People trust Generative AI, are we going to fight this or work with it?
Today in health, it people trust generative AI. Do you, my name is bill Russell. I'm a former CIO for a 16 hospital system and creator of this week health. Instead of channels dedicated to keeping health it staff current and engaged. We want to thank our show sponsor, short investing in developing the next generation of health leaders. Short test artist, site, parlance, and service. Now check them out at this week. Health.
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All right. Reading this story. It's work week work week.com. Should consumers trust generative AI. And then it says wrong question, and this is actually focused on another industry. It's not specifically focused on healthcare. I'm going to bring it back into healthcare because I think the question they're asking is.
Should consumers trust generative AI. And the, the, , conclusion is that they do trust generative AI, probably more so than we're comfortable with. So. They, , cite a couple of things. According to a recent survey from the Motley fool, 54% of us consumers have used chat GPT to recommend a financial product such as a credit or debit card bank, account, broker mortgage, lender, insurance provider, or personal loan at this different survey. Also from Motley fool found that 47% of us adults have used chat GPT for stock.
Stock recommendations. And while that's probably not a great idea since the model was trained on, , a couple year old data or at least it's, it's a cut off at a certain timeframe. , people are still doing that. Consumers are bullish on the technology and according to another survey for the nationwide retirement Institute, 31% of us consumers feel chats, GPT.
We'll provide better financial advice than a human financial advisor in the next five years. The percentage jumps up to 37% for gen Z and a whopping 43% for millennials. The optimism is to put it mildly, not shared by those human financial advisors. And let me give you a little feedback here. It is by.
This is a quote, is by no means going to provide you. With a way to beat the market Douglas bone. Parth a certified financial planner and president and founder of bonafide wealth tells CNBC. Boda Parth. Himself put chat GPTs financial acumen to the test. It says the results. Weren't great. He asked the tool to build him a hypothetical diversified portfolio with 80% equity and 20% fixed income and gave it a few parameters, risk, characteristics, and guidance.
As to what kind of exchange traded funds. He wanted to use. I was presented with a table that added up to more than a hundred percent. He says after enforcing Jean Chatzky beauty of this, I tried to correct this error, but didn't necessarily pull the right information. He says, , You know,
it's interesting because I think when people interact with chat CPT, It's not hard to come up with a stereo, say, Hey, this doesn't work. , what I'm finding is that the people who are getting the most out of it. I really do work at the prompts and continue to work at the prompts and get better at it. That's not to say that these models don't hallucinate and it's not to say that they don't have current information, but it is to say.
That the prompt does matter, but that's not the point of this story. The point of this story is people who trust these models. And so the LLMs are getting used. And that is the, the primary, , the thrust of this story. So because on democratizing access to expertise, let's start here as a general rule. I think humans tend to trust experts more than we trust regular people. And we tend to trust regular people more than we trust machines. Driving is a good example.
If Lewis Hamilton is chauffeuring you across and you get the idea, we don't trust. Self-driving cars as much as we trust. A limo driver. Here's the problem though. Experts are inconvenient. Right. Limo drivers are inconvenient. Experts are a pain to deal with. They generally don't communicate well. They speak in jargon.
They equivocate and constantly change their minds. And because there aren't a lot of them and their expertise is in demand. They aren't very accessible. Lewis Hamilton doesn't have time to show for you across LA. And if he did. You wouldn't be able to afford him. That's over time. Society has come up with a lots of mechanisms to make expertise more accessible.
One of them being large language models. Examples, they give Wikipedia gold Wikipedia. According to the co-founder is to create the world. , create a world in which every single person on the planet is given free access to the sum of all human knowledge and the Wikipedia essentially put encyclopedia's out of business, social media while the internet did that. But encyclopedias, social media compared to the noble mission and nonprofit status of Wikipedia.
I know that social media feels like an incongruous inclusion on a list of technologies that have democratized access to expertise. But I think you can easily make the case that social media has had a big or bigger. Impact on the dissemination of knowledge. Then Wikipedia. And I think that's absolutely true. My brother and I were having a conversation and he was talking about the weapons systems being used in the Ukraine. And I'm like, where are you getting this information? And it was Twitter and he was getting it from Twitter or X. Are we good to call it X? Now we're going to call it Twitter, who knows?
, I'll call it ex formerly known as Twitter. That's what I'll do for now. , and he was getting all the information from there. So yes, it is a way to disseminate information. And now we have generative AI and it talks about that while it's still very new. I think generative AI has the potential to be the most accessible interface to expert knowledge ever invented.
And so, you know, we go down and it, it talks about, you know, is this good? Is it bad? A regular person with a question? We'll first go to Google. They might start going to general AI first. And this is why Google is a little concerned. They will go to social media. We'll go to Wiki, Wikipedia. And they'll go to an expert probably last on that list, unless it's something that they absolutely need an expert for, or money is no object. And, , finding an expert is not that hard.
