Hello again. And welcome to the planet beyond Podcast, brought to you by Fu, the leading partner in delivering geo date, from the greatest subs depths, right space and hosted by me John Ba Pitt. In this episode, we're continuing our discussion about Ai, In our short episode with Mo D ba, we looked at the environmental cost of Ai. In this episode, we will be exploring how Ai is already impacting the physical world. Since the launch of chat Gp. Ai has been a constant theme in the news. But large language models are just 1 way. Ai is being used. In our daily lives. From data processing to climate modeling. Ai is going to become an important part of real world decision making. It has the potential to help us prevent disasters, but also be better prepared for when they arrive. Today, we're talking to 3 experts who are steering how Ai is and will continue to be used in various areas of our lives. Can Ask each of you to start by introducing yourselves? Shall we start with you? Thank you very much, John. Hi, everyone. My name is Erin American. I'm I added for the office of innovation at Uni nsf. Thanks for having me. My name is Mar Ko. I'm a chair in digital economy and professor at Q business school in Brisbane, Australia. Pavel. I'm a global director innovation. And in this role, I have an ultimate pleasure of working with a few growth product development community, engineers, data scientists, digital technology leaders. Much of what we hear about Ai is scary. Election disinformation, and deep fakes are already here right now. We'll talk a little later about how we can combat some of these challenges, but let's look at an alternative first. What would the world look like without Ai? John, I I love your provocative question after. Everyone seems to be focusing on how Ai is going to destroy their world and talk about dystopian scenarios But it's important to highlight that Ai has been around for decades. Right? There's been a a recent wave in what we call Generated Ai, but our artificial intelligence technologies have been helping us run the world for for decades now. And so If you ask what the world would look like without Ai, we would have grid locked airports, very slow supply chains. Doctors who do not know what's wrong with us and don't know how to how to respond to it. It'll be much harder for us to learn foreign languages. There's so many applications where Ai is already being used So we've been living with Ai for a long time already, and we will continue to rely it. What are those big challenges that we need Ai to help us with? I think what we are seeing more and more is the impact of climate change, obviously changing populations, young people growing up in environments, which are. In many cases very risk threatening, but also aging population in some other parts of the world old. And the growing inequality and the growing digital divide, I think, also very important to mention. So a lot of uni apps work is obviously with children and young people because we are the United Nations children's fund, But for us, it is always implicitly thinking about future prepare next generations for the world that they would. Be living in. And in that sense, like my role allows me to see what the concerns of young people today are. And it's always, like, thinking about how we want that oral to be and how technology should be used responsibly to allow that world to be better. Right? So this misinformation and misinformation or they fix is is a very real risk that comes from January Ai. But there are other things like bias or discrimination that like, it it's embedded in many side is already. It is part of the world. Ai just can make that. However, for me, Ai and digital other emergent technologies also offer a very real potential to combat lots of those challenges. Right? Make people's lives easier, make people healthier fair, contribute, like, be a very useful tool that we can use to make. Our lives better. So in my, I'm always thinking know, how can we make that useful. How can we make that car more helpful for building the world for humans. Is it a bit like the news? That they love to focus on all the negatives. And very occasionally, out pops a lovely story how humanity is getting on well together. An Ai, as you just said, it's been doing a good job for ages. But what we focus on are those new, different risks Can you imagine the sound running a headline saying, Ai making the world a better place? That's not a quick bait headline. Yeah. I really like what Mark what the point you made because, I I really see this Ai revolution as any other digital revolution we had in the past. In in eighties when all the personal computers scaled up, We also were very afraid that it would take the world, and it inspired many movies at that time. But generally, we can't imagine the life without personal computers right now, and and at this moment, we're climbing this another innovation, s curve, and without this s curve, we actually not be able to accelerate all the energy optimization, climate model, creations, infrastructure modeling, which we do need in order to survive So to me, although, I I, of course, am worried it's what will come to the future and probably even more worried what the future would look like if, we do not have Ai. I want to talk about the driving force behind Ai, data. Depending on the project, we are sometimes confronted with too much data. In other cases, not enough data or or well, not the right type of data. So what issues do we face working with the data we have? If you think about it it's not really about the data volume. Ai helps us to get the right. Data, and and you need the right data to make the right decisions. In the past we've been all fascinating with big