] Marco Ciappelli: So same expression for the garlic hasn't changed much.
[00:01:53] Bruce Y. Lee: Yeah. Well, you know, he, uh, he changes his expression off camera. So, you know, sometimes it's a smile or something, but you know, whenever you talk about society technology, there can be some great things and there can be some questionable things.
So technology, as we've always said, Is neither good nor bad in by itself. It's actually how you use it. So correct,
[00:02:18] Marco Ciappelli: correct And you know what? I like about that garlic. I just thought about it now. It has that Surprise face that you don't really know if he's surprised Excited or surprised shocked It can go both it can go both ways.
So We'll see where we go with this conversation today it's uh
[00:02:43] Bruce Y. Lee: Uh, sexcited or whatever you want to, uh, I
[00:02:46] Marco Ciappelli: think it says no way, but it could be like, no way or no way. So we'll see what it says today. Um, so to recap, like I said, we talked about the singularities near, we talk about healthcare, we talk about human augmentation, of course, transhumanism and, and, and digital upload of our life into.
Into computers and servers to live to forever Assuming that all these things are actually going to come through and uh, and I think that in since last Time we talked about a month and a half ago Um, we've seen already a lot of new things. I mean, we don't get bored in in the world of technology But but the big question that I think is going to help us to pick The the topic that we're going to dive into Today is the question Suggested to me by our friend CHAT GPT, um, with the singularity or that gets near the evolution of technology and all the things that are possible, that they will be possible at a societal level, the question is, is there someone or some part of a society that are standing to gain or to lose this?
Uh, compare with, with someone else. So is it democratic? It's not democratic. Is democratic 51 percent and 49 percent are really unhappy? I mean, that's, that's the big question. So I think we should talk about that today. So inequality in the age of singularity and let's see where we go with that.
[00:04:30] Bruce Y. Lee: Well, you know, if CHAT GPT tells us to do something, then we should do it, right?
[00:04:34] Marco Ciappelli: You don't want to be against it just in case. Just be nice to CHAT GPT. So have you, have you any, have you had any thought maybe following our prior conversation when we, we did sprinkle all of three, all the three of this topic? But I think the inequality And the democratization of technology, how it rolls into our society.
It's always something that, at least for me, from a sociological perspective, it's, uh, it's a question that is always present. Either we talk about internet infrastructure, 5G, uh, even CHAT GPT itself, or, or, you know, what, what level of intelligence are you accessing based off? Are you going to get the free one?
Are you going to pay, 20, 30 a month for it. So what's your thought on that?
[00:05:23] Bruce Y. Lee: Well, we, we, we've seen this throughout history, you know, whenever there are innovations or there's new technology or new resources that are available, uh, you know, sometimes, or many times actually, there's been, you know, one group of people who've had access to it.
And as a result, they've been able to dominate others or move faster than others. Uh, you know, the. You know, if you look at back in history, those who, for instance, were able to develop, uh, you move faster on land, were able to capture more land, people who, uh, you know, there's a lot of, uh, a number of countries that had sea power, so they were able to use ships and then using the ships, they were able to travel further to further lands and, and end up, um, colonizing different places, uh, and, you know, that created.
greater inequities or, uh, uh, or inequalities, inequities, both, um, as a result. And so, but on the flip side, you can take each of those different types of technologies or innovations and say, but here's how it helped everyone. So if you think about it, let's take, for example, sea power, being able to, you know, use ships.
Well, yes, at the beginning there were certain countries and certain governments that had those type of navies, those type of, uh, merchant fleets. And then they were able to take advantage of a lot of other societies and places. But, but now the fact that, you know, you have ships moving around, you can ship grains and, and food to different places.
So you can help places that don't have, didn't initially have access to those resources. And one of the challenges is you've seen throughout history where Maybe initially, you have certain people taking advantage of that technological advantage. But then eventually people realize, wait, hold on a second.
This actually is causing problems in society. And then people start realizing, hey, we're actually connected. Um, and then that's when you start seeing things equal out many times. Uh, you know, another example is the control of infectious diseases. So if you actually look at military history, infectious diseases, many times was actually the victor.
