At Open Athena, we spend a lot of time thinking about how AI is reshaping the future of science and how we can make sure it does so ethically. So I was excited to talk about AI’s impact at last month’s Asian Leadership Conference (ALC) in Seoul, South Korea, where I participated in the panel “Our Next Technological Advantage: Future Ready Skills and Ethical Innovation.”
Our discussion ranged from ways AI is affecting students to the importance of keeping AI development open and beyond. You can watch it in the following video, starting at the 7:13 mark.
Or if you’re more of a reader, you can check out an AI-generated transcript of our conversation below.
What does “future ready” mean?
Ladies and gentlemen, our next session is titled "Our Next Technological Advantage: Future Ready Skills and Ethical Innovation." In this session, we are going to explore how Asia is moving beyond infrastructure to shape the future of global innovation through its people and systems. Join us as we uncover how to empower the next generation to become active drivers of technological progress rather than passive consumers. We are today joined by Mr. Jared Crooks, COO and CSO of Open Athena; Dr. Songyee Yoon, advisory council of Stanford Human-Centered AI and board member of MIT; Mr. Joshua Elder, senior vice president and head of grant making at Siegel Family Endowment; and Mr. Yoshito Hori, founder and president of GLOBIS University. And last but not least, moderating the session is Ms. Jumee Song, senior vice president and COO of Siegel Family Endowment. Please welcome our speakers and moderator.
Jumee Song: Oh, great. Hello and greetings. My name is Jumee Song. I am the chief operating officer at Siegel Family Endowment. We are a private foundation based in New York focused on the impact of technology on society. We also have what we call the inquiry-driven approach to our philanthropic giving. And I'm very excited to moderate a discussion about a topic that is very dear to our heart.
So we often talk about Asia as a center of technological innovation—from AI and semiconductors to digital infrastructure and entrepreneurship. The question before us is no longer whether Asia will lead in technology; that's already happening. The deeper question is who gets to build it, and whether the people building the technologies have the creativity, ethics, and imagination to ensure technology serves society.
Seoul is a particularly meaningful place to have this conversation. It sits at the intersection of world-class education, entrepreneurial ambition, and cultural influence, while also reflecting many of the tensions of the moment: rapid AI adoption, shifting labor markets, and the growing question around responsibility and well-being.
Today's session takes a systems view, rather than treating education, research, entrepreneurship, and capital as separate conversations. We'll explore how they connect, where the gaps are, and what "future ready" really means in the age of AI. We're fortunate to be joined by four founder leaders working across these systems—K12 education, research and higher education, venture investments and entrepreneurship.
I'm going to ask each panelist to briefly introduce themselves, your role, your organization, and in one sentence answer this question: What does "future ready" actually mean right now in your work? Starting with you, Yoshito.
Yoshito Hori: Hello. I'm so glad to be here in Seoul, Korea. I'm from Tokyo, Japan. I'm Yoshito Hori, founder of GLOBIS, which is the number one business school and number one venture capital in Japan. Future ready means "technovate." Technovate means technology plus innovate. I created this word ten years ago because I knew that technology is going to change and innovate society and the world. So "future ready" means learn to know, learn to act, technovate. I'll talk about that later in more detail. Thank you.
Joshua Elder: Hi everyone. My name is Joshua Elder. As Jumee mentioned, I'm senior vice president and head of grant making at Siegel Family Endowment. I oversee all of our philanthropic investments, particularly focused on education, workforce, and infrastructure. In the context of the work I'll talk about today in K12—having been an educator, a principal, and having opened up schools—I'm really excited to talk about how fast things are changing in education and emerging technology, and excited to see so many young people in the audience, because you all are the ones actually experiencing this rapid change that we're facing.
For me, in the work that we do, thinking about how to be future ready is being able to be adaptable—being able to respond to changes, but also not just respond, but to be a part of the change and shape the narrative. As opposed to just being a consumer of what's happening, actually be able to shape it. So thinking critically, being able to solve problems and adapt—and how we create those opportunities is critical, especially in the K12 setting.
Songyee Yoon: Fantastic. You already said everything I wanted to say! So anyway—good morning, everyone. My name is Songyee Yoon. It's my pleasure and honor to be here with these esteemed panelists.
