Nursing U's Podcast
Nursing U is a podcast co-hosted by Julie and Caleb. We embark on an educational journey to redefine nursing within the modern healthcare landscape.
Our mission is to foster an open and collaborative environment where learning knows no bounds, and every topic—no matter how taboo—is explored with depth and sincerity. We delve into the essence of nursing, examining the intimate and often complex relationships between nurses and their patients amidst suffering and death.
Through our discussions, we aim to highlight the psychological impacts of nursing and caregiving, not only on the caregivers themselves but also on the healthcare system at large.
Our goal is to spark conversations that pave the way for healing and innovation in healthcare, ensuring the well-being of future generations.
'Nursing U' serves as a platform for examining the state of modern civilization through the lens of nursing, tackling issues that range from violence, drugs, and sex to family, compassion and love. We will utilize philosophy, religion and science to provide context and deeper understanding to the topics we tackle.
By seamlessly weaving humor with seriousness, we create a unique tapestry of learning, drawing wisdom from the experiences of elders and the unique challenges faced in nursing today.
Join us at 'Nursing U,' where we cultivate a community eager to explore the transformative power of nursing, education, and conversation in shaping a more whole and healthier world."
Disclaimer:
The hosts of 'Nursing U', Julie Reif and Caleb Schraeder are registered nurses; however, the content provided in this podcast is for informational and educational purposes only. Nothing shared on this podcast should be considered medical advice nor should it be used to diagnose or treat any medical condition. Always seek the guidance of your doctor or other qualified health provider with any questions you may have regarding a medical condition or health concerns. The views expressed on this podcast are personal opinions and do not represent the views of our employers or our professional licensing bodies.
Nursing U's Podcast
Ep #016 PT 2 - Resilience and Reflection: Navigating Ethics, AI, and Purpose in Nursing
Why is it that some individuals, despite facing overwhelming challenges, are drawn to the nursing profession? Julie and Caleb share personal tales of unexpected journeys into nursing, shaped by cultural norms and unique life experiences. They unravel the complexities of evidence-based practice, spotlighting the lurking shadows of bias and manipulation in healthcare data. This episode invites you to ponder the critical role of data integrity and the diverse perspectives that enrich our understanding of caregiving—from philosophy to art.
Imagine a world where artificial intelligence grapples with the same timeless questions about consciousness that have baffled humans for centuries. We explore this fascinating intersection, drawing connections between AI's quest for information and humanity's ancient pursuit of knowledge. Reflect on personal stories from the field of electrophysiology, which demonstrate the nuanced dance between human data and AI, guiding us to question what it truly means to be human.
Purpose steers our every action, and within this episode, it becomes a beacon guiding the ethical use of data and AI in healthcare. We traverse history, examining how figures like Florence Nightingale have leveraged purpose to transform care, and consider the ethical implications of AI-driven practices today. Through tales of resilience and survival, we address pressing issues like nursing suicide, urging listeners to find meaning not just for themselves, but for the greater good of their communities. Join us in this quest for understanding and solutions in an ever-evolving healthcare landscape.
He was basically saying that you know, there's not a lot of studies, because studying energy and dynamics like that is very difficult to been involved in. Had our hands in leaned on the bed to hugged the poop, the pee. You know the crying, yeah, the blood, the blood of someone else.
Speaker 2:I was. Actually I wasn't going to be a nurse, and I never started, as a five-year-old guy, thinking, oh yeah, when I grow up I want to be a nurse. Right, that's not the guy's dream, no that's not the guy's dream. Everybody told you you're good. With the knowledge that you have and the aptitude that you have, you can be a doctor if you want it. It's just not my thing. Your head is programmed to yeah, you study the sciences, you do this, you do that. But yeah, I'm also Asian by the way.
Speaker 2:And the Asian thing is, you're going to be a doctor or something else, or an engineer maybe. Came here when I was about 19. And at that time I had only two years of physical therapy school and I only had two more years to go. And here my grandma's going. You need to come over now because your petition came up.
Speaker 1:Hi, I'm Julie.
Speaker 3:And I'm Caleb, welcome to Nursing U, the podcast where we redefine nursing in today's healthcare landscape. Join Julie and I as we step outside the box on an unconventional healing journey.
Speaker 1:Together, we're diving deep into the heart of nursing, exploring the intricate relationships between caregivers and patients with sincerity and depth.
Speaker 3:Our mission is to create an open and collaborative experience where learning is sincerity and depth. Our mission is to create an open and collaborative experience where learning is expansive and fun.
Speaker 1:From the psychological impacts of nursing to the larger implications on the healthcare system. We're sparking conversations that lead to healing and innovation.
Speaker 3:We have serious experience and we won't pull our punches. But we'll also weave in some humor along the way, because we all know laughter is often the best medicine.
Speaker 1:It is, and we won't shy away from any topic, taboo or not, from violence and drugs to family and love, we're tackling it all.
Speaker 3:Our nursing knowledge is our base, but we will be bringing insights from philosophy, religion, science and art to deepen our understanding of the human experience.
