Redefining Society Podcast

“Bizarre Trends and Misinformation: A Look into Technology, Health, and Society” | A Carbon, a Silicon, and a Cell walk into a bar... | A Redefining Society Podcast Series With Recurring Guest Dr. Bruce Y. Lee and Host Marco Ciappelli

Episode Summary

Welcome to the second episode of our series, 'A Carbon, a Silicon, and a Cell walk into a Bar...', part of the 'Redefining Society' podcast. I'm Marco Ciappelli, and Dr. Bruce Y. Lee joins me as we explore the intriguing blend of technology, health, and society that we delve into once a month.

Episode Notes

Guest: Dr. Bruce Y Lee, 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

On ITSPmagazine | https://www.itspmagazine.com/itspmagazine-podcast-radio-hosts/marco-ciappelli
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Episode Introduction

Welcome to the second episode of our series, 'A Carbon, a Silicon, and a Cell, walk into a Bar...', part of the 'Redefining Society' podcast. I'm Marco Ciappelli, and I'm joined by Dr. Bruce Y. Lee as we explore the intriguing blend of technology, health, and society that we delve into once a month.

Our conversation today takes us to a virtual bar where topics range from bizarre TikTok trends like beer tanning to the dangers of misinformation surrounding health remedies. Dr. Lee's expertise in artificial intelligence, digital health, and journalism provides profound insights into these matters.

For instance, we discussed the myth of pouring beer over oneself to activate melanin and enhance tanning—a trend that's not only scientifically wrong but dangerous. Similarly, we examined social media trends that promote harmful practices, such as eating laundry detergent boosters, and how these might be linked to human psychology and a lack of critical thinking.

We also touch on how the allure of simple solutions and viral content can mislead people into accepting misinformation. We both believe in the power of education and critical thinking to help society navigate this intricate landscape.

In our conversations, humor and seriousness intertwine, reflecting on the complexity of our modern society and the role of technology, cybersecurity, and humanity. Our goal is to engage, enlighten, and provoke thought, and we hope you find our musings both entertaining and informative.

So grab your headphones, join us at our virtual bar, and let's explore together the intricate intersections that are continually redefining our society. Don't forget to share, follow, subscribe, and be part of our ongoing conversation.

Until next time, stay curious and never stop questioning!

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Resources

PHICOR: https://www.phicor.org/

AIMINGS: https://www.phicor.org/aimings

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To see and hear more Redefining Society stories on ITSPmagazine, visit:
https://www.itspmagazine.com/redefining-society-podcast

Watch the webcast version on-demand on YouTube: https://www.youtube.com/playlist?list=PLnYu0psdcllTUoWMGGQHlGVZA575VtGr9

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Episode Transcription

Please note that this transcript was created using AI technology and may contain inaccuracies or deviations from the original audio file. The transcript is provided for informational purposes only and should not be relied upon as a substitute for the original recording, as errors may exist. At this time, we provide it “as it is,” and we hope it can be helpful for our audience.

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[00:00:00] Marco Ciappelli: Hello, everybody. This is a part of a new episode, and I hope you watched the first one or listened to the first one. It's kind of a joke, but we're serious. Um, we'll get to that. Bruce, how are you doing?  
 

[00:00:19] Bruce Y. Lee: Okay, I'm doing okay. I've got my, my, my glass tumbler here ready to, ready to get going. 
 

[00:00:25] Marco Ciappelli: I think it's becoming a tradition because when I was editing the other one, I, I had a coffee. 
 

I realized it's like, that's my way to be in a bar at about, uh, 1. 20 in the afternoon. So I'm not going to drink a beer or wine right now. You have water, but you still, still qualify as a drink, right?  
 

[00:00:43] Bruce Y. Lee: Absolutely. And you know, we're still going to be on a mission to figure out what the microbe, the cell, the carbon, the silicone, you know, whoever else is in the bar, what they're actually going to say. 
 

[00:00:53] Marco Ciappelli: So hopefully not many bacteria. 
 

Uh, so the story, the story here is that, uh, we, we get together once a month. This is the second time. Well, officially it's the third time, but the first one wasn't related to, to this. Although it's, that's where it gave us the idea to, to get together and, and have this, uh, This conversation, which is related to 1, 2, 3, 4, 5 things that got your attention in between our session. 
 

And I would say, let's start with a little introduction about yourself, which I can, I can read, you want me to read it from the website? Sure. Go, go for it. Bruce, why, because we need to put the why there, otherwise people might think that I just have a different kind of podcast. Uh, Bruce Wiley is a writer, a journalist, a professor, artificial intelligence, computational and digital health expert and interpreter, but not always in that order. 
 

