[Cynthia Mene]
Good morning, good afternoon, and good evening to everyone joining us around the globe, virtually. And to all of you here, welcome to this exciting panel discussion at the World Bank Youth Summit 2025. My name is Cynthia Mene, and I am the Content Co-Lead as Shwetha said. Thank you. This session, we will be exploring how data-driven and digital solutions are empowering youth to innovate for peace and resilience. I will start by having a quick question and discussion with the panelists, and then we will open up to Q&A. So, if you are online, please put your questions in the chat throughout the session. We will get to it. When it’s time for the Q&A session, if you have questions, we will call on you as we’ve been doing. Before I introduce my panelists, I would like to start by providing a brief context to this discussion today. As we all know, digital transformation is reshaping our world and offering unprecedented opportunities for innovation and development. However, without intentional inclusion, it risks deepening existing inequalities. And as one of our speakers, Robin, said, he highlighted the World Bank Change-Makers report. I’m going to just say a few statistics from that. The Change-Makers report mentioned that 20% of youth globally are not in education, employment, or training, with two-thirds of them being young women. Additionally, over 600 million people live in fragile contexts, facing barriers like limited Internet access, where 38% of them are from rural households, unlike 72% in urban regions. And then, the World Bank Digital Economy Initiative in Africa also mentioned that closing this digital divide could help boost global GDP by 13 trillion dollars by 2030. Despite these challenges, we know that youth are at the forefront of driving digital innovations for development, leveraging data and technology to help reshape economies and foster inclusion. So, this panel will discuss practical solutions and innovative models to ensure that digital transformation benefits everyone and fosters a more inclusive and a resilient future. That said, I’m thrilled to be joined by a lineup of incredible speakers who are at the forefront of this work. I will start by introducing our first panelist, Johan Bjurman Bergman. He’s a digital specialist in the artificial business line of the World Bank Digital Vice Presidency, where he’s helping to build the Bank’s country advisory and lending program on AI. He also launched and is leading a cross-cutting program to advance digital transformation in fragile and conflict-affected states. Previously, Johan invested and scaled up programs and companies that use digital technology to build human capital, create jobs, and deliver services to over more than 30 low to medium-income countries. And then, we also have Beverly. Beverly Hatcher-Mbu. She is a Director of Policy at Development Gateway, an IREX venture. As an international lawyer with over 10 years of experience in digitization, Beverly has led projects in nine countries globally, and she leads oversight and policy positioning for the organization’s agriculture portfolio and also shapes key messaging across DG in AI, in digital public infrastructure, and in health. But previously, Beverly worked at the World Bank Group as a legal consultant, and she’s also on the Board of Accountability Lab. And finally, joining us virtually is Sinead Bovell. Sinead is a futurist and Founder of WAYE, an organization that prepares youth for a future with advanced technologies, with a focus on non-traditional and minority markets. To date, she has educated over 500,000 young people, young entrepreneurs on the future of technology. Shined has advised presidents, royalty, and Fortune 500 leaders on AI and innovation. She’s also a regular tech communal on CNN, NBC, and [unintelligible], and she was named as one of the top 50 voices shaping the future by AfroTech and has won the Mozilla Rise25 Award for her work in championing open and responsible AI development. Thank you all for joining us today and welcome. Okay, so we will start. I have a few questions, so we’ll start. So, this first question I want all our panelists to answer. Please, feel free, but keep your response to at least three minutes for the sake of time. My first question is drawing on the Change-Makers report’s emphasis on a tailored approach to different youth’s population, what innovative digital solutions have you developed or implemented to reach and benefit different or underserved youth, especially like women, those marginalized groups? And also tell us what barriers did you encounter and how did you design your solution to address those challenges? Let me start with you, Johan.