The internet enables. It goes on the internet enables anyone to directly access most expert knowledge. You can actually read those academic research. Papers. Yourself. But instead we need it to be laundered through a series of intermediary layers. Each designed to dumb it down and make it engaging enough to capture the 15 second attention spans.
Of our modern smartphone addicted brains. That is, that is one of the problems. So he says, , you know, if you're an expert, so in this case, he's talking about financial services. If you're a financial advisor, He said, you know, there is a case for optimism. And, , And it is that there's an opportunity to, to disseminate expert knowledge through these tools. And he said, you know, essentially something is better than nothing.
, according to a survey by Northwestern mutual us consumers view financial advisors as the most. Twice trustworthy source. For financial advice in social media as the least trustworthy source. Interestingly, this holds true, even when you like isolate the data to just focus on millennials or gen Z.
And yet, according to the same survey, only 37% of America's Americans work with a financial advisor. And according to a different survey from Forbes, only 11% of gen Z and millennials, Americans work with a financial advisor. So you get where I'm going with this. This is the same thing that's going to happen in healthcare.
Right. So these same surveys, I'm sure we're going to be able to do these same surveys in the next a year or so six months to a year, and people are going to going to be going to generative AI. Yeah for healthcare information. So if you who's us to understand that that that is what's going to, to happen and to figure out a way to become as the health system more accessible for information.
Whether that be. Utilizing the models of GPT for, or even training our own models. And I've talked to some CEOs that are training their own models. Now these are some of the larger health systems, some of the, some of the ones with the wherewithal to do that. , some of the academic medical centers, they are training their own models for different applications.
With that being said, People are going to, going to be accessing this. The best thing to do is to train people on how to access it effectively. Maybe you have something on your health systems site that helps them with the prompts to ask the right question. Maybe you have a prompt generator. , that you help people that generate the right prompts around, , medical challenges and whatnot. But I think what we want to do is we want to become the trusted source.
For information. For anything. Health-related I put a survey out there this week. If you want to check it out. It went out on Monday and it is a lot of health systems have rebranded to health. So it will be blah, blah, blah health instead of blah, blah, blah, healthcare. , moving forward. And I think.
I can't think of one that hasn't. , most half, and we're saying, Hey, we're health companies. Well, that branding hasn't worked. Most people still consider us healthcare, not health. The thing that needs to change in order for us to be considered health is to be the source to be the first place that people go when they are thinking of a health question, they don't think of going to Google.
They think I'm going to go to my local healthcare provider and put a search in there. And, and that, and, or a suite of tools, there could be gen AI tools for us to utilize on the website. There could be a specific chat bot on, on the, there for a website. And the thing that's interesting and distinct about our capabilities is we could take those questions and lead them into a funnel which leads to an appointment with a primary care doc or even a telehealth visit.
So, , they make the case for adding layers to the stack, makes the whole stack more valuable. So regular person has a question. And they say, utilizing these, these various steps, generative AI, social media. , Wikipedia expert knowledge. , the person can get an answer. To those questions. This is a great article, by the way it goes on. And there's more to be said in this article.
But again, it's workweek.com. It's July 28th. It's on FinTech specifically. So you're probably not finding it if you're, , if you're, , just. , filtering your stories based on healthcare. But I think it has application. This is about consumer behavior. How are our consumers? Looking for health data and health information, by the way, I think this is a good story.
That goes along with a, another story. Let me pull it up real quick. , GPT four medical benchmarks. Is interesting. It's not really a story. It's a 33 page PDF published by Microsoft and open AI as the capabilities of GPU for. GPT four on medical challenge problems, and you're going to see. That it does pretty well on these, on these medical specific tests.
But it's not perfect. Right. I mean, so you start to wonder, it's like, are people going to generative AI? Are they going to get the right answer about healthcare? And the answer that is, in some cases they will, in some cases they won't, but it's the same people that are going to Google. And in some cases they'll get the right answer. In some cases, they won't.
And it's the same. People are going to go to web MD. In some cases there's going to go self-diagnosing is as you know, not perfect. , the question is if we're a health company, we are concerned about how to help our consumers. Utilize the information that's available to them. If we're a healthcare company, we just want people to come in our front door so that we can, , get reimbursed for that visit.
So, if we're going to be health, we have to start thinking differently about the tools that are readily available to our consumers and how to help them. Be able to utilize those tools. , interesting story thought. I share it with you. That's all for today. If you know, someone that might benefit from our channel, please forward them a note. They can subscribe on our website this week, health.com or wherever you listen to podcasts, apple, Google, overcast, Spotify, and Stitcher is going out of business. So if you're listening there, you might want to pop over to one of the others, but you get the picture.
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