They were actually the victor. They helped one side defeat the other side because the other side, you know, the smallpox or what have you. Uh, you know, this, this is one of the issues that happened in the Americas when you have people. Yeah. Uh, settlers coming over to the Americas. So, but then the realization came that you need to, well, these are threats as long as these infections, these threats are a threat to some people, it's a threat to everyone and therefore there's benefits in establishing broader infection control measures.
You know, ultimately like vaccines, but at the beginning, you know, different types of measures and care to prevent the damage or impact and the spread of these different types of diseases. So this is not new in society, um, this concept. So we always have to be careful whenever there's new technologies of like, how's it going to disrupt society in a way that's actually bad, that's actually causing inequities, leaving certain people behind.
And then how is that actually going to come back and affect, hurt everyone? So that's important to keep in mind.
[00:08:48] Marco Ciappelli: And you know, one of the things that I hear a lot is when, when technology. Is new is, is usually more expensive and in general, so that the first one that then develop certain kind of technology and adopted in large scale are usually the richest nation in this case, or the one that have a really big interest in.
Conquering this case to go in the America. We got the gun. You don't. And then they find out that they also have a very dark superpower, which is bringing bacterias and and diseases that help because you wonder, how is that hundred of Cortez men Get rid of thousands and thousands of Mayan that that's a big question, but when it comes to the the modern world Many times that the new iPhones for example, they were super expensive then somebody adopted Put it on scale and now everybody has it.
But if you want the good ones, you still have to pay more than the cheaper ones. So there is always the first coast of, of things that some people may be able to afford or not. And oftentimes they say, well, we're just biting the bullet for all of you. Right? We, we buy it, we see how it goes and then if it works, we, we give it to you.
But I think maybe it works if he's a advisor for virtual reality or a smartphone. But when it comes to healthcare, I'm not so sure that the reaches could, should have access to that earlier. You can use as many skills as you want, but I think ethically it's, it's correct.
[00:10:42] Bruce Y. Lee: And we've seen it recently with social media, for example.
So social media, there were, you know, kind of the. Basically the people who built the initial social media platforms and then the early adopters, those folks were able to dominate social media and dominate the, also the messages and what, how social media is actually being used. Now there were people who were coming later to social media, but they don't really have, they may not have control in terms of what's actually being said or presented.
So if you think about it, right, you jump on any of these platforms. There are algorithms that are controlling what you actually see. And so it's not all equal opportunity, right? You, you go out to something and what you're actually presented is, is based on those algorithms. Well, then who's creating those algorithms and who is then whoever's controlling those algorithms then controls what kind of information is spread.
Uh, and therefore, if there's an interest in spreading particular types of messages and those things like that, who has control over that? And so that's a very recent example. Um, and then we can apply that to new technologies like AI. You know, who's actually devising or designing these algorithms that then determine and say certain things.
[00:12:01] Marco Ciappelli: Yep. And, uh, and according to George Orwell, 1984, if you control information, you kind of control everything, you control society. So that's, that's a really, really good point. And, and one can wonder what would have been the algorithm if someone else maybe found out earlier. You know, like, who is that control?
Is that the Communist Party in China? Is that the, the, the, the Nazi in Germany or the rich people in the United States or another advanced country? I mean, I'm not taking political position here. I'm just saying, whomever has control is going to drive his own agenda. Therefore, the algorithm, algorithm is going to do.
The things that matter the most to them. Do you see something in a, in a probably dystopian society, vision of society that could happen in healthcare?
[00:13:11] Bruce Y. Lee: Oh, yeah. There's, there's been a lot of, uh, conversations and concerns about that. Um, so the studies have already shown that there are great disparities in terms of access to healthcare and also, you know, someone walks in, you know, To a clinic and there can be great, a great range in terms of what types of treatments they receive or how they're treated or, you know, how they're evaluated or how they're diagnosed.
That's all that's been known for a long time. And so, uh, so there are already existing disparities in terms of that. Now with technology, the question is, well, technology help alleviate some of those and decrease some of the disparities or worsen it, uh, you know, You might have, uh, if you are extremely advantaged, well, you have access to certain latest and greatest therapies or modalities, whereas someone else might not.
