Transcrição completa de Can technology help to rebuild after disasters?

helping the American Red Cross. Because I think sometimes people always think about the physical disaster, but they don't think about the supply like blood supply. And, "Can we predict how much food that might be needed in a specific disaster area or water?" things like that. So it's really, really great to know that we work for a company that makes that a priority. (06:57): Yeah, and I quite like how we're not just encouraged to use those days as a sort of standard charity thing, "Go and work in a food bank or go and volunteer to do something." We're also encouraged to use our expertise to go and support charities and help organizations with technical challenges that they might have. I just think that's such a cool thing for us to try and do. It makes me feel quite proud to work for an organization like that. (07:20): Agreed. Big tech companies are doing what they can to leverage their expertise. But it's not all about providing aid at the point of disaster, especially when we're talking about rebuilding society rather than just disaster relief. Longer-term challenges emerge that would stretch even the biggest tech organizations. One of those is education. Atish Consalves is the edtech lead for Airbel Impact Labs, the research and development arm of the International Rescue Committee, which was formed by Albert Einstein in World War II to aid refugees. (07:54): Over 250 million children are out of school. Over half of those are in crisis-affected countries. When we think of disasters, we think about interventions like food and shelter and protection. But if education is disrupted for students as was in, let's say, things like the pandemic or in a war or in a natural disaster, that learning loss that happens because of that disruption, it takes years for kids to catch up. In many cases it's too late that kids will never return back into the system. So you've lost an entire generation of kids from that disruption. (08:27): One of the things the group is trying to look at is what solutions are out there, which can actually scale in very challenging contexts. There's a couple of different approaches we are taking. The Venezuelan crisis has been going for a few years, and the response which IRC is a part of is looking at the displaced Venezuelans who are in Colombia. And so there's a large number of refugees and migrants who've fallen behind by a few years. (08:51): Because of displacement, we've been building out a very simple chatbot-based platform that allows them to catch up in a bite-sized format on devices that they have access to through their caregivers or through their community centers or schools. It's using essentially WhatsApp in Colombia. It's using AI, so artificial intelligence, to interact with the students. So they are able to ask good questions like, "Could I continue where I left off last?" So it uses NLP, natural language processing, to be able to interact with the students in a more natural way, but it's also personalized to

their needs. (09:26): It's gamified. It uses just very simple audio-based instructions. At the moment they can use it together with some other learning materials as well. So it's very much integrated into the curriculum. I think what's really interesting and exciting about this program is that it's using very simple, low-tech tools and it can be scaled. Because a lot of the challenge in that tech is that a lot of the solutions which are there are difficult to scale in certain contexts and requires some type of hardware or software engineer. Here, what we're trying to do is try to come up with solutions which can work on devices, on platforms that people already have. (10:00): We've been now testing it with about 1,000 students in two regions in Columbia with a goal to really scale it up in many more regions and apply more rigorous levels of research to see whether... on the impact it has on educational outcomes. This concept of using chatbots and AI to interact with students is now being used in Jordan for supporting students with mental health. It's also being used in Nigeria to support teachers as a job aid. (10:31): I think that's such a cool idea, isn't it? Using chatbots and AI to meet people where they are with what technology they have. It's really quite exciting, isn't it? (10:41): It really is. I think it's an excellent idea, because what they're using is so accessible to all versus it being so isolated technology within a few areas. I think leveraging that, those pathways, is so important for education and awareness and also being able to reach everyone when you need to. So I think it's a great idea. (11:02): Just the personal story. This may get cut out, but when I was in high school, we had a hurricane hit. I talk a lot about hurricanes because we were affected by them so much. All of our textbooks, they had instructed us to put all of our learning materials in the library thinking that it would be safe. Well, the hurricane came, tore the library apart, and we had lost all of our textbooks. (11:23): Oh my gosh. (11:24): So we literally didn't have education materials for a few months until the publishers could basically send everything back to the school new. (11:33): Wow. So you