data. Then we realize that we actually don't want big data because it's too big. We would like to have very narrow insights, which helps us make decisions. So from my, part of the pond, Ai is really driving autonomy help, which helps our robotic vessels, drones underwater vehicles to map the the whole planet without an environmental impact. Ai drive these transformations in the whole of the industries which we operate, Ai helps us run analytics over this data, which we collect and help our clients to build infrastructure, build road builds rail, grow the energy generations such that it does not cause any environmental impact and quite opposite, that it actually stimulates the growth of Biodiversity and it stimulates the the positive feedback on the world because generating green power, it's not green enough anymore. It needs to generate green power and stimulate biodiversity. There's I offer Pa reference to write data that shift from from big data to to write data, I wanted to take it even further and and make data smart and talk about smart data. And and and in order to talk about it. I wanted to share a, a deeply personal story of me getting stuck in in a forest in the woods, you know, hours away from, from humanity from civilization. I occasionally go for for long runs. And by long, I mean, anything between 4 and maybe 10 hours of just just running so forests. And where where I am in Australia, there's, quite often or or every year in Queensland, some back back burning activities are being performed. So, you know, a bit of, the forest is is being burned following the, sort of the first Australian traditions to to protect us from large bush fires. Now, there are various agencies, government agencies responsible for that, not just 1. Depending on, you know, which part of the state it is and who owns a particular piece of land, they might be responsible for this activity. Now put yourself in my shoes as runner who runs through a number of those areas, and and needs to find out whether there's any areas that are close. Because of back burning because, you know, that's that's my safety, and I don't really want to find out 4 hours into my run that I cannot continue running because of of of back. So what I do is I try to find data I tried to go to every agency and find information about what's happening. But I I failed at least once in, you know, in such effort and I did end up stuck in the woods and, you know, having to to go back with very little water. And that's because that data is not smartly coming together. I have to find the data. I would want the data. I would like the data to find me. And that would be smart data spatial organized once, you know, data that knows that if there's an individual, traversing the woods, if you will, then we need to combine data from various, entities, but that refers the same spatial area and present it to this person. And obviously, this is a very, sort of retail exam if you will. An individual going for iran. But the very same situation will apply in in mental other scenarios where we just need to bring together data from from various organizations to help with decision making. The So Pavel, I love your right data. I wanna turn it into smart data. I was just gonna say, I just love that phrase. I want data that finds me that it naturally comes together to benefit the receiver it's a lovely concept and a lovely way to frame it. We also have many, exam. Was from less retail industries, where we see that in the past, we used to provide maintenance advice to roads rail or or cable owners, and these were more based on ad hoc inspections. And right now because of the change in the data acquisition technology and because of the change in the way we can model the the the assets and surrounding environment, we can more embark on the journey of continuous mapping continuous modeling, monitoring, predicting what will happen with this assets in the future, and indeed, provide this data, which finds the asset owner, and helps design the the maintenance programs, which will need to happen in the following years. Proactive data. Proactive data. Yeah. So Ai can help us join data from many sources helping us under stand spatial events. It can help us analyze local conditions. Can we use it on a broader scale? Could it help us map the entire world? Or is not a step too far? Now so these are obviously John you know me these are topics I absolutely love. There is the saying that we know only 1 third of the planet, and that's that's because, know, 2 third is covered by oceans. We we know it but less. But I would like to challenge this statement because I don't think we know 1 third of the planet. We only know the surface of 1 third of the planet, because there is such a wealth of information, which we have know very little about, which is underground, third and here also because of the growth of Ai and and and a model technology and the mapping technology. Only now, we start doing which which even 2, 3 years ago was absolutely impossible. We can deploy sensors in cities doing which helps us to build a complete free d model of subsurface without any disturbance to the city, communication. And this is very helpful because without this, cities cannot love developing in a sustainable way. And we call it ground Iq to indicate the intelligence element in it, and and we're are also introducing a similar technology for the marine environment and also 2 3 years ago, this was absolutely not possible. And right now, we're getting to the situation that we can nearly will we sometimes refer to it as 2 built an Mri model of this our surface. And I I know for the Physics Gigs Mri, different physics principles to what we do with for acoustics. I know that. But the effect