The SiteVisit

The Buildings Show 2024 | Recording Session 3 | Construction Automation: Opportunities and Risks with Mahir Dheendsa

• James Faulkner

Share episode

Send us a text

Discover how artificial intelligence is revolutionizing the construction industry in our latest episode featuring Mahir Dheendsa. Mahir shares his valuable insights into the democratization of AI, highlighting how innovations are making artificial intelligence accessible to all, not just tech experts. We challenge common misconceptions about AI's novelty and explore the anxieties it brings to sectors like construction, where traditional roles stand at the brink of transformation.

Our conversation ventures into the heart of digital transformation in the workplace, tackling the crucial need for cross-generational support and education in new technologies. Mahir provides a thoughtful analysis of how companies are rethinking job roles and scopes due to technological advancements, and we reflect on the variations in digital adoption between younger professionals and seasoned employees. This discussion sheds light on the broader implications of technology across all educational fields and the cultural pushback that persists in some organizations.

The future of automation is here, and we paint a vivid picture of its potential impact on construction and beyond. From autonomous equipment to humanoid robots, we envision a future where AI platforms and digital literacy redefine operational norms. We also delve into the innovative tools reshaping industry practices and the exciting possibility of virtual roles in workplace safety. Tune in to hear how these advancements could transform traditional industries and embrace a digitally-driven future, all while celebrating Mahir’s impactful podcast debut and thanking our listeners for their ongoing support and engagement.

PODCAST INFO:
the Site Visit Website: https://www.sitemaxsystems.com/podcast
the Site Visit on Buzzsprout: https://thesitevisit.buzzsprout.com/269424
the Site Visit on Apple Podcasts: https://podcasts.apple.com/ca/podcast/the-site-visit/id1456494446
the Site Visit on Spotify: https://open.spotify.com/show/5cp4qJE5ExZmO3EwldN1HH

FOLLOW ALONG:
LinkedIn: https://www.linkedin.com/company/thesitevisit
Instagram: https://www.instagram.com/thesitevisit

Speaker 1:

Hello everybody, how you guys doing Nice. Can everyone hear us? Okay, all right, so my name is James Faulkner. I am the host of the SiteVisit podcast. If you get a chance to listen to it, we've got 150-something episodes now that we've done all topics in construction, a lot of technology stuff. I'm a founder of a technology company called SiteMax and did that 10 years ago and so, yeah, love, love technology, like driving it and um, yeah, so here we're at the the building show they've invited us. We've done, uh, two other episodes before this and uh, now we're here with mehir deenza. How are you doing? I'm good, james, how are you? Ah, this is so so many podcasts before this. No, this is my first one. Well, so far you sound great. Yeah, so you're good, you're good. So just a little intro here.

Speaker 1:

Mahir is the program and the specialist for data integration and transforming technology at Lafarge so Concrete Company. We talked before the podcast a couple weeks ago about some of the great things you guys are doing there, and he has a bee in his bonnet when it comes to the digital transformation, how slow it is. We've got one generation that's like, hey, why do we need all this stuff? And you have the younger, younger generation going. Why aren't we using all this stuff? So we got to get to this uh, this middle here where we have uh some buy-in from all the different generations and we've got a lot of cool tech uh coming along the way in terms of software ai we're going to talk about as well, and um yeah, so give a round of applause for me here. Welcome to the site. Visit leadership and perspective from construction with your host, james Faulkner, recorded live on stage from the Buildings Show in Toronto.

Speaker 2:

Thanks for having me. It's a privilege to be here.

Speaker 1:

Yeah, you're welcome, you're welcome, Okay. So I got questions and this is what we're going to get into Yep, a number of things. So it's big. On the AI front, let's just chat about this for a second. So you know, I was very quickly there was a revelation very fast that you really know the difference between a lot of the terms people hear, like generative AI, machine learning, and a lot of people just stuff it all together and say, oh, ai, this, and so maybe let's just talk about a couple of things there. Just forget what are the misconceptions of ai? Um, in general, in construction, like what, what are people scared of? What's the deal? What's going on here?

Speaker 2:

you know the biggest misconception in ai right now is that ai is very new and chat gpt had a lot to do with that. When chat gpt came out at some point last year, everybody hopped on this and everyone's looking at this like this is some new technology and we have to go all in on AI. And you see all these company executives pushing their IT teams, pushing their digital teams, saying, hey, you know, take my money, let's build AI, whatever that means. They don't know what that means, but just do something with AI. Ai has been around for decades and companies who've invested in their digital infrastructure and data integration have been leveraging AI for years.

Speaker 2:

Right, but what we really saw with ChatGPT was a very good model. It's a language model, llm, which stands for large language model and what it really did is it democratized AI Because it made it available to the masses. Anyone can go in, just use language, natural language, and do stuff with it, whereas before you kind of had to be a developer, know a little bit of Python or some programming knowledge. So it democratized AI and then that's why it sort of went viral. But the good thing that came out about through all of this is it got us talking, especially in the construction industry. It got us talking about AI and then pushing us towards at least the right steps.

Speaker 1:

Okay. So the misconceptions, though, is the fact that one of them that it's totally new and it's actually been around for a while. But what is new is this new paradigm of anybody can just use this and I can. You know, like my daughter can hack her algebra test right. You can just basically put it in there and she can get out of there and you know, on the you know, doing a marketing program or doing, uh, an rfp or something like that, you can fire, you can put, put your commands or prompts right.

Speaker 1:

You put your prompts into ChatGPT and you can. It will write an RFP for you.

Speaker 2:

I mean it's crazy.

Speaker 1:

You put the right information in it, so I think that that, as you said, the democratization of using AI and the general public having access to this thing without having any coding background or any kind of experience in computers in general other than Gmail, and you know, and Word Suite or Microsoft products or Google that is.