just had to wait for new textbooks to arrive? (11:36): Yes, we did. Everything had to be... I mean, it put a lot of pressure on the teachers- (11:39): Oh, my goodness. (11:40): ... And back then we didn't have the services that we do today with textbooks. Obviously that situation would've went very differently if it was today. But absolutely, if there's a way that kids have access to a text service like that, it's very beneficial. (11:54): This must have happened during the pandemic. There must have been students that had been out of school at the wrong place at the wrong time, or maybe a new curriculum or maybe they started learning a new subject. They couldn't get into school to pick up any materials. So, thank goodness for the internet. (12:11): Anyway, I guess helping people with their long-term prospects for success is critical, and finding great partners seems to be a key to their success like Airbel. Sometimes those partnerships between large organizations like HPE and the American Red Cross, but both Hewlett Packard Enterprise and Airbel were keen to stress that they are increasingly targeting smaller grassroots organizations. But why would large organizations want to work with small partners rather than leverage their power with other organizations on a similar scale to their own? (12:39): We want to support tech startups that are nimble and that are pushing the boundaries to address these global issues that we have. That's really the foundation of our HPE Accelerating Impact campaign. One, we have a focus on diverse startups on the belief that with these startups, they are really on the forefront of innovation. These founders are the ones with proximity to the issue that they're trying to solve. (13:06): There's a cross pollination of ideas and innovation. It gives us as a company and our team members the opportunity to test new capabilities, to co-innovate with these startups, and to do things that they might not usually get a chance to do. It's that freshness in being able to innovate that is a ripple effect for us as an organization in terms of how we think about innovation, and to continually be innovating. (13:32): An example of an organization that we helped, accessSOS. They are trying to make emergency help accessible to people with disabilities. And so you think about it, if there's a earthquake where you live, someone who's deaf won't really be able to call 911 and have the conversation that they need with emergency services. The founder of this organization, Gabriella Wong, founded it because of her proximity to the issue. Her parents are deaf. Recognizing that her parents would not be able to get the emergency help needed during a disaster or otherwise. Again, the innovation came about because of proximity to the issue to solve an incredible need. (14:17): There was a quote that I really like from a person called Clayton Christensen. It talks about how people don't really want to buy a drill bit. They want to buy a hole. When I think of what small startups are doing, especially ones with lived experience, they're solving for the hole and not trying to sell a drill. Philosophically it's important, but also an innovation is important. Because again, we will discount a huge swath of innovation if we do not focus on smaller startups, especially diverse startups. (14:54): Sounds really interesting hearing Fred talk about how working with diverse nimble groups is a bit of a two-way thing. I really liked his analogy of, "People want to buy a hole and they don't want to just buy a drill bit," which I think it is quite interesting. Do you think there's a tendency for people to focus on the solution and maybe not a problem? (15:12): Yeah, I think there's sometimes

this urgency that comes across when there is an issue. It's like, "We have to fix it right away." Sometimes it's a bandaid to a much bigger problem. But I think when you start to add these elements in of different perspectives... We talk about all the time how important diversity and accessibility is, especially in technology. When you start to add that influence and those experiences into the equation, I do think that you become then the solve for a solution. It's not just a bandaid anymore. It's more of an overreaching success in that matter. (15:53): It's a similar story with the International Rescue Committee. They obviously partner with large organizations, but working locally is increasingly important as well. (16:02): International NGOs and the UN have been talking about localization for many years. It is part of IRC Strategy100 to not parachute that much, but invest in systems, invest in local partners. At Airbel, we are doing it in two ways. First starting with ourselves. IRC is headquartered in Europe, but more of the Airbel team is actually based outside of New York. We have quite a big team in East Africa, in the Middle East as well now. We are trying to diversify even where we recruit and where our teams are based, where our partners are based. (16:38): I mentioned our work in Nigeria where we are working with and through local partners. Lagos has an incredible technology ecosystem. But Nigeria's a big country and in the northeast where there's large displacement of populations of where the IRC works. There's less