[Johan Bjurman Bergman]
Thank you very much. I think the example I would like to share is from our work in the West Bank and Gaza in the Middle East. I just came back from there last week. We had what we call a midterm review mission for our project, the World Bank project there, which is really supporting the IT services industry in the West Bank to upgrade its proposition and to be able to deliver more advanced services to clients. There, it’s really about not necessarily inventing or creating a specific product as the World Bank, but really acting as an enabler for others to do that. I think that’s a lot of how we think about our role as the Digital Vice Presidency, both externally as well as internally as an enabler and a platform to support others… Whether that be governments or our internal colleagues here within the Bank, to really use digital tools as a way to enhance the effectiveness of solutions, improve the efficiency of those solutions, and then really replicate and scale those solutions as well. In this particular project in the West Bank, that really looks like understanding what the main barriers for these firms are, to be able to achieve higher-level and higher-value businesses, to be able to deliver and secure clients. For us, we are supporting them by addressing the skills gap that really exists and the barrier that they have to get the skills that they need to secure international clients. Second, we’re addressing the lack of firms in the market by de-risking the launch of new firms. So, really to grow the pie and grow the market and also grow job opportunities for those people that we help train and equip with skills. Third, we’re providing access to R&D technology, so more advanced technology, which in many cases, these firms do not have the incentives and the opportunity to purchase themselves because either it’s too expensive or somehow, they’re otherwise prevented from accessing this technology. Then fourth, we’re supporting them to professionalize both their organizational structures, their marketing materials, and their product offering so that they then can go out and seek new business opportunities, whether that be in the region or globally. Really, for us, it’s about understanding very, very in-depth what are the barriers that the stakeholders that we’re trying support are facing, whether those be firms in the West Bank, governments in Central Africa, or our colleagues within agriculture or education, and then coming in with specific solutions that can really address those barriers and having a strong rationale for why the World Bank should be engaged based on our comparative advantage as an organization that can really bring expertise, bring financing, and bring a platform to convene partners around these issues. Thank you.
[Cynthia Mene]
Thank you. Go ahead.
[Beverly Hatcher-Mbu]
Great. I got to have my own one, I think. I’m going to be a typical lawyer for a second and answer a question with another question, which is there are two questions I think that we need to be asking when we’re designing meaningfully and we’re designing with young people and marginalized communities in mind is, one, what data do we really need to solve the problem? And two, how can we model and mitigate any risks associated with that. I start there because, and I have an example to back it up. A few years ago, Development Gateway built a dashboard for maternal and neonatal health. The idea being if we can map where maternal and infant deaths are occurring in Ghana, then we can see where the deaths are highest and use that geo-located information to help policymakers target limited resources directed at improving service delivery. We knew going into there was likely to be some sense of some highly sensitive data. So as part of, and we’ll talk about this a bit more in the panel around partnerships, but we thought a lot around what can we do to minimize, how can we make sure there’s a minimum amount of data available for policymakers to actually make an evidence-informed decision around improving service delivery, but how can we protect the most vulnerable? In that case, we used location fussing. So, there’s enough geographic specificity for policymakers to be able to see where the most deaths were taking place. But then, it was not so precise that you could name down to the level of the house or the individual who was impacted. Sometimes I think we overcomplicate digital development, especially in resource constrained environments. It’s not rocket science. If we want to reach underserved communities, we need to meet them where they are. I would leave it there.
[Cynthia Mene]
Thank you. Thank you so much. Okay, over to you, Sinead.
[Sinead Bovell]
Hi, everyone. I’ll try to keep it brief as well. For us at WAYE, we focus on access to tech education and through learning about the future. The big question that we wanted to ask when we were initially founding WAYE is, what do young people, in particular, need to know and understand today about emerging technologies to better prepare for their future tomorrow? And we’ve tried various different approaches to tech education. So, we have our WAYE Talks series, which initially was in person, but we realized we could reach a lot more people by moving that online. We host mentorship days because we realize not everybody is comfortable asking their questions about the future or accessing content online. But then, we found open content using social media platforms where young people already are and consistently reinforcing our message, whether it’s skills, whether it’s understanding how the societal impacts of emerging technologies like artificial intelligence or biotechnologies, or whether it’s what you should be studying today, was the most effective way to reach young people with a consistent message. So, we put together a board. We call them the WAYE Young Leaders Board that help guide the decisions on the content that we share, what stories are relevant? Where are we in this moment? And we try to be as consistent as possible in the messaging that we share. So young people really feel like they know what skills are relevant for them today. How do I navigate the technologies that are coming down the pipeline? I think for some of us, it feels like a freight train. And what other breakthroughs do we have to look forward to or to look forward to in the future? Right now, our audience, I’d say, is about over 60% women, which we’re pretty happy about. We continue to grow our reach and continue to grow our representation. I found even just being a first person of color at the forefront of our organization has really shaped who does feel invited to the conversations. I think even representation, it can be hard to see yourself aspiring in a lane that nobody looks like you. That representation, we feel like has been modeled back in our audience as well. I’d actually say the final thing, it’s one thing, I think, to ensure that young people are educated on the forefront, but making sure that we’re in the background in the policy rooms, educating parents as well, educating educators on what they need to know to shape a future for young people in which they can thrive. So, we really do that two-pronged approach. One is direct to young people, and then the other is the infrastructure from education to parents policy.
