Developing Equitable Artificial Intelligence (AI)- ep.154

As a seasoned technologist, Vincent Broyles brings a wealth of experience in shaping strategic and technical direction across a wide range of industries. With a background in Industrial IoT, energy conservation, and sustainability, Vincent has spent his career developing and monetizing innovative technologies that drive both business and environmental success.

After serving in the U.S. Navy, Vincent transitioned into technical and leadership roles, excelling in areas such as satellite communications, cybersecurity platforms, and augmented reality applications. He has also worked on classified programs and held high-level security clearances. His leadership in global R&D at Websense (Raytheon) and IT engineering at Qualcomm was instrumental in enhancing the reliability and efficiency of advanced chipsets like Snapdragon.

In addition to his technical expertise, Vincent has a strong understanding of the business side of innovation, having held roles in venture capital fundraising, product management, and business development. His work with companies like NEJAVI and DCarbon Solutions has focused on cutting-edge digital solutions that marry sustainability with profitability. Vincent’s work at the intersection of technology, business, and environmental stewardship makes him a key leader at The Data Institute, advancing initiatives in digital infrastructure and carbon data innovation.

Discover how The Data Institute is leveraging AI to enhance digital equity, reduce carbon emissions, and ensure technological advancements benefit everyone – https://thedatainstituteus.org/

Melyssa Barrett:  Welcome to the Jali Podcast. I’m your host, Melyssa Barrett. This podcast is for those who are interested in the conversation around equity, diversity, and inclusion. Each week I’ll be interviewing a guest who has something special to share or is actively part of building solutions in the space. Let’s get started. This week I have an opportunity to speak to a friend of mine. His name is Vincent Broyles, and Vince is a seasoned technologist. He brings a wealth of experience in shaping strategic and technical direction across a wide range of industries. I’ll give you a little sense for his background because he has a background in industrial IOT energy conservation and sustainability. He spent his career developing and monetizing innovative technologies that drive both business and environmental success. After serving in the US Navy, he transitioned into technical and leadership roles, excelling in areas such as satellite communications, cybersecurity platforms, and augmented reality applications.

He’s worked on classified programs, held high level security clearances, and his leadership in global r and d at Websense, which is now Raytheon and IT engineering at Qualcomm, was instrumental in enhancing the reliability and efficiency of advanced chip sets like Snapdragon. In addition to his technical expertise, Vince has a strong understanding of the business side of innovation, having held roles in venture capital, fundraising, product management, and business development. So he works with companies like N Javi and Decarb Solutions and has focused on cutting edge digital solutions that marry sustainability with profitability. His work at the intersection of technology, business and environmental stewardship makes him a key leader at the Data Institute, advancing initiatives in digital infrastructure and carbon data innovation. And he is a fellow board member of the Data Institute. Many of you know that I have been working at the Data Institute as the president and board chair, so I’m excited to have this conversation with Vince. Join me as we kick off this conversation. Vince Broils, I’m so excited to finally have you on the Jali Podcast. Thank you so much for joining me.

Vincent Broyles:  Yeah, of course.

Melyssa Barrett:  I am excited to talk to you about all things carbon, all things artificial intelligence. But first I do want to ask you, I usually ask everybody, how did you even get to where you are today and you’ve had this illustrious career in technology, how did you even get where you are today?

Vincent Broyles:  Sure. So thanks for having me on, and I think I have had pretty strange journey. It’s been all over the place, and I think a lot of it is due to the fact that I like to try to take on challenges or take on things that I haven’t done before. I know it’s in my bio, but I started in the Navy and I was a data systems technician in the Navy. So started in technology very early and then transitioned to satellite communications and doing hardware for L three communications. And I just didn’t really like that and I wanted something more interesting. And so I went into software and I had a pretty long career in the software space and I led a bunch of very interesting environments. I ran the global r and d infrastructure for a company called Websense that’s now a cybersecurity product as part of Raytheon.