Speaker 1:So, whether you're a nurse, a healthcare professional or just someone curious about the world of caregiving, this podcast is for you.
Speaker 3:One last thing, a quick disclaimer before we dive in. While we're both registered nurses, nothing we discuss here should be taken as medical advice. Always consult with your doctor or a qualified healthcare provider for any medical concerns you may have. The views expressed here are our own and don't necessarily reflect those of our employers or licensing bodies.
Speaker 1:So let's get started on this journey together. Welcome to Nursing U, where every conversation leads to a healthier world, will we?
Speaker 2:even be documenting, I would say, and more Okay explain.
Speaker 3:That's really what.
Speaker 2:I'm asking Just everything that you said and more. Okay, now, some people who might be listening to the podcast, who are also nursing pharmacists, might say, oh, we don't do that. That's not representative of everything that we do. Of course it's not, but my experience is each hospital implements it a different way. Right, all that aggregate information, once you collect that becomes a model, once it becomes a model for the hospital, they can use that now to deliver care not just on an individual basis, but also as a health system-wide itself. They can predict, okay, within this population in the city that we have, we are expecting how many 89-year-olds that are going to be happening in so many in such, let's say, in the next five years. Anticipate the needs at that time.
Speaker 2:That can also affect legislation, because with that data legend, how does legislation happen? Legislation happens coming from data also, right, this is the data that we have. In the next five years, we are expecting, let say I'm just going to give a ballpark figure let's say, 19,089 year olds that will need care. How many nursing homes will we need at that time? How do you predict how many nursing homes you need in a certain community?
Speaker 3:I mean, when it comes to data, like I'm very skeptical. I mean, anybody that has taken any statistics class can see how easily manipulated data can be, and so that kind of makes me cringe. Good, who is in control of the data and who is manipulating the data to serve their own needs? I'm writing about evidence-based practice. Julie knows about this. She's read some of it. I'm not ready to share it yet. I'm not ready to share it yet, but the fundamental flaw in evidence-based practice is biases.
Speaker 3:Whoever is managing the research data is susceptible to external biases, which are money, or one of them is money or influence money, influence power. The other one is, you know, I don't know if scope creep is the right terminology, but just the idea that if you have a personal bias, that it should be this, then that is going to influence how you analyze and contextualize data. So there are all these biases that impact. You know how much of the system that we've created is influenced by data that was manipulated for any one of those purposes, and how has that impacted us? It could be, does that?
Speaker 2:make sense? Yeah, it does, and that's why the work that we do as nurses of rheumatists is important to safeguard the data itself in order to be true to your discipline, and at the same time you can't let's put it this way, you can't really isolate bias. It's hard to isolate bias, but you can minimize it right. You can also put safeguards on it so that it's a secure environment to operate in. And at the same time you're also verifications Also. Verifications is very important so that you just don't say, okay, let me give you an example the apple is red. If you say the apple is red, well, is it really red? What if I turn off a certain wavelength of light and I can make it green, interpretation right, so that in a way, the application of that light is also a bias, right. So you got to make sure that when you design your icu or you design um uh, for example, um, I'm looking for a practical application when you're starting an iv, what, what things come up?
Speaker 2:when you're starting IV color right, color of the skin you can isolate certain things so that what stands out is a vein that you can see, right, there's technology out there like a pegaderm or I'm sorry you might want to cut that out or like a plaster that you can apply to it and makes it more visible for people to see the vein once you apply it, and that's how you start driving. There's technology out there that can do that, or you can apply a lamp that will expose that, so you can see that you can use bias in different ways that will affect the outcome. Bias is not necessarily wrong. It's just to say the facts lean towards something else, but how are you wondering? What you said about who holds that that's kind of how bias is applied to is where do you put that light? Where do you shine that light? Whoever holds that light and is shining it on it actually has more power. Make sense, yeah, so that's how I look at our jobs as nurse informaticists doing that, and one thing is you need to learn how to analyze data as well.
Speaker 2:Nurse informaticists are known. One of the things that we are also trained is to how to analyze data on a higher level so that we can spot these biases. That is not making sense. Oh Right, that's good. Yeah, I can show you. I know how to manipulate One thing. Getting the numbers is one thing. Making it represent something is another thing. Yeah, absolutely. And that's another thing that an informaticist do is we make sense of numbers, we chuck it up to the C-suites so that they can see what kind of population they have and where they can make changes in order to appropriate funds or appropriate resources. Better, right.
Speaker 1:What would be an example Like? What would be an example of something that you'd be like oh my God, like you're getting all this data that like this isn't, this isn't working or this doesn't look like it's right. Something that you would take to the C-suite to be like we need to look at this. Can you think of an example?
Speaker 2:uh, let me see one thing that's pretty common would be uti prevention. Right, uti prevention. You look, you look at several. What factors you look at? What factors affect, um, uh, prevalence of utis or prevalence of uh? Are UTIs happening? For one thing, why in this hospital? Why in that unit? Why, what kind of surgeries are happening, the most surgeries that are producing these UTIs? Why is that?
