Artificial Intelligence is on everyone’s minds these days, especially at work. Some people love its ability to take over the mundane tasks we hate doing, while others are afraid AI might take their jobs.
What’s clear is that artificial intelligence is here to stay, and our guest this week is an expert at making it our friend.
Evan Ryan is the founder of Teammate AI, a software company that helps businesses grow without adding payroll, freeing up people to do uniquely human work.
He’s also the co-founder of Lede AI, a company that uses artificial intelligence to create newspaper articles, and the author of the #1 Amazon bestselling book “AI as Your Teammate: Electrify Growth Without Increasing Payroll.”
In this episode, Evan lays out a strategy for using AI at work to give you an edge, reveals the biggest mistake companies make when it comes to harnessing artificial intelligence, and shares his top pick when it comes to AI chatbots (hint: it’s not ChatGPT!).
Resources from the episode:
- Connect with Evan on LinkedIn.
- Learn more about Teammate AI and the work they do here.
- Learn more about Lede AI and the work they do here.
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Transcript
The following transcript is not certified. Although the transcription is largely accurate, in some cases it is incomplete or inaccurate due to inaudible passages or transcription errors. The information contained within this document is for general information purposes only.
Speakers: Evan Ryan and Mark Wright
EVAN RYAN 00:00
It’s not about trying to replace what makes you uniquely great. It’s about trying to replace all the stuff you have to do so you can get to the thing that makes you uniquely. And in the real estate example, I think the thing that I’m most proud of with one particular client, they had a team of two people working full-time and they were able to find and evaluate and qualify eight opportunities in a week across two people. But as soon as you applied the AI to it, we were able to do 150 in 17 seconds. Well, how does that transform the way that this firm is now operating? Oh my gosh.
MARK WRIGHT 00:36
This is the BEATS WORKING Show. We’re on a mission to redeem work—the word, the place, and the way. I’m your host, Mark Wright. Join us at winning the game of work. Welcome to BEATS WORKING. On the show this week, AI as your teammate. Artificial Intelligence is on everyone’s minds these days, especially at work. Some people love its ability to take over the mundane tasks we hate doing, but others are afraid AI might take their jobs. What’s clear is Artificial Intelligence is here to stay. And our guest this week is an expert at making it our friend. Evan Ryan is founder of Teammate AI, a software company helping businesses grow without adding payroll, which frees people up to do work that’s uniquely human. He’s also the co-founder of Lead AI, a company using artificial intelligence to create newspaper articles. In our conversation, Evan lays out a strategy that can really give you an edge using AI at work. He reveals the biggest mistake companies make when it comes to harnessing Artificial Intelligence. Oh, and you’ll find out his top pick when it comes to AI chatbots, and it’s not ChatGPT. Get ready because the future is here, and I hope you enjoy my conversation with Evan Ryan. Evan Ryan, welcome to the BEATS WORKING podcast. I’ve been really looking forward to spending time with you. Welcome.
EVAN RYAN 02:08
Yeah. Thank you for having me. This is going to be great.
MARK WRIGHT 02:10
So, Evan, you’re an expert on AI. You’re the founder of Teammate AI, which is on a mission to automate 10 million human hours by 2030, enabling people to focus on work that is uniquely human. You’re also the founder, co-founder of Lead AI. Which is a company that uses AI to automatically write, edit, and publish newspaper articles all without human intervention. So that’s, uh, news is a topic near and dear to my heart, but AI, Evan, is just simply pervasive right now. I always like to start at the beginning, Evan. So, you were studying neuroscience at Ohio State. You’d plan to become a doctor. You volunteered at a hospital and you said, this doesn’t look like these people are having much fun. Why don’t you, why don’t you pick it up from there? What, why Neuroscience?
EVAN RYAN 02:59
Neuroscience just because first of all, I thought the name was cool, but also, I thought it would be valuable to learn kind of how people work. I liked the nuts and bolts of neuroscience a lot more than sort of the theories of psychology. Like, I thought psychology was interesting, but, uh, but neuroscience seemed to be a lot more practical and kind of the harder of the two science, harder, meaning like more tangible to sciences, and yes, I did. I did stand at a nurse’s station right before I started undergrad. I started the nurse’s station. I was volunteering. I looked around, nobody was happy. And I said, wait a second, why am I going to sign myself up for a lifetime where I already know that nobody’s happy. And, but I stuck with neuroscience cause I thought, you know, hey, learning how people think and how people operate is probably going to be valuable down the line.
MARK WRIGHT 03:50
Yeah. And certainly, harnessing that is something that you do now with your businesses and Artificial Intelligence. So, you went to a conference in San Francisco in 2016, and you saw a guy who could diagnose breast cancer with AI better than people. And I think you told me that was really a turning point for you when it came to your understanding of the value of Artificial Intelligence.