Speaker 1:

I would agree with you. That's sort of that misconception there, but it's definitely changed quite a bit. But in construction specifically, you know where do you sort of see this going? In terms of the, is there a misconception of the fear of the sort of desk job being a threat? You know project management, you know schedules. That can be automatically done If you're going to put a schedule together cannot be generated. You could say just like last project and and give it all the different changes and suddenly, well, the thing that took me like four days to do and now I can have it on an hour yeah yeah, so where's that kind of going?

Speaker 2:

there's definitely a fear, and you know I've been in this. I've been in the space for almost six years now and so I'll tell you a little story. When I started, I actually started with Lafarge as a co-op student fresh out of school and I come into the organization and I start off as like a data analyst and one of my responsibilities was producing month-end reports, and the entire process was done using Excel and I was just really just copy pasting data from one Excel file into another Excel file, downloading data from this source, that source, and then producing this report and then putting everything into a PowerPoint to make it accessible for people, and I absolutely hated this process. Yeah, and I took a step back and I said you know, what are we really doing here? Right, we got to automate this, and so I did some work and we wrote some scripts and became a whole project and I was able to condense 40 hours worth of work into maybe one hour. And we're not talking about some fancy AI, we're just talking about just bare bones, fundamental automation and data integration procedures.

Speaker 2:

And when I told someone in the company about this, they said oh wow, that's pretty cool. I hope you didn't tell your boss. I'm like what are you talking about? He said well, you know, if it was me, I would automate my job, but pretend I'm working 40 hours and then take the rest of the week off.

Speaker 2:

And so a lot of times when we went into site and tried to do this for other people, there was indeed that fear Like look, I'm a data entry analyst people. There was indeed that fear Like, look, I'm a data entry analyst and now we can use AI and scan PDFs and use some sort of training model to automate all that data entry, and they take a step back like hold on, so what happens to my job? But one thing that we're really trying to emphasize with the program, the digital transformation program that I'm leading at Lafarge is we're not trying to replace people. We're here to free up your time so that you can do other things. And I use my example within the company as well. When I freed up my time from that month-end task, I didn't go obsolete, right? I found there's tons of things that we could have worked on and I started working on some more creative projects and actually use my time more effectively, right.

Speaker 1:

Than just copy-pasting here. Yeah, no, I would agree, I would agree there on that. But I mean, I think one of the pushbacks, I mean everyone's going to have their sort of let's say the word lived experience on what they think is going to be their narrative to that, to this discussion. And if you were to look at somebody who worked at a video store, watch out for gone, because netflix is around, there's no video there's gone Because Netflix is around, there's no video, there's no VHSs being rented around.

Speaker 1:

It's gone, gone, gone, gone. Yes, so there are going to be some things that those positions they're not going to be there, absolutely.

Speaker 2:

The question is is that?

Speaker 1:

what are we replacing that with? What is that person going to transcend into? That's going to be a meaningful career. And, uh, transcend into, that's going to be a meaningful career. And obviously it's going to be. Uh, okay, let me ask I'll get another question, so I had this conversation today on another podcast was, let's say that a project is a symphony, okay, and you have all the different players, uh, in in the symphony, you got the violinist, you got the people on the tambourine, you've got the trumpets you got all, you got the entire orchestra and then you have the conductor and the conductor is is uh, you know, here's the sheet music.

Speaker 1:

They know exactly what they're doing and they're gonna they're gonna make sure everything plays in sequence. The question is, which job is most at risk the conductor or the orchestra?

Speaker 2:

because of a I would say it's the orchestra.

Speaker 1:

You would to an extent. Yeah, I had somebody tell me the other day. They think it's the conductor it depends.

Speaker 2:

I think the conductor is the one who sort of brings it all together, but there's different ways of looking at it.

Speaker 1:

Yeah, I would agree. Yeah, because I mean and the reason like that symphony works well as a metaphor because in construction you have the one major change clearly on the field is the environment that changes. It's not like prefab where it's you know, you're not building Teslas where it's just like the hood is going on and then the wheels are going on and it's the same rinse and repeat in construction is different every time, right, because the, the, the actual terrain changes, the building is is being built and it's everything's changing yeah, to an extent, but there are still a lot of manual and repetitive procedures as well.

Speaker 1:

Right, those are the what do they call them? The dull dangerous and 3ds, I think dull dangerous and, uh, I don't know, okay there's a third one you haven't heard.

Speaker 2:

No, no, not yet.

Speaker 1:

Maybe I'll ask chat gpt, it'll probably know yeah yeah, we see communications jobs gone, okay, okay, let's just talk to that a little bit about um, like I think that people now who are able to use AI tools to become more efficient, to get stuff done, they can be the conductor in their own job, exactly.

Speaker 2:

And what I was getting at with the conductor example is a lot of these repetitive procedures. And look, everybody has to go and fill out reports where you might be conducting site inspections, and there's always these menial, repetitive tasks that are part of really every job, and there's usually the most draining tasks, right? So the point is like the repetitive stuff can sort of be automated. We're seeing examples and prototypes now with these autonomous AI agents which sort of work like AI employees, and so now it's turning into a situation where everybody sort of has their own AI intern and all that manual stuff, the data entry, the sending emails, reviewing documents, all the boring stuff that no one really wants to do. You can get AI agents to sort of do that, but you're still the master of your own ship, right? You've got to navigate that, and that's what I mean the conductor, that's what the conductor needs to do. Right Is set the goal.

Speaker 1:

AI is not going to do that for you. It's not going to replace you in the driver's seat, right, okay? So let's just say that, um, we've got. Um, let's say shelly is working and that's what she does, okay. So shelly then is now uh, has they've gone through this transformation meeting and they've met with you and they're like here's all these tools you can do to do all your reports, etc. She's trained now to do this stuff. And then the company is thinking, wow, okay, so now what do we do with her time? Because it's a huge time savings and so maybe the job scope now changes.