Speaker 2:What can we change within that environment to do it Okay? What can we change within that environment to do it? Okay? Could it be? Could be as simple as you know what environmental I would call this I'm trying to think of the term for it Environmental engineers, whenever they suppose, what schedule do they have to clean those lights that they have during operations? When does that happen? What falls under that? You know those microbes can. Actually, if you're doing it in between processes, in between surgeries, does it happen at that time? Right? Because some of these things, if they're cleaning, you know the way that they clean stuff. You can actually see the data right there if you, if you get into the, the, the, the details, into getting those, getting that documented. That's why documentation with nursing is so important, of how, how. That's how we get the data from your documentation. It's not just paper, right? It's not just. It's not just what's in the text, but what's happening underneath that text.
Speaker 3:We can aggregate that so explain how, like how does so? I understand how social media feeds AI, media feeds AI, how our internet activity, every click we make, feeds into some algorithm that is mined for financial gain and insight into my behavior or whoever's clickings behavior. How does so I understand that? So, if AI is intuitive and it's a learning program that is building its own intelligence, I can understand how those behaviors can be interpreted by a learning system and integrated into the learning system. I don't. One of the pieces that I don't fully understand is how biological data is going to be used. How are those two things like the behaviors that that we're displaying in AI, and then just how many times I breathe a minute, or the patient? So the amount of data that we collect as healthcare providers in the healthcare system is so vast. It's huge, it's unbelievable. How is that going to be used? I don't understand that. How is that going to be used?
Speaker 2:I don't understand that In terms of several ways. Actually, you can use it in several ways. One is marketing. Where does marketing come from? Behaviors, behaviors, right. And what's happening? What's the current trend?
Speaker 2:If they have a certain product that they want to put out there, they look at demographics what works, what doesn't? Okay, what data do you show that will prevent infection? Will not prevent infection, right. That's what it's supposed to sell, as opposed to something that we already invented years ago. And then we're just using it. Because, what? Because they said so? Because, because because this is how it's always been and this is how it always that. This is how it's supposed to be, not necessarily if you have experience or evidence-based processes, like your studies, that's what you're doing. Is you're using more current data that might disprove things that happened in the past? That now, because all these technologies are now available, it wasn't available back then, we can prove that this can work for the patient. Now, okay, ai is basically the same thing too.
Speaker 2:Ai has always been with us, I mean since the first time that a caveman did his what do you call this? His etchings on the wall, because it documents things. What we learn from those documentation gets fed into. I mean everything since then and all the information we've done to communicate and put it in a body of knowledge and put it in a system is now being used as what we call AI, because AI is really not a machine. It's really. Ai is a process, basically, of making sense of information. Mm-hmm, right, it's not the server, it just lives there. The information just lives in a server. But if I take out a server, that's what we call a blade in informatics world or in IT world. That blade doesn't do anything. It's when you plug it into the system and it interconnects with everything else, that becomes AI and, at the same time, what is used to market things to certain populations to certain populations.
Speaker 3:So I mean, one of the things that I'm thinking about is, I mean, the interactive element of AI and how it can mimic human interactions.
Speaker 3:Mimicry and, um, it, it brings up for me the idea of consciousness, yeah, and the fact that we actually do not understand consciousness yet, our own human consciousness. Um, so one of the it's super interesting. I will try to find the some links to this idea that we don't understand how anesthesia gases work and we're trying to retroactively, we're backdoor access consciousness. We're trying to understand conscious through the backdoor of anesthesia, because we we use the anesthesia, it shuts off consciousness and and we don't know how that is working. So if we can understand how anesthesia gases are working to shut it off, then we can understand how it works. Okay, that's the idea.
Speaker 3:And so, with that kind of context, because we don't our own consciousness, but we're creating this thing that mimics consciousness, how like, how like, because, again, one of the things that AI brings up is the question of what it means to be human. Ai brings up is the question of what it means to be human, what, as an informaticist like I mean, this gets into personal philosophy and and, um, what is, what are the fundamental differences between, uh, because of being human, and being an ai. What's the difference between us? I mean, we're having such an incredible experience uh, it's such an incredible experience to be human. Like it doesn't make any sense, like this is really a fucking weird experience that we're having right here.
Speaker 2:Sorry.
Speaker 3:I feel like I'm already one of the ones right now.
Speaker 1:Okay, I'm going to change my name from R-I-Z to L-S-D. I guess I don't know.
Speaker 2:You don't understand what.
Speaker 3:I'm getting at.
Speaker 1:I see what you're saying.
Speaker 2:I see what you're getting at, but again from a personal point of view purpose what kind of purpose do you have? What are you wanting to effect? That dictates what is done with the technology itself. Let's bring it back a little bit. Instead of talking about anesthesia gases, I go back to doing electrophysiology as a nurse. Right, I used to give sodium pentothal. I used to give versed, okay, um, oh. Fentanyl, sure out. You know, people have outlawed that name. Now, nowadays, oh, oh.
Speaker 3:So much education is required for that.