Uh, that's, that's a big question. And so this with technology, it's again, it's neither good nor bad. If it's, it's stationed appropriately, then it can help alleviate those disparities. If not, then it can actually worsen those disparities. Um, there have been, uh, someone told me, uh, about plugging in things into CHAT GPT, for instance, and asking questions like, okay, uh, what are the treatments for breast cancer or something like that?
And then try putting in, like, I am a certain ethnic group. What are the treatments? And that person got back fewer options. Versus the first attempt. So by actually identifying a certain ethnic group, then you actually get less options. And that, and you have to ask yourself, well, why is that the case? Well, CHAT GPT is based on the corpus of information that's out there.
And if you make something more specific or something, you know, a group that's not as well studied or, or there aren't as many, much data on, then you're going to get less information. So you're talking about, there's already a situation where depending on who you are, you might actually get different information.
From something that's supposed to provide, you know, an AI driven tool that's supposed to provide information. And, and we know why we know why that's the case because the data, there's a lot more data on certain groups, certain demographic groups than others. And that's an example of further exacerbating the disparities that exist there.
I
[00:16:02] Marco Ciappelli: didn't think that way, but yeah, it makes total sense. I mean, I didn't think that way because I didn't actually do that. Although I normally try to make it, if I use CHAT GPT, very specific. If I'm looking for information for myself, I'm like, we're talking about me here. So what are my options? And one interesting thing, for example, is CHAT GPT.
You talk about the disparity in, in the cultural, all the, all the social demographic, but also, for example, where, where are you, like, for example, I actually experienced this. I was in Italy. I was dealing with a family member that he was going through something. And I, you know, I use CHAT GPT as my, uh, my doctor just to learn certain things.
And he proposed one thing that then I ended up talking to the primary doctor in the department. And, uh, at the hospital. And I said, how about this? And he said, where did you find that? And I said, well, CHAT GPT. And he said, well, we don't do that in Italy here. It was an alternative procedure that is like, yeah, I heard of it, but we don't, we don't do this here.
So it kind of follows. There are many different angles that, that comes into place and perspectives when you, when you look at these things.
[00:17:20] Bruce Y. Lee: Yeah.
[00:17:21] Marco Ciappelli: And our, our, and they are in a, they're intrinsic to our society. So I'm not saying cha, GBT created this, it's, it's just Adi, it's a hereditary from, from the way we, our society are structured.
[00:17:39] Bruce Y. Lee: Yeah. If you're going to, if there are already certain biases and this reflects the biases that exist in the corpus of the internet right now, right, because we know that the way these algorithms are developed is you, you know, at least in case of CHAT GPT, you have the corpus of information that's available on the internet and it basically learns from that.
If something's repeated over and over again, whether it's true or not, it's going to appear in the answer. So in theory, if you said, you know, if you had enough time to like publish tons of articles on, uh, why covering yourself in chocolate is a good thing, you know, and you just repeat over and over again, at some point it's going to be picked up and you look up in the AI check.
Uh, what should I do? It'll say, have you considered covering yourself in chocolate? You know, something like that. So that's basically what it comes from. It's not like, it's interesting because people is with, especially with these interfaces now, you get the feeling that there's someone smart telling you what to do.
Right. So you log on and you ask the question. It feels like there's someone quote unquote smart with lots of information telling you what to do, but you have to realize that just like a person, that thing may have lots of biases and you don't think about it because it just, you know, it's, you think, Oh, it's tech.
Therefore it shouldn't have biases, but it does. And it's not, this tech does not have a medical degree. This tech does not have a law degree. It's just saying, this is what I see everyone else saying, uh, and it's not everyone else. It's certain people saying,
[00:19:32] Marco Ciappelli: yep. And especially when he doesn't even think, but he's just putting together probability and, and.
Well, in a way, it does think, but let's, let's not get into the detail of it. But the point is, is more like a parrot right now, uh, it may be more conscious in the future, but right now it's more parroting whatever it's been fed. So let's, let's take AI from away. Right. So now that we can, let's, let's say generative AI, let's keep AI.