is similar. You end up with a complete 3 d model of subsurface surface, which you can then use to say stay... Sustainably designed cable locations, sustain sustainably designed power renewable in infrastructure. We are expecting so many more billions of people in in in the next years, our current way we growing is simply not mature enough to handle that. Irene, I know a lot of your work at Uni is on using Ai to get a better understanding of the conditions of the earth's, subsurface. Tell us more about that. Thanks, John. I actually wanted to continue just for us. Second. On on Pavel brilliant example of discovering what's on the ground. And uni of example, yeah. Let me describe the situation. In many areas of the world, access to clean water is very difficult. Usually, their, very dry places, well, South sahara and Africa and lots of other parts of Africa. They simply... They don't have enough sources of of water that are easily accessible right away or they are not cleaning So drilling wells on getting access to underground sources of water is super important. That is not just like, oh, yeah. Let's let's build some little, well here and and another 1 there and we will be fine. This is literally a matter of life and death in many areas. Right. If you don't have access to the underground water, if you cannot discover where the that source is, or if you have to dig way too deep to discover it. You lots of people might be crisp. So Uni has supported a an initiative that I think is absolutely brilliant. It's called more water more life. Has been piloted in Mad madagascar Ke and. It's basically they're using Ai for geo planning. So combining different techniques and combining it obvious. But traditional Geo special techniques, to discover where the likely locations of sources of of underground reserve of clean water to to improve access. And we basically doubled the success rates for discovering groundwater reservoirs. That is that is the impact. That is what we can do. And again, it's not about... Oh, I've I've built this very cool algorithm. No. I have saved lives. Yes. Right for. No not not me. I'm not gonna take credit with. But our teams have saved lives of millions of people in and children. Double is an incredible statistic. Rice? Oh, on on another example or another topic of what Uni is working on. Again, putting in people's lives at risk, the... This risk very often comes from natural disaster. Terms. Right? And there are different types of natural disaster so obviously, like, Merrick bush bar as example. Is is and very specific, but cyclical natural disasters such as droughts and floods can be predicted we see quite a lot of industry applications. Come and come in there where... If we know that it's a season where that dropped will call we can map out the area where it's gonna happen or if it's a flood, right. We we can predict not only how many households would be affected how many people would be affected. We can collaborate with the governments to issue early warnings to get people out of the dangerous area. And then if we need to optimize Uni emergency response if we need to say, okay, we will need these manual volunteers in that specific area. That really helps us to to be more effective in responding to natural disaster there's as well as to evaluating the dam or assigning the damage after, after the event there's So for us, like, predicting climate events, predicting, damage areas or or potential risks to to people, really really helps us to reduce risks to people reduce casualties and save children's lives, the early warning systems, Uni uniforms venture fund currently supporting a, a cohort of climate startups, that are... Like, the they're developing localized solutions their development contact specific solutions, which I think is brilliant because they're more accurate if they're based on, on the ground. And they all like, are very keen on health and local communities and I just love the work that all of them are doing because the impact on on their own communities because the impact on saving people's lives is invaluable. I... I'm itching to add to this conversation. What and, John, I hope you don't mind us diving deeper. The the what what power and Arena talked about evo this this image in my head that I need to share with everyone. So when Pablo was talking about, the equivalent of Mri, but for earth. And then Arena talked about the the impact of this more detailed and, you know, more reach data to to help save lives. I couldn't stop by but think that we're reaching that stage where thanks to sensors, thanks to technologies and artificial intelligence that processes all this data. We're reaching a stage where the oceans will become transparent. We will be able to just look through them as if you know, there was nothing stopping us from doing it. And in the same way, the earth, not just the oceans, right, but the ground will become transparent as well. We will, to perhaps some levels see much more than we can see now. But here's a provocation. Right? Now that that we can imagine a world like that. We can imagine scenarios where it's used for good. But also let's think about the value of this information to organizations that might want to exploit minerals, and so on. And suddenly, you know, this they this might have the some some unexpected impacts on, you know, on the society. So I think it's important to us this question as well, You know, once we have this data, how do we treat it responsibly? Who should have access to it. Should it be open or not? I don't pretend to have answers to it, but I think we need to be asking those questions as well. These models are clearly at times beyond what human beings can compute, analyze and... Predict. So