So the question is, what order are we going to address things today? What do you feel more today than of all these things?  
 

[00:02:04] Bruce Y. Lee: Well, it all depends on, you know, it's all depends on the minute to minute or hour to hour, but you know So yeah, one of the things I do is I you know cover health health care science for Forbes And so, you know, we're in the bar, uh, we're in a virtual bar right now, uh, and it made, made me think of one of the things that I wrote about or covering, you know, I've been covering every now and then I'll cover these different types of TikTok trends. 
 

Um, and of course, you know, as you know, if you're told something to do something on TikTok, then it's absolutely 100% factually correct. Um, and one of the trends was beer canning. Uh, I just thought about that because, you know, we are in the bar and so there's actually this trend that's going around. Where people are telling you to take beer and you go out in the sun and you pour beer all over yourself. 
 

And that's supposed to help you tan. Um, because the hops in beer is supposed to activate. Melanin. That may sound all well and good, uh, but you shouldn't do that.  
 

[00:03:08] Marco Ciappelli: I was thinking that was going to be your point, but let's explain why.  
 

[00:03:12] Bruce Y. Lee: Yeah, well, so first of all, beer essentially has an SPF of zero, maybe one or so. 
 

So you're basically going out there and you're cooking out there. Um, in the sun with all the ultraviolet radiation, which can, as we know, can damage the skin that can lead to all these things like actinic keratosis. It can make your skin age, um, uh, faster. And, and, and I think for the most part, most people don't want their skin to age faster, but you never know. 
 

Um, you know, you might be trying to get that Gandalf look. Uh, but, uh, then, uh, you know, of course there's also the risk of. Heat stroke, but you know, everyone wants in particular is worried about skin cancer when you go out to the sun and get too much sunlight. Uh, so that's a real concern. So you're essentially having beer covering you without anything, even if you put suntan. 
 

You know, sunscreen that might wash off that sunscreen. Uh, so that's one problem. Uh, two is you smell like beer if you cover yourself with beer and that, uh, you know, last I checked, there aren't too many fragrances or colognes out there. There are beer based, uh, you know, sort of makes you feel, smell a bit like the, you know, the floor of a bar or the. 
 

for the bathroom in the bar or nightclub. That's not great. Um, so you're not going to attract a whole lot of people doing that. Um, but you may attract flies, flies and bees and things like that. Um, so yeah, so in general, not a good idea to do that. Uh, there are many safe ways to tan. You can tan with sunscreen, you know, even if you have SPF 30 or above, you can still. 
 

Um, so yeah, one of the things I do is I, you know, keep, keep an eye on some of these different types of social media trends. Um, you know, there, there is that, and then there's also a social media trend where people were advising, uh, folks to, uh, to eat. Borax, I, if you're familiar with Borax?  
 

[00:05:18] Marco Ciappelli: No. Well, it sounds familiar. 
 

[00:05:21] Bruce Y. Lee: It's bt it's not Borat, which is that, uh, yeah, that's the comedian, that movie, uh, uh, character. Um, and it's not the Lorax, which is that character from Dr. Seuss. Borax is actually a laundry detergent booster.  
 

[00:05:34] Marco Ciappelli: Okay. Yep. It, it kind of clicked something there. Okay. Yeah.  
 

[00:05:38] Bruce Y. Lee: Um, and in general, not a good idea to eat laundry detergent or anything associated with laundry detergent. 
 

[00:05:44] Marco Ciappelli: Wait, wait, wait. Is that the one that come in, in little, uh, little  
 

[00:05:49] Bruce Y. Lee: type pods? Those are type pods.  
 

[00:05:51] Marco Ciappelli: Wasn't something with that too, a while back? Yes. Yes. See, there's too much stuff. Good stuff coming on.  
 

[00:05:57] Bruce Y. Lee: Exactly. Yeah. I actually wrote about that, uh, several years ago, I believe back in 2018 or so that was a social media trend. 
 

The type pod challenge where you basically take these type pods. Put it in your mouth and show people that you're holding in your mouth. Um, not a good idea. Uh, in general, like in general, laundry products do not belong in your mouth. That's a general rule. Um, when you sit there and you're doing your laundry, don't sit there and say, gee, I wonder what that would be like in my mouth. 
 

That's not a good idea. Um, so there was that, and now there's this borax trend where people are claiming eating this laundry detergent booster is going to do all sorts of things like protect you against Alzheimer's and cancer, or I can't remember some of the other claims, but infections that can like protect you against infections. 
 

Um, And, you know, my point is like, if you're poisoning yourself with laundry detergent, then yes, that may protect you against other stuff, but because you don't have an opportunity to get other stuff, uh, but it's a bad idea. Yeah, you cannot get all sorts of problems by eating borax. So don't eat borax.  
 