Speaker 1:

Now that she is now able to do something, that is actually going to add more project consciousness, because not stuck behind a computer doing stupid reports all the time, even though I'm saying reports are not stupid, they're required but it seems like such a bad use of a human's time. 100 right so, but there's going to be buy-in on the hr side of keeping shelly around a, because you know, construction, in my opinion, is mostly good to most people. It's like a and most people are good in terms of their intentions around people they don't want to like just fire people and let go, especially in the, in the sort of management roles. True, so shelly is like okay. Well, we love shelly, we want to make sure that she's around and let's say shelly's like. You know what I actually am, I've got a job somewhere else and she leaves.

Speaker 1:

Now the job opening. Will that job change or will it be? You know? On the job description will it say looking for PM or assistant PM. That does this and that's part of the job description, because we will get there For sure, unless you don't know how to use these AI tools in order to do what you do. So I think schools are going to have to show this as well, so it's going to have to go all the way down the line.

Speaker 2:

Yeah, schools, and I think it is changing. Now we're starting to see it where basic, fundamental computer skills are now being embedded into every university program and they're teaching this in primary schools, elementary schools now as well. We know that engineers. Before it was the case where if you're not a computer engineer or a software engineer, you're not going to know any sort of programming. But now we're even seeing civil engineers, who mainly deal with concrete and structures even they're taking courses now on programming. So that's what's leading to that shift.

Speaker 1:

So you're right More people are going to have to use this. It's going to be a requirement that's going to change the entire project management school, trade school kind of paradigm in terms of what's in this course.

Speaker 2:

But at the same time, I think especially now what we're seeing with ChatGPT and natural language, where you don't necessarily need to be a programmer to interact with these tools either yeah, they're pretty set up and forget it right. So the barrier to entry is decreasing.

Speaker 1:

Yeah, that's true, so it's going to be easier for more people to participate, and I think what we're also seeing I know this is based on the Google suite, for instance, like Google Docs. I mean you start to realize how good that is at its predictive stuff.

Speaker 2:

I mean, mean it starts to be?

Speaker 1:

like oh, okay, that's, do you want it this way? I've been doing stuff on spreadsheets. I'm like crap, this thing is like it's, it's, it's like in terms of the formulas it's giving me hey, do you want this? No, next one, next one.

Speaker 2:

I'm like uh yeah, okay, that's pretty cool, right?

Speaker 1:

yeah, it's pretty cool because, like, it just takes the time down. Yeah, um. So let's just chat a little bit about um. We've got some pressures in terms of the different generations. We have the generations who are pretty much tapped out in the like how much, how many monthly fees for SAS software do we need to be paying for these licenses per users? I mean the amount of money that's being spent and actually being wasted on software that's not being used.

Speaker 1:

It's true, there's tons of that. And now there's this other thing. It's like okay, well, we now want to start using ai and there is probably a okay, well, could that save you money or is this going to make us more efficient? There's going to be a curiosity or there's a. Yes, but technology, technology in general, not just AI, but just digital transformation. Why is there this resistance from the older generation compared to the younger generation? Who has this expectation that, if you're going to give me an app and you're expecting me to download and it's a bring my own device to the job site and you're going to give me an app that sucks, why does this app that I use for work, when I'm doing my site orientation or I'm going to fill in my time card for the day. How come that doesn't feel like Airbnb and Uber? The expectation of how good that has to be down here and then you have the other generation.

Speaker 1:

That's like, uh, yeah, I mean, how much of this do we really need?

Speaker 2:

it's true you know, in construction. One thing I've noticed is there is definitely an aging workforce. A lot of people are like a lot of baby boomers or have been in the business for a while. My old uh manager started with the company when he was 25 and he retired at 65. And that's a trend. I noticed, especially at Lafarge, that people stick with Lafarge for the entirety of their career.

Speaker 2:

That's not really the case so much in this day and age, with the new generation. People are hopping jobs left and right every couple of years, every couple of years, and I mean it makes sense too, because people want to change. It's just the environment we're in, but that definitely contributes to the change. But at the same time I don't think I would blame only that. I think a lot of it is culture as well, where there's sometimes just resistance to technology. I know I heard there were these cases where they were installing cameras into delivery trucks that would just monitor drivers, into delivery trucks that would just monitor drivers, and these drivers, in protest, would rip these cameras out because they said this is just Big Brother watching us. So there's a bit of resistance there.

Speaker 2:

But at the same time and I'll tell you a little story about one of the projects that I led and what I learned from that. I had a situation where we looked at the quality control process and the entire process had not changed since the 80s. And that's just because the management had been around since the 80s. And so it looked like you walk into this quality control lab giant calendar on the wall, the way it has all the scheduling on it. They track all the test results on pen and paper, put it into like index cards and put it in a little cubby, and then somebody at some point will enter this into a computer. And the point is, I mean, by the time that data gets into the computer it's probably too late.

Speaker 1:

Oh and inaccurate.

Speaker 2:

And inaccurate, because there could be mistakes. Sometimes you can't read their handwriting, right. So there's that. And then so we said we're going to digitize this process, we're going to build an app. It's a pretty and I said this is going to be a quick win for us, right? So we sit in a boardroom and this is important, my team we sit in a boardroom we think about what this process should look like. We build the app in a few months, we take it to market or, in this case, into the field, and we say here you go, this is the app, it's all digital. Now Thank us later. Goodbye. A month later or a few weeks later, we come back and we say how's the app working? It must be great. And they say, yeah, you know what? We're not really using it. I say why not? I thought it would be a no-brainer. And they said it's just not there. The pen and paper process was easier for us. It made sense, it's what we're used to.

Speaker 1:

And so that's what they did. So can you just break down on the different generations who were saying and these are young people too.

Speaker 2:

These are technicians as well. Yeah, people around my age saying this stuff, right? So I was thinking back. I thought maybe this is just the old heads who would push against it. But no, the young generation was we're used to pen and paper. It's just much easier. So I go back to our management. I say this is what I heard, and one of the responses I got from management was give me their names, I'll talk to their boss, we'll force them to use it. Okay, because sometimes you know what people are probably just resistant to change and we'll just force them to use it. So I said okay.