[Cynthia Mene]
Thank you very much. Thank you, Johan. Really exciting to see the work you’re doing to use digital tools to enhance the effectiveness of solutions. Beverly, you mentioned about data and how that’s helping to protect those vulnerable populations. And then, Sinead, also thank you for bringing up. Thank you for empowering youth, them with the right skills they need to thrive and building on when you mentioned digital infrastructure. I also want to ask one question again. You have educated over 500,000 young entrepreneurs on the future of technology. How can we better prepare young people to thrive in the digital economy and actively shape digital future? And then, building on that, I want you to also share with us if there’s any foresight-driven curricula or experiential learning model that has proven very successful to either equip on the side of youth, especially young women with the mental skills they need to thrive in this AI-driven labor market?
[Sinead Bovell]
Yeah, and I’ll actually start with the latter part of that question. Strategic foresight is a form of practice that has been used for decades. How do you spot trends and data and understand the complex systems around them? And one thing I always like to say is nobody can predict the future, and that’s not the practice that I’m in, but it’s also not a surprise. So, if you can think about what patents have recently been filed, how have different technological breakthroughs in history traditionally shaped how society has evolved? When you equip people with those skills, they can start to understand how the future may unfold. One of those skills is long term thinking. We often, even within education, study for the immediate unit test right in front of us. We don’t think about how does what we’re learning today, how could that intersect with a different technology or a different society and change how we evolve in four, five, six years, just taking a different horizon. Even just things like “what if” questions. So, what if this happened? What if “X” happened? And mapping out different trends which really build a muscle for long-term thinking. Another part of strategic foresight is cross-disciplinary thinking. We think about school often in silos. You have science, you have math, you have history, but helping students and helping young people to think at the intersection of it. How does what you learned in history and what you also learned in science, how did those interact for example, historically? So, it’s a formal practice. We just don’t really introduce it to young people. I happened to stumble upon it during my Master’s taking a course. And when I finished that course, I realized everybody needs the tools to understand the future so we don’t feel so caught off guard by it. I think for a lot of people, it feels like you’re playing Whac-A-Mole with headlines when you can see different trends coming and anticipate how technology will impact your own job. I actually think that’s one of the best ways to prepare for a future with AI. Instead of being surprised as to how it might impact a career that you’re interested in, if you start to anticipate, how has this technology evolved? How have past technologies, for instance, like the Internet, changed the devices we used. What did those devices lead to? We had a smartphone that led to a creator economy. If we have a tool like AI and we talk to it more, does that mean we’ll probably look at our smartphones less because we have a system we talk to? Those are types of trend lines that don’t require deep technical expertise. They just require more complex thinking. And then, the second part of your question was, how do we prepare people? What are the meta skills for an AI-driven world? Of course, working with AI systems as a hard skill. I put AI with reading and writing. Reading, writing, and working with AI. This doesn’t mean knowing how to code a supercomputer. It’s just understanding the basics of how, its strengths and its weaknesses. But I think the more important skills, I mean, I would bet on somebody who had deep thinking skills and judgment skills and critical analysis skills more than somebody who just knew how to prompt an AI system. Because when AI can give you 10 pretty decent answers, which one are you going to choose? That’s a deep judgment skill. That’s more complex, higher-order thinking. The future of jobs, it’s up in the air as to what AI will and won’t be able to do. But if you flex those muscles of judgment and critical analysis, maybe you don’t consider yourself a finance person, but in a world with advanced AI systems, you might still be the best person to lead the finance department because of your judgment skills. AI does a lot of the critical analysis and the financial number crunching, and you have really good judgment, you know what scenario would be optimal for the company. So, the skills in the AI age, some of them are technical, but most of them are, and I don’t want to say soft skills because I think complex thinking and deep thinking can be harder, but those are the types of the foundational skills necessary to thrive in the digital age.
[Cynthia Mene]
Thank you, Sinead. Good to know that
[having]
judgment skills is really important. Thanks for sharing that having the long-time thinking and cross-disciplinary thinking is really helpful. So, I will turn to you, Johan. Given your work with the Cross-Cutting program within the World Bank, could you tell us how can we imagine technologies like AI be harnessed in such a way that we can breach digital divides? And how can we empower young leaders and entrepreneurs, especially those in FCV regions, to enhance the work that they do? If you could share some use cases or prerequisites, that would be helpful. Thank you.
