1. Content Made with AI Is Obscuring Real Information – Tech Field Day Podcast

The internet is full of garbage, isn't it? It just seems like it's being overrun by AI generated content, SEO oriented content, and it's getting flooded as all of the social media networks are gamed and algorithms and everything. Well, there is an antidote to that, and that is real opinions from Real People.

Welcome to the first episode of the Tech Field Day podcast. That's right, the On-Premise it podcast is now the Tech Field Day podcast, and we're kicking things off with a discussion of community, of credibility and of reaction to this, everything that's going on flooding the internet with garbage content. Welcome to the Tech Field Day podcast, where we bring together a group of independent technical folks to discuss important concepts in technology and community.

This episode is related to the Tech Field Day events series where we bring these folks together on person or on premises, as it were, to discuss key concepts with companies in the industry. Each episode of the Tech Field Day podcast features a central unifying premise that we are going to discuss throughout the episode and try to come to some kind of consensus on this podcast is brought to you by Tech Field Day, part of the Futurum Group. And I'm Steven FoST, organizer of Tech Field Day, and President of the Business Unit.

On this episode of the Tech Field Day podcast, we're talking about community and credibility and the importance of having a voice now that so much content is optimized for search engines and optimized for advertising and even AI generated. Before we get into that, let's meet who's on the panel today. Hi, I'm Gina Rosenthal.

I'm the CEO of Digital Sunshine Solutions at Fractional Product Marketing Agency in Austin, Texas. com, or you can also find us on me on the Tech Aunties podcast. Hi, I'm Colleen Call.

I am a global event and marketing strategist. I'm Frederick Van Herron. I am the founder of Hyphens, a company active in consulting and services for the AI markets.

You can find me, um, as Frederick v Hern on LinkedIn. So we are here at AI Field Day this week in California, and we've been hearing all about the infrastructure that supports ai. But one of the things that keeps coming up, especially from the delegate community, is the impact of AI on society, on communities, on the world, the risks and challenges of ai.

The and, and, and it goes way beyond some of the things that, you know, I don't know, normal average people out there are worried about in terms of, you know, hallucination or AI is gonna steal my job or whatever. What, what worries me the most is that AI is really flooding the zone with basically fake content that is generated just for the purposes of attracting advertisers, attracting views, attracting clicks, that kind of thing. Mm-hmm.

Gina, this is one of those things I know that you've been deeply involved in and you know a lot more about it than most. Tell us a little bit about the, the credibility challenge and the importance of individual voices. I think right now, what's, what's changed and what's different, um, than maybe when we started with communities and social media, um, a couple of decades ago, it's crazy to say, but it, what's different now is that, uh, the content has to content more and more to be able to find individual interesting real content from experts or people very passionate about different types of domains.

You either have to know where to look, or you have to be in a community where that content's going to be promoted. It's no longer easy to find it on the social media platforms because of the way their algorithms work with their different priorities they have for how users interact with their platforms. Google is increasingly difficult to use as a search engine because they are prioritizing, um, AI driven content at the moment.

But, you know, in general, over the last several years, if you haven't conformed your blog, and I know I'm guilty of this because I want to have the visibility, if you haven't conformed to the way that their SEO guidance is, then you won't, um, show up on the top, on the front page, so people may never see your content. So what worries me is, you know, we've got this community here, so we know lots of people that make very, very expert pieces of content or point to other expert pieces of content where we can read those and stay up to date in our field or up to date in what's going on with the world. But, um, if you don't have that community to point you to things, how do you find the really researched nuanced information, um, that helps us function as a society that holds us together as a society?

Or are we gonna be just if, if things keep going the way they are, we're just gonna have this word salad as what is informing our lives about technology and other things too. Yeah. It really seems like that's the direction that it's heading.

And it makes me really sad because, you know, I, I was reading an article earlier today about product review sites, and they were pointing out that the, um, the Google search results for, you know, best whatever, best air purifier for pets or whatever, these search results are completely dominated with inauthentic content based, not on actual lab testing and reviews and stuff, but, but optimized for search engines. And even worse, that the publications abs right out lie about it. It, and they say, you know, in our extensive testing or based on expert evaluation or whatever, because they're gaming the system, and it's the same, like you say, when, when it comes to sites like Twitter X or even, you know, LinkedIn, Facebook, TikTok, Instagram, whatever you, you know, the site that you're looking at, the content is optimized to rise to the surface by experts and, and that really essentially makes it inauthentic.