Speaker 2:

So I go back a few weeks later and I say are you using the app? They're like, yeah, because we're forced to, we have to use it, but we're also using the pen and paper're actually still so now they're doing both. It's made it less efficient. So I said okay, I'm definitely missing something here. I'm going to put my boots on, I'm going to put my hard hat on, I'm going to spend a week with you and let's go through this process. And then I realized you know, it's a construction site. The way we set up the form is like you've got to go top to bottom. There's no safe progress. You're wearing gloves, you can't type on a phone. So then I started seeing all the little issues and, truly, you know, you grab a pen, grab a paper, you just jot something down, scribble something, and then just forget about it.

Speaker 2:

So I realized that there were gaps in the app, and I think that's contributing to the issue of adoption is the gap between the boardroom and the field. And so when I spent time on the field and we really, really refined that user experience that you were talking about right, really get that down and that process probably took maybe three times longer than the actual development of the app. But once we cracked that code and we got the UX down to where it needed to be, the app scaled itself. And we started in one city, we started in Hamilton, then we started in Toronto, and then this app blew up and now it's all over North America, even including Mexico, and it came to a point where, instead of us dealing with resistance from these employees, people started calling me and saying, hey, I heard this really cool app that you built. When can I use it? And so that's what I mean. I think it's again the gap between the boardroom and the field. But once you spend time in the field and address that gap, these things will scale themselves.

Speaker 1:

Wow, that's a good story. Yeah yeah, it is interesting how we have this very high benchmark level of user experience that we require these days. It's true Because we all use these apps on a daily basis. Some of you might have used uber to get here. I mean, I just flew in from vancouver. As soon as I land here, it's showing me all the places I went when I was in toronto last time I was here. It's like which one of these you want to go to? I'm like all right, there it is that's where I went last time.

Speaker 1:

I mean it's just awesome right and you know, I think that it was the user experience that anybody could have said look, we're going to go and try and change the taxi industry, but unless that app was killer awesome on the driver's side and on the customer side, it just wouldn't have worked. So I think what you're saying there is that gap between the boardroom and and the, the field worker. Let's say we're the field level. It's also like that in the office too, like sometimes the software, the project management software, can be clunky. It's like we're still dealing with the email. I mean yeah.

Speaker 1:

What's the a lot of companies dealing with Slack these days.

Speaker 1:

Sure, yeah, slack, yeah, others yeah, just real hands in construction, slack Anybody flag yeah, okay, yeah, um, it just seems we're in this time, right now, where things need to be. Maybe ai is the solution. I mean, the other day I looked for an ai email box cleaner because I've got a couple of gmail. Like some of you guys, I've got a gmail, a couple of gmail accounts, some I pay more attention to than others. I've got like 25,000 unread emails in a Gmail account. I'm like, how do I even deal with this? And so an AI cleaner to just go in there and says okay, here are all of the ones that you were sponsored for, here are all of the different contacts, here are the ones that you opened Any of these. Do you want to just keep putting it down like that and then delete the rest?

Speaker 2:

Yeah, and I think you're right, ai will help. I think it's a tool, maybe not the only tool, but it is a tool that would help. One thing it definitely helps us with, especially from a development point of view, is move faster. Developers use AI tools to write their code and also improve their UI, and one thing we're seeing now. So before it's like you want to make a UI change to a software, there's a whole pipeline you've got to follow. There is, yeah, but now there's these tools where it's literally just a prompt move this from here, move that there, and it'll do the code in the background and change the UI. So it helps you move a lot faster, and I think what we'll even see in the very near future is customized user interfaces for the end user. Maybe you like seeing things one way, I like seeing things one way, and it can all be very prompt-based. You don't need any coding knowledge and you'll be able to customize your own unique experience Exactly, and that's one thing that we're finding.

Speaker 1:

I mean, at SiteMax, a company I founded, we've got a couple of views. You've got one. When you go into the project, you see that view. And then, on the on the uh, the company side, you look at all your projects. You got that view.

Speaker 1:

I'm like, well, I will say to my, to my team, like well, maybe I don't want to see that view. Yeah, you know, like these little uh alerts that I'm seeing here is just not relevant to me. Um, but you know, what can happen is if the structure of the actual page or the mobile application is not ready for like what? If it looks really stark. You know what I mean.

Speaker 1:

Like, let's say, you get a field worker, all they do is time. Well, it'd be great if the app actually just was about time. You know what I mean, rather than the empty box with just the clock symbol. You know what I mean? Because it just makes it. It's almost a self-esteem thing. This is all I get to use, you know. So there's lots of things that I think can be done on the UI UX side. Let's just chat a little bit about when we had our call, a pre-call. Before, when we met each other on the Zoom call, we talked about risks of AI, like what are some of the things that the catastrophes that we need to be looking out for that could happen here?

Speaker 2:

So there's two things here. One thing is it's all about the data that you're feeding AI. Right, it's all powered by data. So if you have garbage data going in, you're going to get garbage data going out. So that's one issue, and I think that's something that companies need to pay attention to. The second issue is hallucinations, and that's led to a lot of funny incidents I would say humorous incidents that we've seen.

Speaker 2:

I know we talked a little bit about that Air Canada example where they had this AI chatbot on their website so somebody asked it about their bereavement policy and it gave them unfactual information and Air Canada had to honor it in court because they said whatever the chatbot said is basically what you have to honor. There was another example where, I think, somebody convinced a Chevrolet chatbot to give them a new truck for a dollar. So there's always these risks and I think it just comes back to corporate executives sort of driven by FOMO, the fear of missing out, because we're seeing these AI headlines Everybody wants to cash in, nobody wants to be left behind and sort of just jumping on these things without really understanding what they're supposed to do and it's just moving too quickly and not understanding the fundamentals. But if you go back and you just stick to the data fundamentals and do the data integration right, you'll be fine.