I'm the managing partner of Principal Venture Partners, a Silicon Valley-based venture capital firm. We invest in early-stage AI-native companies. In terms of future readiness, I think it's something we can't talk about without openness to accept new norms and the flexibility to learn. When we think about the future, we have a tendency to think about it in a linear fashion—to think about what technology is going to automate or replace what we are doing today. But what is going to happen is that with a new platform shift and adoption of new technology, the work process itself changes. We have to think about what is the role of the human, what is the role of AI, what is the role of technology. There will be a lot of extrapolative thinking that needs to happen to imagine what the future is going to be. So I think staying nimble, adaptive, open to change, and having the courage to embrace it—that's going to be important to be future ready.
Jared Crooks: Good morning, everyone. My name is Jared Crooks. I am the chief operating officer and chief strategy officer for Open Athena. We build foundation models and work with research institutions such as MIT and Stanford to create opportunities to accelerate scientific discovery with AI. We talk a lot about technology, a lot about AI, and I think the question regarding how you think about the future and future-proofing can't really happen until you talk about the infrastructure that is needed to create it. In my line of work, having access—the folks who have access to create and build those tools—will really dictate and shape the future of how we apply this for the greatest impact in society. So I think a lot about that, and I think a lot about the people who are going to be building it and who have access to it.
The system is failing to prepare people
Jumee Song: So we just described what future ready could look like. But I'd like to take a moment to be honest and discuss where the system is actually failing to prepare people for this moment. Josh, from your perspective in K12 systems, what's not working and what's the cost of that?
Joshua Elder: Thank you. I think this question scares me a little, especially if there are people in the room who are in education, because I think oftentimes when we speak of education we are often pointing out the negatives and we forget about how challenging it is to be in education and the responsibility that educators have. I think our education system is still operating in a very linear function—there's a very traditional pathway in terms of information you're expected to learn, pathways you're expected to take once you finish your K12 schooling, whether that's higher ed or workforce or advanced degrees, and then there are expected outcomes—jobs you're taught to aim for. And in the world we live in right now, especially with AI and other emerging technologies, that just doesn't exist.
Until we can figure out how to create a system that allows students to really be the creators, the innovators—to think about how they can leverage AI and emerging tech to create solutions to problems they care most about—we're just going to continue to exacerbate some of these inequities and issues where K12 is not preparing students for the future. It's complex and challenging, and oftentimes in education we don't love ambiguity. We love to have a very straightforward way, because it's easier to have these preconceived notions and solutions to drive toward. But we really do have to ask ourselves where we want to see students in the future and how we create those opportunities. It's going to be messy and uncomfortable. But until we actually make that change, we're not going to set these students up to be successful in a rapidly changing world.
Jumee Song: Thank you. Songyee, did you have a response to add?
Songyee Yoon: Yeah, I think that's a great point. I think there are a couple of things I can add on to what Josh just mentioned. For example, in terms of thinking about education—just repeating what has been done in the past—I think our current education system was designed about 200 years ago, optimized for delivering knowledge in a world where knowledge is rapidly being commoditized. Knowledge is now available at everyone's fingertips. What we really need is creativity and problem-solving skills and new types of skills that we have to train for. But in terms of curriculum design and teacher readiness, we have not invested enough in how to measure creativity, how to measure problem-solving skills, and how to improve them so that our future generation can navigate this new changing environment.
At the same time, I think education has been focused on preparing our next generation for the new world, but those who are in a position to determine what should be taught are themselves in the process of adapting to this new technology. We've seen what it's like to be a digital-native generation, what it's like to be a mobile-native generation. I think what we are faced with now is an AI-native generation. They don't have any problem adopting and using the technology as a tool. What's going to be more important is how we train them so that they can be part of shaping the future—coming up with new standards and new platforms to include everyone going forward.
But I think the way we're currently thinking about it is how to train them to be fast adapters and users of the technology, instead of thinking about how they can shape the future. I think those are the areas that could be catastrophic if you're not prepared enough.
Jumee Song: Thank you. And Jared, when working with students and researchers trying to move from learning to actually building something—where do you see where they hit a wall?