[Johan Bjurman Bergman]
Great. Thank you, Cynthia, this is obviously the eternal question, how can we use emerging technologies to really help improve outcomes for young people? I think we need to think about it in two prongs, if you will. First of all, I think it’s very simple. It’s really getting the tech into the hands of these young people, the innovators, the entrepreneurs, and let them start experimenting with it. We are seeing some examples already of this working. In Nigeria, for example, a Gen AI chatbot really improved learning, it helped students in after-school learning get the information that they may get in six months, in just two weeks. We’re seeing in the Democratic Republic of Congo, in the mining sector, foresight-driven AI and forecasting is helping mines access the capital they need to grow, improve safety, and create good jobs. In Burkina Faso, there have been pilots with computer vision AI looking at diseases of plants and helping improve how you treat those and increasing yields by up to 30%. We have these small pockets of pilots of results that we’re seeing, and I think we need to really start learning as much as we can from this, gather to your point, the data on how these are working. But then the second prong really is a bit more on the scaling side, because if we continue with small pilots here and there, that is not going to have this impact that you’re talking about, Cynthia. Really there, it’s about understanding, first of all, what evidence do we have so far of AI or emerging technologies being able to bridge those divides? Then second, what is the approach we can take? I think for us, we know AI is different than previous technologies in the sense that it can learn, it’s heavily data dependent. Gen AI can also create new content. Sometimes it hallucinates a little bit. It can help you do some high-skilled work. Our research or our colleagues’ research here at the Bank have found that on the opportunity side, we’re AI being able to really democratize access to knowledge. So, that’s a positive thing we can access, and I’m sure you’ve experienced it yourselves, accessing really insights that you weren’t able to before. It’s improving productivity, it’s supporting faster innovation, and it can also help on the broader level enhance services trade and close the gaps between markets, overcoming language barriers and such. But then on the risk side, we’re seeing also the potential that countries that do not adopt or are not able to adopt AI quickly can really struggle in the future to create good services jobs, to create high paying jobs and get locked into a situation of low stability and low earning jobs. It can lower the incentive to learn because why should I go and get all these new skills when I can use AI to get them? It can widen inequality between countries and also within countries based on who has access to AI and who doesn’t. There’s also a timing aspect here. Some people are saying AI will have these effects within the next one, two years. Talk about AGI. I think we’re trying to take a bit more of a balanced view, looking perhaps to Sinead’s point at what can we learn from previous general-purpose technologies like electricity, like the steam engine, in terms of what it took for capabilities to be translated into applications and then be adopted. This can really take a lot of feedback, a lot of testing, a lot of learning. We’re seeing with these previous technologies, it took decades to go from actual capabilities to actual adoption in the market. We really need to keep a good eye on the timing of these aspects as well. In terms of the approach for FCV countries or FCV context that you’re asking about, I think three things. First, what are we trying to use AI for? We’re not going to use AI for AI’s sake. We need to have a specific use case. We need to have a specific problem. Then we need to understand what specific AI technology should we be using to address this problem. Do we need generative AI? Do we need computer vision? Do we need some other type of AI technology? Second, what are the prerequisites based on that technology that we’ve picked? For us, we like to think about this in terms of three or four Cs, the foundational connectivity and energy to really connect you to the Internet. Second, compute, whether that’s on the edge, on your phone, in the cloud, or GPUs that are in a data center on the premise. Third, what we call context, which is really the data wrapped in strong governance and safeguards. And then the fourth, which is the competencies, like Sinead was saying, the skills really both to use, but also to build AI. And then last of all, which is really important here is the FCS context. We know that on the one hand, we have the Ukraines of the world, which are classified by the Bank as an FCS context. But on the other side, we also have countries like Somalia and Central African Republic. These are very, very different. We need to understand how are those solutions potentially exacerbating drivers and risks of fragility, and how can they support the resilience that we really need to build. In summary, really encouraging a two-pronged approach. First, getting the tech into the hands of the young entrepreneurs and innovators and start experimenting and really learning as much as possible, and then feeding those learnings and insights into broader efforts to improve the prerequisites and build up the capabilities that you need to have impact at scale.
[Cynthia Mene]
Exactly. Thank you, Johan, for sharing those wonderful insights. And then over to you, Beverly. I would like to focus more on the policy aspect. I know your work in terms of advancing the framework for digital public infrastructure highlights the importance of interoperability and governance in DPI. Could you, based on your experience, tell us what policy levers have proven most effective for governments in establishing data governance standards that empower youth-led innovations, either in health, in agriculture, extractive industries, and beyond? And building on that, also maybe share with us, how can youth voices be integrated into the development of digital policies that impacts their future?
[Beverly Hatcher-Mbu]
Great. Thanks. Any more questions? No, I’m just kidding.