EVAN RYAN 04:11
Yeah, because I was so close to the sciences. I looked at so many scans of so many different things going through the neuroscience degree. I was so close to the medical field still, even though I knew I didn’t want to be inside of it. And then to see this kind of fusion of the technology and the healthcare field come together. And wow, like if what I’ve been taught about the healthcare field, which is that you’ve got those best and the brightest people that are working on solving the hardest problems. If we can do some of that solving with AI, or, you know, in that case, what happened was this company was better at diagnosing breast cancer from CT scans and MRIs than a team of board-certified doctors, not just one. And so, if we could have this technology really augment the humans. Well, you know, what does that free up the best and the brightest to be able to do down the road? If you’re not doing the routine, well, then, you know, how is the ball being pushed forward? Or how are we pushing the limits of what we currently think is possible on the timelines that we think are possible? And so, yeah, I was hooked on, I was hooked on AI from there forward. The only problem was I didn’t know how to code. So, from there, I bought a used iPad. Because I was broken in college and I used a free game made for preschoolers to teach myself how to code and the rest was history. I was into AI.
MARK WRIGHT 05:26
What was that like in the very beginning? What did you guys focus on?
EVAN RYAN 05:29
We really were building kind of mobile applications. We were building, uh, we were building any software that we could quite honestly, to pay the bills. And so, we would take, we, I actually took our first couple of software clients before I knew how to code properly. Like I had done some experimenting with it, but I was by no means at the point where I should be taking a software client on, and so I’m really grateful to our early customers for that. But we were building any software that we could just to get the experience where, uh, now we focus a lot. Almost all of our energy is focused on taking the boring, repetitive tasks that humans do in a day and giving them to computers. Like you said, our goal is to automate 10 million human hours by 2030. And we measure our success based off of how many hours did we take from the human to get to the computer? But it’s always the boring, the repetitive stuff. We’re not trying to take the creative stuff, the stuff that people feel they’re uniquely good at, or they feel like they drive a unique amount of fulfillment from it’s the stuff that’s very boring, very repetitive, very rote. And we fell into that really on accident when I was starting the company, there were so many tasks that had to get done that I didn’t want to do because they were boring. And so, I, using my very, very limited technology, started automating those tasks that were super boring. And I thought, wait a second, if I like only doing fun stuff and I don’t like doing boring stuff and I can automate all this boring stuff, I’ve actually never met anybody who likes doing boring stuff. I bet they also would really like to have all this stuff automated for them so they can focus on just the fun stuff.
MARK WRIGHT 07:11
Evan, give me an example of what some of the boring stuff is.
EVAN RYAN 07:15
So, a lot of data entries, something that a lot of surprisingly senior level executives do, is they update KPI dashboards. So how it happens, I think, in a lot of companies is there’s a week goes by. And so, the executives talk to their direct reports and they say, what happened here? What happened here? What happened here? What happened here? They got all sorts of numbers and then they update the KPI dashboards. Then they walk into their executive team meeting with these new dashboards. But that takes two, three, four hours, not including, by the way, the time that it’s taking their direct reports and meetings. And we’re using AI all the time to automatically gather all this information and then automatically populate into the KPI dashboards. Maybe even generate a report that the executive team can have on a daily basis instead of on a weekly basis saying, hey, here’s the status of the business. Another one is a lot of people are doing research. They go to the same 10, 15, 20, 25 websites to check in and see what’s happening today. What happened here? What happened there? Is there anything new that I should be paying attention to? Uh, but that takes an hour and a half, two hours a day to check all these sites. And so we do a lot of automating around scraping those websites for our clients and then just sending them the information that they need instead of them going, clicking most of the time, there’s nothing that’s valuable. Hey, we found something we think this is valuable. Take a look and provide human review afterward. I know a lot of really kind of large manual processes and the real estate industry, for example, how do you find great deals in real estate? Well, it’s a manual process, but it’s very data driven. You know, there’s certain numbers for what makes a great real estate deal work. And there are certain numbers that don’t. And you take those numbers and you understand what’s going into the deal. What are the sales documents say? And we can take all of that and prepare it for an investment committee so that inside of the firm, the investment committee is just reviewing the deal. They’re not going out and looking for the deal. And most deals don’t work out, or they’re not going to be good fits. And we take it and we just say, hey, these are the top 10. These are the top 50 deals that you should be looking at. Don’t worry about the other thousand.
MARK WRIGHT 09:31
That those three examples are just mind blowing. When you start to think about the amount of time that we waste every day, searching and hunting for the stuff that we think is going to make our work more productive and our lives better. Gosh, you know, just the real estate example, you know, maybe you’re an investment you know, company, you’re interested in a certain zip code, maybe a certain square footage, a certain type of property.Oh my gosh. And if you’re a doctor, of course you want to know all the latest research on whatever your expertise is so that you’re not having to search for that every day.
EVAN RYAN 10:02
Yeah. It’s really, it’s not about trying to replace what makes you uniquely great. It’s about trying to replace all the stuff you have to do so you can get to the thing that makes you uniquely great.And in the real estate example, I think the thing that I’m most proud of is, and with one particular client. They had a team of two people working full time and they were able to find and evaluate and qualify eight opportunities in a week across two people. But as soon as you applied the AI to it, as soon as we applied the AI to it, we were able to do 150 in 17 seconds.Well, how does that transform the way that this firm is now operating? Oh, my gosh. We used to have not enough leads. Now we have an overabundance of leads and you have to reevaluate what it means to be a great.
MARK WRIGHT 10:48
Yeah. Evan, I’d like to talk about why AI is suddenly exploding now. Can you give us sort of a time frame?A history of a I over the past 8 years or so?
