The Algorithm Knows Where You're Digging Before You Do

What if the next threat to buried infrastructure isn't an excavator's bucket….it's an algorithm that already knows where every line is buried? 

Mike sits down with AI strategist, futurist, and bestselling author Peter Swain, who has led more than 1,400 technology projects with companies like Apple, Microsoft, and Google, to confront a question the damage prevention industry can no longer avoid: could big tech effectively map North America's buried infrastructure without ever touching the industry's proprietary records? 

Swain's answer: yes... through correlated data alone, sets up a wide-ranging, unflinching conversation about AI models already measuring in the genius IQ range, predictions of an end to all disease within a decade, and why regulated industries will be dragged forward by rising expectations whether they're ready or not. 

Along the way, the two dig into the failure of regulation, our own culpability in giving data away for convenience, and evidence that human critical thinking is measurably declining just as we need it most. 

It ends with Mike answering a question few industry leaders would touch: what happens if AI makes his own job unnecessary?

 Listen for:

9:17 How long can a safety industry afford to move slow?

14:00 What does genius-level AI mean for human judgment on site?

20:04 If AI takes safety jobs, can UBI catch the fall?

25:29 Could big tech sell the buried world back to its owners?

31:01 What happens to dig site safety when critical thinking fades? 

Connect with Guests:Peter Swain, AI Technologist | 5x Best Selling Author | International Keynote speaker

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Transcript

Announcer (00:02):

You're listening to The Safety Moment Podcast by Utility Safety Partners. Safety is always a good conversation and it's a click away. Here's your house, Mike Sullivan.

Mike Sullivan (00:16):

Welcome to the Safety Moment Podcast. Nice to be back. My guest today is Mr. Peter Swain. He's an international keynote speaker on artificial intelligence and he is just one of the most fascinating individuals I've ever had the chance to speak with. He's the author of a number of books and coming soon is the AI Survival Handbook. You can go to Peter Swain's website, peterswain.com. And if you go there, you can also find him on LinkedIn, actually. And if you go to his website and you scroll down, you'll see the book. It's also the link there to get your AI audit. Check this out. It's really interesting stuff and I can't wait to get into it with Peter. So we're going to do that right now. Peter, thank you so much for joining me. We were chatting earlier and we had a great connection last week and our introductory chat, I suppose.

(01:11):

And some of the things you were telling me about artificial intelligence has still got my mind swimming. So I don't know how much of that we're going to get into, but as I mentioned last week when we were chatting, introductory call, what I do and what the industry I represent is more so the damage prevention industry and what lies below, trying to know what's below so it doesn't get damaged during any kind of uncontrolled excavation. And there's obviously an artificial intelligence influence is going to come into that and we are expecting that and we're all winding up our policies and crossing our sevens and dotting our Js, but there's so much more to it than that. And when we spoke with you last week, it really got me thinking of what we could be facing here. So to jump right into it, I mean artificial intelligence is going to impact my business, the business of preventing damage to buried infrastructure, buried utilities.

(02:11):

And one of the things we were talking about last week I wanted to get into right away was over the last decade, maybe more, seems like about a decade, could be longer, Google has been mapping the surface of the globe and everything we see, everything we touch has become a data point for Google to map and to put it out there for us to use. And the concern I think is the data of the buried infrastructure that exists throughout all over the planet, but more so where I am right here in North America, because that's where I live. A lot of that information is provided to us to manage the business that we do, but the level of the data that we receive is not to the level that the industry, the owners of the asset would have obviously. How close or how is it even possible for somebody like Google, enterprise, like Google, to somehow scrape the data that exists today through various data points to try and map that underground network and put it out there.

(03:24):

I mean, it's a concern. That's some of the information we need to keep not secret, but it's proprietary.

Peter Swain (03:31):

And the simple answer to your question is yes, but why bother? So let me ask you a question if I may. What is your favorite car?

Mike Sullivan (03:49):

My favorite car? A 1970 Buick GS or GSX or GS455.

Peter Swain (03:57):

1970 GSX or GSX 455?

Mike Sullivan (04:02):

GS455. Yeah.

Peter Swain (04:04):

GS455. Okay. So that's your car preference. Do you wear an aftershave? No. No. What is your favorite TV show from school, from being a child?

Mike Sullivan (04:21):

Oh boy. Mash. Probably not true, but yeah.

Peter Swain (04:30):

And what's your favorite sport?

Mike Sullivan (04:35):

Peaceball.

Peter Swain (04:37):

And what team do you sport?

Mike Sullivan (04:39):

They're no longer in existence.

Peter Swain (04:42):

Oh, what were they?

Mike Sullivan (04:43):

The Montreal Expos.