[Laughs]
Just to lighten the mood. I think Sinead and Johan have set me up really well here because I think the core of when we’re thinking seriously about data governance is, it’s complex systems at scale. In Nigeria, Development Gateway, we’ve been working with the Ministry of Health around tobacco control and tobacco use impacts on youth. It’s called DaYTA, if you want to look it up. So, we’ve set up two expert groups, one in survey implementing presentation and the other in youth advisory. And we structured the program in this way because we’d learned in a pilot in DRC that we had a larger, one large expert group, and the youth voices and youth perspectives in that group kept getting lost. The expert group often went down some tangents that were quite highly technical, and we knew we were missing out on the insights we needed to shape the data use strategy for the program. We knew if we were missing it, that our government partners were as well. When we started up in Nigeria, we started set up in two structures so that there was a clear pathway in which we could repeatedly, recurrently receive and engage with youth perspectives on the data use strategy around how do we manage healthy outcomes for young Nigerians and then setting the research priorities. I share that example for two reasons. I think, one, overarchingly, if we want to change, if we want to transform how we manage, store, and use data, a.k.a., data governance, then we’ve got to be very clear about how we translate insights into structure. It’s great to collect lots of ideas and have space for that innovation, but it has to go somewhere. Otherwise, we spin our wheels and we’ll burn people out. Young people have a lot of energy, bring a lot of energy and fresh perspective, but I don’t want them to feel jaded that they’re putting all these ideas out into the world and they’re not translating into systemic change. For me, for us, what that means is we need to move away from, “Oh, yeah, there’s a young person on this committee” to, “Here’s the outcome document of this drafting committee,” and we can point in clear ways to show where a youth perspective or particular communities have been taken into account in X, Y, Z ways that now form the basis of that drafting strategy, that technical program, whatever it is. I think interoperability has three components, but we often get stuck on the first two. We talk a lot about data interoperability or data integration and connectedness. We talk about systems, maybe if you’re lucky, but we forget that it’s fundamentally about people. If we want digital infrastructures to expand upon the best of what humans have to offer, I think we need to be thinking in very tangible ways about how we transform the technical requirements, the policy committees, the oversight mechanisms, whatever the format is, and really think about how those venues, those avenues, can espouse nuanced perspectives. So, that’s a feature to have nuanced perspectives, not a bug or an inconvenience.
[Cynthia Mene]
Thank you. You asked if there’s any more questions, so I’m going to ask you one more question.
[Beverly Hatcher-Mbu]
Excellent.
[Cynthia Mene]
Yeah. Can you tell us more about what partnership models have you found most effective?
[Beverly Hatcher-Mbu]
I thought about this question for a long time, probably longer than I needed to. Again, I did mention at the top of the hour, I’m a lawyer. I sit on things for a long time. What I wanted to say on this topic, I think it’s easy to throw out, we just need more public-private partnerships, or we just need X group of people in the room, and that will fix everything. We’re all looking for a silver bullet that is going to make these technologies and these approaches work, but what we actually need to be thinking about is partnership models as a constellation in the same way that we need many stars simultaneously to see clearly at night or clearer at night. We need to think about partnership models in the same way, especially when we’re talking about inclusive digital public infrastructure. A model that DG is using in Ethiopia is engaging with universities outside of Addis to cascade a data standard around livestock, improving data and systems integration for livestock. Did you know that undergraduate and graduate students and their professors are some of the biggest users of livestock data in Ethiopia? I did not know this. Maybe you are not surprised. It was great for me to learn, but essentially, I learned from our embedded team that universities were often getting missed in a lot of these digital initiatives, these cascading and training opportunities because they play an often informal role in translating contemporary and up-to-date research in real-time in the communities where they lived and studied, and they weren’t getting caught in the traditional value chain in terms of training and thinking about how we expand scale. I think Sinead touched on this in her answer as well previously, but I think we really want digital public infrastructure and AI to be new, but we actually, I think there’s a lot of power in considering these new and emerging tools on a continuum of digital transformation. As part of that continuum, we have to talk about where we failed. We have to talk about where we have partnership blind spots. Which traditional and nontraditional partners are we not working with, but we should be? Are we thinking through where relationships are in communities and who people trust and working with trusted partners to improve data use, to improve digital engagement? Are we working with Imams and religious leaders? Are we working with trusted youth leaders to expand our idea of who should be in that model and how they drive scale and impact for digital initiatives? And lastly, I’ll end on this point. I think it’s really critical for DPI for Digital Public Infrastructure, to not get stuck at the payment and the ID level, divorced from services and experiences that all citizens, and especially young people, feel on a day-to-day basis. There’s a room for both. It doesn’t have to be an either or. It can be both and. We need to think about inclusive DPI. Addressing power asymmetries, not as an inconvenience, but as a necessity. We want technology to wish away the problems that we as humans have created, and it’s not going to do that, but we can face that head on by using DPI, whatever the next buzzword is going to be, as a new opportunity to restructure some of those partnership models and how they function.