EVAN RYANS 11:01
So, AI has been a field that’s been developing over the last 50 years, but AI, as we think about it now, where, um, the machines are very intelligent, maybe you didn’t have to use conventional code, like a conventional if then statement to write it. It’s really a field that’s 10, 15 years old.What happened in 2019 was Google essentially invented what’s called a transformer. That transformer changed the way that these algorithms were able to understand and process data. It made it a lot faster and made it a lot, and more energy efficient and ultimately allowed it to scale much better. Before that, it would take an hour unbelievable amount of data, and it would take an unbelievable amount of compute resources in order to be able to do relatively small tasks. Because of this invention by Google, it led to inventions like ChatGPT. And these other large language models that are kind of taking over all the time. So, it was a 2019 innovation that really didn’t come to fruition or yield itself a massive return until 2022.But all of a sudden, here we are, and the underlying kind of structure of the way that these algorithms work has completely changed.
MARK WRIGHT 12:15
So, walk me through the process, Evan. When you meet with a client for the first time, let’s say they just have a run of the mill business. You can name what it might be. Uh, where do you start the process of deciding what we’re going to use AI to solve?
EVAN RYAN 12:28
So run of the mill businesses, I think are some of the best businesses to use AI. And a lot of times in Silicon Valley, in the media, every company, they talk about how every company should become a tech company instead of every company being a company that delivers an incredible product or service for their clients. They just use tech to do it. And so, I think the run of the mill businesses that already have great client relationships, they already have great products and services. They have excellent teams. They just want to continue to grow. I think that’s some of the those are some of the best places to be using AI, but the first most important point to start at, is what is your bigger future? And it sounds I think a little bit cliche, but the opposite of it is the most expensive mistake that we see a lot of businesses make. So, what happens when businesses do the opposite? Is, uh, the leader of the business, the executive, the CEO, whoever goes to a conference or listens to a podcast like this, or sees a video. And then they walk into work the next day and they go to their team, and they said, we need to figure out how to use AI. Come back to me in a month with what we’re going to do. In our view, that is a solution in search of a problem. And it ends up being a very expensive, painful mistake because whatever you hope the vision for the future is going to be ends up not being what you get. So when we work with clients, we say, first and foremost, what’s your bigger future as a company?
MARK WRIGHT 13:59
Like, where do you want to be? Right?
RYAN EVAN 14:01
Yeah. Yeah. Where do you want to be? And we’re going to work backwards to figure out what technology you need, how to build it, those kinds of things. To make sure that we’re building the technology that suits your future. The second thing, and this is, I think the biggest hangup for a lot of businesses that are not in tech is, well, how do I use it? I keep hearing about how AI is going to change every industry. I don’t want to get disrupted, but I don’t know how to use it. So, we first ask, what’s your bigger future? What do you want to do? What’s your vision? And then second of all, who are the most important people to help you achieve that vision? Like on your team, who are the most important people to help you achieve that vision? And those are the people that we’re going to free up with AI. We’re going to take all the stuff that they hate to do so that they can push the ball forward as fast as possible. They can drive that creative new strategic value as fast as possible because they’re not doing all the other stuff. And then we can work through what the AI needs to be.
MARK WRIGHT 15:05
Wow. That is such a brilliant vision because let’s say there’s a person on the team and she might be just killer at closing business, at making relationships, at going out and networking. And if she’s doing these data projects and filling out spreadsheets and stuff, that’s not the best use of her time, right?
EVAN RYAN 15:24
Absolutely not. That person should not be spending time updating the CRM. Now, of course she has to be updating the CRM because we have to know what’s going on. We have to be keeping a data trail, but what if the computer could do a lot of that stuff for her? So instead of spending three hours a day or two hours a day, updating the CRM. She’s spending 15 minutes a day updating the CRM. Well, you would get not just the two hours per day back, but you would also get two hours per day. We usually say times 1.33 plus 33 percent in all the time that she was spending dreading updating the CRM that now she doesn’t have to spend dreading it. So, she’s no longer got dread time and she’s no longer got task time. That’s now three hours a day that she’s gotten back to her two and a half hours a day that she’s gotten back to just focus on closing and making relationships.
MARK WRIGHT 16:13
Yeah. And without AI, the traditional way of growing is we need X amount of new business or X amount of new capacity. But what you’re doing is creating efficiencies, which immediately goes to the bottom line. That’s just brilliant. So, Evan, I think I’d love you to address fear because there are, I think, two kinds of businesses today. Those who are completely afraid of what’s happening with AI and those who are super excited. But I think a lot of the fear is like, like you said, how are we going to use that? And, you know, the marching orders go out, hey, everybody go figure out AI. What’s your best advice for that business owner who’s kind of afraid to dip their toe in the water here?