[00:07:09] Marco Ciappelli: Wow. 
 

So many places we could go with this. Um, so, you know, I think we were talking last time about AI and, uh, and how you start your days asking. CHAT GPT, what to do today, because you trust it so much and, and that, that's, that's a good joke, but at least I think it's, it, it's almost like one of those situations where reality is weirder than fiction. 
 

Right? So, you know, compare with these ideas. Um, it sounds to me that I will listen to AI more than TikTok to start. So the point is, why, why do you think that there is these trends that are clearly horrifying? Let's, let's use the word and why people do, do they really believe it or they just go along with the, with the joke for exposure and I don't know, some celebrity moment. 
 

What's your take on that?  
 

[00:08:09] Bruce Y. Lee: Yeah, I mean, I think there's a combination of several things and, and there's a lot of tile, um, tie in with. AI and CHAT GPT as well. And I actually had a conversation just yesterday about this. Uh, there's concerns that with, you know, naturally, AI and CHAT GPT, lots of potential benefits. 
 

But one of the potential pitfalls is that there can be a tendency to lean on things which are simple, meaning that, um, you know, if something's presented in a simple way, a simple solution, then that can be more digestible. So, uh, so I can explain how that applies to AI in a second, but, but when it comes to like TikTok messages or social media messages, many times they're very simple. 
 

And when you get information that is simple, but there's maybe some potential grain of truth, then, you know, in general, if you sit there and say, Oh, that doesn't make sense, but there's something like that. When something goes viral, like you hang a grain of truth on it and it tends to spread very quickly. 
 

Now. With the Borax situation, if you look in the scientific literature, there are some studies that have looked at the potential benefit, potential, because there's just a few studies, of using Boron, B O R O N, Uh, to treat, like, to treat potential different types of cancers, to potentially help with rheumatoid arthritis. 
 

Uh, people looked a little bit, maybe, you know, boron in, um, uh, nutrients, like in food, like you can have different levels of boron in legumes, for instance, or, um, you know, uh, different type peanuts and those things like that. Fruits, vegetables. But Boron is not the same thing as Borax.  
 

[00:10:02] Marco Ciappelli: Sounds like a new Elon Musk product. 
 

You just add an X.  
 

[00:10:06] Bruce Y. Lee: Yes, exactly. So, um, but that's the argument that's being used by some people on like, there's this kind of blending of info and it's confusing. And, you know. People who are not familiar with what Boron is versus Borax might say, Oh, well, but yeah, there are, I guess there are some studies which look at Boron. 
 

Um, so there's a lot of that going on. So if you dig deeper into some of these social media trends, you'll see that there's some of those complexities. You know, you sit, you sit back and say, Oh, that's silly. Why are people doing that? But then you say, well, okay. There's certain kernels of truth that maybe cross over to some degree. 
 

Um, or people think of, Oh, it's something that's used for laundry detergent. Therefore it cleans stuff. So, you know, why not put it in my mouth? Well, obviously that's a, that's an issue, but so what we're seeing is it's interesting, it is a sign of like. You know, what are the factors that help something communicate? 
 

Communications occur. What are the factors that help something spread? If you think back in, I don't know, high school, um, you know, how rumors spread, uh, and so if you didn't know someone and you hear this rumor and you're like, oh, okay, uh, that person wears this shirt. So, okay, that probably makes sense. And you don't really know, that's in high school where you actually can see the person. 
 

Imagine on social media where you don't really see people and all you do is see this image and you think that maybe it makes sense. Um, so that has a lot of implications because, you know, when you jump back to CHAT GPT, uh, some folks, some folks the other day were worried. They say, well, people start just relying on AI things without asking, like, how did they actually come up with it? 
 

Um. And also, uh, well, they start relying on AI analyses without saying, okay, well, what about alternative analyses or how do we actually come up with something like this? And that's really key because we have to remember that when you quote unquote AI something, there's an algorithm behind it, right? 
 

There's some type of algorithm. It can be very simple. It could be someone just flipping a coin or it can be something really complex. And we don't talk about that. As much because we all throw it in one category. Um, so we really need to stay curious and ask ourselves what's actually behind the algorithm. 
 

When someone comes to you and say, I've gotten, you know, an AI approach that can help you, uh, improve your business, or I have an AI approach that can help you decide what foods to eat or an AI approach that can help you determine the treatment you have to add. Next question should be, well, what's behind that? 
 

How are you actually figuring that out? And it's very similar with social media trends. You're like, okay, that seems really popular. Okay. You're, you're making some kind of sense with that. Well, what's behind that? How did you come up with that? Why are you telling me to do this? So I do see some crossovers in terms of that. 
 