AI is used in medicine, has been used in medicine for a while, way before CHAT GPT. It's been used in many other fields. It works, especially when you have a tunnel task that could be looking at x ray, looking at specific things, and it can, it can ingest and digest way more data than than what we can as human in a much shorter amount of time.
That's how we create new vaccines so much faster. Now we can run tests without having to actually test people, simulation. And I know that's, this is your field. When, when the company, a pharmaceutical company, when a hospital, Decide to invest into something. Do you think that it come into consideration the, the inequality that in the population, I mean, how do they pick something versus another?
Is that, is that ethical? I don't know. I don't even know if you have the answer, but.
[00:21:14] Bruce Y. Lee: So you mean like basically, you know, they choose some type of technology like a medication or something like that to further
[00:21:21] Marco Ciappelli: like focus billions of dollars into developing the treatment for something versus something else.
I mean, it's a pandemic. Sure. I mean, that's That's shit for everybody. So, but in, in other things, developing machinery, robotics, uh, I don't know anything.
[00:21:40] Bruce Y. Lee: Yeah. So I, you know, I was, uh, in a previous life, uh, working equity research, which is basically, you know, when you work for an investment bank and you, um, uh, value a company, um, part of what you, what you try to do.
So I covered biotech companies. You look at. Their technology in this case, many, you know, many times medications. And then you look at like the market size, the potential market size, and then you look at the risk, how likely is this technology, this medication to reach the market. And that's where a lot of decisions are made.
So, you know, you put together a spreadsheet and say, okay. Ideally, you want the largest market possible. You want the fewest competitors as possible, and you want the lowest development risk. And that leads to a positive financial decision. And that's what, that's how many of the decisions are made. So if you notice, equity does not necessarily play a role.
I mean, it may play a role in terms of the sheer number of people. So like if something's very common, uh, a disease that's very common, then that's likely to be kind of a larger market. Okay. But it doesn't really play a role in a lot of those financial decisions in terms of, um, uh, you know, whether it's, it's a, uh, good product to go with to, to further develop.
Um, and that's a problem, but also you have to think about, well, why are these decisions made? Well, if you look at a pharmaceutical company, they've got shareholders, they've got their stock price, Uh, they've got, you know, the profit margins that they have to achieve and those type of things. And they're being watched carefully by all their shareholders and say, Oh, why did they, why did they acquire that drug?
Why did they out license that drug? You know, why are they developing this and that? So that drives a lot of their decision making many times.
[00:23:41] Marco Ciappelli: Is it making me money or not?
[00:23:44] Bruce Y. Lee: I'm sorry?
[00:23:45] Marco Ciappelli: It's making money or not?
[00:23:46] Bruce Y. Lee: Yeah, basically.
[00:23:48] Marco Ciappelli: That's the bottom line.
[00:23:50] Bruce Y. Lee: You know, the other issue is that over time, things which drive equity or things that help all of society actually in the long run may make more money, but in the short run, it may not.
Right. Right. So. Um, many times companies these days are thinking very short term, you know, what's gonna give biggest cash infusion or the biggest profits as soon as possible. Um, so that's, that's the disconnect many times.
[00:24:27] Marco Ciappelli: So here's another question then, this is when we let the market decide and the market, let's face it, doesn't care much about ethics.
It cares about. I mean, I'm not saying we're going to produce atomic bombs because somebody's going to step in and eventually say no, although I'm sure much money has been, bless you, much money has been making on, on, on atomic bombs anyway, or weapons and all of that. But, um, if, if you have a situation where the decision are driven by a healthcare system that is national healthcare system, so I'm thinking Italy, the UK, France, whatever.
Is there, is that more ethical in your opinion or, or is still money driven because no matter what, even the party at the power is somehow having to show that they're not throwing money away and that there is an investment in that.
[00:25:32] Bruce Y. Lee: Well, I think one of the challenges is there, there might be the belief that a lot of things are market driven right now, but they aren't right.
I mean, I think one of the challenges in healthcare is there are a lot of middle people that are involved. That then, you know, throw off market dynamics. And sometimes that can actually impede, um, the adoption of technology. Uh, so, uh, you know, there are some technologies that were developed a long time ago, but, you know, people kind of pushed against it because it would be a threat to their bottom line or their situation.