EVAN RYAN 16:53
Well, first of all, I think let’s define AI. So, if we’re gonna, if we’re gonna try to overcome the fear Let’s define what we’re talking about. We define AI as a computer doing a task that a human used to do. And we think it’s the most kind of broadest, most encompassing definition of AI, because it really encapsulates the mindset of computers are doing more, humans are doing different. Now, if we can kind of move forward under the assumption, that’s the definition that we’re going to use. Then the next kind of question that I would have for the particular entrepreneur is, do you remember the time where you kept all your files in a filing cabinet? Maybe that time is now. That’s okay. But do you remember when you kept all your files in a filing cabinet? And then like Google drive and one drive and Dropbox came out and we started digitizing all these files. We moved them up to the cloud. And so in order to find a file, you used to have to get up from your desk. You’d walk over to the filing cabinet, open it up, take the file, read it, put it back, close the filing cabinet, walk back to your desk. Now, you can just go to your search bar. You search a couple of words, and it pops up for you. That is a computer doing a task that a human used to do. So, as we talk about overcoming the fear, I think the most important thing is you’ve already done this before and you’re already using AI. This is just a slightly different type. This is just a different tool on the tool belt. And we can expand the ways that we use it to focus on saving. The killer salesperson, for example, two hours a day.
MARK WRIGHT 18:39
So, Evan, the tools that you guys use, can you break those down a little bit more for me? Do you write custom software for customers or do you have, like, a toolbox of already existing tools that you can just plug into their operations or how does that work?
EVAN RYAN 18:53
So, we want to find the best tool for the job. And sometimes the best tool is just the current systems that your technologies that you’re using. Sometimes we can really easily move you from the technology that you’re currently using to a much better piece of technology that will help grow, help you grow faster, help you grow easier with a little bit of training. A lot of times, we’re writing custom code and that’s because a lot of times our clients processes are unique. We really want to take your standard operating procedure, take your process, as it currently gets done, and mimic that with code. That’s how everybody sleeps really well at night, knowing that the process is getting done the right way every time. So, in the way that we work, we’ll watch your team go through the process, we’ll watch your team do their job, and then, we will build a process map, like a really intense process map so that somebody off the street could pick it up and they could start working in your company today. Then only after we’ve made sure that we’ve covered all the bases, then we start to write code to actually resolve that. And a lot of times I think people think, oh, well, custom code is going to be super expensive. A lot of times it’s just as cheap, if not cheaper than trying to customize a lot of the out of the box solutions. It just allows us a little bit more flexibility. Now, when we’re not doing process automations like that, when we get requests, for example, for what’s the best AI tool that you’re using right now, the best AI tool that I’m using right now, and that we recommend to absolutely everybody is a tool called perplexity.ai. Um, perplexity.ai is, it’s the best, it is your replacement to Google search. It looks a little bit like chat GPT and that has a search box, or it has like a chat box there and you can press go, but it goes out, it you’ve type in your question. It reads the internet and then it summarizes its answer for you, and it cites its sources. So that when we’re using, when we’re using code, it’s to automate a process. When we get a request, what’s the best tool you’re using now? It’s perplexity.
MARK WRIGHT 20:56
Wow. Evan, talk about some of the other tools, Microsoft, you know, Google, all the biggies are now sort of doing these concierge-like things, like, you know, that as you’re searching, as you’re navigating, you know, this is AI that can help you. What are some of the other tools that you see that are effective that maybe is just an easy add on for our daily lives?
EVAN RYAN 21:19
Well, I think that Microsoft and Google. No matter what email provider you use to run your business, they will add all the same features into their suites. So right now, Microsoft has Microsoft copilot. Um, it’s really great at a couple of things. It’s really bad at everything else. Um, but it’s really great at helping you find files fast. It’s really great at allowing you to chat with your meeting transcripts. Chat with your notes. What are the action items from this meeting that I just had? And Google’s adding similar features. I use Microsoft Copilot. We run on Microsoft, but I know Google’s is basically the same. I think that it’s good, not great, to be quite honest. I think perplexity is far and away the best tool that anybody could just pick up and start using. I estimate that I save about 10 hours per week, thanks to perplexity.ai. And, I wouldn’t say that I’m going to recommend anything else.
MARK WRIGHT 22:11
Okay. And is perplexity, is that a subscription basis or how does that work?
EVAN RYAN 22:16
You can do it for free, or you can pay $20 per month. The $20 per month is just going to get you a better output. So, I do that because I think it’s worth the money, but you can do it for free as well. And it is just unbelievable.
MARK WRIGHT 22:28
Yeah. So, Evan, give me an idea of some of the ways that you’ve helped. Your clients become more profitable as you’ve implemented AI. What are some of the success stories?
EVAN RYAN 22:39
Yeah. So, we, like I said before, we do a lot with website scraping and finding data and then sending it to our customers so that, uh, they just have the data that they need right when they need it. They don’t have to do any searching. They don’t have to do any finding. And, and there we’re usually saving between five and 10 hours per week for one person. So, they’re getting back upwards of 250 to 500 hours per year. That is, that’s like a lot of time back. We are doing a lot with moving data from one spot to another saying, hey, we’ve got all this data from your CRM and from your ERP and from your website. Let’s make sure that it’s all in one centralized spot. And then we can put it into your dashboards for you. That’s happening all the time as well. And we’re looking at saving, you know, 5 hours, 10 hours, 15 hours per week and human hours, that’s all getting poured back into the business on much better stuff. That is the really big thing. A lot of reports. So, a lot of times our clients say, hey, can you create a report for us based off of this, but I want it to be written in natural language. Like I want it to be nice to read and we can send it off every single morning before they’re in the office. Here’s the state of the business. Here’s what’s going on right now. Here are the things that you might be missing. And there we’re looking at maybe 45 minutes, an hour per day, but more importantly, maybe that report was only going out once a week or once every other week before And, now it’s going out every day or every other day now. And so, there’s this massive new visibility gain inside of the business.