Um, what does that do to you as a viewer, as a reader? You know, what do you think? Well, I think from, first of all, from an AI perspective, if you look at the, the growth of ai, it's all driven by an open source community.

I mean, community in general. Uh, when we say that we typically think about algorithms, but at the same time, a lot of the advances in AI is coming from the community, generating that data. As far as the larger enterprises, I agree that data is curated by them.

You know, the information we're getting is the information they want us to hear about. Um, but I think that that will improve. Uh, let's take an example.

A generative ai, it's a lot easier nowadays for people to build their own system, some generative AI system where they provide, uh, data from the community and provide alternatives to the larger enterprises. So I, I'm definitely more hopeful that based on tools like generative ai, that the community will have access to more, less curated data and more data that is being provided by the community. Did somebody mention that?

One of the vendors mentioned that, and I don't remember who it was, that they were slurping up all of our blog posts and on a certain topic, do you remember who that was? I'm not making this up. I do remember it, but I hope that you're right.

You know, 'cause I can remember, I, what worries me from being in, you know, marketing situations at the big vendors is, um, when it gets away from the product marketers and ends up on the global marketing team where they have a, if it's, especially if it's a very large organization, they have a very pretty picture they wanna paint of how that company is, which is a great pretty picture. But when we need to get down to the nitty gritty and understand how do we deploy this, how do we use it, what do we do when there's a problem? I mean, this was this, and that's why you created Tech Field Day in the beginning, isn't it?

Is definitely why I started blogging in the beginning. Yeah, absolutely. And, and I think that the goal originally was that the voices of independent technologists would be more credible, more valuable resources for people than marketing content or professionals.

That, that there was, um, a value in listening to the voice of practitioners, the voice of independence, the voice of people who cared more about sort of what the product is and how the product works than what the companies are saying about it, or the size of the market or the potential investment or whatever. Um, but I, I think that it goes way beyond enterprise tech. I mean, you know, in almost any space, right?

There's a, a crisis of credibility, right? The pretty picture is, is good, but who's going to listen? And then to your point, yes, uh, AI is, is is putting together all of this information and spewing out something that they think is a pretty picture.

But long and short of it is that the, the software engineers and the people that are reading or, or, or welcoming this content, they're not gonna, they're not gonna read it and they're not gonna accept it unless there's some authenticity to it. And me hanging out with the open source community or anybody in the cloud ecosystem, um, and the community, they like the unplugged versions of, uh, of, of people. And they can spot generative AI or any ai, uh, content, uh, in a minute.

So if you are, which is, which is interesting when, when I use it, I use it as a starting point, and then I put my whole self into it, um, just to have my voice and tell my story. And I hope that that's what people are, because when I see the people doing content creating, and they are using ai, but what makes them, um, stand out is that it's the Marino, ou js, it's the, uh, the Cory Quinns that they have their own voice, whether they're ship posting or just talking about anything or having a coffee or, or something like that. So I'm not sure, I mean, just based on being here, uh, for the last three days, we've heard about the infrastructure and, and everything technical, but where is the voice once you get all that information?

What happens when you have to be a real person and u using it, but what makes it authentic? Yeah. I think you make a good point.

I think one of the problems we have today with the solutions that are available today, like Google and others, is that people forget to make up their own opinion, right? Mm-hmm. You ask a question and you mm-hmm.

You, you take the answer as the one and only answer. Yeah. Uh, I think people need to learn again that they're, they have to make up their own opinion, but at the same time, they need to have access to a variety of data sources through the community so that they can make up their own opinion again, like we used to do, and, and make those decisions, um, for themselves, as opposed to answers being given to them as, as a done done fact.

I agree with that completely too. We now, we had the conversation about long form content, Steven, that you didn't think people wanted to read that anymore 'cause it's long. And I kind of pushed back, and I love that you read the long term, long term format, um, article that I sent to you about this.

But, um, I, I pushed back because I think as technologists, not only do we want someone's opinionated view of something, um, 'cause that's, I've done that, but like, what I've always done is I am like a librarian. I will give you the links to everybody talking about it and, and a synopsis of it. So if you wanna learn about this topic, here's a synopsis, here's where to go read it.

But like, to get to the point where I can give like a lit review on a certain topic in a blog post, it is a lot of reading. There's no way to have an opinionate opinion about anything without reading a lot or watching a lot of videos and, and taking it all in. So the question becomes how can you find that content if it's getting increasingly hard to find it in a search engine or if it's, um, like I won't, I am not on Twitter X because of all the reasons lots of people got off.

I just refuse to be on it now. So I'm on Mastodon. It's not the same.