Speaker 2:We should just do a quick little educational blurb right here. My point is this is how my mind works. Whenever I take care of a patient, I do my assessments, I get to know the patient. I talk to the patient beforehand. The reason why I do that is I want to know again what data I want to know. What kind of patient is this? What kind of uh information? Like I asked, hey, how are you doing? You know blah, blah, blah, did you go to? Uh, what kind of things that they did?
Speaker 2:Or you know, of course, all this input is already going. What age is this? Okay, what age is person? What gender is she? Uh, what does she, uh, what does she or he bring with her?
Speaker 2:And again, a lot of this has bias already in my head of what it is right. But instead of seeing the differences and putting them apart, I tend okay, what's the commonality here? Okay, I tried what I'm trying to ascertain, what the purpose is for me, as a person who's giving sedation, is to know, because one of the things, one of the objectives we have as an electrophysiologist, a physiology procedure, is that they completely lie. Still, you know, straps are only going to work. So much, right. So me I'm trying to basically inhibit some of their movements and I have to give alcohol. Right Versed is an alcohol, it's a benzodiazepine. When I give benzodiazepine I can change the dosages I give. Do I need to give this patient more during the procedure? Do I put it up with fentanyl so that it kind of puts them to sleep? Also, with electrophysiology, you want different behaviors during the procedure itself. Do you want them to be able to talk to you if they're feeling pain, or do you want to be able to just zonk them out and actually test the defibrillator to see if it works? Or do you want them to be able to say hey, I'm feeling that, because that's all part of the procedure itself? And also you don't want to completely put them out so that you don't see the effect that you want to pinpoint where we do ablations, which basically deadens the nerves not the nerves, but the impulses to prevent arrhythmia happening. If they're asleep and they're relaxed, you're not going to get that effect right, so you need to know where to map it.
Speaker 2:My job at that time was to make sure that I give them enough alcohol, just enough, so that that behavior happens right. I classified my. I have this internal thing. I classified my patients into four different things, and this I get from talking to them what kind of drunk are you? I don't ask it that way, of course. I take it from hey. So what do you do? What happens?
Speaker 2:I look at behaviors, I track those, basically, and put it in my head. I don't chart that, of course. I'm not going to put that anywhere, but in my head I want to know what kind of things to expect. Is she giddy or he or she giddy? Is she going to be violent? He or she violent, or is he going to be quiet? Is he or she going to be crying? Is she going to be emotional? Those things are put in a database back in my head, thinking okay, now you can control the situation, the situation. I can give more to this patient or I can give less, so that at the end of the procedure itself, we've achieved our common goal. We've taken care of the patient, we were able to implant either the pacemaker or we've been able to isolate the impulse in the heart. Good enough that we've given the service.
Speaker 2:And then you wake them up. That's the thing too, because once you wake them up, that's also how you know, paki, when you and I worked at the Paki before you know how to, I guess, direct the conversation so that you only have what minutes? 42 minutes to an hour. You want to keep them safe during that time. So that's when they become they have they still have the after effects of the drug or the benzodiazepines you know, and you're you're kind of making them put in boundaries around that so that they are safe and able to walk by the time they wake up, right, sure, so what happens sometimes I mean some of the, some of the disasters I've seen was a patient just bolting out. Yeah, you want to make sure that those people are strapped down until a certain time so that once they wake up uh, the procedure itself they're going to be safe, right?
Speaker 3:So how does that correlate back to kind of the strangeness of the human experience and the strangeness of not understanding human consciousness and yet creating a machine learning system that mimics human consciousness? It's hard.
Speaker 2:I mean, somebody probably already has this in mind already. Okay, sure, I'm not the best informaticist, I'm not the worst informaticist, right right, but somebody out there is really working on this so that they can correlate that. You're going to find commonalities again and predictive models in order to inject that into your working knowledge and making that apparent. It goes back to the light Again. Like I said, an informatist is like a light that shines in on the data. You shine it right there so that you can see a little bit better. You shine it right there so that you can see a little bit better. How I mean, based on your mission or based on what you want to see how do you manipulate the data Not manipulate, I guess the word is not manipulate how do you represent the data so that you're making that surface a little bit?
Speaker 3:So the question is really rooted in what I'm writing about, which is nursing suicide and um, and the angle that I'm approaching it from is through criticizing evidence-based practice and so working back through the history of evidence-based practice, which takes you back to reductive reasoning. You, you know deductive reasoning and and reductionist thinking is when you, when you scale back evidence-based practice, what you're, what we're doing in evidence-based practice is what's called reductionist thinking, where you have a problem that you've identified, you have your bias, that is, informing um, the perspective that you're approaching the problem from. So, like, you know what is a watermelon. It's got the rind on the outside, you know, with a couple of different layers, and then you get into the heart of the meat of the watermelon, you cut it in half and you see the, the beautiful vascular system that that innervates the, the entire watermelon, and then you see, uh, the seeds okay that's watermelon, right?
Speaker 3:yes and no.
Speaker 2:Yeah, because then you have, you have the uh well, persim person does that too. They're just smaller.
