GREY MATTERS w/Brian Peret: How AI Is Impacting Multiple Industries

Brian Peret: Welcome friends, family, strangers, and enemies—if even you exist out there! Welcome to the show today!

This is Grey Matters, and my name is Brian Peret.

Gratefully coming to you from the studios of Radio St. Pete, St. Petersburg, Florida, in the lovely Tampa Bay area. In a world where so many things seem black and white, the truth really lies in the grey matters.

I thank you today for joining the second episode of this journey as we endeavor to find the truth in all kinds of topics that are important to you, that are important to me, and are important to us. Throughout our journey, we will examine music, we will examine culture, we will examine community activism, and today we will examine technology.

In my day job, I have the pleasure—the honor—to serve as the director of CodeBoxx Academy. CodeBoxx Academy is a workforce training provider located here in St. Pete and serving the entire Tampa area and the surrounding areas to help people get jobs in tech and start their careers off on the right note.

You all know what the biggest, most prevalent topic in tech is these days? We see it on our phones, we see it on our websites—artificial intelligence. It’s a buzzword. And my friends and my family, today artificial intelligence is going to be the topic that we explore.

Now, most things—there’s the black and the white. So, what’s the black and white when it comes to AI? Well, the black side is, obviously, AI is coming for your jobs. And that’s true. There is a jobs report in 2023 that was published by the World Economic Forum, and this report tells us that by 2025, artificial intelligence will displace 85 million jobs. That’s 85 million people. That’s 85 million day-to-day jobs that are going to go away because of AI.

Let’s take a moment and examine what these jobs are so we get a better idea of the world we’re going to be entering. The jobs that will be replaced—these jobs are going to be the repetitive and predictive tasks. Think data entry, where you’re typing in the same thing over and over again. Or even think something like a truck driver—a task that can be done, is monotonous, and can be managed by an autonomous model or whatever. And also, factory work. This is something that we’re already seeing, where robots are handling a lot of the manufacturing—not only in America but throughout the entire world.

In addition, jobs that require data analysis and pattern recognition—these types of jobs are also going to be replaced by AI. Think about market research. Where once we had a bunch of really smart people with spreadsheets crunching the numbers to determine trends, we can achieve the exact same result using AI. In pattern recognition, we can think about insurance adjusters— all kinds of different industries where the ability to determine patterns, up until now, has been a highly labor-intensive task—AI will take that job. As well as jobs with high degrees of standardization. We’re seeing this already in security, where AI is monitoring crowds to identify potential individuals. We’re seeing it in the chatbots that we go and use on websites that ask us if we need help. And though they are still frustrating and not nearly adequate enough, in my opinion, they’re getting better and they’re leveraging these large language models to help people manage their customer service requirements.

Read Our Blog: What to Look for in an Artificial Intelligence (AI) Program

Yes, AI is coming for jobs. It’s coming for 85 million jobs. But on the other side of this coin, AI is also coming to the rescue. There are so many problems and issues and processes that AI is going to support. That same report that said AI is going to cost 85 million jobs over the next five years also says that AI is going to create 97 million new jobs. That’s a net gain of 12 million new jobs over the five years of this study.

Let’s talk about the kind of jobs that are going to be created. These are jobs for the humans that are going to be needed to build, train, and maintain these models that we talk about—the ChatGPTs and all of these other things that are being used on all our platforms. People still need to build these, and train them, and assess them.

In addition, the implementation of artificial intelligence is creating an entirely new economy. Think back to when the Internet was really becoming prevalent—all the economies that were generated because we had the Internet: things like social media, distributed workforces, streaming television. These are all industries that were created because of the Internet. We may not have even had a chance to imagine them before we had a tool like the Internet. AI will likely do something very similar to that. And as this economy is being created, there’s going to be an entire service economy that is created to support these AIs.

Just like every other tool, the application itself will drive industry. Think self-driving cars and things of the like. With AI, we are entering a realm where you’ll be able to be picked up, dropped off, get your goods delivered—all without the process of having a person involved in that.

These AI tools increase productivity. And in any business, if you’re able to increase your productivity, that means you’re able to make more money for the amount of time that you’re putting in. And if you make more money, you can hire more people. So just the fact that we’re implementing these AI tools allows us to increase our productivity and create jobs again. There’s going to be a 12-million net addition of jobs because of AI.