Speaker 1:

Yeah. So when I look at AI integration in the field, what worries me a little bit is project consciousness of okay, that's got that dealt with for me, especially on the safety side, like it is a.

Speaker 1:

I even see this now. I see people who are just punching radio buttons yeah, yeah, yeah, yeah, yeah, yeah Done sign at the bottom. They didn't actually look at that one thing that was on that line. I see people who are just punching radio buttons yeah, yeah, yeah, yeah, yeah, yeah Done Sign at the bottom. They didn't actually look at that one thing that was on that line. They didn't look up and go, okay, yeah, that's good, some do, hopefully most do, but some are just like going through there and you add AI to that and let's say it asks you a question have you looked at this? No-transcript if you start to rely on something else.

Speaker 2:

I've seen examples of that, especially like the data entry example I mentioned, where it's this great, big win we're able to automate data entry. You don't need to sit in front of a laptop and enter numbers anymore Great yeah. But every now and then it might miss something, it might make a mistake, and so if we're seeing a case where people just ignore it and say, oh, the AI is handling that, I'm just going to move on.

Speaker 1:

Oh, yeah, exactly.

Speaker 2:

That's a bad practice, but I think it just comes back into culture and establishing good procedures and policies within your organization and being mindful of that. That it can make mistakes, but, to be fair, so could a human. So, just making sure that there's this cross-validation, that you're making sure that things are being done correctly, but I think, look, it's always the response of the human in the loop right. Even when things are being automated, you've got to have a human in the loop right, and AI is not here to replace us. It's here to complement what we do.

Speaker 1:

Yeah, I like the human in the loop. Wow, there needs to be a website with a human in the loop. You should make that. Yeah, yeah.

Speaker 2:

I don't think I came up with that. I probably read it somewhere, oh you don't.

Speaker 1:

Oh, I see. Oh, that's cool. So, in terms of, do you envision this? Let's go robotics, and let's go robotics. And so the hardware mixed with AI, like how is this going to be manifesting itself? Let's say, 30 years from now? What's this job site going to look like? I mean, are we going to see a significant decrease in the amount of human beings on a job site? Are we going to see drive-by-wire? Is it going to be installation by robots? Like what do we?

Speaker 1:

I don't know, did anybody see this? The painting robot? Have you ever seen this? Yeah, I mean, the thing is, no one cuts as well as that painter. I mean, it's insane, it's true, it's perfect, right, and and then that's a skill, right, that's a skill. As a painter I'm. I tried to paint my own, my own, uh, living space. Yeah, not, it's not easy to to do a nice cut and not get on the on the ceiling, that's true, but that thing's perfect and the people who can do it have learned over time with that steady hand to be able to do that thing, or they have a specific tool that does that, etc. But are we going to see this? Just total transformation of the job site within 30 years?

Speaker 2:

that's the million dollar question. Right, are robots here to take our jobs? But you know, sometimes I say, instead of asking are robots going to take our jobs, maybe we should ask are our jobs turning us into robots? And and we, we look at. You know, I like to use the example and I get what you're saying.

Speaker 1:

We're already cyborgs right now. I mean, if you look at most people know I like to use the example and I get what you're saying we're already cyborgs right now. I mean, if you look at most people walking around, they've got their phone in their hand. It's true, it's so bad. I've walked around a number of times and I've said to my wife honey, where's my phone? She's like it's in your hand. Oh, like I forgot it's there. It's become this appendage, it's like. It's like. It's like. So we're cyborg. It's just that we can just decouple it like we can just drop it on the table. And now I'm not a cyborg anymore, even though I'm yearning for that. Will you ever leave your phone at home? That's terrifying. You can't live without it. No, I mean because we were just so connected to that. That's right, okay. So the question is let's go to like what's the Neuralink version of construction? Look like.

Speaker 2:

The Neuralink version of construction. That's an interesting one, it is. Well, we've seen what Neuralink can do, right? You saw the monkey experiment they did, where they installed Neuralink into a monkey where it can play Pong online. So you're basically able to control computers without using your fingertips, right? So are we going to see that, where people are plugged into Neuralink and able to control things? I don't know, it's tough to say, but one thing we can at least see in terms of the trend is that robotics are taking over many procedures, especially things that are repetitive. You mentioned the painting example.

Speaker 1:

Here's automatic cranes or the dangerous stuff like going into crawl spaces and all that kind of stuff. That too right.

Speaker 2:

We're seeing what drone technology is capable of right in terms of LiDAR scanning and 3D modeling and just bridge inspections. Before you had to install scaffoldings to do inspections. Now a drone just flies over and gives you a 3D model right.

Speaker 1:

So, like, in terms of um, like, I always look at the lowest common denominator of the digital transformation side of things. So you know, I recently renovated, you know, our condo in vancouver and you know I gotta go get the drawings from the city. Okay, well, they're not giving me bim models and until all of that is transferred over, we're gonna be stuck in that past, because some of those aren't even vector drawings. Sure, they're raster old scans of, like hard drawings. So you know for, in order, yeah, for sure, if you're going to be building an airport, you're going to build a hospital, that's going to be a bim model. All the hvac, everything's going to be in there, all the layers.

Speaker 1:

You know about the stuff and and it's kind of ubiquitous on that higher level, but that's not the majority of the revenue and construction in north america. It's like renovations, it's like ti's, it's building warehouses, I mean it's it's not all the hospitals and airports. So in order for that tech to really really take hold, I should be able to go to the city planning office and get a set of 3D drawings. You should be. How long is that going to take? And the question is will there be an AI service that will transform them into the 3D ones.

Speaker 2:

That's a good question. How long is the city going to take? They'll probably be the last ones to adopt it, because it's the government.

Speaker 1:

But until then we're going to be stuck with 2D drawing.