LinkedIn is not the same. LinkedIn is actually tending more to the marketing curated side than it is to the more Yeah. Opinionated pieces y'all are talking about.

So it's almost like we need to bring web brings back. We need to start using my Rs rest reader again. You know, that's the kind of stuff we probably need to do.

But I think there's also a cultural problem, meaning, you know, you provide a bunch of links, but if those links are like three or four pages long Yeah. People don't have the attention anymore to read three or four pages. That's right.

It's 300, 400 words and then they get bored or want to jump into something else, which is another challenge, which means that you all, you almost have to say whatever you need to say in the first 300, 400 words, and then kind of follow up with arguments, which most likely people don't read. And I'm guilty to that myself. There's so much information that if somebody gives me, those are the 10 PDF files you have to read, most likely I will spend maybe a few minutes on each and then make a decision if it's really interesting to continue.

But the likelihood that I will grasp whatever is in that PDF is, is very slim. And again, I think it's a cultural thing. People don't read as much as we used to.

One of the things I think that, that AI brings to the table here, though, is a lot of people, myself included, are using generative AI as a way to summarize content. Mm-hmm. There's a risk to that because although generative AI is really good at summarizing content and surfacing the key points and helping me to kind of understand what this article is about, it is no, you know, it's no replacement for actually reading the article.

And, uh, I find that it will sometimes make, you know, hilarious mistakes in terms of what it thinks is important. You know, I, um, I will use it, for example, um, to, you know, with my RSS feed, you know, what's this long article about? And, uh, often it'll come up with, with, with good stuff like this, article's about this topic and this topic, and they say this thing and this thing, but then there'll also be a little bit in there and, you know, and then they talked about their lunch and, you know, they talked about their recent vacation.

And it's like, okay, that's good, but that's not really what I was going for with the summary. But, you know, I mean, AI's gonna AI and that's kinda what's gonna happen. And I wonder if that could be a problem, sort of AI on the reader side could be as big of a problem as AI on the content creator side, because more and more we're gonna see AI tools used in that way on the reader.

What do you think? Well, I think the worst thing that can happen to us is that the only content being created is the content being generated by gen generative ai. Because then we kind of like in a vicious circle where, you know, the reality, we, we can't escape reality at that point, or, or the perceived reality, I should say.

Yeah. The old joke about, I used AI to generate the perfect email and then the person on the reception, I, I used AI to read this email and summarize the bullet points to me, There's a couple of problems, right? The innate thing about use losing the humanity because you have people.

That's how we come up with, I do not believe AI on its own will generate content, especially in a generative AI way, based on how that works, that becomes a spark of a new idea to do something new. That's what humans need to do. And that happens based on our own individual lived experiences and our curiosities and, and all the rest of it.

So, we'll, we'll see different articles and maybe have an idea of a different thread that pulls through it. Um, I'm usually pretty good at finding the one that nobody ever thinks about. That's a really weirdo stance on it.

Um, but it keeps everybody on their toes. So it's fine that that's part one. But what happens if you're somebody just coming into our field and you don't know how to find blog posts being written by a real person with experience, with an opinion of how to do something, or how things are, or how things used to be and how that led to how things are, if you're a brand new coming outta college person, how do you get that information anymore?

Because that's how I got it. You know, blogs were, it started probably right after some big advent. I would get so much information from there.

But what if that doesn't exist now in this world because of generative ai? Then we're robbing the next generation of technologists of ways to pull the information together in their own heads and, and innovate the next things, Right? But I, I think that comes back to what I said earlier about cultural is, is somebody who's born in, in, in the two thousands or the early two thousands, you know, any question is being answered by the phone, right?

They pick, pick up their phone and, and get their answer. They, they don't, they don't understand that there, once upon a time was a library where people had to go to, to figure things out and learn new stuff. Nowadays, learning seems to be this, this five second thing you do on your phone where you ask a question.

And I don't think that's fair. I don't think that's fair to say about them, because I know that that's a lot what they do to get the starts of the answers. Most of them will sit through a training class, most of them will come and ask to sit with you.

And they, they want their older peers to give them that insight and help them see along. And I think that if we strip away this whole idea of writing content or having, um, um, complicating content like Steven does with Tech Field Day, I think that's, um, I think it's, it's, we're we're, we're cheating them out of something. But in a sense though, and I know that we're mature, so when he we're older, but are we giving them the benefit of the doubt?

Because I think we're worried about a lot of things because that's the way how we were taught. They are probably processing this information way better than we did, uh, back in the day. Um, and they, it, it will probably be not as worrisome.