And that was a long stretch. I did there and just amazing people and opportunities and running a global infrastructure environment was very challenging and I really enjoyed the challenge. And then I decided to go over to Qualcomm and did another infrastructure leadership position there for the infrastructure supporting chip engineers, like 3000 chip engineers there that we supported. And that was also very challenging in an environment that I had no knowledge of when I took the job, and that’s always intriguing to me. And so then I jumped into the startup world. I did a VR startup that was way, way too early, but it was fun and very challenging again. And then I transitioned into the career that I have now, which is in smart buildings, smart cities, analytics, ai, and I led a smart buildings product for a company called Synchronous. And when that business unit was closed, it started becoming Covid time and synchronous said, Hey, we don’t want to do that business unit anymore.

And so I started with my co-founders, JD and Neil. We started N Javi and took everything that we had learned and a bunch of relationships that we had built and potential contacts that we had from that smart buildings world. And we started in N Javi and just continued, and it’s been a really exciting ride. At N Javi, we started consulting for smart buildings and smart cities and IOT, and that very quickly showed us an area of targeting commercial refrigeration. And so we now are very laser focused on saving energy and commercial refrigeration using ai. And that message is resonating with grocers all over the world and we’re having great success and it’s very exciting. And so that’s where I’m at today and who knows where I’ll be tomorrow, but that’s where we’re at right now.

Melyssa Barrett:  So Javi, tell me a little bit more about what Javi does aside from that portion.

Vincent Broyles:  Yeah, by the way, Navi is, the name is a miracle that we came up in five minutes. It’s Neil James and Vince Navi.

Melyssa Barrett:  I love it.

Vincent Broyles:  At first it was a placeholder and we needed a name and it was a placeholder, but everybody loved it. And we even got these funny rave reviews from an attorney that we have that said, where did you get that name? It doesn’t mean anything. It’s not a language. It doesn’t have any connotations. You get a nice short URL. And I was like, it’s total coincidence, but it’s stuck and we like it.

Melyssa Barrett:  That’s funny.

Vincent Broyles:  What we do is we have a product called DLH Dynamic Load Harmonization that is a cloud-based digital twin of a grocery store’s refrigeration. So if you think about all the cases that you get food out, frozen food out of or cold food, and so we build a digital twin of all of that, and then we apply AI to the digital twin and then that a then predictively optimizes the energy consumption in all of those cases. And so it saves the grocery store a ton of money and a ton of energy. It’s a good sustainability story for them because everybody’s coming out with the sustainability commitments that they have a very difficult road to try to meet. And so this saves them a lot of energy and gets them a lot closer to be able to meet those goals. It helps them to satisfy several of the UN SDG markers, the goal of the 17 different categories of SDG goals and the bottom line is it saves some energy and saves them money. And grocery stores have a really hard time. The margins are extremely tiny, really low. And so anything that you can do to save them a dollar is a huge value to them. It is new technology because it’s AI and this convergence of AI and cloud and connectability and all of that coming together, but it is time for that. And so we’re seeing a lot of interest and a lot of progress.

Melyssa Barrett:  That’s awesome. So in terms of, I know you also have had some interaction with carbon emissions and all of that. Talk to me a little bit about, because I am privileged obviously to have you sitting on the board at the data institute as well, and tell me a little bit about just the road to carbon emissions. I feel like there’s a lot of conversation happening about carbon exchange, but there’s also a lot of challenges, I guess I’ll call it related to carbon exchange and the sustainability of it.

Vincent Broyles:  So I think whenever you’re in the world of energy savings now there’s a component of that where you would like to or attempt to apply some sort of carbon value as well. And it is interesting and difficult because, so things like what we’re doing in the Javi, it’s not really a blessed template for that to apply directly to a carbon credit, but that world has been very interesting to me and I do think that it will get there. You’ve seen very recently a lot of, if you want to say waste, fraud and abuse in the carbon markets where there’s been double selling and people call it greenwashing and all of this negativity in the carbon world, but I think all that’s going to get ironed out. And anyway, I hope there’s a future where companies that take energy saving measures or carbon saving measures can easily attribute that to carbon credits or some sort of carbon value.