MARK WRIGHT 24:13
So, you wrote a book called “AI As Your Teammate” for people listening. I’m guessing that would be a great resource for them to have to understand this whole thing. What’s the biggest takeaway from the book that you can say, Evan?
EVAN RYAN 24:25
I think it’s that you can really be the dominant kind of controller of technology. You can control how the technology develops instead of having the technology control you. And when you think about it like a teammate it makes it so that you can really clearly, I think, visualize where you use it and where you don’t use it. And it makes it so that for your team, who might be very afraid of AI taking their jobs, AI is a teammate for them too, instead of a competitor.
MARK WRIGHT 25:00
That’s great. So, let’s talk about Lead AI. You’re the co-founder of this company that uses AI to automatically write, edit, and publish newspaper articles. I moderated a discussion last week in Seattle on the future of journalism with a long-time journalist here named Joni Balter. She’s just an amazing, iconic journalist who’s worked at the highest levels, but some of the takeaways from that discussion with her will play directly into what you’re doing in this industry.
EVAN RYAN 25:27
Yeah, so we write high school sports articles. So, the problem inside of the American media landscape right now is that the advertising model on the internet has kind of broken the conventional media system. The cost to create an article for a human, a lot of times, especially in local media, far exceeds the revenue or exceeds the revenue that the newspaper is going to achieve. So, uh, this data is a little bit old, but if you, for example, wanted to cover the local high school basketball game, you would pay for a reporter to go to the school, watch the game, return home, write the article, and then publish it. In order to return that investment just on the reporter, that article would have to get 25,000 clicks. Well, I don’t know about you. Like, I don’t know, 25,000 people reading about the local basketball game, but it’s very important to the community that we continue to cover it. And so, where Lead AI comes into play is really all about this idea of, well, what if we could take the journalism that has to be covered, but it’s not profitable for the newsroom. It’s not necessarily the journalism that people going to journalism school back at university that they’re dreaming of doing. Like, I don’t know a lot of people who are like, I can’t wait to go to the basketball game on a Tuesday in February when it’s dumping snow, right? What if we could take all of that journalism? That’s very informational. We’re not trying to change minds and change hearts. We’re just trying to deliver information. And what could, what if we could give that to AI? So, communities can get what they need in the humans can focus more on changing hearts, changing minds on editorial on asking great questions and those kinds of things. So, we’ve now published well over 700,000 articles all across the world to cover high school and prep sports and a little bit of professional sports here and there, but I think it’s been really great so far to be able to help the media landscape. I think continue to develop as the AI starts to do more and more.
MARK WRIGHT 27:34
Yeah. I’m curious, Evan, how that process actually works. How do you get the information from the game, uh, into the form of an article?
EVAN RYAN 27:42
Yes. So, there is not a centralized data store for prep sports in the United States. And so, we use a service called ScoreStream. We’re partnered with a service called ScoreStream, which crowdsources sports scores. So, there will be 7,800 high school varsity football games on a Friday night. People in the stands have downloaded this app. And they update the box score. So, it’s very simple data, but they update the box score and what’s happening during the game. And out of 7,800, it’s unbelievable. Out of 7,800 games, they’ll get 7,700 games worth of data. So, it’s incredible how many people are updating the score on this app from the stands. And then we get those box scores and then we can write around those box scores. So, we’re not trying to replace the journalist who’s writing, you know, the super in-depth piece about the state championship winning team. We’re really trying to report the information on here’s what happened in the game. If you want to read a little bit more, you can read over here. If you want to see what else was going on inside of the region, you can read over here, but we take the box score. We understand what happened during the game. Using all using conventional code. We don’t use ChatGPT. We understand what happened during the game. And then we write the article based off of the way that the game seeming to seemingly went based off of the box score.
MARK WRIGHT 29:04
Does the algorithm also scrape social media? So if people are posting on Twitter, wow, Johnson made an incredible pass in the fourth quarter. Is that part of the algorithm at this point, or no?
EVAN RYAN 29:15
Not right now. The challenge that we face is how do you know that the data was reliable? And inside of the media landscape, the most important thing is to tell the truth, tell the facts as they were. And so we considered scraping social media. We considered trying to find comments or finding kind of quote unquote influencer accounts that we could follow that might be giving us a little bit more play by play. But the challenge was, you know, if we publish incorrect information that reflects really poorly on our client, who’s the newspaper. We’d rather publish less, but know that it’s accurate.