technology players there. So, our role has been to incentivize some of these really interesting, exciting technology partners who normally work in places like Lagos to work together with us. In some of these humanitarian contexts where it's let's say, a bit more dangerous to work, where the connectivity is not so great. So, we are essentially running an ed tech incubator there. (17:16): That's another way through which we are localizing, is ensuring that we have the right partners on the ground to understand the problems, and then who potentially also understand what potential solutions exist in that space as well. Our role is much more around investing, bringing in specific expertise around design, research, behavioral insights, technology. Connecting to global players, coordinating, sharing best practices and research across different contexts rather than being the direct implementers. We try to find partners who are as local as possible and then as global as necessary. (17:56): There's a phrase which both Atish and Fred use when we interviewed them called, "Parachute aid." It refers to Western organizations coming in and basically providing solutions from above. Understandably, that's now thought of as a bit, well, patronizing. Working collaboratively is very much seen as the way forward. In fact, the UN actively encourages aid organizations to work this way. (18:19): It does make sense. Obviously, aid organizations can only do so much in areas where the basics needed for a tech solution just are in place, like connectivity or electricity. So how do you work in those kinds of conditions, even with local partners? (18:34): In many contexts we work in, let's say sub-Saharan Africa for example, there is very poor connectivity. In northeast Nigeria where we work, the power grid is pretty much knocked out. Our priority there when looking at the barriers and then looking at the solutions is to map out solutions which can work in low power, no power situations. If they do require power, as most ed tech solutions do, that they have all alternative sources of power. (19:01): We are working on a talking book solution there, so it's very simple. It uses normal books, but with a special printed ink, which a very simple pen can recognize, and then make that content on the pages of the book more interactive by providing some sort of fun activities around it. But the pen is charged through a solar. It can be charged with solar power. (19:24): In terms of connectivity, we look at solutions which where the content can be offloaded, or offline accessible on the devices. But we are also looking to partners where connectivity is needed. We are living in an increasingly connected world. There are partners, technology partners, that we try to work with to ensure that there's at least some level of connectivity or some level of bandwidth that we can use. (19:48): We partnered with Meta to get WhatsApp messages, for example, at no cost to all our learners. But we are also exploring connectivity solutions with partners like Cisco. In the future, we could look at partnerships with the likes of Starlink, for example, to reach connectivity to places where you don't have any infrastructure set up for that. (20:09): Now, with the best will in the world, there's some areas that aid organizations just can't work in or get access to. One of those is war zones. When things are moving quickly, you don't know where people are going to need help or where they will be in order to provide it. Ukraine is a great example. (20:29): When Russia invaded in February 2022, over eight million Ukrainians fled the country and another eight million have been displaced within Ukraine. That is just an astonishing number of people within a year. That's more or less the equivalent of the state of New York, including NYC, up and leaving their homes. Some of those people were already internally displaced following the war in 2014. We heard earlier from Valerie, the refugee living in London. She was one of them. (20:58): My name is Valerie and I'm from Ukraine. I'm the growth business development and sales executive in IT for more than 15 years. I worked in the rockstar companies in Ukraine such as Vodafone, Turkcell. Worked for international IT companies as chief growth officer. And then I started my business, strategic management consulting company in IT. We used to help Ukrainian startups

to enter European market, and we have done women in tech programs. But when the war started, I had to flee from war with my two children to Lithuania. I've been waiting for the documents to come to the UK. (21:47): Were you in Ukraine in January this year? (21:49): I can have to step back to the 2014- (21:54): Of course. Yeah, 2014. (21:55): Yeah, because we lived in Donetsk, the city which was occupied by Russians in 2014, so our fleeing from war started there. I took just my bag and two children, and we left the city. We didn't know where to go. And so I had to start my life from a scratch in 2014 in Kyiv. Now also as we did in 2014, I simply took a suitcase and we left because Russians were bombarding Kyiv. There were some fightings in the street of Kyiv, so I decided that it's very hard for my kids to live in such conditions. It took us more than three days to