The Importance of Data Literacy in an AI-driven World

Artificial Intelligence is rapidly changing the way we lead, teach, create, and build businesses. But just because AI can do something, does that mean it should?

In this episode of The Peeples Exchange, Dr. Regis Peeples and Keara Peeples explore the importance of data-literacy in our ai-driven world and share best-practices when it comes to the use of AI-outputs and data-validation.

Whether you’re a founder, educator, creative, or leader navigating the changing digital landscape, this episode offers thoughtful perspectives on balancing technology with human purpose.

Transcript

SPEAKER_01 0:05

Welcome to the People's Exchange, where business meets education. I'm your host, Kiara Peoples.

SPEAKER_00 0:10

And I'm Regis Peoples.

SPEAKER_01 0:12

And today we're going to talk about the importance of making data-informed decisions in business and education. Because in the world where AI is rapidly evolving, technology is running really, really quickly and speeding, I mean, this foot is on the gas. It's important that we as individuals practice using data responsibly and make data-informed decisions throughout our day-to-day lives. So, Regis, why do you think that data-informed decisions are so crucial today?

SPEAKER_00 0:37

So it's really important because we do live in sort of a post-truth world, meaning that we live in a world where there is a lot of misinformation. There's a lot of technology that's designed to misinform people and manipulate consumers. But also on the academic side, there's a lot of misinformation and research that is not valid or rooted in any truth. And a lot of people don't take that extra step to kind of decipher what's real, what's not real, what's manipulation, what's not manipulation, what's sort of hegemonic influence uh or hegemony, meaning when a place sort of sets these rules and standards and culture and kind of sets the tone for what is real or not, regardless of the facts of reality. Um and in some cases, obviously, with hegemony, it can involve truth. But the point is we're being sort of persuaded rhetorically all the time, and we need to equip ourselves with the tools necessary so we can decipher between what is useful, what isn't useful, um, but also what is real and what is not real.

SPEAKER_01 1:43

Perfect. Thank you. And you mentioned that sometimes people don't do that due diligence naturally. What do you think the reason is for that? Like, why aren't folks actually validating this information?

SPEAKER_00 1:55

In my opinion, and look, I can't speak for anybody in the world, um, but it seems like sometimes when there is enough trust with something or enough belief in something, that it doesn't matter if the information is misinformed or lacking in certain areas or just flat out untrue. Um, a lot of times when people can justify their beliefs as true, then they will just choose to believe something that's true. Um, and at the same time, a lot of people when they're researching, don't necessarily go through the steps needed to sort of vet or fact check the information, especially if it's something exciting that sort of aligns with what you already thought about and believed in the beginning. It'll be like that reaffirming moment where it's like I knew I was right, um, as opposed to, okay, this agrees with me, but let me check in some other places and make sure that it's cohesive across the board.

SPEAKER_01 2:50

Yeah, I think that is a great point. Um that latter point you just mentioned, where folks kind of think it's a certain way and they think the data is gonna look a certain way, and they get a answer that kind of like coincides with what they thought. They don't do any further research or any further validation. But at the end of the day, when you think about it, that's still kind of a bias in its own. Um, and it's important to remember as we are navigating our day-to-day lives, as we are moving throughout our work days, that our opinions, our thoughts are not facts. And I remember uh in college, um, all the English classes that I took, um, and you can speak to this as a college professor, but like all the English classes that I took, we were always writing research papers. And then there were some professors that I've had, or one professor that I had, and he was like, Hey, I want you to write a paper about a different opinion that you don't believe in, and use, you know, these different data tools and these different like, you know, scholarly articles and things that nature prove that point, you know? And it doesn't necessarily mean that like at the end of writing that research paper, you have to agree with what you wrote, but it was just a really creative exercise in a creative way to test your thoughts and to test your beliefs and to test your biases because they're not always factual. And I think this is becoming extremely important where there's so much misinformation just online. Like I can open up any social media platform, and there's all these people that feel at times that they are thought leaders on a given topic, spreading their opinions as if they're facts. And that's another reason I will just kind of piggyback on what you say, what you said earlier that it's so important to do the work. Uh, and that is the work that most people don't want to do. Um, so yeah, I just think there's so much at our disposal that the facts can kind of become convoluted.