And we really have to, you know, think about that, I think.  
 

[00:13:14] Marco Ciappelli: The crossover for me is that you can't just pinpoint everything to technology because ultimately we are the one that made technology. I mean, I wrote a quote the other day, I put it on my website It is, AI is only human after all. Because... We, I mean, even CHAT GPT, it goes on and read everything that we wrote so far in the internet. 
 

So if it's learning, I mean, it's kind of like replicating our biases, replicating some paper that maybe somebody else put out there and it was completely fake. But hey, it's on the internet. It must be true. They said it on the radio. I guess the Martian must be here on our planet and we're just going to go ahead and believe it. 
 

And what surprised me the most is that we have such a powerful tool. We have the library of Alexandria of modern day in our hand, in our phone, and we just go in and And read, read jokes on it, which is no use in exactly what the power of it is. I mean, you can cross reference instead of just blindly following the crowd. 
 

So it's, it's very much a human problem. It's I, in my opinion, it's, it's a human problem, not much of a technological. 
 

[00:14:39] Bruce Y. Lee: It's what goes into it. I mean, it's all like, you know, technology in itself is neither good nor bad. It's what, what it can facilitate and what, yeah. And then you're building things in the technology that will match human decision making. So it's what, what are you actually programming into it? Um, and you know, that's another thing to keep in mind that also, you know, sort of riffing on this, this, this, um, Uh, crossover with between AI and social media, we have to remember that, you know, there are algorithms that are governing who's seeing what on social media because, you know, social media obviously is this huge flood and fire hose of stuff. 
 

So you don't see when you, when you log onto something, you only see a very small percentage of what's actually on that platform because it's what's being presented to you. Uh, so I use the example. I remember I was writing, um, but I was writing a couple of years ago, uh, something important about, Yeah. Uh, you know, people were wondering whether you can transmit. 
 

COVID via farts. So I wrote about some, you know, the evidence because, you know, people worry about, Oh my goodness, I mean, if people farting, am I going to get it? And I said, you know, don't, don't worry too much about that. There was some, like some rumor that was spreading around that, that, um, and spreading around pun intended that, uh, that, uh, farts could transmit. 
 

So I was, I was sort of debunking that. So that also, as a result of that, I guess I. Maybe was searching for farts. Um, and then I also, for another reason, uh, uh, had, you know, some people had sent me some animal videos, videos of animals so that I looked. Look at some of those videos. Well, lo and behold, when I logged onto, uh, YouTube, um, I was suddenly presented with a lot of videos of animals farting. 
 

So, basically the algorithm said, you obviously like farts, and then you obviously like animals, so here's some, some, um, some videos of animals farting. So the algorithm were doing that. They're presenting you a certain thing, and then, as you talked about, um, you know, how do these things spread? Well... The social media platforms will also identify the people who are more likely to be interested in seeing something and they'll see it and then that will propagate as well. 
 

So it's, it's the interface between, you know, what the technology is doing and what people are actually doing as a result. So that and. Bang, we suddenly have a social media trend as a result, you know,  
 

[00:17:12] Marco Ciappelli: and for something is very useful because if it's true Let's say, you know, let's look at how that started or I mean commercially started Amazon right like that if you like this then you're gonna like that and Make sense if I buy books about the Lord of the Rings. 
 

I made like The Hobbit. Okay I mean, like Harry Potter, I mean, like, uh, you know, a lot of other in this genre, but don't ever make the mistake to go and buy something for, I don't know, a kid because all of a sudden, I mean, I like the Lorax. I like, uh, all the, the, the, the little, I mean, the, the fairy tales. 
 

But then all of a sudden it's like, Oh, it must have changed his taste. Now let's just give him everything with, you know, with, for kids. So it's, it's, that was the beginning of a very simplified algorithm. And now it's much more complex, but it seems to me, I agree that it's still actually leveraging on this very, I mean, it's kind of like, don't share Amazon account with your wife because then you're, you're going to have to, you know, you're going to be suggested makeup. 
 

I may not need it. Right. So it's, it's so smart and yet not so smart. That's like a smart point.  
 

[00:18:31] Bruce Y. Lee: Yeah. It's interesting because I've, I've seen, um, you know, I w I've seen this over the years too. I still remember that, uh, it was probably about, well, it was definitely about 12, 12 or 13 years ago. This was after the 2009, 8, pandemic. 
 

And so what many people don't realize is, uh. Early on in the flu pandemic, there was discussion about whether to do things like close schools and, you know, close workplaces and things like that, but it was determined, you know, and, and, and our team was involved with, uh, this work trying to help determine, well, is it worthwhile closing schools and all those things like that? 
 