arrive to Lithuania, and then just one ticket from Venice to London to get here. (22:55): The thing is, Ukraine is an absolute hotbed of tech enterprise. It was probably the most scientifically and technically advanced state in the Soviet Union. That enterprising spirit is still around. Ukraine and its tech founders were pinned as a unicorn factory a few years back, spawning startups like Grammarly, GitLab, airSlate, and Preply. As well as a massive dev and support outsourcing industry. In fact, interestingly, Ukraine's IT industry has grown by 23% over the course of the war, which is pretty astonishing. (23:28): That culture of problem solving and lateral thinking has spawned a huge number of projects to help protect and rebuild the country. Even in situations where it's impossible for traditional aid organizations to step in. Two of those organizations are RebuildUA and UaDamage. (23:46): My name is Oksana Simnova, and I am project manager of RebuildUA project. Our project was founded at the beginning of the war by two partner companies, SmartFarming, and Vkursi Zemli. Both of these companies are working in agritech sector. (24:06): The main goal of our project is to help our country to go through the hard times now. We try to help our country in damage assessment of the settlements. We try to cover all the damage settlements in Ukraine, and also we are exploring some new areas where we can be more helpful, more useful for our country. (24:31): When the war begin, more of our employees started to volunteer. But after several weeks we started to figure out how we can be more efficient, be more useful in our helping. Considering that SmartFarming has more than eight years of experience in aerial mapping and drone shooting of the territories for Ukrainian agricultural companies, and Vkursi Zemli specializes on processing open data, we came up with an idea that we can collect and analyze data of the destruction of the damage building. We also started from processing satellite data, but then we switched to the drone shooting, because satellite data was in limited availability and

low precision. (25:30): My name is Vitalii Lopushanskyi. I'm a CEO and co-founder of NeuroMarket. This is an app store for neural networks. During the war, we founded the project UaDamage. We started to use our expertise of computer vision and machine learning to annotate huge areas. This help with neural networks. We don't know how to shoot, but we know how to think, how to use artificial intelligence. So we saw this is... We research list of cases, how artificial intelligence can support and help for our country in current conditions. (26:07): We found one very good case. It was used by Americans after one hurricane. They annotated with the help of neural networks and satellites images, they annotated a huge area. I realized we can also do that. So I contacted CEO of that project. Unfortunately, the technology was closed because it was commercial project. But he explained me the basics, what they've done. And it inspired me to found our own project and to do it for Ukraine. (26:39): In case you think that these are companies operating in relative safety, this really is tech on the front lines. (26:46): I'm located on the south from Kyiv, seven kilometers from the south. So yeah, I can see all, everything what is happening. Drones fly, missile fly, so we can see everything. It usually happens under about our house, unfortunately. But in the beginning of war, in the very first few days, it was shock for everyone. Because I woke up at 6:00 in the morning and I heard blows, and I saw a lot of military actions around me. First of all, the first day I asked my family to move out. I grabbed everyone, everything, and they moved out on the second day. (27:24): How exactly do these two projects work? What's their story? (27:29): Mariupol had a lot of destruction. A lot. It was a huge case for us, big start point for us to do this for Mariupol. (27:37): And it was on the shelling. (27:42): We realized that we need to show to everyone, to all over the world, what is the level of destruction. Unfortunately, we couldn't use to show it on satellite images because it was closed information. We cannot share it. But pre-test data in vector layers, we could show. This is what we have done in... A first step for UaDamage. Processing Mariupol and showing to everyone the level of destruction. (28:07): Yeah, and then we share the results with local government of Mariupol for free. (28:13): It was a huge challenge to us. In military time to get the satellite data, this is challenge. But I contacted a list of companies. I remember Microsoft, it was the first company and they answered to me, "We have data set which was pushes for humanitarian purposes for people so they can move out to plan the road back, road from the Mariupol." (28:35): We use this data set, and we successfully run pilot project, analyze the area. With the help of neural backup networks, we can identify the buildings the layout of the building, of each building on the image. Then having data before and after destruction, we can compare. Compare and see the level of destruction, and then add it to the map so everyone can see it and use it like a vector without images. (29:09): This is