SPEAKER_00 4:41

Yeah, and I really love um that assignment you were given. I do something similar. And to the point of the podcast and sort of this idea of staying informed, um, one thing you can use are databases. You you mentioned that your professor had you looking up scholarly articles. You know, databases are peer-reviewed, um, meaning that, you know, other scholars have confirmed and affirmed the information and its value in context to the subject. Um, then there's this really great database called opposing viewpoints. So basically you search up a topic and it'll tell you the pro side and the anti-side, and then the neutral side in the middle. Um, and it basically gives you articles for each individual argument and then also articles that are impartial and just giving information as opposed to trying to get people to lean on a side. That way you can really become informed, yeah. Um, instead of, you know, being pit against one side or the other through some kind of rhetorical battle.

SPEAKER_01 5:40

I love that. And I actually want to open the floor up to ask you a question. Um, as someone that does a lot of reading, um, you verify a lot of information. I mean, you're a professor, you're reading papers all day. Um, I'm curious to know has there ever been a point in time in your life where you thought something was true and you did some digging, um, you used some of the tools that you just mentioned just now, and you were proven like wrong about something you thought was true? And what was that example?

SPEAKER_00 6:07

Yeah, so I would say when I was younger, and I this isn't something that I necessarily on my own thought was true. It was something that was taught in the classroom. Um, but there was this huge discussion about the Native Americans dying from food bacteria on ships, and no mention of genocide of the native indigenous peoples of North America. It was a story of Europeans helping tribes that were running from other tribes. So I guess there's a tribe here, and then they're migrating west to run away from other native tribes, and then the Europeans landed on the east and flanked the natives in between the two groups to help them. Um, and then they were just basically given different land that later turned into states in the United States of America as a gift for helping the running tribes, which is crazy. I see. Um, because obviously we know there was a mass genocide and the land was taken and so on and so forth, um, and the people were exploited. Um, and it's just something that I remember learning in preschool in kindergarten and first grade, and then as I got older and my parents started telling me more history about the country and sort of paying attention to my history book, they're like, hey, this isn't maybe these things happened occasionally in some scenarios, but this is not the general truth of what happened. Um then I started doing my own research and I found out like, whoa, like this is creating mass genocide. This is wild. Um, and then I started to sort of realize in my textbooks that there were a lot of mistruths and manipulative information. I'm not gonna name the brand of the textbooks, but I will say that people are very conscious and aware of that publishing company that still exists. It's very unfortunate. Yeah, a lot of districts kind of strayed away from using them, but they still are.

SPEAKER_01 8:02

It makes me think about um some of the bills that have been introduced um, you know, down south, um, what they're trying to take out of textbooks because we don't need to tell the story anymore. We're a new nation, like right, this is no longer our history. But the thing is, if you are not aware of the facts, if you are not aware of history, that is how history repeats. Thank you for sharing that example. I think it's very relevant not only to what you experienced as a child, but what unfortunately I feel like if certain things are pushed to that final step into that final line, others will experience. And I think it's important that we educate our youth on what really is going on. Now we keep these records of things that have actually happened in our history. Um, but that's just crazy to think about it from an academic stance, kind of something you thought was true, something that you were being taught in the classroom, which may have been very minuscularly true, but there's a lot more to the story. That's actually a great segue into my question for you. Why does data validation matter in the academic space? So you shared about some things that you learned that were not the full story or in some cases correct at all, but later down the line, um, I guess can you share any other examples of why data validation is so important in your space?

SPEAKER_00 9:22

So, particularly within English, especially, and you know, my English class is a little bit different because I actually have students writing about different topics they're researching. I'm not necessarily just doing grammar and sentence patterns and all of that good stuff, right? I have my students looking at globalization and researching products and brands and writing about that. Um, I have my students looking into political correctness culture and writing about that. Or I'll have my students take, you know, literary theories or critical theory lenses and apply them to current events to interpret the events through that lens, you know, regardless of their personal beliefs. And the one thing I will say is important is that the information is in fact accurate. And one part of all of those assignments, regardless of the subject matter, is that they look at how the narrative is different on different platforms.

SPEAKER_02 10:12

Yeah.