Uh, you know, there's, there's functions in, in medicine, for instance, that could potentially be replaced. Yeah. By technology. But if, if the people don't want them, don't want to be replaced or they feel they're worried about that being replaced, they're going to push back against it. Also, you know, we talked about, um, uh, Pharmaceutical companies, et cetera.
They're not solely looking at directly who's going to buy it. And these things like that, they're looking at stock price. So it's the investors that, that play a role. So you don't have a clean market, meaning that you don't have a direct, you know, years ago, markets were simple. So if you were hungry. And I came along and I say, Hey, here's a bunch of hammers.
Would you like to buy a hammer? Unless you eat hammers, you'd be like, go away. I don't need you. Until I came back and say, here's a bunch of avocados. And he said, okay, I'll pay you. So therefore I am meeting your need. You're paying me as a result. That's when the market works, right? You have a need. I, I I'm producing something that's useful, et cetera.
But the problem is the market has gotten so complex with healthcare, with insurance companies. Pharmacy management companies, all these other things so that, um, You aren't really, you're really separated. Supply and demand are really separated in many ways. Uh, and that's one of the challenges and that's what's prevented in many times the fusion of technology and healthcare.
And it's also prevented. More equitable situations as as a result.
[00:27:45] Marco Ciappelli: Right, right, right, right. How about the new technologies? So when, when we talk about transhumanism and, and, and getting into a higher advanced technology, we can talk about the crisper, the nanotechnology, narrow interfaces, genetics and, and all of that, which may, as we talked in the first episode, related to this.
extend life to, to many, many, many, many years, but also resolve issues before they even arise. And I want to, I want to touch on this. I know it actually could be something for another episode, but for human augmentation, but I think there is an angle. There's always an angle about inequality anyway. So, um, how is this going, do you think, to apply when we talk about technology that are there right now?
Like, I give you an example, like, I read about all this new technology. It's very hard even for me that I talk about it all the time to understand if it's, wait a minute, is it going to be available or is there but not available when the regular Joe is going to get advantage of it? Because I know that CRISPR Technology is extremely expensive, so it's probably just going to be at use for so what's the dynamic for things to come and It's kind of like an autonomous car.
They're kind of there but we don't see them around because there's policies and stuff that right so
[00:29:33] Bruce Y. Lee: yeah, so I mean one of the challenges is that when Uh healthcare related technology is available Then you know one of the interests is in Quickly recouping a lot of the R and D costs. Um, and then on top of that, you know, expecting a certain profit margin because, you know, you spent years.
Not making profits. And then you want to make a lot of profit. So then as a result, the technology is priced very high. So it's, it becomes, and then the other challenges in many cases, it's not. It's again, it's not a straight market, right? So it's not like someone's putting up a crisper lemonade stand and people are walking by and like saying, Oh, I'll have one of those.
Um, it's the insurance has to decide, well, we actually cover it and insurance will cover it based on how much pressure there is to cover it. And who's pressuring it, you know, all those different things. And then different people have different types of insurance. And so there's different levels of insurance.
You might have great insurance or. Or terrible insurance that doesn't cover things. So it's so complex in that way. So undoubtedly that's going to initially create a lot of inequalities in terms of who can actually get it. So certainly if you can afford to say you're got billions of dollars laying around and you say, well, money's an object.
I want access to this. You just pay directly. You're going to be first in line. Um, if you are in a situation where. Okay. You may have some money, uh, and your insurance will cover it to some degree, but you still have to pay, then that's a decision you have to make. And then if you're, if you don't have the money and your insurance doesn't cover it, then you're out of luck.
Unless someone, you know, you'd start a GoFundMe or someone else comes along and says, Hey, I'm going to buy that for you. So that's the problem. You, you may not have access. Again, it's based on the resources that you have, or it's based on who you might be connected with. So, yeah, that's, there are all these built in mechanisms already that make access to technology, health technology, unequal.