a really interesting case. You have a company in a war zone using AI to analyze satellite imagery to assess damage. And another using drone tech developed in agriculture to assess and log damage to buildings in order to help restore normality later on. That's pretty amazing. (29:25): Yeah, absolutely. And it is a mammoth task. It's estimated that 150,000 buildings have been destroyed in Ukraine so far since the war started. Being able to map and assess large areas using whatever technology you can bring together is absolutely vital to making progress in rebuilding. The fact they worked together really shows the power of collaboration and partnership, because they couldn't work without each other. (29:51): To be honest, the neural networks, they didn't do everything well because the diversity of cases is huge. So we asked Oksana and RebuildUA to support us to help to validate everything we annotated. So then we can additional train neural network and increase the quality of data processing. (30:14): Yeah. Because we approach the data manually, and we can use some additional information, some additional photos from the drones. We shoot the damaged area or the settlements and get thousands of photos, and then we merge the thousands of photos into one large orthophoto. In the next step, we start to process the data. We digitize manually the boundaries of the buildings, and identify damages. Our approach is more precise, so we can help Vitalii to train their algorithms and improve this technology. (30:59): And then based on this received data with information provided by our other partner, Kyiv School of Economic Institute, we publish infographical reports. And we spread these reports through the mass media to draw attention to the problems of every settlements. (31:28): Wow. That's pretty fascinating, right? (31:30): Yeah. Actually it could work in a load of different scenarios, because the satellite data can be gathered and analyzed from pretty much anywhere. The drone footage can be collected using satellite internet and solar charging in a lot of cases. It's absolutely not foolproof, but it's an amazing way of using lateral thinking to provide solutions to help rebuild society. We've covered tech to help people at the point of need. We've covered tech to help rebuild, but we still need to talk about tech to help prevent the fallout from disasters. (32:01): This is one which both HPE and Airbel talked about as being a key pillar of their work. The idea that prevention is better than cure. That's not necessarily saying that tech can stop earthquakes or convince people that war isn't the answer. It's saying that by preparing people on the ground and predicting disasters, you can help people ride out the storm. (32:22): Obviously, the company

that builds supercomputers and the NGO providing education over the airwaves are going to have slightly different approaches to this. But the core belief and principle are the same. For Airbel, prevention is much more about helping teachers in high-risk zones get ahead of the curve. (32:39): Research has shown that for every dollar you invest in preparedness, you have a tenfold return on mitigating the impacts of the disaster when it hits. What we've been trying to do now is looking at methods to anticipate disasters in some cases, particularly around natural disasters. Using things like AI and looking at climate models to see whether things like floods are coming and what can we do in terms of preparing school systems, preparing teachers, preparing communities for this upcoming disruption. Whether that's having early warning systems that can then impact how these systems can become more resilient that mitigate the impacts of when the disaster happens itself. (33:24): The longer term idea is to invest in systems so that IRC doesn't need to be there on the long term. A lot of the work that we do in investing in systems... So if it's education systems, whether it's even around things like policy and strengthening systems around how our school systems can recover quickly. Looking at how best to invest early in education, literacy, numeracy, but also in things like social emotional learning and play-based learning. (33:51): These investments that happen over years can have then this longer term impact that when disasters, which especially in context where disaster are protracted, will have a significant outcome in terms of learning retention and reducing, let's say, school dropouts for example. One of the big challenges for the group is around reducing out-of-school children. (34:15): All of these pieces which we do around preparedness and investing systems, are things which will have an impact when there are additional disasters. In many contexts that we work in, you also have complex disasters. For example, recently we saw with Syria you have the war which has been going on there, and then you have an earthquake on top of that. Some of the work that we have been doing there, for example, in the region around play-based learning, around social emotional learning, some of that work could then be deployed very quickly to the programming around the earthquake as well. (34:47): For HPE, it's all about leveraging computer power to predict the future. Because if there's one