Peter Swain (04:47):

Okay. I'm going to ask AI to give me its best guess at age range, gender and location based on car preference aftershave, favorite TV show and sports team. What's your best guess of age, gender, and location of this person? And you agree, just for the sake of audience, I haven't asked you any of these questions

Mike Sullivan (05:23):

Before.

Peter Swain (05:23):

No,

Mike Sullivan (05:24):

We haven't. No.

Peter Swain (05:26):

Okay. Definitely male, age 56 to 62. Guessing on Quebec, leaning to Canada or Northeastern US, but most likely answer is 56 from Montreal.

Mike Sullivan (05:49):

That's where I was born. Not where I live anymore, but yes, it's where I was born. Yep.

Peter Swain (05:53):

Okay.

Mike Sullivan (05:53):

And I am not 56, I'm 60. Close.

Peter Swain (05:56):

Oh, 56 to 62. So we're in the right range.

Mike Sullivan (05:58):

Yeah. Oh yeah, in the rate range.

Peter Swain (06:00):

Yeah. So that was five random pieces of information. Facebook has over 60,000 on you and Google has 60,000 as well. You don't need to know the answer to what piece of cable is and what piece of ground if you've got the corresponding dataset. For example, the diggers that were sent to the location, which is on a satellite map, you know the equipment that was sent there, the electricity requirements that are being drawn from power stations and substations. I don't know the industry well enough, but my point is that you add up data points. So when you add up data points, you have enough data points to make a pretty accurate prediction that might not be right in the micro, but is right in the macro.

Mike Sullivan (06:46):

Right.

Peter Swain (06:47):

Why bother scraping the data? That's really hard to do.

Mike Sullivan (06:50):

Yeah. With available data, you can begin to make some pretty close assumptions, obviously, within a reasonable parameter. Yeah. I mean, I get that. So yeah, asking me the kind of car as a muscle car. Yeah, he's a guy, right? Now you asked me the team I support Montreal Expo as well. Yeah, it's going to be in that timeframe. But then you get into some ... Those are, like I said, five questions. You get into 50 questions, 500, 60,000. Yeah. I can begin to see where that's really narrowing that gap where ...

Peter Swain (07:24):

Yeah. A lot of the conspiracy theorists say that your Alexa device and your Siri device is listening to you, but there's no evidence that that is the case because we can track what data is being sent from the device to the network. You can see it and it isn't there. So when people say, "Oh, my Siri device is listening to me. " Well, actually the actual truth is scarier. It's that the algorithm knew that you were going to refer to that comedian on that day at that time to that friend.

Mike Sullivan (07:54):

Based on the 60,000 datasets?

Peter Swain (07:57):

Based on your 60,000 plus looking at the other eight billion people that they've got those 60,000 datasets on so they can see, oh, people that look like Mike, talk like Mike, walk like Mike talking about the new Bill Burr sketch. Therefore, other people that walk like Mike talk like Mike and look like Mike are going to probably talk about the Bill Burr sketch. And out of all the people that spoke about the Bill Burr sketch, 78% of them drink Cause Light. So we should show them this new promotion for this new cause product.

Mike Sullivan (08:33):

So we're getting into a very minority report type of scenario. If you remember the movie with Tom Cruise and we're getting into that scenario, you're walking down a digital hallway and you're being bombarded with advertisements based on you.

Peter Swain (08:50):

We've been there for quite a while.

Mike Sullivan (08:52):

It doesn't look like that Hollywood version just yet, I

Peter Swain (08:55):

Guess. Yeah, exactly. It doesn't have the gloss and the glam on it, but that is exactly what's already happening.

Mike Sullivan (09:00):

We're already there. It's fascinating. I feel like we're so behind from where I am, the industry I represent, the industry I work for, I feel like we're so far behind. We have a lot of catching up to do and I don't know if we can.

Peter Swain (09:17):

Regulated industries tend to go slower for obvious reasons and things where there is risk of loss of life and limb, obviously they move slower as well. I think you can because I think you'll have to because the expectation of delivery that we will all start to have is going to be ... Now let's take an example like a dentist practice. Let's say the dentist practice, they have an AI. This is prosaically easy now. It knows the patients, it knows what they do for a living, it knows whether they're employed, it knows whether they're parents, it knows the type of dentist that they want to work with male or female or not. It knows when they do a checkup. It knows whether they respond to email or text or WhatsApp messages as a primary mechanism. So it optimizes the calendar in order to keep the dentist 100% booked, but also by doing pre-work on the x-rays from last time so that it can look at what appointments might go over slightly so that you're never late.

(10:29):

The dentist is never late for an appointment. So as soon as you walk in, the dentist is ready to see you. They're operating at 100% efficiency and you have a fantastic experience as a result of this.