SPEAKER_00 10:13

So let's hypothetically say that there is a protest going on, and the protesters are on social media live streaming saying, you know, we're being forced out by the police, they're violently resisting us and we're peaceful. And they're filming everything and they look peaceful. But then maybe if you look at a print journalism article, it might say violent protesters wreak havoc downtown. And it might call them violent and say they were being destructive and use all this very strong language. Well, what's true? Is what's true what's printed in the article, or is the live stream the truth?

SPEAKER_02 10:48

Right.

SPEAKER_00 10:48

And even if there is some truth to the live stream, were they showing you the violent parts or were they purposely excluding it, and vice versa, for the news article? So then it becomes a thing about how many sources are you gonna look at? How can you verify the bias? How can you sort of use your critical thinking to decipher well what is true? How can there be seven different stories about one event?

SPEAKER_01 11:10

I love that. So what I'm hearing you say is in your space, uh data validation matters because it promotes critical thinking and just kind of unpacking biases.

SPEAKER_00 11:20

Yes. And then alongside that, I have students create what's called an annotated bibliography.

SPEAKER_01 11:25

Okay.

SPEAKER_00 11:25

So you know, you have your works cited page, your bibliography, but an annotated bibliography is when you take a source and then you evaluate certain criteria. So who's the author and what are their credentials? Why should we even believe them in the first place?

SPEAKER_01 11:38

I remember now it's all coming back to me. Uh, because when I was a student, I did a bunch of those. Yes. Yes. Um, because it's not so much find the information, but just also fact check the credibility of the person that is writing, or not so much fact check, but just do like a, I guess, an ethos background check. Like, is this person credible? Right. Like, what steps would you advise your students or anybody that's looking to fact check or uh reputation check or you know, bias uncheck uh anybody writing something that they might want to use to validate their own research?

SPEAKER_00 12:15

First step is what are this who's the author and what are their credentials? That's the first thing you need to look up. So do they have a degree in the subject? Are they a specialist? Yeah. Um, have they had any instances where people have had them get in trouble for mistruths, right? Yeah. Um, you know, even in mainstream journalism, you know, there are news networks that have been sued for misinformation and lost lawsuits and had to pay out money for knowingly falsely reporting information. So you want to check, hey, has this person ever done that? Who's the organization they work for? How credible are they? So on and so forth. For sure. So it's not even always, does this person have a degree in this? Are they a specialist? Because information can be passed on by anyone who has the ability to communicate, but you know, there is more ethos with that. So the other thing is um, what kind of bias or point of view is the article written from? Can you tell what side they're on and what kind of rhetorical strategies or devices are they using in that article to persuade you? So that's something you'd want to put down in the annotated bibliography. The other thing is um who's the intended audience? Who is it written for? Is it written for an academic audience? Is it written for students? Is it something written for people of a certain faith or belief? Um, because that also incorporates into the bias and that also will determine how it's written if the person is considering audience. Um, the currency of the source. So a lot of things have been proven and disproven over the years, and sometimes what students will do on accident or researchers in general, is that they'll find an article that's just out of date. Maybe the information was verified as true, but science has evolved and it's no longer applicable. So, how current is this information? Does it still stand? Is it still valid? You gotta think there was a time when people thought the earth was flat, and if you said the earth was round, you would die. Aye is blasphemy. How dare no?

SPEAKER_01 14:04

There's still some people that believe the earth's flat.

SPEAKER_00 14:06

Okay, well, I'm not here to argue if it's flat or not. I'm just saying not me though. Now there's a common consensus that the earth isn't flat, but there was a time when that was what was taught. All right, Kear. So can you let us know why data validation matters in the business world? Let's switch, let's switch gears here.