And we determined no, no, no. Far too expensive, not worth it. There's going to be a vaccine coming down in the fall. So probably not necessary. So I remember after the pandemic, there was like a get together of, you know, people who were involved in the response. And one of the things that was said is, Oh, uh, we have to be prepared for this because then, you know, sometime in the future. 
 

Not if, but when a pandemic comes around, there needs to be concerns about doing non pharmaceutical interventions. So, you know, mask wearing, social distancing, closing school. Should it be done? How should it be done? Etc. And I remember there was this conversation about, well, we need to build computer models to represent what might happen. 
 

And, uh, I remember the conversations start off and there's a bunch of people in the room and someone said, okay, let's see, uh, what type of people are more likely to, uh, panic more, uh, men or women? Someone said that. It's like, that, that's a ridiculous question. Like, you can't say that, oh, You know, one particular sex or one particular demographic is more likely to panic than another. 
 

You know, it's very, there's all kinds of people out there and all kinds of, you know, things, your backgrounds, your beliefs, people around you. All these things like that. Uh, but I give that as an example that, you know, you can come up with a very simple, simple behavioral algorithm that just like kind of just uses stereotypes and biases and just say, this person's going to do this, this person's going to do that, and I think that's some of the stuff that you've seen out there, some of those algorithms, um, and there's a real danger behind that because it doesn't really represent the person. 
 

Uh, it can actually misrepresent the person in many ways. Uh, these algorithms are getting more complex, but, um, but there's still simple ones out there. So we really have to look, again, we have to look under the hood what's actually being produced.  
 

[00:21:14] Marco Ciappelli: Yeah. You know, I'm going to pick your brain on this because I mentioned I'm kind of writing this philosophical thoughts about sociology and society and, and, um, and technology. 
 

And then funnily enough, I use, I have dialogue actually with CHAT GPT. And it's interesting because if you ask the right questions and if you give the right prompt, I'm actually learning a few things. It makes me think, right. And I think I mentioned this last time. So there is one that I. I kind of compare, you know, going into space and when people ask you, you know, like our friend Charlie's Kamarda as an astronaut, like why you go to space and, you know, to explore because that's what humans do. 
 

And, and also it's a way to learn about ourself. I think like. Going in space has convinced a few people, not all, that planet is actually a globe, right? It's spheric, it's not flat, but not everybody's on board.  
 

[00:22:12] Bruce Y. Lee: It's not flat, Marco, what are you talking about? I'm a little, I'm a little distressed by hearing this news. 
 

[00:22:17] Marco Ciappelli: Like I said, not everybody is on board with that. But, so, I was running a parallel with looking in all this artificial intelligence now and technology. It's a way to really say, look, it's not... This is just the way we are. And I don't want to be dystopian, but there is a reason why we've been doing war and we're believing in really stupid things and that we've been fighting science even when science tells you no, look, this is really proven. 
 

This is what it is. And now we find all that in the tools that we create. I mean, they are reflecting ourselves. So... I don't know what's your thought on these and how these maybe apply to, to medicine as well. I mean, you, you work with data, you're, you're showing people, look, this is a fact, and people are going to be like, yeah, no, I don't care. 
 

Uh, don't, don't, don't tell me how I should think. Um, yeah, but this is a fact.  
 

[00:23:15] Bruce Y. Lee: Yeah. So you're talking about how some of this stuff can elucidate how people are thinking about things or, um,  
 

[00:23:23] Marco Ciappelli: Well, you know, it's kind of like, okay, you know, pointing finger to how bad AI can be. It's kind of pointing the finger on how bad human can be because it's carrying the same biases that that we always had. 
 

[00:23:40] Bruce Y. Lee: Exactly. Yeah, so, you know, I've been in the computer modeling and AI field for for a while now and one of the things that we talk about is that When you try to build models or you try to build algorithms to represent how people think, uh, or act, it can actually tell you a lot about how people think or act, right? 
 

And so, um, you know, you, every day you make decisions about things and people, but if you were actually sit there and kind of write it out, like sketch out, why are you making certain decisions? Why are you making certain assessments? It is very enlightening. Because we all, we all assume, you know, I've, you'll hear it as many times. 
 

People will say, Oh, I don't have a bias bone in my body. Or, you know, I, uh, you know, I'm very clear. I don't see color. I don't see all these types of things, but then when you actually look at it, you know, everyone has their biases. Uh, there's not a single person on earth that does not have significant biases because whenever someone walks into the room. 
 

Or something happens, you immediately already have a mental image of something. Like you already make some kind of assumption. And, you know, many times we have to hold ourselves back and say, Oh, no, don't assume that person is that way because they're wearing that shirt or they look that way or something of that sort. 
 