And then there’s another world, a bunch of friends and colleagues of mine are also working on being able to attribute some sort of carbon value to personal changes. So if you were to do solar in your home or you were to change out your pool pump or you were to do X, Y, and Z, we believe that individuals, and this is part of the data institute philosophy as well, that those sort of credits or that sort of value should be able to be applied to everyone. It shouldn’t just be for the rich or it shouldn’t just be for big corporations. It shouldn’t be the well-heeled on one hand, paying off the well-heeled. On the other hand, there should be an equity in making life changes or making environmental changes that reduce carbon. Everyone should be able to benefit from that in some way. And so it all comes together in my belief that anything that you do to save energy and reduce carbon, there should be a value that is attainable in some fashion. I dunno, that’s where I’m

Melyssa Barrett:  At. Definitely. So you brought up greenwashing and all the waste, fraud and abuse. Tell us what that means.

Vincent Broyles:  So greenwashing is just at a very high level, greenwashing is when companies put out these plans and they’ll buy credits and they’ll do things to say that they are green or that there are zero impact or that our sustainability is a zero impact, but maybe it’s really not. Or maybe they purchased credits that have been double sold or that don’t really mean anything, or they’ve purchased credit out of a forest that no longer is there or those kinds of things. Greenwashing has become a big overused term, but that’s the idea behind maybe someone who’s accused of greenwashing, they’re doing

Melyssa Barrett:  Those kind of, it’s not real, right? It’s not real. So as we take this road from a data institute perspective, we’re obviously focusing on digital equity, digital equality really for all. How do you see the transformation of intelligent infrastructure or digital transformation in the United States and how it connects with all these other industries?

Vincent Broyles:  Yeah, the United States by the way, I think is behind as we for sure look in other areas of the globe, they’re ahead legislatively, they’re ahead in peer pressure among companies and people and customers. But I think where all of it’s going, no matter who you are or where you are, is everyone started realizing the need for a standard. And that’s why the Data institute, the Nonprofit Data Institute has a goal of reaching standards like that. And one way to create a standard is to create limits and parameters. And I think a way that we are looking at it and a way that the world is going to look at it going forward is that these things should be measured and the way that you measure energy consumption, the way that you measure water consumption, the way that you measure carbon emission, all of that is through sensors, right through IOT.

And so there’s also a paradigm of a lot of carbon value right now is based on future results. I’m going to build this forest, I’m going to protect this land, I’m going to build this big sequestration plant and it will save so much. But I think one of the interesting ideas to me anyway, is to make those investments, whether they’re even if they’re forests or carbon sequestration or if it’s an energy saving measure or whatever, make those changes. And then maybe you have to get that certified or there’s some sort of certification level on that investment that you make, but then measure the amount of energy saved, measure the amount of carbon saved, and then create a digital asset out of that measurement and then have that be the item that has value attached to it. And so if you think about it that way, if you think about this digital package that represents an amount of carbon, avoided amount of energy saved, then that digital package then becomes tradable, becomes a piece of value as if it were a dollar or a piece of silver or whatever, a commodity. And going forward, if you believe in that paradigm and you believe that you’re creating these little digital packages that have actual value based on a measured savings or avoidance, then why can’t everybody produce those and why can’t those things be traded for value? Even if you just live in an apartment and you put a little solar panel on your balcony and you get one of these things in a year, why can’t I still trade that one thing I created this year for 12 bucks or whatever it is, whatever the value is,

Melyssa Barrett:  Right? Yeah,

Vincent Broyles:  I think that’s where we’re going. I hope that’s where we’re going because that speaks to the equity equitable opportunity for people who want. And then imagine if you, right now you’ve got companies doing it, but what if you enable this and then all of a sudden you have a billion people participating in avoiding carbon, reducing energy consumption, a billion people are participating, that’s going to have a huge impact.

Melyssa Barrett:  Wouldn’t that be awesome? That’s a good thing. Our whole focus is of course all about equity and making sure that citizens are at the table, especially when it comes to privacy. And because right now you have a lot of cities that are like, Hey, let’s put up all these sensors everywhere. And I don’t think a lot of people know, or I should say a lot of city officials maybe aren’t asking questions related to where’s the data going? Who gets to use the data? Can they sell the data? What are the limitations that need to be put on the data? All of those things. And you talked about the connection between iot, so can you spend a little time talking about what your thought process is in terms of data being exchanged, and then maybe we can broach that into the AI conversation. I think everybody’s like, how’s ai? How does it work, and what are some of the risks associated? So

Vincent Broyles:  I think that if you think about people or businesses or any entity really on the data side of it, we are like data streams or a natural stream of data from the minute you wake up, what time did you wake up, what kind of clock woke you up? Was it your phone? Was it a clock you have for breakfast? Where did you go to work? How far did you drive? What kind of car did you drive? All of that. If you think of people or entities as these streams or these wells of data, then like I said, what time did you get up? What kind of car did you drive? Where did you go to work? How much gas did you use? How many kids do you have? What’d you eat for breakfast? All of this data. And the same with companies. How many employees do you have?