SPEAKER_01 14:22

Yes, and thank you for sharing all those best practices and then the things that you do within your classroom to ensure your students are thinking critically, um, and also kind of leaving their biases on the table and fact-checking themselves because it's so important. Now, uh flipping a page now into the business world. So we talk about that world of academia, best practices there. Uh, but why does data validation matter in business? Well, I would love to answer this question with an example of what can go wrong when you don't do a little bit of research and you don't ask those questions, right? Like, huh, is this accurate? Is this true? So there's a story, I don't know if you remember, but in 2024, there is this company in Hong Kong. Um, and I'm not gonna say the name of the company. Um, essentially, you know, AI is and was a thing that was growing and evolving. And at this point, you know, AI could do so much and can still do so much. It can create fake videos of people, it can create fake characters that look like real people and impersonate people, it can create uh fake voices, it can call people, right? And act like it's someone that you love. So, with all that information, keep that in mind. So there's this company in Hong Kong, um, and there's this individual that worked directly with the C-suite of this company, and he was responsible for financial like transactions and things of that nature. So um the CFO, or so who he thought was the CFO, invited him to a call, a video call. So he joins the call, um, and there's all these people that he thinks he works with on the call, and it looks like a real call. Um, but this is not a normal protocol for their business like operations, right? However, it does look like the people that he knows with and works with and trusts is there. And the CFO instructs him to do a certain amount of transactions involving their business funds, right? Long story short, he was pretty much scammed by individuals and hackers using deep fake videos and uh characters and things of that nature to create this simulation like, hey, you're actually in this meeting. And therefore, he then went out and made all these transactions and he lost the business millions and millions and millions of dollars because what he thought was an actual real meeting. So, where does the data validation come in? I think in business, it's important just to do a little bit more, I would say, due diligence when it comes to any like sudden rapid change in your protocols and your operations. Uh, if something seems out of the norm, it may be. And uh, I think when it comes to data validation and in the world of AI, it's important to just move with more curiosity. Like I've received text messages from my CEO when I was working in corporate before I owned this business. Uh, but I've received text messages, um, hey, Kira, I have a quick favor to ask you, right? We actually had a Slack channel when there was anything that looked a little bit suspicious or odd, where we'd say, Hey, hey, so and so, did you actually send us this message? Hey, so and so, is this actually coming from you? Is this a request from you? Well, we validate in that way because of the rising amount of just identity theft, hackers uh that corresponds with AI and just the power of AI where it can impersonate people, it can impersonate sometimes emails and things of that nature, right? So I think in business, you know, it's super important to validate um where requests are coming from and just doing a little bit of extra uh legwork to make sure that those requests you're receiving are coming from the person that you think is coming from. Whether you create your own security channels or security protocols, I'm sure that you would have hired maybe a specialist to help with those operational changes uh when it comes to security in the rapidly growing world of AI. Yeah, Regis, long story short, you're definitely going to want to validate, you know, where these requests are coming from in the business space. And that's one way that data validation plays a crucial role because you can lose money. And we've seen businesses lose money.

SPEAKER_00 18:14

Thanks for sharing that. It really, I think, will help our viewers better understand that data validation is not only about the research side and getting information off the internet, yeah, but also word of mouth, uh direct correspondence with others, whether it's through video servicing, chats, phone calls, and messaging, just being conscious and aware, I guess, of the technology that exists and the ways that people can use that to mismanage money, rob you, scam you, take advantage of you and all other things that fall in that wheelhouse. So for sure.

SPEAKER_01 18:46

So in addition to validating data, I also want to share the dangers of not doing enough research or not listening to the data when it comes to running a business. So um, there's a saying, you know, what's not broken, uh, don't fix it. And when you're growing a business or you're scaling from one stage of a business to another, that is a very dangerous philosophy. And uh I'll give another example because I love to answer these questions with examples, but think about Blockbuster. So uh we're millennials, so we were we know the whole Blockbuster thing, right? Uh for anyone that's listening that is not a millennial and doesn't know what Blockbuster was, you want to share what Blockbuster was?

SPEAKER_00 19:27

Uh yeah. So basically, Blockbuster was this store, and you could go in, rent DVDs and VHS films and things like that. Uh, you pay some money, bring it back during the due date. It was basically like a library, but for cinematography.

SPEAKER_02 19:46

Yep.

SPEAKER_00 19:46

Um, they also have video games you could rent out. Although that got a little bit tricky, people would take their broken video games and swap them with the Blockbuster one. Oh, and then they started putting seals on all their products actually so they could differentiate. Um, but yeah, just a rental spot.