And it can be very enlightening to actually sketch these out and write these out and then look at that because, like you said, that tells you more about human behavior. Um, so you're absolutely right. When people talk about AI and those things like that, ultimately it comes down to what are humans putting into it. 
 

Um, and so we should work more on look at more of that, look at that more in a positive way and just say, okay, this is giving us some insight. That's why it's so important to know what's under the hood with all these algorithms. So important.  
 

[00:25:42] Marco Ciappelli: Yeah, you know, make me think about you probably read it. It's a it's a book called Blink. 
 

The Power of Thinking Without Thinking, uh, Malcolm Gladwell. And that's a brilliant book. I remember I'm actually pull it out now 2007 and it was like, you know how you make assumptions and then you dub those assumption because it's not maybe logic, but you already know that. I remember the example of Some expert of art, he knew that a certain painting was fake, but everything, every data was telling him that it was not fake, but his first impression, he noticed something that blink that, that second, you know, so what I'm saying is sometimes it's actually a positive thing that we make this assumption and we made this decision immediately, but we don't control it. 
 

Right. So there is the good. And then there is the bad way you make your, and your assumption is really wrong.  
 

[00:26:45] Bruce Y. Lee: Yeah. You know, if you look at, for instance, a lot of these approaches, AI approaches, you know, machine learning, for instance, etc. It's important to understand how these come about. They, you know, what they do is they look for, different algorithms are designed to look for trends in different ways, or, you know, kind of go through a series of processes. 
 

And they've been developed in ways to basically mimic, I mean, that's how humans think. Like, for instance, if you develop an AI algorithm that says, I'm going to look for any association in general between two or three different factors. And then if I see an association. I will apply it. That's what we do in with, from a human standpoint, but many times that's biased. 
 

Right. So say, say I go around and like every time someone wears a hat, you know, put a pie in my face or it happened once. Oh, okay. Oh, again, a third time. Then I started saying, I got to watch out for people with hats because people wear hats. They put a pie in my face. Right. But then you sit there and say, well, that, okay. 
 

Makes total sense. I mean, you don't like put on a hat and suddenly realize, boy, I really need to put a pie in someone's face. Right? That's just, that just was happenstance. That just happened to be that. Maybe it's some other factor that drove those three people to happen, put a pie in your face. But that's what people will do in their thinking process. 
 

And then that's what some of the AI algorithms will do. They look for that trend and they say, okay, this is what I think is going on. Um, and we, and many times we forget that, right? Because we think that an AI thing is just someone that's thinking it's been programmed a certain way.  
 

[00:28:36] Marco Ciappelli: So I think I was just asking you these before, and then we kind of got sidetracked, but Is this helping medical research more than, I don't know, damaging it? 
 

And I mean, I know it does help, but does it also help people to understand what's happening under the hood? Or maybe as educator, we're not doing a good job at that, see what I'm, where I'm going with this.  
 

[00:29:06] Bruce Y. Lee: Yeah. So in medicine, it's interesting. And this is this, and there's been a lot of news that's been cropping up recently about this, about, you know, different types of applications of AI to, uh, uh, different aspects of medicine. 
 

And I think there's certainly areas where it can help immensely. There's certain areas where it can help, but depends on how you're actually applying it. And then if you apply in the wrong way, it can hurt. And then there's certain things where we really should not be using it. Um, and so I would say areas where, and there's a lot of areas like this medicine where that involve very, um, you know, using kind of large amounts of data, things that are just very, like, intensive that you don't necessarily need to have a human. 
 

within it, or you can have a human on the site where we can double check what a human does. So like, you know, one example of course is, you know, you looking at like x rays and CT scans and those things like that. Sure, why not have, um, some type of computational or AI approach to help synthesize all that information and provide some additional information? 
 

You can still have a human checking to make sure it makes sense, but that can help immensely. Or when you're working with large amounts of data to give you some insights. Those are areas when absolutely can help. I'm seeing some areas where they're talking about, well, can we use AI to show empathy? Um, and that's, that's opposite. 
 

Like, I understand in the absence, like, if you have absolutely no one, that can help, but that can also go down a slippery slope because, uh, empathy is a complex thing, right? So, some people try to break it down and say, well, empathy is, you know, saying things like, oh, that must be hard for you. That must be hard for you, but a lot of it's really actually understanding a person's situation, knowing someone over years, you know, like, like, for instance, if you have a doctor that you've known for like 10, 20 years, that's very different from a doctor that you've known for like 10 minutes. 
 