What time did they get to work? How much energy did you consume? How many trucks do you have? All that stuff. This data is just flowing out and it’s being sold by companies for revenue. And I don’t necessarily think that’s a bad thing, completely a bad thing. I think that those companies invested and created all the ways to create and save them. Somebody made your iPhone and somebody created your car. So they have a certain amount of, I don’t know if the word is a right, but I think they have a certain amount of entitlement to some of that value. But the individual or the company who’s creating all that data does as well, especially if you think about the fact that we can’t really turn it off. You cannot function now without being watched in your data being recorded. And it’s almost not possible.

I mean, not in the US anyway. And so because of that, I think individuals should have a right and a way to profit as well. And also it’s a huge opportunity because if you think about the amount of data that we produce, and it might not be worth that much, but it could be a life changing thing for people who are economically disadvantaged. So there are people who, if they could make a hundred bucks a month or 200 bucks a month off of their data, that would be huge to their life, and they are creating that data, it is being captured and it is being sold. So to me, there’s an opportunity there for politicians or whatever, we might call it a universal basic income or something, but just really a way for them to profit off of all the data that they’re creating that’s going out into the ether, the internet and being sold profit.

Melyssa Barrett:  And it’s interesting you say that because I always think back to, I spent a stint at a payment technology company, and one of the jobs that I had was president or CEO of a credit reporting agency. And one of the things, I’m not saying credit reporting is perfection. I’m just saying I think that back in the sixties when we didn’t have credit reporting, people would make judgements that were very individualized. If my dad walked into a bank, they’d be like, Nope, you’re the wrong color or whatever. Whereas at least when we think about credit reporting today, there’s a score, there’s information that’s in there and that people have the right to actually go in and validate what is in there and if it’s accurate.

And I think in a lot of places where we’re talking now with all these sensors and things that are coming out, you don’t necessarily have an opportunity to fix anything if something is incorrect or maybe captured incorrectly, whatever the situation. And so I think it’s interesting when you talk about this, I’ll coin your term, universal basic income because I think everybody, it’s expensive to live in so many places now and a few hundred dollars or whatever it is, could absolutely make a difference in people’s lives. I was literally talking to somebody last month and I was telling them that this one man was responsible for helping my father get to college. I think it was just a few hundred dollars that he raised for him at the time, but it has literally changed the trajectory of our entire family. We’re college graduates. It’s totally changed where he would have been and how his life went based on that. And so it’s just interesting to me that we can have such a conversation and then you bring in this industrial revolution around artificial intelligence and what that means because almost like you have all of this data, but now you’re putting it on steroids because now stuff is being made up about you. I put my name in and it’s okay, that information is not actually accurate.

So how do you think people are, do you view artificial intelligence based on the stuff that you’re doing both at N Javi and where you think it’s going? These models are significant, they’re speedy, but they’re not always accurate, and there’s some risk to some of these models as well. Yeah. Let’s pause for a moment. We’ll be right back.

Vincent Broyles:  My world is really around narrow ai, the generative AI and the chat GPTs and all that stuff. That’s a different world for me. I think it’s amazing because I use it all the time and just the time savings that you get when you’re trying to write things or you’re trying to respond or manage your content or whatever. It’s amazing. But so my world is around narrow AI or AI that is used to solve a particular problem, especially in an industrial problem like we do at N Javi. And so I really believe, and I’ve been trying to write a little bit about this recently and do blogs and stuff on our website, but I really believe that any, I don’t know if any is the right word, but industrial processes that use a loop, it’s commonly referred to as a PID loop where, or any situation where there’s basically software or some sort of electronic control that can be modulated controlling machinery, that whole world is going to get taken over by ai.