SPEAKER_01 20:04

So basically, Blockbuster was a huge company back in the day. Uh, unfortunately, it's no longer around because they did have to file for bankruptcy. They closed all their locations, but they had a choice at one point to change their business workflow to a streaming platform and to actually acquire Netflix at that time. So in the early 2000s, uh, Netflix is a new um business on the block and they're bringing a whole new philosophy and a whole new prototype when it comes to just how we work with videography, right? With the introduction of streaming, Netflix arises and um Blockbuster is given the opportunity to acquire Netflix, they don't do that, but then they see that there are a growing amount of consumers that are actually preferring streaming as opposed to actually the old school method of going in, renting a video, and returning it. And despite all the information and all the data that existed at that point in time, and despite all the market trends that were there as well, they actually didn't kind of budge at all. Um, as you know, we see when it comes to the involvement in different spaces, trends change, you know, and even though it's not broken at one point, it could be broken later. Um Blockbuster didn't actually move fast enough. And unfortunately, they could not keep up. Really, consumers were just more comfortable with just streaming from at home, not having to worry about paying drastic and crazy late fees, right? Not having to worry about physically returning like physical videotapes. Um, it just became a thing of the past. And unfortunately, Blockbuster became a thing of the past as well. And I think when it comes to the business space, data validation is so important because you must stay on top of market trends and the changes when it comes to market trends in your space, so you are not, you know, blown out of the water or you're not left behind.

SPEAKER_00 21:46

Yeah, and it's crazy because in 2000 they had a chance to acquire Netflix, like you said, for only fifty million dollars. And Netflix is worth way more than fifty million today. And, you know, it only took About 10 years from then, like 2010, there it was a billion dollars for their bankruptcy, which is a lot of money.

SPEAKER_01 22:05

Yeah, it's just crazy to see how important data validation and staying on top of uh the information received and actually not just knowing what's going on, but actually moving in a way that corresponds to the data thereafter, uh plays a role.

SPEAKER_00 22:20

I think that um this story about blockbuster you're bringing up intersects very well with our topic because sometimes when you give people information, since like I said earlier, we're sort of in this post-truth world where we have a lot of misinformation, people calling things fake news, we have AI generating and creating you know, deep fakes and things like that. Um, I think one big thing to discuss is denial. And I would argue that Blockbuster was in denial that this market trend really had value. Oh man. And now you can rent movies on like Amazon for $3.99 for 24 hours. I mean, people are literally you literally can rent things without even having them. It's just data now.

SPEAKER_01 23:03

It's just I love what you said about denial because um when I was working in the corporate space, um I would advise businesses from small to medium and then eventually enterprise businesses to make certain decisions based on trends, right? Uh, that we're seeing in the data. But then also I would take information and trends I'm seeing in the clients and take it back to the team to say, hey, this is gonna make or break our next phase, right? And sometimes there was that theme of denial, right? Maybe, for example, in my space, there's a certain product that's being pushed to the front that maybe our the customers at that particular point weren't really asking for or it didn't really solve their needs in the way that um those folks thought that it would. Um, so denial is really important to think about like, hey, am I denying the facts that are here? And for what reason am I denying? We can kind of bring it full circle back to the very beginning of this conversation when it comes to just our own kind of biases, like, oh no, I see this one data point, and that kind of corresponds to what I think. There's so many different pieces that we can be pulling from as well. And even beyond that, it's so crazy now as a small business consultant to see like how many business owners don't actually know certain metrics when it comes to the success and the growth and the retention of their business. They don't know their repeat purchase rates, right? Um, they don't know their customer acquisition costs, right? They don't know their profit margins, they don't know these things that really makes or breaks how you move forward in that next phase. Not only having the data at your disposal, but actually educating yourself in a way so that you understand what that data means and then thereafter making the decisions necessary so that you can stay relevant, you can stay in the game, and you don't fall behind like some of the other businesses we've seen.

SPEAKER_00 24:44

Yeah, definitely. Both in business and academia, the ability to interpret the data and the information is super important. Just make sure that you're not just looking at something and assuming you understand it because you're literate or you know, you have your degrees and things like that. I mean, everyone always has the ability to misinterpret something at any given moment. So yeah.

SPEAKER_01 25:03

And in business, if you don't really know what you're looking at or how to interpret data, there's so many different tools that are at your disposal, whether it be, you know, um, if you just ran a campaign on Instagram, you know, Instagram Insights, or, you know, if you integrated Google Analytics with your website and you want to understand like conversion rates and quarter to quarter, why it's different, things of that nature, it's important that you not only have the data, but that you know, like you said, how to analyze that data. And if you don't know, I highly recommend that you enroll yourself in some kind of data analysis program or course so you can make educated decisions or hire someone that already has that information ready at their disposal, like us here at People's Coach.