Right. So, so we just have to be careful about those things. And I think one of the challenges here right now is we're seeing it applied in a very haphazard way. Um, so in some cases, I think it can be very helpful and other places more challenging. We also have to remember that diagnoses, um, It's a combination of looking at the facts, looking at, you know, the evidence, it's never 100% and then you're also bringing in like balancing factors, like balancing the personal person's personal situation and those things like that. 
 

So there's a lot of complexity involved in there.  
 

[00:31:48] Marco Ciappelli: Sometimes I feel like we're kind of rushing the future. Wanted to be there, but it's not really there. It's kind of like when people I mean you mentioned empathy and When you hear in the news that some researcher like Google or Microsoft or any other AI program, they're like well I'm really seeing cognitive reaction in the machine and everybody's else like, I think you want to see that that doesn't, they don't really love you. 
 

It's just binary number going in there. You want it to love you, but maybe you're kind of deluding yourself. So maybe we're rationing. We need to keep it. I think in the way in the things that really work and it's kind of like tunnel focus objective I know AI works really well when you're trying to make it to human. 
 

I don't like the word Okay, why do we call it? Intelligence artificial intelligence. I don't know. It's intelligence is a pretty big. It's pretty high standard. We couldn't call it I don't know. Artificial, um, kind of getting there.  
 

[00:33:03] Bruce Y. Lee: That would be, uh, A K, uh, G, uh, A K G T. A little harder to say. Yeah,  
 

[00:33:12] Marco Ciappelli: but I mean, you know, you set the expectation pretty... 
 

Pretty high. The bar is high.  
 

[00:33:19] Bruce Y. Lee: Absolutely. Yeah. I mean, I think it's, you know, again, that's the problem with, with catch phrases and catch words, they, they don't really kind of, um, portray really what's going on and I've, we've seen this many times before that when technology comes out, there's not really, there can, many times there's not really. 
 

Thinking about how best to use it and how best to apply it. Like, you know, technology gets, comes out, everyone kind of rushes and says, Oh, and it becomes the buzzword. So everyone's like, let's try to incorporate it. And one of the things I've seen in the AI field is, you know, the quality of the AI ranges from stuff that's very good and very well thought out to just, just garbage. 
 

Like people will call something AI, but it's really garbage and it has nothing to do. So people just rush out just like any fad, they just rush out and they know if I, if I attach this to this, it's going to be cool. I'm going to be cool. I'm going to have lots of friends. I get, you know, be able to get funding or people are going to buy this stuff. 
 

And then, you know, there's this rush. And then what happens is there's this rush, you get all these applications and then you have to sit back and say, Oh my goodness, what kind of mess did we create? And let's, you know, now we've got to clean it up. Instead, what you have to do is at the same time, you have to start thinking about, well, what's the best ways to apply this? 
 

What, where is this really needed? You know, how do we sort of integrate a lot of the human and social and behavioral aspects into what we're actually doing and do it sort of in the smart way, otherwise we're going to, we're going to miss a lot of opportunities. I think that's, I think that's one of the big challenges right now. 
 

[00:34:54] Marco Ciappelli: Yeah, yeah, I don't know the role of regulation. I think in this case. It's uh, it's quite important I know the few days ago. There was a big meetings at the White House With big company in AI. They're saying yeah, it's a voluntary Subscription to the program so we'll see if they actually do it, you know, but you know, they were there I don't believe in pausing it because it seems A train already left. 
 

You can't just pause it. Like, I know everybody stopped that, but you know, the fact that we're talking about it, but I'm afraid it, I don't know. I don't want to, I don't like to compare it to, to the atomic bomb. And we can talk about a Hoppenheimer, the movie or other things, but it's, uh, it's there and I'm going to stop it. 
 

[00:35:47] Bruce Y. Lee: Well, that's why things, things like, for instance, I mean, you know. Your, your, your podcasts, uh, Marco, where you were talking about technology. I think those are things are really important because these are conversations that need to be had. And then you, at the same time, when you're developing AI, you need to develop the other stuff too. 
 

You need to develop different types of infrastructure. You need to develop different ways. You know, people kind of thinking about these issues, people think about the straight, you've got to develop strategies and those things like that. Um, and, uh, you know, we've just seen it time and time again, technology will come out. 
 

It will never be. It doesn't get fully leveraged like you've missed opportunities. It gets used haphazardly right in some ways wrong in other ways. Um, so this has been a repeat cycle. So I mean, it's great that you're, uh, we have people like you talking about it because it needs to generate discussion and there needs to be more support for that. 
 

I think. Yeah,  
 

[00:36:43] Marco Ciappelli: I agree. And most of all, don't eat borax.  
 