So if you’re talking about commercial refrigeration like we do, there’s a controller, which is essentially a mini computer, and it sends commands to the compressors and the rest of the refrigeration cycle that says, do this, do that, change this pressure, change this temperature, whatever. And AI can learn about that process and optimize it better than any human being ever will be able to. And it can do it every minute or two minutes, and it’s unmatchable. And the same thing for say, refineries, manufacturing, these optimizations that AI can do. Imagine a human being trying to optimize a thousand store grocery store chain, every store, every compressor, every case, every day, every hour, every two minutes. It’s impossible. The amount of people you would have to have, even if you had a million people doing it, it wouldn’t be as good as the ai. And so I think that’s where it’s going.

This industrial 4.0, industry 4.0 and the industrial iot world is all going to get consumed by ai. You’re still going to need people to create the AI and apply it and watch it. And just like you said, sometimes the AI is interesting, goes off the rails a little bit, and you get weird answers. So you’ll always need people. It’s not all the people are going to go away and it’s just going to be this computer’s running everything. But I think the opportunities for efficiency, the opportunities for carbon reduction, the opportunities for greater increases in productivity, have a partner who’s doing refining AI in the refinery industry and the number of barrels produced goes up. You can talk about whether you want to be on fossil fuels or not, but as long as we are on them, let’s don’t fight each other on how efficient they should be. That should be as efficient a process as possible. And so AI is going to push its way into all of those applications, and the amount of productivity and efficiency that’s going to create is going to be huge.

Melyssa Barrett:  And I think what’s interesting to me is it reminds me of, I don’t know if you’ve seen the movie Hidden Figures haven’t. Okay, you have to watch it

Vincent Broyles:  Now. I’ll watch it.

Melyssa Barrett:  We had Catherine Johnson who was doing all of these calculations to take these astronauts into space, and there was this entire group of women who were doing all these manual calculations, and then IBM comes in and puts in this massive computer. And so it’s not like the people all went away because they still had to make sure the machines were functioning properly, making sure the calculations were correct, all of those things. But it reminds me of that with a twist on the secretarial pool back in the seventies or whatever when computers came in. And there were a lot of secretaries that were like, oh my God, we can’t have computers. And so we always have this nerve wracking kind of stress when it comes to some significant change that we’re making technologically. And we think that the robots are going to rule the world, but really it’s this upskilling that is being done so that maybe you don’t have somebody going in and reviewing the refrigeration, as you said, but you still need somebody to say, Hey, is all the data looking properly? What’s happening? Let’s make sure things. And so there’s a lot more analytics, there’s a lot more jobs that are created, but there are different

Vincent Broyles: Jobs

Melyssa Barrett:  And

Vincent Broyles:  Evolution. Evolution

Melyssa Barrett:  Of people. Yes.

Vincent Broyles:  Yeah.

Melyssa Barrett:  So what do you think of the, are there risks in terms of not only just inaccuracy, are there even in the business that you see developing in industry, whether it be, I dunno, we be talking about transportation or whatever, autonomous vehicles or something. That kind of stuff I will say gets me a little nervous when we’re talking about taking a car and getting in and there’s no driver and stuff like that. I’m like, oh, I don’t know. I’m a little more, I’m not an early adopter on there. I appreciate the

Vincent Broyles:  Innovation. Yeah, I think it’s interesting because I do think that, and one thing that we do is whenever we apply an AI process, there’s always a fail safe. There’s always a, if this thing looks like it’s going to reach a certain set point, or if you lose connectivity or the network goes down in the store or whatever, there’s all these fail safes that say allow it to continue as it would have before any AI was applied and that type of thing. And it’s funny, I always think of in the self-driving car world, I’m always afraid of, I’m not afraid of the car too much. I have a lot of trust in

Melyssa Barrett:  The car, the

Vincent Broyles:  Vehicle AI and the car. I’m afraid of the other people I know when I was a kid, I would’ve tried to screw with that self-driving car as much as I could have to see what would happen. And I don’t want to be in that car when some kid decides to do that or whatever, or an accident or a road that’s not painted properly or something. And so that’s what worries me. And I think

Melyssa Barrett:  That’s the nerve wracking part. Yes.