(10:41):

It doesn't take too long of that being the standard before that becomes the expectation. Who's going to go to a dentist that keeps you waiting in a waiting room? You'll be like, "Your dentist, oh no, my dentist just put this new system in place. It's amazing." As soon as I walk in, they don't even have a waiting room like you're like, "What do you mean they don't have a waiting room?" "Yeah, they don't have them. You just walk straight up into the chair and they just do the job. It's awfully phenomenal. "You're like, " Wow, I'm going to move to your dentist. "That becomes the expectation.

Mike Sullivan (11:10):

That becomes the expectation. And like you said, we could be there. We are there now, but we're not all acting like we're there now. Is that a human condition thing? We're not ready for it?

Peter Swain (11:25):

I think that we like to have the illusion of control and I think the companies that extort that control like to allow us to think we have control because I think it suits them for us to think that. I kind of think it's the same as being married. If anyone thinks that I've got the power in my relationship, they are definitely not married. Power is gifted to me by my wife every so often so I can take it out for a little test drive.

Mike Sullivan (11:50):

The illusion of power is gifted to

Peter Swain (11:52):

You. I have the illusion of power and she gives it to me in a very generous way. Hey, I have this. I'm taking that back. Thanks very much.

Mike Sullivan (11:58):

Yeah. Well, yeah, I've been married a long time. I know the feeling and I respect it. That's the way it is.

Peter Swain (12:05):

100%. So when they say men rule the world, I'm like, " Which world are you in?

Mike Sullivan (12:08):

"Exactly. Yeah. No, I agree. So you've authored, is it one book on artificial intelligence or ...

Peter Swain (12:20):

We've done a couple. I've done seven books now, but I say two focus specifically on AI.

Mike Sullivan (12:25):

Okay. I mean, this has been coming a long time where we're at today, but it's just going to start accelerating, I think. I mean, we're already accelerating down a path towards artificial intelligence. In my domain, it's a buzzword, but it's way more than that. To call it a buzzword, you're already behind. This is going to be world changing.

Peter Swain (12:50):

Yeah. Have you ever heard of Moore's law?

Mike Sullivan (12:52):

No.

Peter Swain (12:53):

So Moore's law was written by a guy called Moore from IBM in the 60s and his prediction was that the capacity of CPUs of computer chips would double in half the cycle. So it'd go from like two to four in 10 years, then four to eight in five years, then eight, 16. And unbelievably, he's been on track for 86 years. For 86 years, computers have doubled in capability in half the amount of time. And what's quite interesting is AI has followed the same curve, give or take, but from an IQ perspective. The IQ of AI has doubled in half the period of time. And at the end of last year, we saw the first set of commercially available, what's called frontier models, like from the big companies. We saw the first set of frontier models that measured higher than the average human. So the current IQ of AI is in the like 140s to 150s, which puts it in the genius category.

Mike Sullivan (13:55):

And you're saying that that could double?

Peter Swain (14:00):

There are estimates out there that say the measurable IQ of AI could reach somewhere around 30,000 by 2030.

Mike Sullivan (14:09):

So when we talk about AI being capable of curing cancer, the common cold, that sounds like reality to me.

Peter Swain (14:21):

Yeah. The head of Google DeepMind came out and I think it's the second part of this prediction that really blows me away. He came out and said, I think it was mid last year that he predicts an end to all disease within a decade. Wow. Fascinating. 2035. But here's the bit that's actually quite fascinating for me anyway. Nobody disagreed with him.

Mike Sullivan (14:46):

Wow.

Peter Swain (14:49):

The bit I'm always listening to because I live in quite a hyperbolic space. I'm listening for the Warren Buffet or the Elon Musk or the Mark Cuban or the Bill Gates, somebody that has seen the same thing these people see to go, "Nah, that's aggressive." All of them went, "Yeah, that sounds about right."

Mike Sullivan (15:07):

I remember seeing a billboard five, 10 years ago. I think I was in Florida actually driving down the interstate and there was a billboard and it said the first person to live to 150 years old is alive today.

Peter Swain (15:24):

And

Mike Sullivan (15:25):

I thought, oh, that's a bold statement, five, 10 years ago, but listening to what you're saying, yeah, maybe. And they may have

Peter Swain (15:35):

Been

Mike Sullivan (15:35):

Born that day, but ...

Peter Swain (15:38):

Well, we're reaching, what do they call it? The longevity escape velocity. The longevity is escape velocity is if you look throughout history, we've added, say I'm going to make up the numbers, but the point still stands. We've added one month to our life expectancy every 10 years, then one month every five years, then two months every four years. I think it was last year, it finally crossed the gap where we added more time to the average life expectancy than the time it took us to add it. So the average life expectancy this year versus a year ago is longer than the one year we spent finding that unlock.