SPEAKER_00 25:43

And something else that's really important outside of all those things, also remember to double check websites and things like that, have a little bit of what's called information literacy. So I mentioned annotated bibliographies, which are a part of that, but it's also understanding like website tags and things like that. For example, dot com means commercial. So if you're on a dot com website, you have to remember that commercial websites, people can pay to advertise, they can pay to put certain information on the website, whether it's true or not, and things of that nature. Um, and then you know, you have.orgs, which some people feel like is more credible than a dot com, but really a dot org just means organization, and organizations have their own interpretation of information and things like that. I used to teach a lecture about MartinLuther King.org. It was this old website. I don't know if there's a new version that's real now, um, but basically it was a website with a lot of misinformation about Martin Luther King that was made by a racist organization. And a part of the lecture, and this is one of the tools I want to give to the viewers, is that I would use a URL website checker, which is a tool that'll tell you when the website was first created, how long it's been on the internet, uh, how many scams have happened, if any, through there, are there any viruses on the website? Yeah. Who is the publisher and creator as well?

SPEAKER_02 27:03

And what was the name of the tool again?

SPEAKER_00 27:05

Um, well, there's a lot of different ones. The one that I used to use doesn't exist anymore, but the point is there are a lot of different URL checkers. You can check URLs and get a lot of information. Just look into you know that tool itself.

SPEAKER_01 27:20

Awesome. And before we close out, one more topic that I want to kind of touch base on is just AI. So we talked about data validation, we talked about data referencing. Uh, but when it comes to AI, I think it deserves its own small segment because it is just rapidly taking over all of our lives. And although it's been around for a while, I feel like at least in the last five years, we've seen it advance in so many different ways. Um, whether uh we have cars that are driving itself, we have customer support chats, right? That you're never really speaking to a human, but it might somewhat feel like you are, but you're not what you are, but you want to. Um sometimes so folks are using AI just to create their whole websites, right? Or PowerPoints or anything, everything and everything and anything, you know? Um in your opinion, when is it a good idea to use AI in business or academia? And when is it not a good idea to use AI?

SPEAKER_00 28:18

So I would say that it's great to use AI for brainstorming if maybe you're not sure what a word means, or you know, hey AI, can you explain this concept using this kind of theoretical lens and things of that nature? Um, I would argue that that's a great use of it. Or if you're using like Grammarly premium to correct sentence structure, sentence patterns. Yes. Most spell check tools are it's AI, they're just scanning for algorithms.

SPEAKER_01 28:42

And I think you told me that Grammarly is an AI.

SPEAKER_00 28:45

Yeah.

SPEAKER_01 28:45

I didn't even know that. Uh, we were just having a conversation, him and I over dinner, and he was like, Did you know that Grammarly is an AI? And I was just like, No. And I'm like, okay, well, that's a healthy way to use AI, like you said, uh syntax, grammar structure.

SPEAKER_00 28:59

But the problem comes when people are like, write me a three-page essay based on this prompt. Um, and we're always gonna know because we use AI to check for AI. And there's also AI you can use to hide that you're using AI, which is crazy. Uh so we're gonna.

SPEAKER_01 29:15

So how do you check for that if they're hiding? Oh my gosh. So you're you have an AI to check if they're using AI, and then you have an AI to check if they use something that says that they're not using or that they're using to look like they're not using AI, and then you have all these AIs.

SPEAKER_00 29:31

Yes, there's just multiple, and then they're just basically at war. Um, some other unhealthy uses in academia, there is a new AI, and I always hate talking about this because then I'm like, see, look, students are gonna see this, they're gonna go find it. But I'm gonna bring it up anyway. But this one, okay. Uh there's a new AI that can actually log into log into your school systems, it can do blog posts as you, it can log in and out so you have account activity. It actually can make spending. It logs in as you so you don't even have to touch the. Even though they have that check if you're a human thing, like there's AI that can do that stuff now.

SPEAKER_01 30:05

Um where do we draw the line? I'm sorry.

SPEAKER_00 30:10

It will create typos and errors so that it's not perfect.