MARK WRIGHT 29:50
Yeah, that’s great. Well, let’s talk a little bit more about just the media landscape. And, and as you mentioned, so this is from my discussion on the panel last week, since 2005, the U.S. has lost a third of its newspapers, a third of its newspapers and two thirds of its journalism jobs, you know, and people just are not subscribing the way that they used to. And we’re losing an average of two newspapers every week in this country. Most experts agree that local newspaper jobs. And, you know, shuttered news organizations are not coming back. But what’s coming next is really interesting. We’re seeing a huge jump in the number of independent digital local news websites. So, tons of little mom and pop websites are sprouting up. Really democratizing information. But knowing who to trust is getting harder. So that’s, I think that’s an interesting model that you have that it’s like, you know, it’s the old cliche, just the facts, right?
EVAN RYAN 30:45
Just the facts. Yeah, we’re seeing that as well. There’s an organization called LION, Local Independent Online News that is growing rapidly right now from really well natured, well-intentioned people that are seeing, wait a second, like we don’t have anybody really covering our community. They’re not trying to stand up to the folks in Washington. They’re just trying to cover their community, and we’re seeing a ton of that. I think it’s really healthy for the media ecosystem, to be quite honest, to uh, have it be a little bit more decentralized to allow all sorts of different voices to flourish because it also then allows the different media organizations across the country to collaborate on what’s working well and ultimately grow further faster.
MARK WRIGHT 31:34
So, I cut my teeth as a legislative reporter way back in the day. Back in the old days, the News Bureaus, Associated Press and UPI, they had staffs of reporters in every capital in the country reporting what was happening. And those feeds were picked up by all the news organizations. So, everybody knows what’s happening in the State Capitol. Same with city councils had multiple reporters from every media outlet. I’m looking at your model and I’m thinking, you know, if it’s just the facts and if this is important stuff that our community needs to know about, you could potentially scrape these accounts from government agencies to at least describe what’s going on so that we know that this initiative on, you know, water rates or garbage or sewer or whatever got worked on this week. And this is something, you know, about it. Is that sort of the longer-range play with this?
EVAN RYAN 32:26
Yeah, our vision is, and we, I think that there’s a fundamental kind of divide in what the news is, and people confuse one for the other. So, I think there’s informational news, which is, these are the facts that you need to know about this thing. And then there’s editorial news, which is changing hearts and minds, having the difficult discussions, starting to ask the tough questions. AI is not something that’s here to take editorial news. AI is really great at restating the facts. And so, our ultimate vision, yes, is that the AIs are able to cover the informational news, the stuff we, these are facts, they’re being restated for you so that you can stay in the know on the things that are really important. So that the humans can focus on the editorial side and the humans can focus on changing hearts and minds. They can ask the tough questions. They can be starting the conversations that aren’t currently being had. And I think that’s the right balance. Like, like you said, that’s how it used to be with the Associated Press is the Associated Press would report the facts on whatever was happening, a particular thing, or even with, uh, the old high school prep sports. They had Team A beat Team B with a certain score. And so, the Associated Press was great at reporting the facts. Unfortunately, they’ve gotten smaller and smaller over time. They can’t cover quite as much. And I think that AI will pick up a lot of that slack so that the humans that went to journalism school that are trying to do their best to change communities the way that they see fit can go back to doing that instead of, I think, what happens a little bit right now, taking informational news and trying to make it editorial.
MARK WRIGHT 34:13
That sounds like a perfect augmentation of this sea of information that we’re drowning in right now. And I love how you’ve distinguished, Evan, between editorial news and factual news, because the editorial side of news asks the question, is this the right thing for our government to do? Is this the right direction that we should be going? Is this the right budget amount that our government should be spending? And there are all sorts of ways that you can come about that. And that really does take, I think, the expertise of a human being with a lot of experience to try to figure out that kind of news. But the value that I see is just, it’s just immeasurable if we all have our pulse on that stuff that we should know about because you’re absolutely right. There are no bodies where there used to be bodies to figure this stuff out and to bring that information to the public.
EVAN RYAN 35:03
Yeah. And they’re not coming back. It, it, one of the big things inside of it. Media sphere. One of the big things when specifically referring to high school sports is people wish that they could open the paper. They could go online and see what their local reporter was saying about their local team. And unfortunately, like those times are our past. So as we look towards the future and not towards saving local news, but just towards making local news much healthier, I think letting humans really operate where you are uniquely human is the best case for the outsets. It’s the best case for the journalists, and it’s the best case for the readership.
MARK WRIGHT 35:44
If AI is this good today, how much better is it going to be in a year, in five years, in ten years? What do you think is going to happen with AI in that time window?
EVAN RYAN 35:55
I try not to predict the future. Had I predicted what, had I tried to predict what would happen with large language models, for example, I would have been very wrong. In fact, one of my, one of my kind of favorite stories to tell about ChatGPT is that the technology that exists inside of ChatGPT was available over a year before ChatGPT was released. It’s just that it was only available to developers. And so there really wasn’t that much that was taking place. There were acute few services here and there, um, that were trying to leverage it, but it really wasn’t until it got packaged just the right way. That it, it started to take off. I would have never seen a chat bot coming though. So I really try not to predict the future, but I think that what excites me right now is the same thing that I think kind of make me feel a little bit tired. It’s the pace, the pace of AI right now is incredible. The, I feel like every week I have to upskill the company, like here’s what’s new and here’s what’s new in AI. But at the same time, one of the things that’s really interesting that I’m starting to really enjoy watching is that the more things change, the more they stay the same. So, while the pace of AI and this tech development is increasing and the stuff that is coming out today is so cool, it’s so much cooler than the stuff that was coming out six months ago, and I would imagine six months from now, it’ll be even cooler than it is right now. The fundamentals, the things that like really bring me peace are that like building great products, having great relationships and hiring great people, are still the three most important things, maybe not necessarily in that order. And the technology I think is just here to augment us. It’s just here to help free us up to do what we’re really great at, just faster.