thing computers are getting much better at these days, it's predicting the unpredictable. (34:57): But the pre part of a disaster, I think that digital transformation and technology has such a crucial role. I think about access to data. I think of, related to that, street imagery, connected devices, and earth observation technology. I think of improvements to capacity that allows us to process and analyze this data, and for us as Hewlett Packard Enterprise looking increasingly towards the edge and what can be done there. (35:29): We work with many meteorological agencies across the world. India, for example, Australia another one, Singapore recently. One of the organizations that we have a chance to work with really closely is the National Center for Atmospheric Research. NCAR, for short. They have used our technology to better predict wildfires. Wildfire behavior is heavily influenced by many factors. It's influenced by wind, it's influenced by humidity, influenced by terrain. Influenced by the vegetation, and all these micro factors affect our ability to predict, and in so doing contain wildfires. (36:08): NCAR, they're harnessing latest advances in science and supercomputing, which we help with, to really drive insights from large, vast amounts of data. And very different data. Vegetation data from satellites, to national water models and outputs that we get from there, to data on terrain, and even ground level moisture data. They combine all these things together to see how it affects our ability to understand where wildfire risks will happen, and to really localize it. (36:48): We've been able to help them so that they've been able to do it as little as a half mile. They're able to get the level of detail, which really helps the prediction of which areas are at risk of wildfires, and how our first responders can more quickly respond. But this is the exact type of problems that supercomputers were built to solve. And to help forecast and enable us to do a better job of predicting where disaster would strike, and increasingly narrowing down our accuracy of prediction. (37:22): Absolutely fascinating. You can really see how these technologies from across the spectrum can start to intersect. Fred's talking a lot about IOT and connected devices being used in conjunction with street views and satellite mapping, which intersects really closely with what DamageUA and RebuildUA are doing. Meanwhile, Airbel and the IRC are using similar data to prepare society, especially in the education space for the predicted disruption. It's definitely an exciting future. (37:51): It certainly is. Where next for our guests today? For Vitalii and Oksana it's about scaling up and overcoming the logistical challenges they face before looking to their next big challenge. (38:06): One of the biggest challenge for us is the ratio of the capability of our team to the number of objects that require to be analyzed. We have 20 people. Eight of them are pilots and 10 of them are GIS specialists that annotate the data. When we started to analyze Irpin, it takes for us almost two months because it's very large area. (38:41): We have very limited period of time to fix the destruction, because people are starting reconstruction by their own. We plan this year expand our team, and we require more equipment, more drones. And we plan to attract some regional teams of pilots that can help us to cover the all territory of Ukraine. Vitalii helps us

in automation, the process of digitizing. It's a very good cooperation. (39:18): I think together we can collaborate and annotate everything much more faster in case of increasing capacity of drones. In addition, I want just quickly to add, a lot of territories are right now dangerous for agriculture, for growing food- (39:35): For growing everything, yeah. (39:36): ... any kind of food. Yes, yes. That is why those territories should be demined, should be clean it up with the special devices, special technologies. (39:47): Yeah, but now it takes tens of years to demining all the territories of Ukraine. Tens of years. Now we try to figure out is the better approaches to do this, because for demining shooting, you need to use some specific sensor, LIDAR and infrared. (40:09): This is our next challenge right now, because this is really huge program, and need to be done from different angles. Shooting high quality images by drones, by [inaudible 00:40:21], and processing it to be a neural network will help us to do it faster. And accelerate it to do demining, not in 10 years, but in two or three years. Let's be optimistic. Right now we are working on annotating bomb cutters, and linking this data to pedestrian register, and then to ownership of property, of land property. So territory can be properly... Demining processes can be properly estimated and prioritized. (40:51): That is quite amazing, because mines especially are quite dangerous for decades after any war. So yeah, any tech that can help that is quite a big deal. At the moment, I think it's people with sticks and metal detectors and things like that. So yeah, if they can use technology that could really change the world. For Fred, it's all about continuing to invest in high-tech solutions and diverse partners across the spectrum to change