And they, but if you can see on the TikTok, I, I hate, I know I didn't, I wasn't supposed to bring up TikTok, but people want that authenticity Yes. Content. They can tell, they can tell what is ai, um, uh, generated, especially with video and some of the content.

I think that these, uh, this generation is smarter, well, not smarter, but is smart, smarter than we think they they are, because based on how they learn and how we learn, it's, it's totally different. And sometimes I think we have to give them the benefit of, of the doubt on how they consume this information and what works for them. No doubt is that is generated, um, right.

Um, by, I agree. I Think it's also volume gear, right? They, they're being exposed to a lot more mm-hmm.

Information and, and problems than we used to be exposed to. There's a certain sense though of, of generational media literacy. And so the Gen X people, um, had were very sharp, um, when it came to, uh, printed and, and, and video mm-hmm.

And television. And, you know, we were cynical about ads and we were cynical about, you know, reviewers and experts and so on, you know, millennials, you know, they came up in a different world and they were very, very sharp, uh, and media literate about different things. You know, I think you're right, Colleen, that, that it's very likely that people who've been raised in an environment of artificially generated content and are, you know, are, are gonna be very savvy to that and, and careful about, about questioning that.

Um, but back to, to Gina's point about how do you find this stuff? Mm-hmm. Um, I think that people in all generations are hungry for, not experts, but just credible voices.

Exactly. Yeah. You know, it's not about expertise.

I think that, you know, there's this idea that, you know, back in the 1950s, like, you know, the media was all, you know, deferential to experts, you know, and expert opinions. I'm not sure how true that was. I wasn't alive then, so I wouldn't know.

But I will say that, um, nowadays I think people aren't so much hungry for expertise as they are for a credible voice. So I think people will happily watch a, um, an inexpert person trying and struggling to install a piece of software and discovering the configuration of it and discovering how to do it, and, and really truly learning and understanding the intricacies of the system. I think that they, they will respond strongly to that, maybe more strongly than somebody who I don't know, is on the development team and just bang, bang, bang, and I'm gonna do this, and I'm gonna do that, and I'm gonna click here.

And, and that gets to the tech Field Day demos, right? So if you're at Tech Field Day and somebody's doing a demo, we always encourage the companies to bring sort of an SE or somebody who would actually be installing this in the field because it gives that sense of credibility. This is somebody who has sat on that data center and sat in front of that keyboard and done the thing.

And it makes it feel more real than a product manager doing that. And that's kind of what we're going for in all sorts of areas with Tech Field Day, but it's also what we're going for with the delegates. In other words, you guys are here because you represent the world outside the room.

And so that's one reason why the delegates include analysts and writers and end users. And sometimes we like to throw a curve ball, crossover delegate in there, somebody who doesn't know the subject. Mm-hmm.

Because of that, because it's not about expertise, it's about credibility. Right. And so you yourselves are the credible voices.

I I'm, I'm, I'm going on because I get excited about this stuff, you know? Do you feel that way? Do you feel like credible voices Most of the time?

Yeah, I think So. I think if, if the best way to learn is by making mistakes or by watching somebody else make the mistakes, I think those are the ones where the times where you learn the fastest, right? If everything goes fine, then it looks like it's straightforward and people will not appreciate the complexity and the work that went behind that.

So, um, when I was running an engineering team, I always told my, my new employees, I told them, I want you to make mistakes, which they didn't, they didn't really grasp in the beginning what I, what, what I was telling them. But making mistakes is the fastest way to learn, and that's still true. Independent of what you do, making mistakes is the best way to learn.

Yeah. And, and I think that that's one of those great things. We have a, a field day rule, which is if you have a que to the delegates internally, if you have a question, ask the question because somebody watching this video is gonna have that same question, even if you think it's a dumb question.

Um, and, and I think that gets to that, right? Yeah. I, I, I think, and if you don't make a mistake, you don't, you don't understand how it works behind the scenes.

If you don't have to fix something, you don't know how it works behind the scenes. And I think if you don't ask the question, that goes to everybody having their own unique view and bringing it to the table. For sure, somebody out there is gonna have the same question, but also people may have not thought of it from that perspective.

And it opens up a whole new round of questions when you ask it. And that's the importance of, uh, being together and asking questions and mm-hmm. You know, reading people writing about making their mistakes and then fixing them and, you Know, well, is the purpose of AI is to make things perfect, or will someone teach AI to fail?

It doesn't need much help. Well, the best way for AI to improve is to make those mistakes over and over and over. Yes, exactly.