Mike Sullivan (16:21):

And I believe that. I mean, I look at pictures of my own family, like my grandmother, she went on my mom's side. She passed away at 74 years old. And you look at pictures of her when she was 70 and she looked 85. And today, I mean, I look at pictures of people who are 75, 70 years old. They don't look like that. They look a lot younger. I mean, we're in better health. I do think that we have better medicines and you name it, that are taking care of us. People are surviving things that they would never have survived years ago. I had a sister who died of lymphosarcoma when she was nine years old. Today, she would have lived. I'm sure she would have lived just as a product of the time. When you're telling me that the intelligence of AI will far exceed anything, I mean, beyond the capability of any person well beyond, then okay, so all these people are going to live longer.

(17:25):

Well, where are they all going to go?

Peter Swain (17:27):

Well, that's where things start to become problematic and it's where you look at somebody like Edon Musk and go, "Maybe you're not just crazy." Because if everyone lives for all that extra time, where do you put them? What do they do? But also at the same time, if you've made the workplace that much more efficient, how do they earn?

Mike Sullivan (17:50):

What

Peter Swain (17:50):

Are they

Mike Sullivan (17:50):

Going to do? Yeah.

Peter Swain (17:51):

What are they going to do? So how are you going to feed and house all these wonderful extra people that you've got on the planet and how are you actually going to give them meaning and financial gain and all those wonderful things? And it's a very interesting time because if anyone tells you that they know what the future is, they are flat outlying. I've been nominally called what's called a futurist, like somebody that whose job it is to kind of make these big bold predictions as to what's going to happen. And I've been pretty good to spot on Acura in the world of technology since for about 30 years. I've been able to see like a five, 10 year horizon because beyond five or 10 years, things start getting accidental events just start changing things. Yeah, too many variables. Yeah. Like COVID massively accelerated the work at home phenomenon and that kind of thing.

(18:48):

I can't tell you what's going to happen this time next year. It's gone because the formulas, the math doesn't math anymore of how capitalism works, it doesn't work.

Mike Sullivan (19:05):

And so if you look at that and if we're all living potentially longer and where are we going to go? What are we going to eat? How are we going to sustain ourselves? You look at the narratives that are trickling in and is it by design? Is it by just chance? For example, universal basic income, that's something that we hear about here in Canada. It pops up from time to time. Although people may not want to agree or believe it, we are predominantly a pretty socialist country here. And the way I see Canada right now in terms of the unemployment and the spin on that, I begin to wonder, are we going to see universal basic income almost be not another experiment, but a requirement for people to actually survive?

Peter Swain (20:04):

Yeah. The problem is with UBI, universal based income is there's no proof that it works. There's four countries in the world that have done it. They've been asked for their cashflow statements. They're like, "Okay, show us that this actually results in productivity." And unfortunately, humans as a general rule, if you pay them not to work, decide not to work.

Mike Sullivan (20:26):

They won't. COVID showed

Peter Swain (20:27):

Us that. A great sentence from a comedian in the UK is great idea, wrong species. But what UBI does is it steps in and it kind of stems the bleed a bit whilst we have a bit more time to think about how we're going to ... It buys us a couple of years, but really not much more than that.

Mike Sullivan (20:46):

In some respects, I think we're getting close to that now and I don't want to get too political here, but I think the waters of UBI are being tested right now in places like Canada. And I think it was Margaret Thatcher had the famous quote, "The trouble with socialism is eventually running out of other people's money." And that's exactly what would happen, right? It's not sustainable. It's just not sustained. In the world that we know right now, maybe artificial intelligence will solve that. Well, we just go about it this way and I don't know if that's even possible. But going back to what I was talking about at the top of our chat here, all those data points and whether we're looking at the buried assets that provide us, sustain our way of life, whether that's natural gas, electrical, you name it, those assets are meant to be preserved, obviously safe from a safety perspective.

(21:50):

And if there is the potential or the desire for a Google to scrape that data, however you want to call it, and publish that, I see that they could and if they can, maybe they do. What I'm getting at is these tech giants at some point, they're going to do what they're going to do and we've seen that already, right? I mean, with just Google mapping the surface of the earth, yeah, sure it was great. We all get to use that data, but really what was that exercise for? Just because they could, maybe, but they're going to do what they're going to do because they can and who's going to stop them?

Peter Swain (22:35):

Well, I certainly think you have a valid perspective and you can certainly say who's going to regulate the people that get you elected because Facebook, if a politician can't advertise online nowadays successfully, then

Mike Sullivan (22:58):

No point

Peter Swain (22:58):

Running.