[00:31:43] Marco Ciappelli: Is technology though, as we mentioned earlier, a smartphone or any other technology, Like something that cost a lot of money at the beginning. I mean even television, right? I mean tv They were like, oh 4k. It's super expensive like, you know thousands of dollars now. They they just want to Throw it at you and pay whatever you can so because because you get to the point that is Is economic economical enough to to have a model?
Where it's not by the quality but by the quantity so you want more people to buy it and and then eventually Everybody can get it. Same thing as I said, smartphone. So technology allows new things to happen and also allows to lower cost in the longer run. Is that happening exponentially in healthcare as well?
Because when you look at, and I am not, I just see what I, what I see here and there, but sometimes there are this medication that come out and it's like, yeah, this is 10, 000 a pop. And I'm still surprised to be honest with you when I see the bill that the insurance pay compared with what I pay, not insurance in Italy, but that's a different story.
Like I can see my insulin, for example, like if I need insulin in Italy, I'm like, yep, I don't even, I mean, I'll pay for it because it's 50 bucks what it will cost me 600 a year. So the point is, beside politics, can, can we imagine maybe a world where technology is going to get so good with AI and everything else that maybe we don't need these labels, those big tags, price tags on, on medications?
[00:33:37] Bruce Y. Lee: You mean helping technology, helping
[00:33:40] Marco Ciappelli: technology, helping to really make, uh, medications and any medical devices and, and all of that much more affordable because it becomes a scale economy instead of something that only few people can afford.
[00:33:58] Bruce Y. Lee: Yeah. I mean, there's real opportunity for technology to significantly decrease R and D costs and to significantly decrease the timeline.
So that, that, those are the arguments. For several things, you know that, Oh, it takes so much time and effort to develop these drugs. Therefore, we can afford to pay all these, you know, uh, charged prices with premiums to kind of recoup a lot of that investment. And also that, that there's that argument, Oh, look, we invested in all this for all this long time.
Therefore, we should have an exclusive patent for X number of years. Before other people can, can compete in this. So there is the opportunity that if you have technology to help facilitate the development of these things, making them easier and quicker than yes, that could certainly ultimately bring down costs.
So, you know, one example is technology that to identify drug targets. So you say, okay, many times you have a situation where you identify what's gone wrong with a certain condition, you know, what enzyme is not working, what kind of body part is breaking down, what have you. And you say, okay, we know the pathways for this.
Can we find some type or develop some type of medication that can then act at this pathway? What you used to do is it was trial and error, right? You used to try it. You try different things. You try it in the lab and see what happens. You might accidentally find something like that's how, um, antibiotics were found, right?
Uh, and the box were found because some mold grew in like one of the dishes and like, Hey, that's actually getting rid of a lot of the bacteria there. Pure, you know, happenstance. So with technology that can become a lot more organized. And say, okay, rather than like trying like three times, three things at a time, four things at a time, you can try like a hundred time things, thousand things in Silico.
Like you can do it in a way with a computer that you can't nearly do as fast with humans. So that could save. Um, then there's sort of the adjusting of the, The, uh, medication, there's a lot of adjustments that they have to curry. You know, once you find a target, you still have to adjust things. Computers could help with that.
AI can help with that. Uh, it can help better design clinical trials. Maybe someday we'll be able to do more virtual clinical trials where you have a virtual human where you can try different things and that can sort of either go along or supplement, or in some cases. Uh, you know, surpass what you do in humans, all those possibilities.
And when you can accelerate drug discovery and drug development, you can also ultimately reduce the cost as well.
[00:36:51] Marco Ciappelli: Yeah. I was reading something about that actually, where, I mean, I think it was connected still to, to the vaccine development where regular vaccine will take 10 years or so, because you have to.
Tested then get permission tested to a larger amount of people and and and how That's what the skepticism of a lot of people like. How did you develop the COVID vaccine in In no time, right? It's not possible. That's that's sorcery sorcery right there Um, but it's because you you can actually simulate a lot a lot of things and and probably actually simulate Even on a more diverse range of subjects, compare with what you would pick to, to test, I don't know, hundreds, thousands of people to see if it actually works or not.
[00:37:41] Bruce Y. Lee: Oh, absolutely. You know, if you look at clinical trials and studies have shown this clinical trials tend to be a select population and it's another diverse population.