Speaker 2:

It's true, and look even now, in terms of information sharing, the choice of most people is to share information with PDFs.

Speaker 2:

If you're on a job site, you're getting tests done, whether it's a soil test or a concrete test. Whatever. That data is being transferred using email and PDF, which is one of the worst ways of transferring data, because someone has to open that PDF and then probably type it into one of their systems and these systems don't interact and don't talk to each other, and I think that's a problem that us as an industry is going to need to come together to solve right, coming together with some sort of protocols or something. Usually, I think, when there's a large player in software, like we see with Google's and Microsoft's and these big platform companies, they're the ones who are really good at driving that change. The problem is these big construction software companies. They're very archaic and they're due for disruption, and I think that's what's going to drive all of this is, we disrupt the big players, the big software players in construction, and as more people adopt that, that's going to drive more people to change.

Speaker 1:

Yeah, I would agree with you there. The question is is that everything's typically about ass covering, right If it goes to legal? Show me the PDF.

Speaker 2:

That's true, it's true, it's what we're used to.

Speaker 1:

Yeah, and so if everything comes down to the fear of litigation and the fear of proving your point, then you're going to want that lower common denominator thing. It's true, that has that like what we're, I mean, with Sitemax. Right now we have three different types of signatures. One is certified and has a certified signature like a docu-sign, and other ones are just like yeah, we did it.

Speaker 1:

So, there's three different types. You can choose what you want on your process. But those different things, um, that digital signature is a thing, right, so maybe that and it's a thing, a legal thing, right, it means you were there at that point and it was a digital signature. So, um, do you see that changing to? Maybe you, you know, like a facial recognition that was me, or like there's lots of things that can change.

Speaker 2:

It should be, I mean, yeah, the thing is, there's a psychology concept where they studied people who stick through toxic relationships and the reason for that, they say, is because we're not always attracted to what's best for us. We tend to chase what is familiar. Yeah, and that's the thing I mean. We can apply this to technology and technology adoption as well. People don't like what's best, people like what's familiar. So I guess it's something to think about, especially for digital transformation teams. When we integrate new technology or introduce new things, we have to make it seem familiar. So there's less resistance to change and I think you're right that there's tons of ways of doing things better. But it's about how do we make this more resistance-free and familiar.

Speaker 1:

Yeah, I would agree with you. There does need to be a technology change on the software side that is going to revolutionize something. I remember back when PlanGrid, which is now an Autodesk, when someone would say here, I'll just send you the drawings. They're like what, what do you mean?

Speaker 2:

send me the drawings. Yeah, just give me your phone number.

Speaker 1:

Boom, there are the drawings. I mean, that was a transformational change that changed a lot of things. People didn't have to have that roll up of drawings in the tube in order to get some information, it's true, right, so you could do, you know, uh, you could just mark up a screenshot of drawings and, just you know, send it off to someone else, that they could, you know, make a change of drawings in other ways. So I mean, this does that. I just wonder what that next thing is that's going to be like on the jobs, like holy crap, have you seen that thing?

Speaker 2:

It's true. And, look, it's about finding the incentives for the user right. If it can make your job easier, it's a fun feeling, it's a good, comfortable feeling. The problem is that, again back to that, we talked about the city giving you scans, right. What's their incentive to give you a 3D model? Right? And that's something we've got to think about. Even testing companies sending you PDFs with test results. It's a pain for me to have to go through that PDF, but for that company it's just export a PDF instead, right? So it's and that's something we need to figure out and especially software companies need to come together. And how do we incentivize that for the user?

Speaker 1:

on the other side. Yeah, because all they're really doing is just transferring the inconvenience. True, exactly the transfer of inconvenience. That's how construction is often right. Oh, here you go, you got your thing, now you deal with it. Oh, you got your thing, now you deal with it. It just keeps getting punted down the line.

Speaker 2:

Yeah, and again, I haven't figured out how to incentivize that procedure yet, but I think that's something for us to think about.

Speaker 1:

Yeah no for sure. So let's just chat about what you've done with Lafarge and et cetera. So you've been utilizing some tools there, utilizing AI, different types of technologies. Take us through some of the stuff that you've been doing, Maybe some examples that people can draw from.

Speaker 2:

Sure. So there's tons of examples. One of the things is we take a data-first approach. So when I started, like I told you, that month-end process, everything was very Excel-based. That was the case for a majority of the organization, right, A lot of procedures were still pen and paper. So that's the first step is we got to apply good data integration principles, and what that means is your organization. You have tons of softwares, tons of systems, data scattered, siloed all across. You need to enforce a data lake and a data warehouse infrastructure, which basically means you integrate all these sources and bring all of the data into one place and then you clean it up and you organize it in a good relational format. So is that what you guys did?

Speaker 1:

That was the first step right Forget about everything else.

Speaker 2:

You've got to focus on your data fundamentals and once you get there now you can have advanced analytics. Now you can apply machine learning, and so then we work on some pretty cool projects. So right now we're working on a project to as you probably know, uh, cement is one of the leading causes of co2 emissions in the world. That's because co2 is a byproduct of cement production. So anything we could do to reduce cement or increase cement efficiency in our concrete mixes is a huge win for us and for the planet. So that's what we're doing is we're building these machine learning models that are trained on our historical performance data, all the ready mix or concrete tests that we perform, and then trying to find cement efficiencies to reduce the cement. So that's a project we're working on.

Speaker 2:

We're piloting a project right now in one of our aggregate quarries where there's this long two kilometer conveyor belt, and right now we had two technicians whose job was to just drive along this belt and make sure there's no kinks, make sure there's no cracks or any issues with the belt. Now we've actually employed a robot that's going to do the exact same thing. It just has a camera on it, it drives around the conveyor belt, and so we freed up time of you know two technicians so that they can go and perform other things. And that same robot can do more than just that it goes around, it checks for safety, health and safety violations. Take us through that. How does it do that? It's just a robot on wheels, it just drives around, it has ai built into it and so it's a train to to perform these tests, because we've taken images and fed it historical data so it knows what a problem could look like. Okay, so what?