Let’s step back, now that we know the sky is not falling, AI is not going to destroy us. AI is also not going to be our savior and solve all of our ills. With that in mind, let’s take a step back and look at the big picture. What is AI? It’s a term often thrown around, rarely used accurately, and often we don’t step back and think: what do I mean when I say these words?

AI—artificial intelligence. Definition: the ability of machines to perform tasks that typically require human intelligence. One more time—the definition of artificial intelligence is the ability of machines to perform tasks that typically require human intelligence.

Let’s take a look at some of the main silos or categories of these tasks. You have language processing. You speak to me, or I see an image—taking that audio or that visual and translating it into a message—that’s something our intelligence does. Image recognition—being able to see something or feel something and recognize it, from an amorphous object to, hey, this is a mint, or this is a microphone. And complex reasoning and problem solving—taking disparate ideas and assimilating them into one.

But one thing that artificial intelligence currently lacks is emotion, consciousness, and the true ability to learn and adapt, right? These qualities are essentially human. Artificial intelligence still lacks these. I want you to hold onto that because when we’re talking about the kind of skills and the kind of jobs and what AI is going to mean in the future, it’s going to be that human part that’s going to be very important for us going forward.

Depending on who you speak with and depending on which test you use to verify, artificial intelligence may or may not already have been achieved. Almost certainly, the tools that you are using do not qualify technically as artificial intelligence. They go under something else we call machine learning, right? These are things—these are large models that are trained to recognize patterns in data and make inferences.

So we’re not dealing with artificial intelligence per se, it’s more machine learning. And I want to spend a minute here to break down what I mean when I say machine learning, for it goes deep into us understanding how these tools are used. There are five main steps in machine learning: data collection, feature extraction, model training, testing, and iteration. Let’s go over each of those five. First one—data collection. Gathering all the data and feeding it into this model. That’s the first step: recognizing what our data set is going to be and the machine that we’re going to put it into. Second step—feature extraction. From this data, how do we pull out what it means? From looking at a trend of temperature data over time, how do we see that a heating streak is coming up? When looking at the waters in the Caribbean, how do we know that that turns into good conditions for a hurricane? Those are features that need to be extracted from the data. You use those features to train the model so that the model knows what to look for when they’re looking at the data. So you train this model to observe the data of the water in the Caribbean, and you use that to tease out the features. Once you’ve trained the model, you then have to test it to make sure that the model is good—that’s the fourth step.

And finally, iterate all over to make sure that you’re improving the model. Data collection, feature extraction, model training, testing, and iteration—those are the keys to machine learning. And no matter which tool you’re using out there, you’re likely using a tool that leverages machine learning.

With that being said, let’s talk about how AI is being used in the workplace. We talked about how it’s automating repetitive tasks: data entry, scheduling, and email responses. These are all tasks that can now be managed through AI. This frees up time for more strategic work and ensures higher accuracy and reliability of the tasks and processes that you’re doing.

An AI computer model works with much higher fidelity than humans—who get tired, who have to eat, and who are inherently fallible. So, automation of repetitive tasks and data-driven decision-making is another benefit. It can be difficult for a human being to make decisions on large sets of data. We are finite in our ability to comprehend and assimilate different data sets.

But with these AI tools, we’re able to analyze large data sets, generate insights, and forecast trends. And one thing that’s good is that whenever you’re using data-driven processes, whatever business you’re in, you’re going to find that that gives you more credibility because it’s a language that you can share with somebody else—the data, the ability to recreate the actual life that we’re living here.

How else is AI being used in the workplace? It’s enhancing creativity. This is the first thing that I really saw was cool with AI. Just go onto your favorite ChatGPT or whatever and have it make you a poem, have it write you an essay, tell it what your biggest problem is, and have it propose solutions. These are ways of thinking and generating creativity. It’s a great use for these tools. I use it to combat inertia, right? Like that blank page—that is the biggest villain in my work. Whether I have to create a course, a website, or a plan, I ask my AI to do it. Generate that first plan for me, and I go from there. It allows me to deliver polished results faster. Improved communication. Almost everything that I send out or publish, I run through one of these tools first to curate what we’re looking at. And curation is a key word here. I want to pause a minute and talk about curation. It’s one of those key skills that we’re going to need. Whenever you get the output from one of these tools, we need somebody there who understands the output, who understands how it can apply to a business, and curates that result. We’re going to get back to that. I do want to come back to how AI can improve communication. It helps you create clear, concise, and impactful messages. These tools have the ability to go out and scour every written word and help you tailor your message to get the intended outcome.