[00:36:48] Bruce Y. Lee: Do not eat Borax. Do not cover yourself with beer if you want to tan. In general, it's not a good idea to cover yourself with beer. Uh, if you want to go to a date or a job interview and you cover yourself with beer, most likely it's not going to come out. 
 

[00:37:04] Marco Ciappelli: Unless, unless you apply to work at Oktoberfest in Munich. In that case, it may help.  
 

[00:37:10] Bruce Y. Lee: Then it may be positive. Yeah, it may be a positive thing. The Borax, still not a good idea. Still not a good idea. But the beer might,  
 

[00:37:20] Marco Ciappelli: wow, I'm wondering, like, and then, and then we close because of course, we will come back next time and take it over. 
 

I'm sure we're going to go in AI again, because you have to talk about that. But like, so if these algorithm would detect that people are pretty much hurting themselves by talking about eating more like algorithm, please look for eating food. Mouth and borax in the same sentence You know alert and let's stop this but then You go into politics, into like freedom of creating content and one thing and another, like, could we use it for good? 
 

Like seriously, like when you monitor chat for terrorism or, uh, you know, child pornography and then you act. But I mean, you know, can, can we maybe leverage technology for this kind of thing? I'm not comparing that with what I just said, but in a way it's like, why not use it if we have it?  
 

[00:38:26] Bruce Y. Lee: I remember actually watching a, um, a speech by speaking of Borat, uh, speaking of Borat Cohen, the, um, the actor who plays, uh, he, he gave a talk maybe, I don't know, several years ago where he was talking about how, um, you know, it's not, you've got social media and people talk about like, you know, freedom saying whatever you want to say, well, like in the past, if you wanted to publish something in a major, you know, You know, newspaper or anything like that, but you can't just say anything, you know, so, so, you know, that when you're reading, picking up the New York times, when you're picking up time magazine, it's been through editors and very careful, but it's been fact checked and all those things like that, you know, for the most part, you know, every now and then there's, there's, there's, there's something missed and then they go back and for the most part, everything is, you know, checked and there's, there's legitimacy behind it. 
 

Yeah. On the flip side, you have social media. None of it's checked. I mean, maybe some to some degree. There's a big difference there. So you, you have to say, you know, it does that make sense? Like you, you can't just say that, Oh, okay. This is, um, you know, this is the same thing as, as a media publication. It isn't. 
 

Things have been checked a lot. Whereas social media, you can, you can, you can make something up tomorrow and just post it up there and it could, could go viral. So we have to really decide. Um, if, if something is being treated like a legitimate source, then does that need to have the same checks that other real legitimate sources have? 
 

Those are real, real questions that need to be asked. Because that's  
 

[00:40:13] Marco Ciappelli: a real, real, real, real deep question on, I mean, yeah, we've always regulated that. That's why we used to say, if they said it on TV, it's true. Because yeah. You know, unless you lived maybe in, uh, in a country that was making propaganda, the, the way of governing, then, uh, then yes, you know, like somebody check fact that when you look at a documentary or, or any show on science, you usually say that there is a lot of people working. 
 

In the background, that fact check, that they research, that they interview, that they tell you who they interview, what the bibliography is for writing a certain article. And now you just wake up one morning and go out there, which is beautiful from a access to create information. And it really suck because for the same reason, because it's too easy to create information. 
 

So I think with that we can leave the bar. I think it was a really good conversation. We're in for about 40 minutes. Uh, there is more where they come from. There's this bar that you're sitting in. It's really cool, by the way, that AI made that.  
 

[00:41:33] Bruce Y. Lee: Well, yeah, thank you. I think it's a great bar. As you can see, there's no one else here. 
 

Uh, so maybe it's the fact that I pour beer all over myself that that's why no one else is here. But who knows  
 

[00:41:43] Marco Ciappelli: is the is the Bruce bar. There you go. All right. Well, Bruce, uh, I always look forward for to this conversation, not knowing what we got ourselves into, but I hope people enjoy it. I enjoy it. Make me think. 
 

Uh, I learn a lot of stuff from you and, uh, and I hope you are also enjoying it as I hope that the entire audience is so there'll be linked to all your social media. There'll be linked to, uh, the YouTube video if they're listening, or if you're on the YouTube and then you want to share the podcast, you can do that. 
 

And, uh, yeah, just subscribe. Stay tuned. We'll get together again in about a month from now. And who knows? I mean, a month is. It's a lifetime in technology and, and, uh, and medicine as well. So a lot can happen. All right. Well, stay safe until then. And I'm really looking forward to meet you again in the same bar. 
 

Me, you, a carbon, a silicon and a cell, and then we'll see what happened. All right. Very good. Take care, everybody. Bye. Bye.