Speaker 3:Well, I mean, a watermelon is anything, it's any problem, it's anything that you want to understand, anything that you want to reduce down to an empirical form, meaning the bottom level of knowledge that we are capable of understanding. So take that back to the Enlightenment, where we abandoned for the most part in a lot of ways I won't say most part, in a lot of ways we abandoned religious answers to the existential question. There was the Thirty Years' War, which was a terrible per capita, more people died than in World War II and at the end of that we entered what's called the age of reason, where we started answering the existential questions through reducing our material experience to its lowest form, to its empirical form, and that process of reductionist thinking became evidence-based practice in what we have today. So it is an objective, analytical view that answers all of the existential questions, answers all the existential questions. I didn't, I could not have articulated any of that 10 years ago or, you know, 15 years ago, 20 years ago, but our entire education was predicated on that premise and, and so it, our experience of caregiving is so objective in so many ways.
Speaker 3:And we go into the. We go into these incredible analytical mind spaces where we have this body of experience that informs every choice that we make and it's so objective and for me, in my experience, I lost meaning, like we've already talked about today. We have all lost meaning in our lives and I am trying to understand through through doing this writing and through trying to understand my own experience and how I got to the place where I lost meaning and and I think, and so it really is, that objectivity that's, you know, you know, just kind of excise is excises, the subjective experience that we're having, we have, we have, we are so much more dynamic than just being one side of objective. Does that make sense? Yes, so I think that gets back to my question about AI, which.
Speaker 3:What does it mean to be human? Because to me, the thing that was, you know, contributing to the, the breakdown of my psychology, was really a lack of meaning. So what does it mean to be human in an age when we're going, you know, it would seem that we're going to be interacting and dependent on something that is entirely objective? Does that make sense? Yeah, it does. Did you track that, okay?
Speaker 2:good, good, I would go back to the basics Land the plane guy. Basically, I guess what you have to ask yourself is what do you want? You go back to that. Remember what I said earlier you end with a purpose.
Speaker 1:Yeah.
Speaker 2:You start with a purpose. Okay, now, with EBP, you try to be blind about when you're gathering data. You try to be blind, but you have a plan of what are you trying to prove? That question also comes up in my head when I'm asked this question what are you trying to prove? And the thing is, you've got to know what you want as a purpose first. Right, because what happens sometimes is you have all this data, you have all this raw information. What do you do with it? It becomes information.
Speaker 2:Remember the, the high, the mass, mass loss hierarchy. I forget what it is now. Yeah, yeah. So you go from what? Hierarchy of needs, hierarchy of needs, and also the, the classification of information. Like, for example, you have raw data which is numbers, right, you have the numbers. How do you make sense of the numbers to get to the next level? Once you get the numbers, that gives next level, you tend to what we call, in the businesses aggregate all this information so that you get to the wisdom. A final final. Your final result should be wisdom, right, being, having the knowledge and make sense of it. Yeah, but that you already have that as your endpoint, basically. So, going back to being human, I'm going to ask I mean, I don't like answering questions with asking questions what is it? What defines a human for you?
Speaker 3:answering questions with asking questions. What is it? What defines a human for you? Well, it's. I mean, that's the so, the so, the like I'm. I'm not going to answer that directly, yet part of what informs all these questions is when, when I hear you talk about all the data that is collected by the companies that's being used to formulate the AI.
Speaker 2:They're not formulating AI. They're basically meeting their objectives of their what do you call this Stockholders. Each company has a fiduciary responsibility to address what Profitability right, so they have objectives already in mind. However, they're trying to find okay, based on the behavior of this, how can we affect that? How can we direct the flow towards more profitability or the objectives of the company itself?
Speaker 3:So then, the question that I'm actually asking is a moral one. Could be, I think it is. I mean that, that, that, how you know, that, that you know. I mean I I'm certainly not an expert on on what capitalism is or any. I mean, I'm a nurse. I what do we know about?
Speaker 2:that Right.
Speaker 3:I exist in a system that I don't fully understand, but capitalism, removed from any morality, seems to be a pretty oppressive system, just like any other system.
Speaker 2:Yeah.
Speaker 3:Any, any system removed of of that human element of caring.
Speaker 2:So I guess, if I may, the point I'm bringing about is if, to answer your question, is what makes you human, your definition of being human, and, at the same time, if you're gonna to be designing a what do you call this? Or creating a process, you have to have the end in mind, but you're also you're also basing it on ethics, a body of knowledge and, at the same time, the regular regulatory rules that you have to abide by in order to affect that. Because even if you have ethics and it doesn't, you know, there's always just look at the us right now there are certain laws that are different from what people define as their own ethics, right, so you have to put that all together in order to affect the final product that you want. Because if you can't get to the place, to the purpose that you want, because it's one, it's against the law, certain, it's immoral to do that, or what you call is immoral. It's actually I look at it as more ethical.