[Cynthia Mene]
Thank you very much. Just like you said, I think Digital Impact Alliance also mentioned that a multi-stakeholder approach to digital initiative proves 3.4 times higher than a single sector project. We’ve seen several effective models like private, public, and people partnership. We’ve also seen academic, practitional collaboration, digital collaborations, as well as the cross-border tech alliance. But moving away from that, I have one last question for you, Sinead, before we take questions from the delegates. What role does storytelling and digital literacy play in empowering you to take control of their digital future and also advocate for their communities?
[Sinead Bovell]
Yeah, I’ll start with digital literacy, and I think I touched on it a little bit. Digital literacy gives you the hard skills to participate in the future. I think digital skills are the foundation. If you don’t have, whether it’s the know-how of how to use a tool, understanding how to navigate a tool, how to use this system safely, and are they optimal for you? Should you be there? You are essentially locked out not just of the future, but also of the present. I tend to see digital literacy the way I see reading and writing. I see it all interchangeable as the foundation for access and the foundation for building, and also for democratic participation in many regions throughout the world. But when you combine digital literacy with storytelling, it’s a really powerful intersection because storytelling gives people a way to make sense of the technology and the change around them. It helps to turn an abstract idea, whether that’s an algorithm, whether that’s data privacy, and whether that’s in genetic engineering, into real relatable narratives. And so, when you can craft shared stories, it actually really deepens your understanding of the technology and how it could affect you in your day-to-day life in ways that you would want it to, and then in ways that you wouldn’t. And you can start to build solutions and understand aspects of resilience and prevention when it comes to technological evolution. Even asking questions, who does this empower? Who does this disempower? That really enforces digital literacy by helping people to think about how tech works and how it benefits. But I also think, perhaps even most importantly, storytelling inspires people to want to participate in shaping the future because it gives people something to fight for. I think a lot of times the stories, and rightfully so, we tell about technology or stories what we maybe don’t want to happen or the fear of how things go wrong, but it is impossible to build towards the futures that you want if you’re only thinking about the futures that you don’t want. But it is great privilege to be able to have the time, the resources, to pontificate on futures you do want. And that is part of the gap. I mean, there’s profound power in who gets to pick the problems technology will solve. And that is part of... That’s somebody’s story. When we say AI is going to change this and it’s going to change that, that is somebody’s vision of the future, but what about everybody else? And I think storytelling is an accessible way to bring in tech literacy problem solving in ways that are inspiring, accessible, and helpful.
[Cynthia Mene]
Thank you very much. Now I’m going to open it up to questions, but I’ll take one question online from one of the online delegates. This one says, what practical steps can youth-led initiatives take to build meaningful partnerships with global institutions like the World Bank, like Development Gateway, especially when working at a local level with limited resources and reach? I think Johan and Beverly could speak to this.
[Johan Bjurman Bergman]
Do you go first?
[Beverly Hatcher-Mbu]
No, by all means.
[Johan Bjurman Bergman]
Excellent. Thank you, Beverly, for putting me on the spot. The World Bank has a country-based model, which means that in all the countries where we operate, we have local staff, whether they be from the country or internationally recruited and based there, who are in charge as task team leaders of the projects that operate in the country. I think for youth-led organizations, and specifically, since you asked on the community level and at the local level, I think it really starts there. Understanding who is the person or the people in that specific sector where you and your organization are trying to have an impact to change the narrative, and really work for inclusion. So understanding and finding out who those people may be. Then, I think for the Bank, understanding what projects are currently under implementation, what are we trying to achieve, what are those components and activities. This is available online on the World Bank portal, on the World Bank’s website. And then, seeing how might you, as a youth-led organization within that specific area, engage on those components or activities, or alternatively, strike up a conversation about if there is a next iteration of this project, of this technical assistance, of this analytical work, how might you engage with the people who are really taking these efforts forward? I think really understanding who the people are in your sector in the country, understanding what the current efforts are, and then through dialog with those people, seeing where is the Bank planning to go and affect change in the next 5 to 10 years, and seeing how you can really collaborate and bring those perspectives into the conversation. Thanks.