MARK WRIGHT 37:52
It’s interesting in a very short history in human existence. We’ve, you know, when the Gutenberg Press was invented, this ability to put words on paper and give them to other people who could read the words. You know, maybe a thousand miles away or 5,000 miles away. It was such a shocking new development. And that wasn’t that long ago that the ability to spread language and thoughts on paper was just a groundbreaking achievement. As we look at human evolution, are you, do you think that this AI explosion, this AI period in our history is going to be seen as something as big as say the Gutenberg Press was?
EVAN RYAN 38:36
Yes. Yes. And I’ve actually been doing a lot of studying of the Gutenberg Press lately, so it’s interesting that you bring it up. A couple of things that I learned that I thought were just fascinating in that before the Gutenberg Press was invented, there were 8,000 books in circulation. In the 50 years after the Gutenberg Press was invented, there were over 500,000 books in circulation. Yeah. And people, I think that it’s hard to wrap your mind around it, but also the reformation took place. We were in the midst of the high renaissance, Europe was going through unprecedented economic expansion, and so there was just this whole, and by the way, the, the biggest scientific breakthrough that happened after the number one reason why people went to the doctor after the Gutenberg Press was to fix farsightedness because they needed to be able to read and everybody was farsighted because in the past, before you were reading all the time, danger was out there. Danger was right here, it’s too late. So, everybody had to fix. Yeah. So, everybody had to fix farsightedness. And I do think that AI will. I think that AI will be, uh, is I think it already is, but it will continue to be on that level of the printing press, the computer, the internet. And then I think the fourth thing will be AI. But I think that a lot of people want to say that this is, uh, a new era, a new kind of like evolution in technology. I would argue that it’s the continuation of the same evolution that’s already happening. But yes, I think it’s going to be that groundbreaking. And the stuff that we’re seeing already is kind of indicating that it is.
MARK WRIGHT 40:17
I’ve heard people in their 20s express concern that AI may be used in inappropriate ways to dishonor people who create original art and original things. Have you heard that from 20 somethings? It seems like there’s, there’s a fear there that what makes us uniquely human is going to be somehow lost at some point to artificial intelligence.
EVAN RYAN 40:43
Yeah, well, actually my girlfriend is a graphic designer. She has logos, websites, brands. She’s incredible. And her boyfriend, me, does AI. And there are so many of these image AIs and logo AIs and all these other things. And so, we, we talk about this all the time because there’s this dichotomy in our relationship, which is my boyfriend trying to automate my career. And…
MARK WRIGHT 41:08
I would love to sit at the breakfast table with you guys, man.
EVAN RYAN 41:11
Oh, it is quite, it is quite a discussion. Um, so I think there are two things to talk about. The first is IP creation. It’s like the creation of this, we’ll call, I’m going to call it IP, this intellectual property, and then there’s IP protection. So how do you make sure that it doesn’t get ripped off? I think that on the IP protection side, first of all, computers have been ripping off IP since basically as soon as they could, but I think that, uh, AI is not the tool to stop the ripping it off. I think that maybe that will be a use case for the blockchain is to be able to kind of stamp that this is the original. So, I mean, I don’t know, right? I, again, I try not to predict the future, but if I had to guess, I think that the blockchain will be excellent at intellectual property protection and protecting that originality.
MARK WRIGHT 42:03
Yeah. So, it would be like a piece of art that’s has some sort of encryption in it that that marks it as the original.
EVAN RYAN 42:11
That’s exactly right. So that you know that what you’re what you created, you get to sign your name on, just like 500 years ago, artists would sign their name on their paintings.
MARK WRIGHT 42:21
Right. Right. And that could even be used to renumerate people, right? To give them credit. And maybe you can use this song or this graphic art for whatever you want, but give me a, uh, an incremental, you know, piece of money for the right to do that.