the face of disaster preparedness around the world. (41:18): I think on one hand it's really leaning into the power of technology, supercomputing for example. How can we continue to develop world-leading supercomputers to increase the speed of delivery with our supercomputers, and to advance research because of our supercomputers. Like you said, making sure that different regions and communities get to benefit from the technology that we produce. With our frontier system that we've created for Oak Ridge National Laboratory, that is an example of how we're really changing the game with supercomputers. We are excited to do more, and I anticipate HPE continuing to be a leader there. (41:57): The other aspect is something that we talked about to make sure that we do not overlook innovation ecosystems. We're increasingly looking at how can we support diverse-led startups that are working in the climate tech space, for example. That are enabling more clean and affordable energy, and that are helping both communities and enterprises transition to a more sustainable way of living and operating. And so, taking really a whole systems level approach. And us

as a tech company enabling the right kinds of partnerships, enabling the right kinds of innovations, and enabling the right kinds of insights throughout the ecosystem. (42:40): For Atish, it's all about continuing to innovate and overcome the challenges they face in getting tech out to countless children in need around the world. (42:51): A lot of edtech solutions will require a base level of infrastructure. So, the availability of internet, the availability of power, the availability of devices. Which isn't the case for a lot of context we work. And so we need to work around those challenges. (43:04): There's issues of digital literacy, especially as we want more school systems and teachers and educators adopting these. There's a lot of work to be done around bringing teachers along the journey. It's not about replacing teachers with edtech. It's about a different role, in some cases, for teachers around facilitating and supporting the students. It helps them support. (43:23): In our cases, for example, we have teachers sometimes teaching a classroom size of 150 or 200. So it's not about eliminating the teachers for sure, but it's about supporting them to support such a large classroom size. There's both a techno-optimism and a techno-pessimism barrier to solve. There people who are very excited about this stuff without fully understanding what it'll take to implement a solution like this. There is techno-pessimism, so people just don't sometimes believe that these kind of solutions will work in their context, rightly so in some cases. But there are definitely opportunities to implement them with some tweaks and with some better design decisions. (44:04): I think the big investments are then at the policy and advocacy level. So, we have been also advocating for better investment in connectivity. There was a large declaration last year led by UNESCO and a few other organizations called the Declaration on Connectivity. Which said that as... This was during the pandemic, but as more was moving online, then we need to ensure that there is a minimum level of infrastructure connectivity starting to be seen as a basic human need. Without that then this education layer is also not available to them. (44:40): For Valerie, who inspired this episode, the future is definitely looking bright. She wants to play her own part in helping to rebuild it one day. (44:48): Last nine years, everything goes not according to the plans. I learned to be more resilient, flexible, and adaptive to many things. And work out and figure out very difficult situations in life. Currently, I'm looking for a C-level position in the UK company, and I have many interviews with very interesting companies. I have received an offer for chief executive officer in the American IT company. If there would be an opportunity to have a bridge to Kyiv, I would love to do this. I think there will be those people who will reconstruct and will help economy of Ukraine to raise and flourish. I do not give up. I never give up. (45:51): It's so good to hear that things are turning up for Valerie, and best wishes to all of our guests today. Keep doing your great work. That's it for this episode. Next time we'll be looking at the ways we can make more energy as global demand grows and grows. (46:09): You've been listening to Technology Untangled. We've been your hosts, Aubrey Lovell and Michael Bird. A huge thanks to our guests, Valerie Kuzmenko, Fred Tan, Atish Consalves, Oksana Simnova, and Vitalii Lopushanskyi. You can find more information on today's episode in the show notes. This is the second episode in the fourth series of Technology Untangled. Do make sure you subscribe on your podcast app of choice so you don't miss out, and to check out on the last three series. (46:37): Today's episode was written and produced by Sam Datter, Michael Bird and Aubrey Lovell. With sound, design and editing by Alex Bennett. And production support from Harry Morton, Alison Paisley, Alysha Kempson, Alex Podmore, Alyssa Mitry, and Camilla Patel. Technology Untangled is a Lower Street production for Hewlett Packard Enterprise.