I think it's an in an infinite thing, right? It never stops. Yeah.

I think the day AI stops learning that, that's the day, you know, that ev everything will go status quo. Well, the thing is, is it's a trust factor for people to, to, to trust content and, and, and, and we'll just trust what, what they want to hear or what they want to, to know the knowledge. Um, so if we teach, 'cause I'm, I'm, I have my Skynet, if on right now, if we teach them to make mistakes, uh, would that make AI perfect?

You know, if they suddenly you ask them a question and it sounds like that it wasn't the right question, well, well, you know, but then he's, he's credible. Oh, this, this gen generative AI is credible. You see what I'm saying?

It's just, Well, it does, it, it gets to a point where I think that a lot of the time I think people have this sort of, um, the imposter syndrome where they feel like, I'm just faking it up here. I don't know what I'm talking about. You know, they're gonna figure it out.

But I think that truly emotionally intelligent people realize kind of get beyond that and realize to embrace that. Yeah. To embrace the fact that you don't know what you're doing because hello, we are learning.

And for me, those are the best moments of conversations, whether it's at tech field day, on camera, or in the evening, uh, afterward, or in our regular lives, is when people are smart enough to say, wow, I don't know about this. I'm gonna try something, or I'm gonna listen to someone, or I'm gonna try to do some research and find something out. I'm gonna share that, you know, back to the origins of blogging, right?

Right. Gina, I mean, you and I were there when this, you know, this whole blogging and social media thing kind of hit technology and it was all about people learning and sharing their experiences, learning It was basically, I'm trying to do this thing and I'm gonna write about it while I'm trying to do it. Right.

And what was so cool about that is I was in education, I was a trainer, and, um, I wrote training materials. So I had lots of, uh, ways to, I did have ways to point people towards really great resources, and that's what I did. But being a trainer and seeing how people were searching for information and how to fill that information need the best way, um, yeah, that was, it was really great back then.

I can see a lot of repeats now, but I think that's what makes us human. And that's the difference. I don't, that's why I think that gen generative AI machines will never be able to do that.

Yeah. Even if it makes some mistakes and thinks it's, you know, and, and then that makes, that won't make it human because the way that it's programmed is just to repeat the next word or predict the next word that's gonna come up. So it's only as good as the corpus of data that it was trained on.

Right. So it can never make mistakes enough to get new data into it. A human's gonna have to do that, and it'll never make the mistakes or build the, the real physical human neural pathways to have this need for information.

Like, why didn't that work? What do I do next? And go through all the steps to actually make it happen.

Unfortunately, the neural pathways don't work that way. Right. The neural networks don't work that way, even though that's how they name them.

Yeah. I, I think that really ultimately, um, to kind of wrap up this discussion, I really feel like the ultimate answer to the question about the, uh, uh, if I can say in ification of, uh, of the internet is people, it is those of us who are out there talking about things, looking at a camera, being ourselves, being our real selves, you know, warts and all, um, admitting our, our own failings and, and, and trying to learn and trying to learn on camera, uh, trying to share that with the world. And honestly, not to toot my own horn too much, but that's exactly what we try to do with Tech Field Day.

That's why I created Tech Field Day. That's why I value this community. That's why I wanted to do this.

That's why I do this podcast. And, and everything is because it's a great way to share and learn and grow and experience. And it just so happens that it's also the antidote toward the flood of AI generated content and the flood of SEO and the failure of, uh, basically all these social media systems that are all algorithm fired now and hide everybody's content.

It's all about finding a few real people, seeing who those real people really talk to, getting to know people at conferences online, in communities, and continuing to build those connections. So before we go, I'm gonna give you all a chance to, uh, tell us a little bit, um, where can we connect with you and continue this conversation. com.

com. You can find me on LinkedIn at Gina. to, You can find me on LinkedIn, Colleen call, that's C-O-L-L-E-E-N-C-O-L-L.

And you can find me on Twitter X at Colleen call. As for me, you'll find me on social media at s FoST. I am on X, Twitter and LinkedIn.

And yes, Mastodon, and I would love to hear from you. You'll also find me on, uh, three weekly podcasts, the, uh, utilizing tech podcasts on Monday, the Tech Field Day podcast on Tuesdays. And, uh, the weekly News rundown on Wednesdays.

And you'll find all of these in your favorite podcast application. This podcast is brought to you by Tech Field Day, the Independent IT Content creator event. com.

You, we are part of the RUM group, and you can find more on that website. Thanks for listening, and we will catch you next Tuesday.