Mike Sullivan (23:00):

Yeah.

Peter Swain (23:00):

So I don't know. If I was a politician, it would be a very brave stance to take against big tech. So I think they are fairly beyond control to some degree We let it happen though.

Mike Sullivan (23:19):

Well, I mean, it happens almost in the dark of the night when we're not watching, right? We're not paying attention and suddenly it's in our face with nothing we can do about it.

Peter Swain (23:31):

Is either we weren't paying attention or is it that we didn't care enough to have any conscientiousness? So let me ask a question and I'm just going to be contentious to prove the point. I assume that you have read the terms and conditions of Google recently.

Mike Sullivan (23:50):

No, but I'm pretty sure I

Peter Swain (23:51):

Probably

Mike Sullivan (23:52):

Signed off on it. Yeah.

Peter Swain (23:53):

Yep. Facebook, did you read that? May have

Mike Sullivan (23:58):

Read a synopsis of that. Yeah.

Peter Swain (24:01):

This is what I mean. We gave these things away voluntarily because we didn't care enough to check because unfortunately for us, and I'm not saying they didn't exploit this, I think they did, but humans crave convenience above all else. So when we're given wonderful recording platforms like Riverside working, "Oh, we'll just do this, " then we're like, "Oh great, let's do that. " Did I read the terms and conditions of Riverside before coming on this video? No, I didn't. I'm saying we have to have some culpability in the equation. We can't just say, "Oh, you did this, you did this, you did this. " No, we collectively allowed this all to happen

Mike Sullivan (24:43):

Over time. And whether it was innocently at first, but it's evolved to the point where I think big tech, it's potentially beyond reproach now. I

Peter Swain (24:54):

Would agree

Mike Sullivan (24:56):

And they're going to do what they're going to do. And as to your point earlier, well, if they were going to map the buried world, why would they? Well, I don't know. Why would they map the surface? I don't know. It's convenient for us.

Peter Swain (25:10):

Because it's monetizable data that can be sold to somebody else.

Mike Sullivan (25:13):

There you go. So that's why they would probably do the same with the buried utility world, right? The network that supports everything. And who's going to pay for that or who would pay for that information? Probably a lot of people.

Peter Swain (25:29):

Well, we'll probably sell it back to the same people that it just took it from.

Mike Sullivan (25:33):

Well, that too. Yeah.

Peter Swain (25:35):

But because it'll be, we can see insights in this data that you can't see. So here's the thing that you can now access in order to ... It's like, hang a second, that's our data. It's like, yeah. And then big tech

Mike Sullivan (25:45):

Gets even bigger, right?

Peter Swain (25:47):

Yeah. And big techs and around the circle we go.

Mike Sullivan (25:50):

Yeah. Yeah. So when we talk about this, again, artificial intelligence, where are we? I mean, there's always something that comes next. And we're not even in my world anyway, we're just at the tip of the iceberg of artificial intelligence. But when artificial intelligence becomes like to talk about the movie, The Terminator or whatever, becomes self-aware, which it seems to have achieved, what does it create next? I mean, that's the scary part. If it's that much more intelligent than we are, thousands of times more intelligent than we can ever be, what does it create next? Where does it take itself? Because we're not in control anymore.

Peter Swain (26:35):

No, but I don't know. I don't know how to answer that question. Again, anybody that posits an answer to how does something that more ... What does something that much more intelligent than do will- We

Mike Sullivan (26:48):

Can

Peter Swain (26:48):

Never figure that out. It's like that question is asking my dog to predict by behavior three o'clock tomorrow.

Mike Sullivan (26:57):

And that's the scary part, I think, right is we know what it's capable of

Peter Swain (27:02):

Right now. And by the way, in that analogy, I'm only three times smarter than my dog and we're talking about AI being 300 times smarter

Mike Sullivan (27:10):

Than me. Yeah. Yeah. I mean, it depends what kind of dog you have. When I had a dog, I was probably, I'm saying 10 times smarter than my dog, but that just depends on the breed, right? But exactly. I mean, AI is going to be ... We wouldn't be able to hold a conversation with AI at that point. And that's the part that ... How do you pull that back? You can't. I don't think we can.

Peter Swain (27:38):

I think it's maybe beyond the point. I mean, again, I don't want to make this into a political conversation, but the very scanned amount of regulation that was in place was actually removed when President Trump came to power. So the time when we could have safely put some guardrails in place, it does seem like we've walked past that point. It's certainly what people are still calling for, but there's a lot of money to be made by a lot of people in what's going on. So it does look like it's going to carry on accelerating and accelerating quicker, not slowing down.