Speaker 2:And, at the same time, do you have the resources what resources, what technology is available to you at that time in order to make to get to where you want to be as a purpose? Right, so you think of it as, think of it as if we can relate it back to nursing um, back in the day. I mean, go back to, I mean it's a lot of it told. All the other thing, too, is opportunity. If the opportunity presents itself to you, you've got to know where to take it. But in order for you to take it, you've got to be prepared for it. By what? Your education, your experience, what?
Speaker 3:kind of opportunity are you talking?
Speaker 2:about. Look at the Crimean War. When I say Crimean War, what do you think about? I don't know my history that well. Well, this is the thing. Crimean War, that's probably when that happened. We had a lot of wounded soldiers, right. Who was taking care of them at that time? Nurses were taking care of them. Nurses were taking care of them several doctors, of course, but nurses were the primary caregivers at that time, in the midst of the war itself.
Speaker 2:The main person who was hopefully you know, the podcast listeners who are on the Google right now are Googling this and will try to correct me about it, but from my knowledge, at that time it was an opportunity that presented itself to Florence Nightingale, the embodiment of what Evidence-based practice she's known to have OCD Right.
Speaker 2:She's known to have OCD At that time, she was ahead of herself in terms of documentation Right, and at the same time, she also had a mission to take care of patients. So you have your ethics, your technology and also your means and the opportunity to do it, because from that war itself, although you may I mean people might have might look at it any, at any war as a um, what do you call this? As an ugly thing, as a negative thing. But from that war was born evidence-based practice, a septic technique, right, and that made things happen for us as nurses, right, and also um, research, because she was I mean, she was, that's yeah. And again, those soldiers that she was. She was thinking if there was no opportunity for her to take care of soldiers from their injuries, from something really ugly that happened at that time, the knowledge we have right now wouldn't be there.
Speaker 3:Maybe it would just come from a different angle.
Speaker 2:Yeah, so I guess to answer your question regarding how to you know. Question again, I lost myself.
Speaker 3:I mean it's. My premise is that the that ai fundamentally is is, uh, putting. It's causing us to ask the question of what it means to be human yeah again, because it's we don't understand. We've created a system or a tool that mimics consciousness when we don't even understand what it is ourselves.
Speaker 2:Correct, yeah, and again, its purpose is at the center of it. What's your purpose of being human? How do you even define being human? At the same time? Right, Because you can look at AI. A lot of people look at AI. Oh, I'm not going to touch that with 10-foot pole. We should stop AI right now and do nothing with AI. Right, Some people say that. Or there are some people oh, let's embrace the future and actually do something with it. Right, Some people look at AI as bad. Some people look at AI as good. But is it really Right?
Speaker 1:Well, and can you say? Can you say what's their purpose? Because, you bring up Florence Nightingale and you said the word purpose. So you know several times and she wouldn't have done what she did unless she had a purpose.
Speaker 2:Correct.
Speaker 1:Her purpose, her what seems to be be was she was not there to gather data.
Speaker 1:She was there to help the soldiers, in that she gathered data and it was provided and able to be extracted, but what really got her there and kept her there was purpose. And so if you have purpose behind the use of AI, if your purpose is to use it for bad, then that you're going to get that outcome, and if your purpose is to use it for good, or furthering, or you know better outcomes looking at things, I think that's a bottom line that can be drawn. It's purpose, and part of being human, I feel like, is having purpose.
Speaker 1:Because, AI, just in and of itself has no purpose. It itself doesn't have a self-purpose. It's there to be used and manipulated, but it's the person and and and really neither does data, until a person, a human, puts meaning either into a program that you know, talks about the data, identifies it and extracts outcomes from it. You know but that, but there's purpose in that program. There's purpose in the person who is looking at the data, and so is their purpose. Financial gain Is their purpose, patient safety Is their purse is their purpose, to make things easier for nurses to not have to double chart certain things. You know, I think purpose is a thread that has kind of gone through all of these conversations and the back and forth and you know, could be part of what defines being human versus just being AI.
Speaker 2:Yeah, it's all that.
Speaker 1:Yeah.
Speaker 2:Yeah, but at the end point I always look, okay, what do I really want to do with this, right?
Speaker 1:So again, what's your purpose, what's the?
Speaker 2:purpose of it, you got to use your tools, and I mean even purpose itself is a tool to get what you want right. So like, for example, you have applied to today's um. If you apply yesterday's um, um knowledge in terms of what happened during the crimean war, remember I said technology, you had the opportunity, you know, you had you opportunity, you have to, you know if you apply it. Ai is basically the same thing as it's a tool. If you want to simplify it, you can say it's a tool, right, but it's just a bunch of numbers, spreadsheets, excel files, all put together so that it presents a certain number to you or not, a certain number to you or not a certain number, but a certain picture to you of what the numbers are representing. Right, even excel itself is ones and zeros, sure, but you put all that and aggregate it together, or put it together so that it represents something that's meaningful for you, something, something that has meaning to you. You have to have a meaning and a purpose as well yeah, yeah, just having a purpose.