surely, Ai could also have the capability of warning us about potential, negative or unforeseen consequences. Is that possible or or am I just being na, That's a brilliant question, John. I think I've I totally agree that Ai is of obviously much better than than humans are predicting many different scenarios and map and thinks at scale like that computational efficiency is what we love Ai for. However, good human judgment or, like, really, really take responsibility. Ai is a machine. It cannot be accountable. You cannot say, I trust the machine because ultimately, that's just the computer. Humans need to be and can troll that needs to be human or reside. And what I love about pavel examples are the examples of of freely brilliant data scientist and engineers on working with technology, right? Using algorithms responsibly, rather than, expecting the machine to be this some miracle cure. Mh. Right? So the technical expertise is to, like, the key component of this Follow up from what you said in and, I I heard this story that even steve jobs. Didn't believe in, machines without control of the human. Apparently, the first imac had a handle because... Mh. Jobs said that you cannot trust the technology, which you cannot throw out of the window. I think this is why the hand voice is there. But even more, John now to your point because you said that Ai helped us understand. And this is exactly this. What we do with this understanding, And this is yet another, topic for a discussion and that's what Mark touched on, because we can use this understanding indeed for good or for bad unfortunately, sometimes. But it just allows us to change the information, which previously was not even considered to be information into something, which is truly useful. And I just have 2 examples in my head. 1 more from maybe Mar area, I spent some years in Australia as well. And I've been exposed to many stories, like, stories from thousands, years old from indigenous people. You know, there were no maps. Thousands thousands years ago. Know that the maps, the stories were maps. Mh. And right now if Ai, we have this unbelievable opportunity to change the stories of people, explorers, stories of divers, up and locks. Into geo special information because they describe where they been and describes have to get there. So the the this is more a people story example. But I I could see a similar example in the world of more geo special sensors, which is maybe closer to my heart, or already started techie. But we sometimes say that or there is a noise in the sensor data. Mh. But if you think about this, there's no noise in the world. The noise is just the information We don't know how to interpret yet. We don't... We don't we say there's no. We say they're are outliers. But this outliers is probably an information about maybe the the malfunction of the sensor, which if we understand, we could actually use to improve the sensor, but Ai helps us understand and change it data points maybe like these outliers. Or people stories into information, which we can then apply, and indeed, there is a big risk how we apply this. But similarly, there are bit risk how we apply other tools or which we also gained in the past 50 years. I have another Steve Jobs quote for you. Steve jobs used to say that a computer, it's a bicycle for the mind. It it it is the most efficient device adding that speed and and allowing us to to move faster. And I think I would expand on this quote, and I don't have such a catchy way of saying that, but just just like we discussed here, those technologies are giving us additional senses. Right? So so I love the conversation about, no noise in the world. The in the the business call when I... Work with businesses. So it's a slightly different space, but but we teach entrepreneurs, to listen to the lack of signals and listen to, you know, what what everyone else ignores because that's where the opportunity sits. And those those technologies are allowing us to turn noise into valuable, right, smart, proactive. However I want to call this this new data. We've talked about how Ai can. Help us predict disasters. But what about our everyday lives? How how might we see Ai influencing the physical world for people living in major cities to make them more sustainable. So John, which you mentioned to we strive to make cities more sustainable. We know that in the next years, there will be even more people heading towards cities and this mega policies which will just grow. And it's by the statistics we have right now, the the construction this in part particularly concrete production is 1 of the key poll in the world. And the we in the engineering reality, we try to really make sure that safety is has the highest standards. And in many cases, foundations are over designed or bridges are over designed. But that's purely because we don't have sufficient data to be less conservative. So so it's it's normal. I mean, we would like to make sure that, infrastructure is safe. And with all these technologies and Ai enabler, which we have right now, we can truly collect the data of an accuracy, which helps us us to design the foundation to d design the bridge, which is truly fit for purpose. We don't need to over design it, and then we can also additionally, merges it to various technology existing these days, which allow us to to optimize the foundation systems files, this type of structures and really get to the point that we can save on the material, which is then 1 of the key producers of this Co2 at the moment. Let me challenge that a little. I think data and recommendations backed by data of that nature. Have been around for a while, But they haven't led to a reduction in safety factors, and therefore cost