Vincent Broyles:  And I think the human part is to be the guidelines on the AI to harness ai. It’s like when the car first came out, people probably said, you’re going to go too fast and kill yourself or you’re going to do, and the point of the human was to drive the car, somebody has to operate it. And so somebody has to just talking in very simple terms. Someone has to operate the AI and put limits on it and make sure it’s being used properly and doing what it wants. But that’s what software engineering is all about. And the people who are working in AI every day, they know that that whole paradigm. And so I’m not too scared of it. I’m not worried about it ruining the world or anything, but you have to be responsible with it as well.

Melyssa Barrett:  Absolutely. And I think what I get nervous is when I walk into a test station, for example, who’s testing on real world roads and then they’re testing on things that may not even recognize that there’s a person that doesn’t look like that crossing the street and there’s some very real, what kind of testing are we doing and is it heat signature? Is it lidar? What are you actually using to make sure that you can recognize everyone and everything that’s coming in front?

And I think we’ve come a long way. We’re continuing to grow in lots of different ways technologically, but as you mentioned, I think we are definitely behind. So anything we can do to help I think makes sense. And I love the fact that people are starting to think about value when it comes to you as a person have a value. And that’s not to say it’s a hundred or 200 bucks, but in terms of the data that you give the information about you, there is all of these things that are more or less valuable like your credit score in a way. But there’s got to be opportunities for us to improve our lives so that everybody can thrive and that we can deliver equity. I think we just passed indigenous people’s day and we spend a lot of time, we don’t think a lot. I think a lot of people may not think a lot about indigenous people and the land that they sacrificed, but I know I was doing a bunch of research on the land I live on, and I was flabbergasted by just the amount of law that was created to destroy Native Americans, my area, literally kill them with a bounty.

It was insane, and I had no idea.

Vincent Broyles:  Yeah, interesting. Yeah, I didn’t know that either.

Melyssa Barrett:  Yeah, there are so much history to what we have been doing that when we think about ai, I think we need to bring that all with us. And I think in a lot of cases, AI doesn’t have the history because we’ve suppressed the history. And so we need to make sure that people are telling their stories, bringing their entire selves with them as we go out and focus on artificial intelligence.

Vincent Broyles:  I think so. And I think it’s important to remember that AI knows what we put into it that addresses the point that you’re making. We have to put truth into it or it’s not going to come out. That’s why I like to stay on the narrow AI side. We’re just saving energy. That other stuff is not just That’s a good thing.

Melyssa Barrett:  Yeah, it’s a good thing.

Vincent Broyles:  But I think it’s important to, when you think about the value of data, and you might think people, I’ve heard people say before that it’s too hard. How could you pay everyone? They have your credit card, they have your banking information, all these, I don’t see any blockage to subscription style remittances for data. If I’m going to use your piece of software, there’s a little EULA or a little acceptance that I have to do when I’m installing it and say, I’m unaccepted, blah, blah, blah, whatever. How much, not you, but as a company, they know how much data they’re going to get from you. They also know how much they’re going to sell it for. Why shouldn’t you get a little eight bucks from that one company on your credit card every month? And those add up the more things, and then there would be a huge rush to start using all these products.

If I knew I could apply, I could start using five different products that sort of watch what I do. I don’t have need. I know there’s no privacy in the world anyway, so I’m going to go use those products so I can get that eight bucks, that 10 bucks, whatever from each one of ’em every month, and then all of a sudden it’s building up and I’m getting a nice little piece of value for my data. And then I don’t feel like these are all big evil companies that are ripping me off and stealing my data. I feel like I’m participating and I think would actually be positive for the people and for the companies together. I think we would get advances out of that as well. People would participate even more. But yeah, I started rambling there, but

Melyssa Barrett:  No, I think it’s good to have all these different perspectives because I think a lot of what you just said assumes a lot of trust and we have to figure out, you’re like, Hey, the no privacy really exists. There should be some, we need some privacy. So well,

Vincent Broyles:  That could be the flip side of it is that if you create these at the data institute, if we think about this and we are able to create guidelines that say if you take data from someone, you have to compensate them for that. That’s probably a pretty complex conversation, but you have to, and they have to accept that. And if they don’t, then you can’t take the data and you can’t sell it. Right? That’s the flip side of that coin. I think that would be a much more equitable situation going forward. If everyone knew, okay, I’m giving up, like me, I would totally give up my data. I know it’s all out there anyway, and I don’t any, I would give it all up and then I would get a check and I’d be really happy. But some people would say, no, I don’t want you to have any of my data.