Mike Sullivan (28:15):

Where do you see AI taking us in the next 12 to 18 months?

Peter Swain (28:23):

I mean, who knows? Claude Methos was just released, which found zero day software exploits in 80% of common release systems that are out there, including banking systems. I think we'll see an increase in unemployment and at the same time seeing an increase in unemployment, I think we'll see an increase in productivity from companies. I don't think that equation has been fully stressed yet because the credit system provides a lag in that side of things. I think we're carrying seeing layoffs in knowledge worker led economies, which is the US, Canada, Europe is predominantly now knowledge work, not physical work output.

(29:13):

I mean, if you go further than 18 months, if you start going to 36 months, 48 months, then I think we start seeing viable AI robotics like Figure One and Optimist Prime from Tesla that then start actually ... You'll see somebody have a robot in their house as often as you see a cyber truck. So it'll still be a rarity. It won't be commonplace, but you'll certainly see it like, "Oh, there's a dog walking a robot." I think that you'll see that within four or five years. I think we'll see original math and science invention. So I think we'll see new science exist within 18 months to 24 months. We've seen it solve math problems that haven't been solvable by humans yet. That started happening in the last few months, problems that have existed for a hundred years. AI started solving in the last couple of months.

(30:14):

There was a new release today of a new model, so we'll see another set of that come out today. Very, very soon we will have new science that didn't exist courtesy. This

Mike Sullivan (30:27):

Might sound like a really dumb question, but if we had a math problem and we couldn't solve for a hundred years and AI solved it, how do we know they solved it? How do we know AI? Because

Peter Swain (30:38):

That's point of math, the proof works. In math to solve a math problem, you're creating a proof. But yeah, we will get to the point where we can't actually fact check anything AI does.

Mike Sullivan (30:48):

No. I think that's what I'm getting at. At some point we can't even do that. What are we then? What happens to us? Do we get dumber? Do we get

Peter Swain (31:01):

Smarter with AI? We've been getting dumber for 10 years. So roughly every five years they do an average IQ test of the planet. We got dumber for the first time ever five years ago. So the average IQ of the planet dropped about five years ago and it's basically all linked together of this is the first generation now coming through that only ever had Google. So they didn't need to remember anything. It's always right

Mike Sullivan (31:28):

There at their fingertips.

Peter Swain (31:30):

Yeah. For example, if you agree to meet your mates at the mall, your mates might not show up and you and I would have to figure that out. Yeah. Call them or go home or do something else or da, da, da. Now you just go, dude, where are you?

(31:47):

Even the idea of meeting somebody at the mall is a completely alien idea. I took my kids to Disney a couple of years ago and they were trying to swipe the TV, trying to explain to my children the concept of cable, because they've both got iPads and we only have Apple TVs in the house. So all of our TV is on demand. They have never been in a scenario where TV wasn't on demand. Wow. So they're like, "Well, how do we choose what works?" I'm like, "We've got these different channels and you can see these grids that shows you. " And they're like, "But I don't want to watch that. I want to watch that. " And they literally genuinely walked up to TV and just started swiping. It's seven o'clock, so these are the only things you can watch. And they both said, "Dad, this is rubbish." And I'm like, "Yeah, it kind of is.

Mike Sullivan (32:40):

" This is life, dude. Well, they are and that's the expectation they have, right?

Peter Swain (32:46):

But when I grew up, we had three channels of TV.

Mike Sullivan (32:50):

Yep. And we

Peter Swain (32:51):

Had to

Mike Sullivan (32:51):

Stand up and walk over the TV and physically turn the knob.

Peter Swain (32:55):

Yep. Didn't have a VHS player, didn't have a Betamax player. I had three channels. It was this time, that's what you're watching. I remember my dad explaining to me how you keep track of snooker balls on a black and white TV.

Mike Sullivan (33:12):

Yeah. I guess that would be a bit of a challenge.

Peter Swain (33:15):

It's all stuff. So yes, we've got dumber, but the problem there is an interesting question because I'm assuming, I don't know the question to ask for yourself because I'm assuming that most people that listen to do not know how to butcher a cow.

Mike Sullivan (33:38):

I hope not.

Peter Swain (33:38):

But they know how to eat beef, right?

Mike Sullivan (33:41):

Sure.

Peter Swain (33:42):

Most people here don't know how to strip back a spark plug or change or pull out an engine of a car. You don't need those skills. The question where this becomes, what I'm saying is as tools are invented and as new processes are invented, the knowledge that is required reduces because the tool or the process does the work instead of the human having to do the work. The problem with this set of in the AI spaces, this is critical thinking that's being negated. It's not just it's critical thinking, emotional awareness. It's very transferable thought processes that are being reduced and eradicated versus just tangible skills. But what comes of all these things? Honestly, the answer is who knows?