and therefore carbon reductions. And I would put it to you that the problem has been human beings, not being prepared to take the leap to reduce the safety factor from 10, down to 5. Because of what a computer recommends. No. III do agree on it. So we would never compromise safety. I mean, the industry would never compromise safety and it's good. It's just in the human nature it is to just make sure that we are more on a safe side. There's even this joke without, being offensive to when a engineers who I am as well, if you ask an engineer, how much is pie, they will tell you occupy constant. They will tell you way it's about free, but use for just in case. And that's... And and that's because we would like to make sure that they're the highest level of safety. So, again, it's normal. It's actually desirable. But without sacrificing safety, we can apply this new subsurface modeling techniques and new Ai, generated models in order to provide accurate information about the state of, in this case, subsurface, which would then allow you to understand, truly how this, in this case, political foundation pile of of of a, a wind turbine or or a building or or a bridge, how it interacts with the soil? And how will the soil respond And and what should be the geometry of this particular structure not to over design. So I don't think we ever had these tools, and and because we didn't have these tools. The information we had to design was quite poor, that the the the the accuracy, the error of this information was quite large. And therefore, it's has been natural that we wanted to stay on safe say. I want us to end the conversation by thinking a little about the potential dangers and how we can best go about mitigating them. Is it possible that we're going too fast? Do we need to stop and think? Or is that not possible? And should we in fact be speeding up? In order to achieve the positive outcomes as quickly as possible. I don't think we can afford to stop and think. I think we can we can... We need to accelerate and think more in the same time. So this, again does not exclude thinking, actually thinking more. Mh. But I don't think stopping is an option. If you look at all the predictions, even with global warming, we ordered this are not entirely certain if we can cap it within 1.5 degree, and if we stop, and really, I truly believe that technology technology's is 1 of the key accelerators and key enabler of the new sustainable reality. So stopping it off it is an option, we need to accelerate, but accelerate thinking even with the higher pace than accelerating the movement. I fully agree with Pavel. I think it's not about accelerating at any cost. It really means like, think what you were doing think about the impact, think about, the consequences, but also, yes, like, if you have technology at your disposal, we don't have a choice related to to not use all the tools at our disposal because the consequences of of of the world without technology would be much harsh or, and and have a much more negative impact. But absolutely again prioritizing responsible development and thinking before you leap, read, thinking how you're going to do this, thinking of what needs to be taken into account prioritizes I I feel like I'm repeating lots of the arguments that we've already talked at length today. But this is really, Key a really key message that we should not stop absolutely not, but we should also not compromise safe and we should not compromise human responsibility and human thinking. Please Mari. Sorry for enter Maybe we agree too much with 1 another here. But again so it's saying that I would also like to challenge the notion of stopping in general. Everything's moving. The world is moving. There's no such thing as stopping. There's there's no point of reference a flower that you could stand on and say, now I'm standing. If you stop moving, you're you're basically going back. Right? Everything's everything's running away from you. So like like both powder, Pavel and and Arena said, there's no option of stopping here. This is also not a trade off, not a not a choice. You can move and think. There's it's like I don't skiing downhill. You cannot stop your you're continuously skiing, but you have to be focused. On the right things, and you you want to make sure that you're not falling, You're not, you know, starting an avalanche, unintentionally. So so that's it. We need to keep moving. Well, thank you all for your fascinating insights into this emerging technology. There's there's no doubt that the future is going to be driven by Ai. It has the potential to be a driving force behind a very positive change. At a time, when we need to meet new and pressing global challenges. But ensuring that the development and governance of this technology is done effectively and safely is going to be of huge importance. The growth of the internet and the digital economy of the past 2 decades also brought about major technological advancements, but also, unforeseen consequences. Governments were too slow to bring about regulation to mitigate the dangers. When it comes to the internet and the potential dangers of Ai may far greater, but that doesn't mean we should stop progress. Instead, we must push forward, embrace the opportunities, and reap the benefits with a clear eyed view of the risk. Ai is already making the world a better place in a variety of ways. For making water more accessible, making our building safer, and our city's more resilient. There is real potential to build a better world using Ai. Thank you for listening to this planet beyond episode. If you enjoyed it, please leave us a rating and review and hit subscribe as we say. Until next time. Be safe. Be remarkable. Be the difference.