Speaker 1:

just just to get really in the weeds on that for a second. So what? What specific things has it found so far?

Speaker 2:

Well, every now and then there could be a kink or a tear or some issues within the conveyor belt and it'll take a photo and it'll immediately alert somebody to address that, pretty much the same way a human would. At the same time it's also doing, like I said, those health and safety inspections. That's the part that I'm talking about though Sure the health and safety.

Speaker 1:

What are the specific endpoints that it is finding or looking for or checking?

Speaker 2:

or cross-referencing, so as a robot is driving around the site and you would have health and safety personnel do the same thing, or if you see somebody for example, but they might be doing a checklist. They do a checklist. They do a checklist, so the robot does a checklist it has a checklist as well, Okay so how does? And there is a daily. Is it seeing the checklist Circle?

Speaker 1:

check. Okay, yeah, yeah, okay. So does it go to certain waypoints then?

Speaker 2:

It has a 3D model of the site in its system. Okay, so it knows where the site is. Okay, gotcha, and yeah, you're right, it sort the ability to maneuver. If there's an obstacle in the way, we'll go around the obstacle. So it does have some no coffee breaks. No, no coffee breaks, unfortunately. But so that's what it's doing. It's just taking photos again, just the routine tasks that technicians would do.

Speaker 1:

It's it's able to perform those routine tasks okay, so, um, so, do you see that as we move forward? Do. Do you see a virtual superintendent? Do you see a virtual health and safety officer on a job?

Speaker 2:

To an extent, yes. And one thing I do want to emphasize, though, and it's a very important principle when working in automation. There's a famous quote that says automation applied to an inefficient system will only enhance the inefficiency, and that's important for us to realize. And even with this example, too, sure, we could have this robot that drives around, but we also need to think about is this the best way of automating that procedure At the same, so that robot can only be at one spot at one time? Right? In certain use cases it makes sense. It's a very long belt. You've got to drive around that belt.

Speaker 2:

But certain cases, if we're just looking for only health and safety violations on your site, it may be more efficient to just install cctv cameras, yeah, and have real-time view all of the time, instead of only when that robot is present. So so, to an extent, yes, but I think software may replace a lot of the hardware as well. So you don't necessarily need a humanoid robot. Who's now the health and safety inspector? It's more of a procedure or a system that's embedded and integrated within all your intelligence systems within the company.

Speaker 1:

Yeah, it's funny. I had this podcast I've done two of them now with a company called Super Droids Okay, and they build these little robots. With a company called super droids okay, and they built these little robots and, um, I had this one, they were on video and they said do you want to see this latest project? And I said, okay, sure, and they, and they said, well, it's a humanoid, I'm like a humanoid, like how much money do you guys have?

Speaker 1:

First of all, I mean to make a humanoid pretty difficult, and so I said, well, why would you make, why would you go through the brain, brain damage of trying to get this thing to walk and balance and do all the things that we just find so obvious as humans? And he says, well, it doesn't need to do that, you just need to sit it in the form factor that was made for a human. Okay, because, like in an excavator, for instance, like everything's here, the pedals are here, it didn't need to stand up and what it does is it retrofits, in a way, all old equipment. There's a lot of it out there with the humanoid thing in it.

Speaker 1:

Yeah, yeah, yeah. So as long as the actuators work in the hands and the cameras there, yeah, and I think this is what Tesla is doing with theirs. This is where they're seeing this going. So that 30-year thing, do we have these flesh people and then plastic people everywhere?

Speaker 2:

There's something that has to be said about that. And look, I don't know, I say look, if you want to build a, a, if you want to design a self-driving car, right, first you build a robot and then the robot sits in the car and then it drives the vehicle. But you look at it like the same example I gave you about inefficiency right, that's a very inefficient way to have a self-driving car. Yeah, you look at what tesla's doing. They, they've gotten rid of the steering wheel. You, you don't need the steering wheel, right, you just build that into the car.

Speaker 2:

So, again, into excavators of the future, you're probably not going to have the pedals and all these controls, you're just going to get rid of them and everything's going to be built into the software. Right, because that's the more efficient way of doing it. But back to the concept of familiarity right, the majority of the world is built for humans and we've relied on human operators for a long time. And I think, to address that resistance of change and to really push this forward at first, maybe humanoid robots are the answer, because you sort of have this generic robot that can perform many different things.

Speaker 1:

Sticking in the old system.

Speaker 2:

Yeah, and you know what A good similarity we could draw to that is when electricity was first introduced, it only did one thing it powered the light bulb. There were no electric appliances, and one of the first electric appliances was the washing machine, and it was very simple. It just it was a motor that spun and, by the way, there were no off switches back then those and, by the way, there were no off switches back then. Those came later. So what you would do is you would unscrew the light bulb and you would screw in the washing machine port Because there was no AC plug. It was just the light bulb, right, but that's what it required to introduce this, because it was what was familiar. Once people got a hang of it and got used to that. Then we introduced AC ports and then electricity changed the world right. So I don't know, maybe humanoid robots will be everywhere. But at the same time, I think, when we get to more efficient design, I think you're just going to have equipment that is just more well-suited for the job at hand.

Speaker 1:

Yeah, I mean the autonomous equipment or the drive-by-wire equipment. This is the other part which I totally see If you see the movie Avatar, and they're in their control spaces and they're not in a bunch of stuff, they're actually just there with joysticks. I think that's going to be a lot of the new future operators is, they won't even be there. The equipment will be there but they'll be in the warmth and being able to chill and doing their thing. Or there's going to be the little command centers. So that's going to be a very interesting place where that will hit. Do you think that as the people change, will the jobs go away, or will those people just be doing something else?