Mike Sullivan (34:33):

Well, I think you hit the nail on the head with critical thinking. That is in my view, not only limited to human race. I think that you see other species do critical thinking in their own way, but we maybe have taken it to the next level, obviously. We do analysis in our heads in a heartbeat, but we can't factor in everything. We can only factor in from our own experience, our own knowledge, our own training, our own education, our own culture. Whereas AI can take that from a global perspective and less time then we will come to that point of making a decision and make a decision. And that to me is, well, you talk about us getting dumber. If we're not exercising that gray matter to do things that we do every single day without even thinking about it, we are going to get dumber.

(35:30):

I mean, I think even for using Google Maps, I'm going to somewhere here in Calgary where I live, I'm going somewhere. I've been here 35 years. I should know how to get out, but just to be sure, I'm going to put it in Google Maps and it'll take me there. And it's become a convenience where I'm now just driving my vehicle on autopilot, it's telling me where to go. That to me is I'm not using that gray matter and if I don't use it, I will lose it. And we're seeing obviously cases of Alzheimer's, dementia, maybe it was always this high, maybe it's higher now, it's better diagnosed. I don't know. But it just seems to me if we're not using our brains, are we at risk of that and having more cases of Alzheimer's or dementia or early onset dementia? I don't know. I'm guessing, but I'm no PhD or doctor.

(36:35):

I can't make that assumption. Oh, I can make the assumption, but I can't make that diagnosis. But it occurs to me that if you're not using it, you have the risk of losing it.

Peter Swain (36:45):

Well, first of all, you could argue that something like dementia or Alzheimer's cases might go down if you don't do that because one of the highest suicide rates is Japan and one of the reasons they believe that that is, or the highest breakdown rates is Japan. And one of the reasons they believe that happens is because the complexity of the alphabet that they have to learn from such a young age, it's that their brain is actually overworked. I don't know if I would ascribe to that and I'm certainly not an expert enough. The question that's in some ways more interesting is, well, why are you driving?

Mike Sullivan (37:28):

Well, yeah, you could be sitting in an Uber or a self-driving vehicle and just taking you there.

Peter Swain (37:35):

Yeah. I think there's lots of what you're saying that is personally, I think it's almost arguing for doing not being. I've got a question for you. You've got a wife and children, I believe.

Mike Sullivan (37:52):

Yeah.

Peter Swain (37:53):

Do you want to go to work or do you want to play with your kids?

Mike Sullivan (37:58):

At the time, yeah, I would rather stay home and play with the kids.

Peter Swain (38:00):

Okay. So why are you arguing in favor of all this work then?

Mike Sullivan (38:04):

I had to put food in the table, had a life to live, I had a mortgage today. But what if you didn't? Oh, if I didn't, then that would be different. Yeah, for sure.

Peter Swain (38:11):

That's what

Mike Sullivan (38:11):

I'm saying. A circumstance is being what they were.

Peter Swain (38:14):

What if we get to the point where the additional efficiency in our lives can actually buy us that time back so that instead of doing all the stuff that we don't want to do, we can just do the stuff we do want to do. One of the things about job loss and AI that I always find quite curious is I've never heard someone say, "When I grow up, I want to work in a call center." All the jobs that AI is taking are not jobs that people wanted to do. When it gets to AI taking the jobs of princesses or trucks, then I'll be worried. But until then, I don't think that's what ... Is that really the purpose of life? Is the purpose of life really to spend your life working in order to get Alzheimer's and die? Was that really the point- No,

Mike Sullivan (39:00):

Hopefully

Peter Swain (39:00):

Not. ... of this miracle? So if we can make the work more efficient, that has to be a good thing to some degree. Well,

Mike Sullivan (39:10):

I don't disagree with you providing there is something that allows human race to continue. If we're looking at AI producing great depression like unemployment, nobody wants that either.

Peter Swain (39:30):

Well, see, this is where we come back to the self-actualized economy. What if you are removed from your job in underground safety stuff because the levels of efficiency, we don't need you anymore. Thanks very much.

Mike Sullivan (39:50):

You know

Peter Swain (39:50):

What?

Mike Sullivan (39:50):

I would be okay with that.

Peter Swain (39:52):

Okay. There are. See?

Mike Sullivan (39:53):

I would. But then again, to my point though, Peter, is I've always said that. My view of the job that I do is if I can make myself or make this job that I'm doing not necessary, that means I've been efficient. We've done things that have moved us to a certain point in time where I'm no longer necessary. That to me is a success story.

Peter Swain (40:18):

But that's me.