In addition to communication, and as a tech educator, I have really seen how AI affects continuous learning. These AI tools allow us to learn at a rate and almost on another level all alone. I remember when the Internet first came in, and you had Google or even Ask Jeeves before that. We had all these questions, and you could go to these prompts and type it in, and you got a wealth of information.

As a side note, I remember when the Internet got big, it knocked me down a peg, right? Because I was the guy that my family would call. I was the guy that my friends would call when they didn’t know something. I’d be sitting at home like, “Brian, who was the president before Jimmy Carter? I don’t know!” Now that we have Google, you can just Google it. And so I’m not quite as smart anymore.

And with AI, it even takes it a step further because these AIs can work as your tutor, they can work as your teacher, they can work as your student, they can play the role of anybody in your educational institution. You can use AIs to create a personalized learning path for you that looks at the way that you learn, tailors the objectives you want, and creates a lesson plan to help you get there independently. And let’s say you don’t even know what you want to learn—you can use AI to even tell you what the subjects are that you want to learn based on your outcome. Let’s say I want to be a long-distance runner in the next two years. And those of you who know me know that’s a gigantic ask. It’s probably not going to happen. But if I did, I could ask my AI model, “What are the things that I would need to do in order to make running a marathon in two years a realistic possibility for me?”

That’s continuous learning. Along the lines of that is personal productivity and time management. I just set up some AI for my calendar this morning to allow me to manage it. And I tell you—the amount of time that this saves me, not having to go back and forth—“Are you free now? Are they free now?”—to be able to have an AI that manages all that for me, that is amazing.

As well as my to-do lists, my reminders—all these things where I would have needed to pay an administrative assistant or use my own valuable time—now I can get that managed using AI.

And finally, the last thing I want to talk about—and it’s last for a reason. In my research, it’s something that didn’t come to me naturally. I was kind of surprised when I saw it. And the more I look into it, I really think there are high impacts here. And this is how we can use AI as leaders. Oftentimes, we think about using AI as worker bees to get our jobs done better. But AI really has a place for us in leadership. Think about it. I can use AI to forecast industry trends. This helps me know which way my industry is going. That’s the type of data I need to develop our strategy going forward. We can use AI to understand which way the market is moving—gathering large sets of data and analyzing them in real time, looking at the same data based on choices made in the past to give us a recommendation of a possible path for the future.

Another interesting place where we can use this in leadership is to objectively analyze employee performance. This is something that’s so difficult for me. I love everybody on my team. Some people I love more than others. I do not want that to affect the way I evaluate my team. The bottom line is most important.

By taking the work that I get from my team, as well as the notes that I write, and plugging those into the tools, I can get an objective assessment based on my own data.

So, now that’s how AI is being used in the workplace. I want to take one minute or so just to touch on the tools that we’re talking about here because there are so, so many tools.

The ones that everybody is likely familiar with: ChatGPT, right? These are the things where you go to a prompt, type in a question, and it gives you a response. These are getting more and more flexible and powerful—from just answering responses to questions. Now they can generate images; some of them can even generate code snippets. Some can even perform actions on your documents.

So, let’s go through them. ChatGPT—that was the first main one that got super popular. Shortly following that, we had some other ones come onto the scene. Google—you know the big name—has Gemini. One good thing about Gemini is that it really integrates with the rest of your Google Docs so that you can use their AIs in your email, your documents, your spreadsheets, and your calendar. It integrates through all of that.

Microsoft has a similar tool—Copilot—that they use for their AIs. Copilot is really strong in coding. For those of you out there who are looking for a tool to help support your development, my recommendation for you is to go to Copilot first.

Let’s say data integrity and ethics are your biggest concerns when dealing with AI. The tool I recommend for you there is Claude. Claude is developed specifically with ethics in mind, making sure it’s the most ethical, the safest one that you get. They also do some really quality work in the responses that they give.

So, we’ve got ChatGPT, we’ve got Gemini, we’ve got Copilot, we’ve got Claude, and the last one to come to the party—Meta is a big one, right? Their Llama or Meta AI. I love this one for two reasons. First reason—it’s open source, which, as a developer, I think the promise for that is amazing. When you allow your code to be used by the developer community, that allows for the environment to create all kinds of uses and adoptions for it. In addition, Meta’s AI is developed specifically with social media and other types of processes involved. I really recommend everybody use Meta AI and look at how it generates images live. I remember I was trying to create a man with a beard, right? And as I was typing it, it was literally creating the man as I typed. When I typed “b, e” in beard, it showed the man with a bee. When I got to “b, e, a, r,” it showed the man with a bear. And when I typed the “d,” it became beard. And I type at about 60 words a minute. So, in real time, I’m seeing it go from bee to bear to beard. Watching it do that, you can really kind of see how it’s working in the background. It’s just the coolest thing ever.