[00:37:50] Marco Ciappelli: Yep.
[00:37:50] Bruce Y. Lee: So, uh, if you think about it, like to be able part of a clinical trial, many times you have to be comfortable enough financially that you can take the time to be in a clinical trial.
You know, if someone who's just struggling to make ends meet, like you have to go to the hospital many times to get tested and all these things like that, um, so not everyone can afford it. Um, you know, the clinical trial will pay you some money, but it's not enough to really just, you know, to completely compensate for all your hassles and, and, and, uh, work loss and those things like that.
But if you could simulate a wide range of different types of people, that could be something very different.
[00:38:35] Marco Ciappelli: Yeah. Well, a lot, a lot to, a lot to think about. So, uh, Also, it also,
[00:38:42] Bruce Y. Lee: you know, when it comes to, I mean, you, you, you probably see all these big pharmaceutical companies, you know, they have, they're huge.
They have all these big, uh, uh, offices and they have, you know, a lot of infrastructure because that's part, it takes a lot of time and effort to, you know, set up laboratories and, and, and, and run clinical trials and those things like that. If you can do that. With a lot less resources, a lot fewer resources that may allow more people to enter the market, more competitors to enter the market.
And then that in turn can also drive innovation and also reduce costs as well. So lots, lots of possibilities.
[00:39:24] Marco Ciappelli: Lots of possibilities and I think it came out from this conversation that yes, there are certainly inequality just because there are inequality period. It's not, I don't, I don't, I don't want to pinpoint or point the finger to technology creating inequality.
I'm not on that side of the street. I'm more on the side of yes, it's, it's like, Like social engineering, right? Social engineering always existed, except that now with technology, you can create it at scale. With AI, you can create social engineering on email way faster than what it used to be to write a letter of the Spanish prisoner and send it to someone hoping that he's going to give them money.
So it's a matter of gullibility, not a matter of it's creating a problem. This is making it more, more popular, I think. Well, that was fun. Um, I think next time we can touch on the other things that we, that we mentioned and I'm particularly. Interested in the getting your opinion and my opinion because I think about it But I never really get much deep into that by myself into Uploading our life into computers.
I mean you you're here now and i'm just gonna throw a teaser there of people getting married to uh, Artificial intelligence. Yeah. Um, being actually very loyal and now with the robotics that become an entire different thing, but, um, established in relationship with them. And, and so what, what if sometimes I wonder it's not an artificial intelligence, but actually is the, the product of somebody's brain and spiritual mind that actually Goes online and people can become friends with them and so forth.
So I think there is a lot of ethical perspective there to look at and Assuming the the feasibility of it as well because I always think like you spend a lot of money to put your So, um, you're, um, your brain online and then what, what, what if there's a blackout and everything goes right? So, um, that may, there may be a way to avoid that, but, uh, who the hell knows?
Um, yeah. So if you're up to that, I think next time we can, we can touch on, on, on this more, even more sci fi. I mean, what we talked about today, I think is very real. And I wanna thank you for kind of helping to shed some lights on, uh, on that. And we, we did talk at the beginning, uh, a candle in the dark and, uh, Carl Sagan and how science, it's not perfect, and I think we just prove it today.
It's not perfect. It's, uh, it's, it's a lot more perfect than sodo science and, and other gullible
[00:42:32] Bruce Y. Lee: things. Yep. Well, as a teaser, I wrote a Forbes article about, I don't know, uh, now it's been about seven or eight years ago on, uh, the, on AI sex bots, and I'm going to explain that during the next, uh, episode.
[00:42:47] Marco Ciappelli: Can't wait for that. If you want to put a link to that, so people are prepared or just reveal it when, uh, when we talk next time. I'm looking forward to that. The garlic just got even more Concern right now Or excited maybe maybe it has some relationship with this expert Uh, but yeah, I want to thank you again.
It was great to chat with you and spend, uh, 43 minutes and uh, and I want to thank everybody for listening and stay tuned for another episode of Carbon a silicon and a cell walk into a bar and to that we're out of guardic as well and bruce And everybody else. Thank you so much. Stay tuned subscribe and we'll talk soon very soon again