Mike Sullivan (40:20):

That's me.

Peter Swain (40:21):

Yeah, but the car models behind you, there's a multimillion dollar business in running a community for people that want to collect those cars. If AI can do the sales and the marketing and AI can do the legal and the financial, so all you have to do is actually just run the community. You could have a multimillion dollar business because the AI could take care of all that stuff that isn't your expertise. It could take care of the company formation. It could take care of the accounts. It could do the social posting to the right places to get the message into the right space. And this is what's called a self-actualized economy. What if every single person could monetize their skill and their passion? That then becomes kind of intoxicating as a potential version of the future.

(41:14):

And that's what it looks to be the only solution. UBI isn't the solution. Capital Works isn't the solution. So what could be the solution? What could be the solution is a return to cottage industry entrepreneurship where instead of becoming an entrepreneur to employ more people and do more things and add more stuff and get the bigger office and get the bigger office and get the VC and then do the exit, it just becomes, "No, you know what? I just want to run just this. I just want to have a $2 million business all on my own, just doing the thing I love doing on an 80% margin. I'll just earn $1.6 million. Thanks very much for doing 15 hours a week talking about Beanie Babies, because that's what I love doing."

Mike Sullivan (42:01):

And some people do that today, right? And now they've done all the heavy lifting, everything themselves and they're quite happy. They're

Peter Swain (42:08):

Quite

Mike Sullivan (42:09):

Happy. No,

Peter Swain (42:10):

I don't agree. I know lots of those people and what they'd rather do is just do the thing they're doing. They'd rather not be doing the social posting. They'd rather not be doing the customer support. They'd rather not be doing the refunds. They'd rather not be doing the Stripe reporting. There's 97 jobs they have to do. I think you said that as somebody that's employed as an entrepreneur, there is a hundred jobs you have to do in order to do the one job you want to do.

Mike Sullivan (42:35):

Right. Yeah. No,

Peter Swain (42:37):

I agree. I love speaking to people on stage, but here is Slack, here is my iMessages. There's my Telegram, there's my WhatsApp. We've been on air for 46 minutes, three, four, seven, 11. I have 19 outstanding messages from people telling me they need me in order to do their job and it's nine o'clock at night. So if AI could get rid of all of that from me so I could just stand on stage and talk to people and do the thing- Do what

Mike Sullivan (43:12):

You

Peter Swain (43:12):

Want

Mike Sullivan (43:12):

To do. Yeah.

Peter Swain (43:12):

That's what I want to do. I don't want to answer this question right here from my customer support team asking me if I want to issue this refund because they went over their cancellation period by a day and they're threatening to put a bad review of us online if I don't issue the refund. I don't want to do that. No. I have no desire to play that part. So let the AI make that decision for me.

Mike Sullivan (43:37):

Yeah. I get what you're saying. I think to my point was there are people out there doing all of the above today to support their passion, right? But you're absolutely right. If they could chip away at 60, 70, 80, 90% of that support mechanism that does support their passion, yeah, they would do it. Of course they would do it. Now, do we get to a point in time where that is the economy that is that we can all be Jeff Bezos in our own little world? Ah, potentially takes a long time to get there and you're not in

Peter Swain (44:14):

There. And that's the problem. It's the transition period that- Oh, the transition of anything. The real problem in

Mike Sullivan (44:19):

AI. Yeah. And that's where we are right now. Peter, this has been fascinating. Honestly, thanks so much. And I will go back to something I said earlier that I'm still not going to do, but if anybody out there is so inclined and you want to have an idea of just how many years you have left, apparently as what Peter tells me, it can do that too. Now, I'm not going there. I am not going there, but I guess based on your location, your age, your gender, your family history, we've been able to do that for a while, but it sounds like AI can do a better job of it today than it could yesterday and it's going to do a better job tomorrow than it does today.

Peter Swain (45:02):

Sadly true. Let's call it a more complete job, not a better job.

Mike Sullivan (45:04):

Thank you. Thanks so much, Peter.

Peter Swain (45:06):

Thank you.

Mike Sullivan (45:09):

That's going to wrap things up on the podcast. I want to thank our producers stories and strategies, and I hope you choose to follow this podcast on any directory you're listening on. And please do leave a rating. We appreciate it. You can follow us on X@utility_safety, on Instagram, LinkedIn, Facebook. We're everywhere. And if you'd like to send us a note, maybe you have an episode idea, you can email us at info@utilitysafety.ca. Just put podcast in dark letters in the subject header and that'll get to us. I'm Mike Sullivan. I'm the President of Utility Safety Partners. Click to know what's above and below. One click costs you nothing. Not clicking, that could cost you everything.