Speaker 2:

Well, certain jobs are definitely going to go away and the market adapts and new jobs will be created. It's as simple as that. We look back at history and we look at the assembly line right Before all the entire assembly line to build the first Ford Model Ts. That was all done by humans. Right, the modern assembly line for vehicles is largely, largely automated, but it hasn't gotten rid of people. The assembly lines just become more advanced and we've came up with more careers and more advanced jobs for people to perform. Right, there were no health and safety regulators back in the early days. Right, that's a new job that was created. Right. And again, same thing with computers. So every new technology that's been introduced, it definitely gets rid of jobs, but it only creates new jobs, and I think that we're going to see the same thing with AI. The market's going to adapt, people are going to adapt and that's going to be the new world.

Speaker 1:

We chatted about that company that I had a guy on the podcast, josh Levy. He's got this company called Document Crunch. It's amazing. You basically just put your documents in and it just goes and finds and it basically gives you a summation of anything that's kind of off. Yeah, it gives you your risks of that contract. What kind of documents Like contracts, contracts and stuff. Yeah, yeah, yeah, yeah, it's crazy, very cool. So the question is, I mean can you upload? Like, what's the new AI for? Is it Notebook, right? Notebook For what? Google's new Notebook Notebook, ml. They got A whole bunch of things. Yeah, yeah, but that one you can upload stuff into and that can be pretty crazy. So I think we're probably going to see a huge transformation happen over the. It's pretty exciting, though. A hundred percent, yeah, I mean. So how are you pushing this through? Like, what is your? How much of your day is like working at Lafarge, doing the thing that you do, and how much of it is like coming to do things like this and advocacy and doing the?

Speaker 2:

It's definitely a lot of both and we are trying to change the culture right, change the mindset. Part of our program is we're offering these digital literacy courses. So we do a little assessment, we send it out to everybody. Everyone's going to be at different levels and, depending on the level that you're at, it's going to recommend some courses for you to take to improve your digital literacy. And not everybody needs to be at the same level. Some people just need to understand basic digital data, computer fundamentals and for some people, depending on their role, they can really really invest in some hard skills that are really going to transform the way they do their jobs, like learning Python, learning programming languages, learning advanced Excel and BI, all that. So that is again, it's a lot of advocacy, because we really want to change the mindset. The technology is changing. We're not building technology, we're just integrating it. But to integrate technology we really need to understand enough about it. Well, you seem pretty passionate about it, I definitely am.

Speaker 2:

I even read technology.

Speaker 1:

Yeah, that's pretty awesome. So do you have any advice on the leadership side of things for people here and for people listening when we publish this things? For you know, for people here and for people listening when we publish this, is there anything that you know? The resistance or the how to communicate change to your you know your, your company and your workforce, that you know we are going to invest in this change doesn't necessarily mean your job is at risk, but it's a matter of we're going to be getting rid of the you know the, the stuff that was dull or it was dangerous, it was or it was just repetitive, the things that you hated doing. We're going to try and make sure that you're not doing those things anymore and you're doing stuff that's going to move the project forward faster. Is there any sort of advice you have on the communication side that you've learned to help people?

Speaker 2:

Definitely, I think. Look, leaders need to emphasize to their workforce that, first of all, all these automation AI tools that we're introducing, we're not doing these to replace people. We're only trying to make the process more efficient. And make sure you make that clear and give them examples where jobs were automated but the people were not let go. They were only given better jobs that improve the quality of their life and help them advance in their careers. Right, that needs to be the emphasis to get rid of the fear of change. So we move away from that talk about, you know, maybe automated out of the job. Right, people should want to automate their jobs so that they can go and focus on better things.

Speaker 2:

That's number one. This is number two, I'd say, for leaders to not be driven by FOMO. Right, to be really just focused on the data fundamentals. Don't try to just use AI for the sake of using AI or be digital for the sake of being digital. You know, there's this one example where there was this one ReadyMix site I think it was in Europe and they managed to automate the entire process, the entire, from when the truck rolls in the batching process, everything out, the entire thing done without any humans. But the problem was it ran three times slower, it's 10 times more prone to failure and it costs something like 10 times more.

Speaker 2:

So I mean you look back at it and you've got to protect your bottom line. It's not about being digital and automated for the sake of it, but it's about doing things better.

Speaker 1:

Wow, that's a pretty good speech. Yeah, all right, that's awesome. Okay, so how can people find out to you? Can you give them best practices? You can help them with stuff.

Speaker 2:

I love to talk about this, so if I'm available on LinkedIn, feel free to connect with me. I'll be around after. And yeah, I'm on LinkedIn. That's really the only place I am right now.

Speaker 1:

Is it? Yeah, there's no new thing you're going to be hopping on Not yet, but maybe I'll think about it, do you? Don't do that? No, no, okay, it was interesting. The last guest was like the millennial guy was like I'm on Instagram and the other guys and the Gen X guy was like I'm on LinkedIn.

Speaker 2:

Yeah, maybe I'll give.

Speaker 1:

TikTok a shot, oh, tiktok. Yeah, you can TikTok that stuff. Okay, well, that's pretty cool. Could you guys all give me a round of applause for Mahir, here? Thank you, we're here here and thank you very much for coming. Thanks again for having me.

Speaker 2:

That was pretty awesome, your first podcast.

Speaker 1:

That's right, first podcast. You sound good in the cans here, so this is good, so this was a great success, thank you very much.

Speaker 2:

I appreciate that, thank you.

Speaker 1:

And thank you everybody for sitting and listening to us banter here and have the great rest of your show. Thank you very much. Well, that does it for another episode of the Site Visit. Thank you for listening. Be sure to stay connected with us by following our social accounts on Instagram and YouTube. You can also sign up for our monthly newsletter at sitemaxsystemscom. Slash the site visit, where you'll get industry insights, pro tips and everything you need to know about the SiteVisit podcast and Sitemax, the job site and construction management tool of choice for thousands of contractors in North America and beyond. Sitemax is also the engine that powers this podcast. All right, let's get back to building.