Speaker 2:I could be a psychopath, sure, and have a purpose, yeah, right. Yeah, I gotta have my ethics, my, my ethics, my purpose, and also the meaning of what that means. So that's how I you know. So that's how I look at it. Did I answer your question? I don't know. It doesn't have to, it doesn't have to.
Speaker 3:I mean, ultimately, my purpose in even exploring the question is connected to Julie and I's purpose, which is combating, fighting against nursing suicide. It's it's has the highest rates of suicide of any professional career. It's incredible. So so I'm trying, I'm I'm analyzing all this stuff, I'm constantly thinking about this stuff, how, like you know, I I feel like it's part of my purpose. I survived, like why, like that. That was a real question for me at the at the very bottom. I mean, I can remember at the bottom thinking I could just be homeless. I could be a homeless person as a nurse. I have watched so many people, you know, when I worked in, I worked in one of the rescue missions downtown in nursing school and a little bit after, and I remember taking care of a couple of guys. One of the one of them was a lawyer who basically just I remember him saying something like he saw through the veneer of society and he just didn't want to participate anymore.
Speaker 2:Yeah, so it was bullshit.
Speaker 3:Yeah, and that was the option that he chose.
Speaker 3:And I was like I mean that's like, wow, blew my mind, right, blew my mind. I mean how, like, how blew my mind. I mean, how do you get to that place? And then I lived my experience and I got to the place where I'm like I can just be homeless. I've seen it, I know how to do it, I know how to navigate the system in a way that I could stay alive and not deal with any of these problems of modernity.
Speaker 3:And at the end of the day, what I decided was there's no one in my life that would benefit from that. There was, there's no. My kids would not benefit. Like like they would maybe benefit in the sense that, um, you know well, maybe maybe they. If I'm not successful in building myself into the best version of myself, then maybe it would benefit them. But if I don't try to make myself the best version of myself, then everyone kind of loses. Everyone loses, myself included. So it became part of my purpose to become that best version of myself, so that I guess my kids would have some like they didn't. My kids wouldn't have to say, oh, my dad just disappeared, he's homeless somewhere. You know that. How embarrassing would that be. Like they don't have to deal with that. Now they just have to deal with their dad that, you know, uh, doesn't always have a regulated nervous system uh, that's kind of my reality right now.
Speaker 2:I'm thinking about that. My kids probably this is my kids probably don't know what I'm doing right now. They could care if I'm homeless somewhere. But the thing is, what's your purpose? Yeah, it always goes back to that.
Speaker 3:Yeah, so. So then the part of the purpose that emerged emerged from choosing to participate in, in, in life, in modern life. Part of that purpose became and it was especially after I found out that our friend had taken her life or lost her life. We don't really know exactly what went down, but when I heard that, because her and I's story are so similar, we had so many points of reference on our journeys down that I became aware of this problem of nursing suicide, and then that became kind of the thing that I've been thinking about for you know six or seven years. Why did I survive and how can I help other nurses not commit suicide?
Speaker 2:Yeah. And the thing is, you've already started with the problem, right there. Nursing process yeah, start with what? The problem, the problem yeah, start with the problem. But you also have goals in mind at the end. Sure, right, yeah, that's basically how your nursing process is supposed to work. Yeah, yeah, right.
Speaker 3:So all this exploration of thought is just, it is, it is just that it is me processing.
Speaker 2:I wouldn't say just it is that, because it's actually the meat and potatoes what people say meaning but of data gathering, making sense of the data itself. You gather the numbers, you try to make sense of the numbers you see, shine a light on something and then find a solution.
Speaker 3:Yeah right which I, I that one of the solutions is meaning correct. I mean, we are meaning making beings, I, I, in fact, one of the things that that, um, one of the things that I can look back in how my psychology broke down, was that I was attributing meaning to things. That was really just my imagination. So, and I think that I, and this is something that I see, uh, in broader society today, which is conspiracy theories.
Speaker 3:So many of the conspiracy theories, you look at it and you're just like what the hell? Like, yeah, but it makes perfect sense to me in a world that has become so dependent on numbers and objectivity, that and and that, those you know because, again back to you, know the Enlightenment thinking, reductivective reason or deductive reason, you know, um reductionist thinking, where it's all analytical and all objective. It loses that subjective, the subjective, uh, meaning, which has, you know, historically been religious, um, so all of that has been removed and we have this heavily leaning objective thinking society. In that context, it makes sense that, matt, if we are beings that innately create meaning, project meaning onto other things, then it may conspiracy theories make perfect sense, like because we're going to make it make sense somehow, even if there's no correlation whatsoever. So to me that is a representation of the dark side of Enlightenment thinking and that's why you never stop learning.
Speaker 2:Because conspiracy theories, where do these beliefs come from? It's information available to them at that time. That's why we never stop talking to each other, because you know your facts and my facts can. Actually, if we talk, if we put a conduit in between, that we might actually come up with the correct deduction and the correct reasoning to what makes sense, or put meaning into what it really is, right to what makes sense or put meaning into what it really is. That's why this discord in terms of just isolated, not even associating with conspiracies, my thing is, sometimes I look at that when I say, hmm, it's not a negative thing, it's interesting. Well, let's make sense of this, gather more facts At the same time. Now let's talk to him and say how wrong he is. That's how, basically. But again, it only happens when there's an exchange of information, right? So that's how I look at it. Yeah, yeah. So these things that even with nursing, I mean some of the things that we believed back in the day, I mean now it's totally debunked, yeah.