For those who are interested in digital marketing, it’s also a very strong tool. You can create logos and images to support social media posts because we all know that text will get you some engagement, but an image will get you more engagement than that. And even motion will get you even more engagement. AI can help you with each one of those to strengthen your engagement.

So, those are the standalone tools. Now, what we’re seeing also is that many of the tools that already exist are adding AI features to support their stuff. Think Shopify. It’s using AI to help you target marketers. Wix, a popular website maker, has AI and other ones too to help you create a website based on a few sentences. Etsy is using this to help as well.

Yes, so many platforms, every major platform is incorporating AI into their processes.

In addition, there are multitudes of specialized tools for content creation, grammar checking, video creation, image generation, voice and music generation, task and project management, transcription, scheduling, email box management, and slide decks and presentations. I’ve got a list here that’s literally dozens of specialized tools, and there are dozens being added each and every day.

There’s a lot going on out there. This is really exciting, and the impacts are happening in real time. In the Tampa Bay area, this is super exciting because the impacts in industry really fall in line with some of the strongest industries we have in the Tampa Bay region. I’m specifically talking about medical technology and financial technology.

Think about how AI is being used in the medical realm: the ability to diagnose. Look at X-rays, blood work, and all these different images, and take all the disparate data and come back with results. I’m sure many of you have heard the stories about how we’re predicting cancer at such an early spot that we’re catching 99% of it—right where we’re looking at blood work and different genetic markers and coming back with such early indicators that we’re really able to treat and move the needle on this.

In addition—and this is one thing that’s really cool—AI is now able to help give a really personalized treatment plan. Gone are the days—well, soon gone will be the days—where you have a diagnosis and there’s a one-cure-fits-all solution. Now your cures are going to be very specific to you, to your metabolism, to your blood type, to your activity level, to your age, to your socioeconomic status. AI can incorporate all of those factors to make sure that you’re getting the best medical results out there possible.

And even more on the hardware side—surgery. AI is being used in surgery, right? We can have these robots that can perform very complex and intricate surgeries. But every single person’s body is different. We need an artificial intelligence that can adapt to these very custom circumstances. And AI is able to do it without the shakes of a human being—without a human being who gets tired, who needs to rest, who needs to eat.

Personally, I would feel much safer with my life in the hands of a robot during microsurgery. It can stand still for however long it needs to, whereas a human being might sweat, slip, or nick something I need. That’s the medical side, which is big here in the Tampa and St. Pete area—and big everywhere.

Also, the financial technology sector. We’ve got some big hitters here in financial technology, and AI is really supporting their processes as well. We spoke about taking all this market data and, from that, getting trends. But also predictive analysis and trading based on algorithms. These are all areas where AI is really impacting financial technology to do some extraordinary things.

In addition to the medical and financial fields, we’ve got manufacturing. We spoke about retail and e-commerce. These are all areas where AI is really moving things along. And it’s also creating a whole new job market.

One of the things I’ll leave you with here, to really excite you and perhaps urge you or motivate you to consider getting into AI as work or pursuing it as a hobby—just as a promise, a light at the end of the tunnel, that gold at the end of the rainbow.

About a year ago, there was a big story—a big hubbub in tech circles—about this AI job post. Netflix was looking to really improve how AI is being used in its platform, and it was looking to hire an AI product manager to come on.

Now, the reason why this became such a big story is the salary that Netflix was advertising to pay for this role. I want you to take a second and just think in your mind how much this would cost. All right. In the room, I’m seeing somebody guess $500,000. In my mind, I was guessing around $250,000. Ladies and gentlemen, friends, families, strangers, and enemies (if there are any)—Netflix was advertising this job for $900,000 per year. That is a reflection of how important these AI technologies are, how powerful they are, and how much they can be used to affect the bottom line.

AI is not here for your job. AI is not going to save you. It’s a tool, like anything else. You have the ability to use AI and become great. I encourage you to do so.

And I look forward to talking to you again soon.

This has been Brian Peret with Grey Matters. I love each and every one of you!

Goodbye!