EVAN RYAN 42:35
Absolutely. And there are some interesting things going on. I’m not a, I’m not a blockchain expert, but there’s some interesting things going on where let’s say I have a conference and the tickets for the conference are on the blockchain, but then the attendees can resell the tickets to somebody else. So, I didn’t go to the conference or a concert is an even better example. So, I buy a ticket to the concert. I can’t go, I can sell that ticket to somebody else, but the artist who’s doing the concert can take a percentage of that sale because it can all be traced. So that’s a very interesting thing that’s going on. I think that’ll really help artists and creatives on the IP or on the IP creation side, you know, how do I make sure that AI isn’t taking my job through this process? I think that there are a couple of things. The first is to me, it feels very, this feels very analogous to the kind of comm computer animation boom. So, before commuter computer animation, they needed to hand draw everything. All those hand artists became computer artists. And then we thought, and actually I was reading, uh, Steve Jobs, like his foundation put out a book of all of his writings, or just some of his writings, but something that was really interesting to me was when he started Pixar, they thought that when they made Toy Story, the first movie, they would have all the building blocks on the computer to be able to replicate and build animated movies really fast from here forward. But what ended up happening was they built all these great building blocks for Toy Story, then their ambitions grew. And so, they had to keep the same staff and they had to continue to hire. And the movies cost more, and they took longer because what they wanted to do was more ambitious than what they were currently capable of, even though they thought that it was all going to be taken by the computer in the first place. I think that will probably happen in the creative space in that what we currently think is possible. The limits of what we currently think is possible would be stretched. And there will be more designers than there were before. There’ll be more musicians than ever before. More videographers than ever before. It’s just that they’ll be using these tools to augment their workflow. I also think that on the flip side, I think that the tools in generating a great logo in the first place, I do think that those will get very good. They won’t be perfect, but I think that they’ll get very good. And so for the folks that are, and maybe the bottom 50 percent of the creative industry. I think that maybe the AI will come attack those jobs, but for the folks that are really uniquely good at doing creative work, I think that they’ll do so much more creative stuff now than, or in the future than they are currently. And I think that there’ll be a lot more people in this space.
MARK WRIGHT 45:23
It’s really interesting that you used animation as an example, because if you look back at some of those earlier animation movies, people had dead eye, and they never blinked, because that would have meant X number of more frames, X number, you know, of additional cost. And I think you’re right, as that expectation of a deeper, richer experience goes. Higher, it’s going to take a unique set of skills to take it to that next level and resources.
EVAN RYAN 45:47
Yeah. Yeah. And I don’t know what that is, but I think that had you gone back to the sixties and said that we’ll have like these computer animated movies that look like this, that look like, I mean, almost avatar level, right? Or in Conto, I, people would have been just absolutely floored. They wouldn’t have been able to kind of conceive that this was possible. So, I think that probably something similar to that will happen.
MARK WRIGHT 46:12
Evan, as we wrap things up. I’d love you to speak just to that employee, that person, that worker in the country who is maybe complaining on a regular basis, that damn AI is going to take my job. And I feel for them. Uh, and I understand where the fear is coming from, but I, I really think that you’re uniquely positioned to explain why they should maybe not be afraid because the whole premise of AI As Your Teammate, that whole thought is really comforting and I think it’s really inspiring. So, if you would, as we wrap things up, talk to that person, Evan, about the fear of losing your job to AI.
EVAN RYAN 46:49
I think that there’s a whole lot of work that people do so that they can do what’s in their job description. And AI is primarily going to do all the work that you have to do to be able to do the stuff that’s in your job description. Now, it doesn’t mean that your job won’t change and your job won’t transform, but I think that every job is going to transform probably several times over the course of the next decade or two. But it’s almost impossible for me as a business owner, for all the other business owners that I know to let go of somebody who’s adaptable and a quick learner. And so, as long as you’re really great at a couple of things, and you’re adaptable, and you’re a quick learner, we can apply those really great characteristics that you have on new problems that are bigger, that are harder, but ultimately for you going to be far more fascinating and motivating and fulfilling down the road. And so, whether it’s AI taking 80 percent of a particular job. So, 20 percent of the people are doing 100 percent of the work and you’re part of the 20 percent or whether it’s AI say, hey, we actually need to use this skill set elsewhere. Can you learn how to do this? Can you be adaptable enough to be able to solve this problem? I think those are going to be the people that best succeed. And there’s a quote, I don’t know who came up with it, and it might sound a little cliche, but the quote I, that your job won’t be taken by AI, but your job might be taken by a human using it. I would say I would probably consider starting to embrace the technology and being a hero to the other people on your team, because ultimately that’ll help everybody in the company move forward faster.
MARK WRIGHT 48:35
Well, that’s something that our producer Tamar Medford is embracing. She’s almost, on a daily basis, coming up with ways to use AI tools to streamline our process of putting information together and podcasts together and show notes and all that other stuff that goes along with it and interacting with people that we have on the podcast. So, we’re, we’re living that every day. And that’s somebody on our team that I’m grateful for because she just has embracing it full on. Evan, if people want to get ahold of you and engage with you, what’s the best way to do that?
EVAN RYAN 49:05
Yeah, so you can head to teammateai.com. Um, check out our website I also created a whole resource hub full of tutorial videos and strategy videos and some other tools that I think are really useful for diving into the world of AI. That’s at teammateai.com/start. Uh, the other way is AI As Your Teammate. The book is great. It’s a super quick read because I didn’t want to spend a lot of time editing it. And my email address is in there as well. So, you can just email me.
MARK WRIGHT 49:34
Well, Evan Ryan, this has been such a rich conversation. I appreciate your thoughtfulness about all of this. And it’s exciting where this is going to end up in the future, but there’s no doubt you’re right on the cutting edge, man. And I’d love to stay in touch and maybe have you back on the show in a year from now.
EVAN RYAN 49:50
Absolutely. I would love to. This was great, Mark. Thank you.
MARK WRIGHT 49:53
Evan, thanks. This is the BEATS WORKING Show. We’re on a mission to redeem work—the word, the place, and the way. I’m your host, Mark Wright. Join us at winning the game of work.