Speaker 3:Oh, absolutely, it's not because it's bad nursing.
Speaker 2:It's because at that time we did not have the technology to have microscopes. Even if we had microscopes, we did not have the technology to isolate color, so that what happened before? Because there's lack of experience right. We did not have that way of concluding and publishing our stuff at that time, because we didn't see all that experience happen. So now that you have the experience, how can you make it work?
Speaker 3:It's not just nursing, it's medicine, sure, it's just about everything but, and that kind of gets to one of the points we've talked about in the past, which is, uh, the fundamental distrust of of the health care system and the and the, the criticism of the health care system that presents itself as this stalwart of truth when in reality, like anesthesia, we don't know how it works, we just know that it works.
Speaker 3:Yep, like, but we're gonna pretend like, like, oh, we're the knowers you know, yeah, we know the parameters of its limits and you know we, we understand through experience what it does, but we don't have the knowledge. We don't have the real. We don't have the real knowledge. There's so many medications that are just like that, like hydralazine. We know that it, we think that it works on reducing blood pressure. I mean, I've seen it work. It takes a little bit of time, but a lot of people think that it doesn't work. We don't know.
Speaker 2:Alcohol encephalopathy yeah, heard about it, right, yeah, when I say that that word, what do you think about it? Negative, positive, oh, it's negative, exactly, but is it? I mean, in my experience, if you can, if you can, if you can explain how alcoholic encephalopathy works, where it comes from, how it happens, what happens after, and you look long-term, what are the effects or the damage that can happen to the brain if you have it for a long time, you can actually have something good comerust of our healthcare system because it presents itself as an objective, absolute truth when it in reality is not, cannot be or can be misused.
Speaker 3:It can be misused Absolutely. I mean, those are like you know. I think I think that's I don't know, that's, that's part of the part of the conversation we're we're having about, you know, evidence based that and conspiracy theories are definitely connected to that and I don't know. I lost my point, I've lost my track of thought.
Speaker 2:But I get relating it to, to I guess it's not really a mission, but it's to my track train of thought about using AI for good and using technology. Basically using technology for good. It depends on where, on what your purpose is and who has who has control of it, right? So it's it's technology, it's there, it's you know it's, it's, it's just there, you, you do with it. It's like being given to you, okay, you, you. It's like. It's like free will. Free will is given to you, right? What do you do with free will is up to you whether it's up to you, what do you make it into a good path? Absolutely a bad path, that's true, right, but it's up to you, because of your ethics and your experiences, that will bring you to where you want to go life my gosh, I could go this deep yeah, oh yeah, it's fun though.
Speaker 1:Yeah, it's really.
Speaker 3:It's cheap therapy he just said it's cheap therapy totally, it is it's real, you know it's real charge.
Speaker 1:I just, I mean, I got some breakfast from it too. Yeah, you know, bring in someone's, someone else's perspective is always enjoyable because, um, it just gives us more things to think about and, you know, broadens our awareness. Yeah, yeah, exactly. So. Obviously you were meant to be on the podcast today, because things like this don't just happen, so I know it was perfect.
Speaker 2:It was perfect.
Speaker 3:I think it was the first thing I thought of this morning.
Speaker 1:when I woke up, I was like that's a thought and that's an intuition, not thinking I wonder who we could get on the podcast. No, it was just like oh, we're having breakfast, let's just do it. I just wanted breakfast and to show off your new truck.
Speaker 3:He's got a new uh new tesla truck uh oh, the truck yeah, yeah, he's like um, straight, like straight in to our lives from goonies. The movie Data.
Speaker 1:Yeah.
Speaker 3:He's got the new glasses with the video thing and he's got the new cyber truck and computer guy. He's going to hit me with one of those punching arms that comes out of the Out of his fanny pack. Out of the fanny pack.
Speaker 2:And this one, a guy who just springs out of a. What do you call this?
Speaker 1:A food truck or a food container?
Speaker 2:Yeah, Just to make fun of people. Oh my gosh, that's funny.
Speaker 3:Well, this was fun All right.
Speaker 1:Yeah.
Speaker 2:Thanks guys. I really enjoyed this. Like I said, this is cheat therapy. Yeah, man.
Speaker 1:Good to see you, Rez Thanks.
Speaker 3:We hope you've enjoyed this week's episode.
Speaker 1:Remember, the conversation doesn't end here.
Speaker 3:Keep the dialogue going by connecting with us on social media posted in the links below or by visiting our website.
Speaker 1:Together, let's continue to redefine nursing and shape a brighter future for those we care for. Until next time, take care, stay curious and keep nurturing those connections.
Speaker 3:And don't forget to be kind to yourself.