SPEAKER_01 30:14

Regis, you have a lot of work to do in that classroom to make sure these students are. I already know how to be.

SPEAKER_02 30:19

I'm chilling.

SPEAKER_01 30:20

And it's just crazy to think about that because it's like the whole point of like writing a paper or doing like a uh research article or whatever is just to promote critical thinking and even creativity, I think, as well. And I I fear for um the future, not to say AI is better, but if you're using AI for everything, like who are you? What do you think? How do you think? Well, you know, like you might not know how to answer those questions in a few years because you're not doing any of the work that actually makes or breaks your character development and your personal development, because you're falling back on AI for everything, when AI is not a human at all. And I actually want to kind of segue on that in business. Like one thing that I really dislike is when I call in and I have a uh a question or a problem I'm dealing with when it comes to a vendor I'm working with, or uh I'm a consumer of a certain brand and something went wrong. And, you know, I can't get to a human. And this has been something I I feel like we've been seeing in our space as I guess uh as consumers for a long time. But I mean, how off-putting is it to um be a consumer of a certain product and then something goes wrong and you spend 30 minutes trying to talk to a human and you never do, and then your answers never get solved because as much as we want to like give AI the weight of human complex problems, humans want to speak to humans. Humans crave, you know, human connection. And now you see AI podcasts, AI influencers, AI this, AI that's like. AI artists there's some music. AI artists, right? Where do we draw the line? I do want to talk about some practical ways that students and business owners can use AI. What are the healthy ways? There are some tools that are helpful in the business space when it comes to using AI and some best practices as well. So I'm gonna quickly chat through that. So I've worked in the software space and in different, you know, in the business and corporate space for eight years. And there's a bunch of different tools that have been around or just coming out and about. And one tool that I think is very, very helpful is otter AI. If you're in a Zoom meeting with a customer and you really just want to be present, you don't want to be typing or writing notes, it will transcribe the calls for you, which is great because it will summarize what your meeting was about. Um, if you send takeaways of the call, which I highly recommend when working with any client to summarize what you spoke about, keeps everybody on track. Uh, you can simply, you know, take that transcription, uh, that summary, kind of, you know, make a match your tone if you want, or there just send it straight after uh to that client. It does actually streamline some workflows in that way because uh instead of you manually writing something or typing something out, putting it in a template, kind of changing the structure and then pressing send, you can make a 35-minute task a 10, 15-minute task, maybe 10 minutes. Otter is a great one. Um, Zapier, I was introduced to Zapier a few years ago. And Zapier pretty much connects two different tools to each other to pass around information. It's like a fake API in a sense, where uh there's algorithms that are created. Um, for example, if you have a website and you have this newsletter that folks can sign up for, um, if you want every sign up to that newsletter to actually merge into your CRM and create a customer contact where you follow up with that customer three days later, thank them for subscribing, share about what's new at your store. You know, you can use Zapier to create that integration without being a uh back-end developer, for example. So AI does help streamline workflows, right? There are some other tools out there when it comes to scheduling as well, um, where you can say, Hey, AI, I'm busy usually during these days of the week. Um, these are this is when I'm free. Um, you know, for anybody that wants to book a meeting with me, this is the best time and things of that nature, or any any kind of follow-ups too, uh depending on the line of your business. If you are in the business space where you should be following up with clients, maybe somebody comes and gets their hair done. Um, and you know, oh, okay, this style that they have, maybe you do like braids or whatever, or um, I don't know, like um a press out or, you know, or whatever. And you say, okay, that usually lasts like six weeks or whatever. I'm gonna have AI automatically text that person or email that person. Um, I'm gonna create an algorithm that says, when X happens, this service happens, these many days later, I'm going to go ahead and say, hey, uh, it's been a while. I'm gonna make a personalized message so it looks like it's coming from me, and it is in a way coming from me. So that customer comes back to my chair. So those are some of the ways that I think AI is great in business. I don't think it's necessarily great when it comes to when you're actually storing confidential information about a customer. For example, if you're like a therapist or like a life coach and someone's telling you sensitive information, once it's in the uh AI atmosphere, it doesn't really go away. So um, you got to think about those security protocols, not only if someone's a fake person, right? But also are you exposing somebody's information without meaning to, right? So that's another way I think that AI can be convoluted at some times and a bit dangerous uh to use. And then also the human-to-human approach. I host writing workshops uh with a friend in LA, right? I would never have AI do that on my behalf. Imagine you go into a creative writing workshop and you walk into a room and there's this robot or uh this screen leading an exercise, right? There's just some things that AI is not going to be able to replace. The human-to-human connection is one of those things, right? Um, so yeah, I think that is a quick summary of when AI is helpful. I also share some tools that small business owners can use when it comes to implementing AI and when it's not so helpful. Are there any tools in your space that folks can use?