[Beverly Hatcher-Mbu]
I think Johan covered most of it. Development Gateway, I didn’t mention this, we’re a nonprofit. We are medium but mighty, small to medium but mighty, but we operate with the same approach and the same model. People who are living in those communities tend to know far more than we ever could, far more than I ever could sitting Washington, DC. I am Nigerian, but I don’t live in Nigeria, and I pay attention to that positionality as much as I can because there are always going to be people on the ground who know better than I do. My job is to help connect what they understand to other global conversations and resources as best as I can. I think in terms of partnership, it’s also about knowing your lane. I think sometimes people are afraid to say that. At DG, we’re often a little bit further up the value chain, generally often working directly with governments on government systems at a systems level. There aren’t always avenues because we have a very narrow scope that we’re building or building data governance or policy in particular ways. It’s a fine balance that we do. We’re building in particular ways with particular partners. That doesn’t mean that we shouldn’t work with youth groups or engage with young people, but there aren’t always opportunities to, but sometimes there are. So, I talked about that tobacco control program, and not because it’s a youth focus, but because in general, it’s about tobacco control, knowing that there are specific impacts on young people. I think it goes a little bit to what Johan was saying, which is that you need to know where your strategy is or where your position is, and then build relationships accordingly. Talk to everybody. Talk to everybody up, down, and sideways. It’s not only the people who sit on the stage, it’s just people who are sitting next to you or people who are online with you in the chat. I think that’s a part of how we build a more nuanced approach to partnerships, whether you’re a part of a youth group or elsewhere.
[Cynthia Mene]
Thank you. That’s some really exciting insights. I will open it up right now. If you have questions, I see… Let’s start with... We have one person here in the front.
[Abhisekh Rodricks]
Hi, and thank you so much for the insightful discussion that we just had. I’m Abhisekh Rodricks, and I am an operational risk manager at UBS. Now that we see that institutions are accepting AI into their day-to-day work and institutionalizing this concept, we see that most of the employees who are working in these institutions are either reluctant or very scared of this concept or the use of jargons and big terminologies like algorithm, AI data, and stuff like that. While creating institutional-level policies on AI, and its governance, how do you think we could bridge this gap and make these policies more accessible to the employees? Because any policy has to be understood by the people who are utilizing or are impacted by it. So, on an organizational basis, how do you think this gap can be breached out? Thank you.
[Cynthia Mene]
Thank you. I also want to take another question, then we can answer both. Okay. We have a young lady just right in front here. Please, make your question brief.
[Speaker 1]
Yeah. Okay. Hi, everyone. Thank you so much for this wonderful discussion. My name is
[Unintelligible]
. I’m a graduate student at the University of Pennsylvania. And my question is, how do you see some of these solutions that you’re seeing that are very digital-focused? For example, we talk about AI. How do you see that interacting with energy systems in some of the countries that you’re working with, especially since these technologies are very resource-intensive, and if nations are already struggling with energy insecurity, resource insecurity, like it was here as well, how does that…? Are there any challenges and opportunities there for these small companies to be sustainable from the get-go as they’re developing in these early stages?
[Cynthia Mene]
Thank you. Sinead, I would like to start with you if there’s a question that you could respond to.
[Sinead Bovell]
Sure. I can briefly respond to both. I’d say for the first question, how do you ensure that people who may be intimidated by technology want to adopt it in an organization, especially when policy and guidelines and best practices aren’t always interpretable by the average person? What I have found in my experience in going into different organizations is building champions within the company. So, whether it’s in a specific sector of the company or a specific team, having somebody that can be that bridge, that communicator between people who are building the policies, who have the in-depth knowledge about the tools. And then, they’re also very comfortable with the teams that they work on, and there’s already a system of trust and shared terminology, shared communication, and they know their team best. And so, they become this champion for how AI gets deployed and ensuring that nobody in the organization gets left behind. And then, the second question about energy and water systems. General purpose technologies, they build on each other, and so do the problems and the challenges. So, whoever doesn’t have access to electricity probably doesn’t have adequate access to the Internet and likely won’t have as much consistent access to artificial intelligence, and that is the reality. So, we still have to bridge and fix historical issues because people will then just continuously be systemically and structurally left out of the future. When it comes to energy with artificial intelligence, I believe we actually do have some of these solutions. I mean, clean energy solutions exist. They’re just more expensive, but that is a choice that companies are choosing to not make. I think that we don’t have to be in this AI energy crisis the way that we are. Water is a different story. We’re going to have to figure out where it makes sense to build certain data centers that are water intensive. And I know right now, most of the data centers are being built in deserts, which doesn’t make the most sense when we think about complex systems thinking. But when it comes to energy, there’s a company in Canada that uses solar panels for their data grid. So, there are ways around it. We just have to make different choices. And that’s really what the future comes down to. We have most of the solutions if it’s a technical problem, but some of the most challenging problems we face are actually human choices that we are choosing to not make.