And then they wouldn’t because the laws and the standards and everything would prohibit that. Then you wouldn’t have, there are data rules in some countries that are very prohibitive, and then the first thing everyone says, Hey, do you want to adopt this technology? The first thing they say is, do you adhere to these data rules? And if you don’t, then you’re stuck. And it’s like a yes or a no. It’s like a pass or a fail. But I think there’s a middle ground there where you could say, people can opt in or they can opt out and they get compensated, and it would enable a lot of technology faster maybe because there would be a new way forward on data.

Melyssa Barrett:  And this is maybe just barely scratching the surface of all the things that we’re talking about when it comes to creating a thriving economy in this new industrial revolution. So I think it’s really interesting. Everybody’s perspective is so different in some ways, but it’s also similar. Everybody has a digital footprint. Usually there is some level of a digital footprint somewhere on you. The question is how do we continue as a citizen to manage our own digital footprint? And the transformation is real, because when you’re talking about putting sensors in roads and highways and building logistic value and all of those things, there’s so much opportunity. But we are living on highways from what, the 1960s or something in many cases. So it’s not an easy transformation to just be like, okay, we’re going to add hundreds and thousands of miles of sensors across the country traveling down the highway. It is a major effort, but it seems like there’s never enough funding to do any of it. Operating with the city and making sure that the community is involved is so critical to how we get to something that really allows everybody to thrive wherever they live, work, and play.

Vincent Broyles:  If you think about it too, on the city or municipality level or whatever, that there might be local jurisdictions where they feel they have a right to value from data as well. People driving on city roads using city resources, and that data is also being scooped up and traded upon and has a value to it. And so cities might be able to find a way to increase their revenue and have more money to do things for citizens based on the data that those citizens provide. But right now, there’s no framework or guidelines or anything to not only not force that, but to not even do it, right. It’s all, it would have to be single negotiation between a city and a big company that trades data or something, right? There’s no standards around that on this is what you do and then could be scaled to cities all over the world.

Melyssa Barrett:  Yeah, it’s an interesting challenge. So it is awesome to have you join me. Any last thoughts on where we should be going or maybe a challenge or call to action to people? I know if you have a refrigeration issue, you should call N Javi, right?

Vincent Broyles:  That’s right. I think that, I wrote an article recently that said that one little piece of it said that there’s a huge hurdle that people in the industry 4.0 arena anyway, in the narrow AI arena, people need to begin to trust ai. There’s no way that there’s all these efficiencies and optimization and energy savings and carbon reduction that we could do if we started to trust and implement AI in those areas. And I think a huge barrier to adoption is people don’t trust it. And that’s, I think a lot of that is just familiarity, education. And I hope that people will start to trust it more. If you trusted driving down the road in your car, let’s trust it to save some energy in a grocery store or a refinery or whatever. It’s not this boogeyman. So that would be my call to action. Start trusting the advances that are out there. Don’t be afraid. Open your eyes and your imagination as to how much better these areas anyway can be with the application of AI and in the cloud and software.

Melyssa Barrett:  Yeah. That’s awesome. Awesome, awesome. Thank you, Vince. It has been a pleasure.

Vincent Broyles:  Yeah,

Melyssa Barrett:  Thanks for coming on and chatting with me on the Jolly Podcast. And we look forward to hearing more from you and the data institute along the way, and certainly blessings to n Javi and all the work you’re doing in that space. I think the more we can do, the better our world is. Anyway, thanks for joining me and we will let people know how to reach you as well. Enjoyed, and I look forward to talking to you more.

Vincent Broyles:  Alright, thanks Melyssa.

Melyssa Barrett:  Thanks for joining me on the Jali Podcast. Please subscribe so you won’t miss an episode. See you next week.