SPEAKER_00 36:03

So I would say for academic leaders um and also professors that don't have the opportunity to maybe have a teacher's assistant or aide or a graduate assistant, definitely the virtual AI integrations with courses is pretty cool. It allows for the instructor to send less tedious emails for things that are maybe simple tasks. Like maybe your student can't find something on the module section, or maybe your student is having trouble understanding the prompt. Okay, instead of them having to make an appointment at the tutoring center and like, you know, depending on their availability, you can integrate an AI into your course that can interpret that information or say, hey student, here's this article that answers this question. Um that way they're also not giving them the answer. And you can actually set up rules within the programming to where the AI will only follow those X amount of rules you set. So you could set a rule that says, Don't give the students any direct answers or allow them to use you to write responses. Okay. Okay. Or you can make a rule that says when students ask questions, only link them to articles with the answers. Things like that. Um and I think that those are really useful tools, especially if you're getting like 20 emails for something really simple over and over again. I would also say that automated AI that can help you with creating bibliographies and work cited pages like scriber.com or easybib.com um and things like that. You just paste the link and it will create the citation entry. Not only will it help you see what it looks like and learn the formatting, um, but it also, if you're cognitively overloaded from writing, can help you just sort of decompress and tedious steps. Yeah, for sure. So I would say tools that point you to resources um and things like that. And of course, we're gonna list some tools in the uh section of the video for people to click on links and kind of see some other stuff too.

SPEAKER_01 37:53

So and there's gonna be a blog article with all these best practices, uh tools that we mentioned, um, hyperlinked uh to those landing pages as well. If you're ever so curious about any of the tools that we mentioned, please check out our website. Much, much more coming People's Encover. So before we close, we definitely want to share some key takeaways to today's podcast. We want to encourage you all to use data as a guide and not a dictator. That meaning there's all types of data that exist. We just shared earlier that there's tools that show your opinion, others' opinions in a neutral stance. Remember that the data that you have to prove your point is only one half of the story. So be open and willing to explore other options, especially when it comes to reaching a final destination point to a certain opinion that you may have, right? Yes, data is a guide, not a dictator, and not a final destination because the data is always changing and evolving, right? For example, some folks at one point thought the world was flat, right? We learned that the world is not flat, right? So allegedly. But yes, um, data is changing, data evolved. So as data changes and evolves, make sure that you're staying up to date with those changes. And also understand that sometimes the tools that you have access to are not the full story, right? Whether it's a textbook and it's missing information or it's written in a biased way, or the person that wrote it is not telling the full story because they believe that their opinions and their biases are facts. You have to be cognizant of that and know that when it comes to data validation, sometimes you don't have the full picture and be open to being curious to learn more about that full picture.

SPEAKER_00 39:28

Remember, data can be manipulative, and even if data is accurate, you still need to unpack the information to understand the better context of the whole story for sure. And that's something that a lot of people do skip over. Just because something is true doesn't mean that you're analyzing that data appropriately. Uh I'm Regis Peoples. I handle the educational consultation side of Peoples and Co.

SPEAKER_01 39:52

Yep. And I'm Kier Peoples. I help small business owners grow and retain their clients through online and offline strategy. Um so we're really excited about the evolution of our podcast, The People's Exchange. And if you're curious about any of these best practices, you can check out our website again. Uh, please subscribe to the podcast if you're not already subscribed. And if you love this episode or you like this episode, we love five-star ratings. Um, all right. So um, thank you so much. Remember, keep making smart and informed decisions and don't be afraid to change when the data tells you it's time to make that leap. Okay. All right, take care.

SPEAKER_00 40:26

All right, see you later.

SPEAKER_01 40:27

Bye.