[Cynthia Mene]
Thanks for sharing. I’ll take two more questions. Okay, so I have one lady down there putting on the blue. Yeah, please stand up. Yes.
[Amina Mustapha]
Hi, I’m Amina Mustapha, and thank you for talking to us about this. I have a question, particularly for Johan. He mentioned that basically the technology should be made accessible to the youths in general. But I’m just curious to know that, for instance, in youths who are in conflict-affected areas, how do you ensure that these technologies are made accessible to them, and especially in terms of funding infrastructure and policy gaps basically in youths affected area, basically?
[Cynthia Mene]
Thank you. Any other questions? Okay, some more hands over there.
[Amber Faizi]
Hi, my name is Amber Faizi. I work at United Nations Foundation. First of all, I just want to say thank you guys for talking today. It’s really inspiring to hear people who are not skeptical about youth’s views. My question is, I wrote my capstone in economics on artificial intelligence, so I’m really curious to see how the conversation evolves, but I think that many of us in this room, AI and digital futures are intuitive, in a sense. It shaped our cognitive frameworks. I’m curious. I know that there’s a lot of talk about tokenization of youth in their perspectives, but I’m curious about the reciprocal learning, intergenerational. How do we ensure that this is not just tokenization or an ideal we aim for, but it’s an actual institutional practice within the systems we work in and that youth voices aren’t always heard with skepticism? Thank you.
[Cynthia Mene]
Thank you. So, Johan, you could answer the first question, and then maybe Sinead and Beverly can take the second.
[Johan Bjurman Bergman]
Definitely. Thank you for this one. It’s a very difficult one, and I would really encourage you to continue thinking about it. I think the framework that I tried to lay out a bit when I made the first remarks, which really looks at AI for what are the specific gaps, and what is the specific context. It’s a useful one to really think about it from a policy and an investment side, but I think within these contexts that are affected by fragility, conflict, and violence, these are all more exacerbated, these challenges in many ways, because when we talk about the FCV context, it really also brings in resource constraints that are much, much more potent than those in many other countries. Any dollar invested in infrastructure towards unleashing AI technology or making it accessible to young people, maybe a dollar that’s deprioritised from something else like health or education, etcetera. The policy side, we have oftentimes very weak policy frameworks in key areas that we know that we need to responsibly deploy AI, data protection, data privacy, cybersecurity, etcetera. We also, on the other hand, have very low capacity within the public sector, often to strengthen and implement and enforce the policies that are there. That’s the second challenge. Then I think a third challenge is that often we see that the foundations for human capital, education, health, are also much, much weaker in this context. We start from a much lower position. In some sense, the approach that we may want to take is to look at what can we do that is both beneficial to addressing this human capital policy and infrastructure aspects as it relates to AI, but also as it relates to societal development more broadly. What we think about as no regrets investments. From the digital standpoint, we think about this in the framework of those four Cs, connectivity and energy, to Sinead’s point about really being able to provide sustainable energy and connectivity with that. The current M300 initiative that the World Bank and African Development Bank and partners are rolling out across Africa. I think it’s a really good example of this, which then is also paired with connectivity. The second one is on the compute. How do we ensure that we roll out devices that can be used for those small AI applications and then provide access to the cloud through the connectivity? How do we help countries think about data as in some sense, the new oil as an asset that they can develop to and also tailor AI solutions that work for them. Then third, providing those skills, which to Sinead’s point as well. At the very basic level, these are digital literacy skills with some tweaks to understand how do they apply around AI. I think if we can make those no regrets investments in a very intentional way that don’t. take away from other key investments, then that is a path that can be sustainable.
[Cynthia Mene]
Thanks. Okay. For the sake of time, we might not be able to take the last one. But I want you to... We’ve learned a lot about how to overcome challenges with AI, data, and skills gap. We’ve also learned a lot on how to drive innovations to ensure a more inclusive and resilient future. I would like to encourage you all to continue to innovate for a more inclusive and resilient future because your innovation matters, and we care about it, and we want to make sure that they continue to make the impact and drive more solutions that impact or help people, especially in marginalized communities. So, thank you all for listening to us, and thank you to our panelists for this session. We’re excited to have you once more. Thank you.
[Sinead Bovell]
Thanks, everybody.
[Applause]