Jared Crooks: I mean, that's such a great question. And I thought the term "AI native" is so important here. Building something, or even having the idea of the application or the tools that you want to create—I don't think there's been a time in human history where you can go from ideation to MVP in a matter of minutes, literally. The question is how do you utilize this for widespread scale or impact. You'll hit a wall with GPU constraints, capacity constraints. You can build something, but is it ready then for others to use it? I use Claude a lot, and I'm sure some of you do—or name your frontier platform of choice—that won't necessarily be publication-ready because of security. A lot of applications that are made by folks that don't necessarily have the security infrastructure will see a lot of limiting access for the technology that's built—with the capacity of GPUs, with the capacity of teams that can really deploy this.
This is why, at Open Athena, we help supplement a lot of professors and principal investigators who have thoughts about the type of research they want to do, and do have graduate students and postdocs to get them to the MVP level. But it really takes a certain amount of specialization. You still need senior software engineers to help implement it and make it scale-ready.
Jumee Song: Thank you. Yoshito, you have created one of the most well-respected MBA programs in Japan. From your perspective, what do you see in young adults or graduates as signals that they weren't well prepared for the complexity of this moment?
Yoshito Hori: I talked about technovate—technology plus innovate—and I think it's good to understand how technology is going to change the world. Technology will change the champion. It used to be a lot of department stores, and now it's Coupang or Amazon. It used to be NBC or KBS, now it's Netflix. It used to be Hyundai Motors or Toyota, now it's Tesla or BYD. It used to be Harvard, now it's GLOBIS. I'm just joking. But anyway, what I'm telling you is that technology changes champions.
Technology will change assets to liabilities. Physical stores become liabilities because of the internet—you don't need them. Transmitters and antennas and TV sets will not be assets anymore—they become liabilities because Netflix doesn't use them. Combustion engines become liabilities because you don't need them in EVs. Physical campuses will not be needed because you don't need them any longer. So in order to understand technology, you have to understand how to use technology to make the assets of incumbents become liabilities, and then you have to be bold enough and invest heavily to become number one in the world.
And for young entrepreneurs—you have to be smart enough to understand technology using technovate, invest heavily to make assets into liabilities, scale so rapidly, and at the same time always be looking globally. That's what you have to do.
Responsibility around AI
Jumee Song: I'd like to now shift the conversation to talk about responsible innovation in practice. Songyee, when you're deciding whether to invest, what signals to you that a company or entrepreneur is not thinking responsibly about AI?
Songyee Yoon: This is such a great question. As a venture capitalist, I invest in very early-stage companies. Some of the companies are at inception—thinking about ideas and how the company can be translated into commercial applications—which means they are launching a decade-long journey for the company to be really successful to the level and scale that we as investors expect. They have to be committed to working on this problem and building the company for an average of ten years.
We know that ten years, especially in this era, is a very long time. A lot happens—uncertainties, change in environment, customer backlash, change in policy, etc. Those who can survive that kind of tide over ten years are those who are ready to run a marathon. There are many winners who can win sprints—they can cut corners. But to win a marathon of building a sustainable, generational enterprise, you have to really stick to principles and think about the implications to society when you build a company of that scale of ambition.
So when I see founders, and we ask questions about where this technology is headed, what the implications of their business are, what the ethical considerations are, and who the stakeholders are—when their answers are "it's not my problem, I'm just an engineer, I'm just building a solution"—we see the sprinter. But we would like to back the marathon runners—those who think about long-term implications, other stakeholders, and sustainability.
Jumee Song: Thank you. Yoshito, in addition to starting an MBA program, you have a 30-year-old VC firm. How do you push both your entrepreneurs and students to take AI responsibly?
Yoshito Hori: In terms of AI, I think there are two ways of using it. One is offense. The other is defense. I'm a basketball team owner, so I'm using basketball terms.
Offense is increasing revenue by creating new models and products. In the case of GLOBIS Business School, we used to be competing against Harvard. Then e-learning came in, so we started producing e-learning. Then MOOCs came in—massive open online courses—so we provided what we call SPARK, small private online courses. Then Udemy came in with subscriptions, so we created GLOBIS Unlimited. And now AI is coming in, so we just have to keep producing new products. New products create new revenue growth, and we become number one globally. That's offense.
Defense is increasing profit by decreasing costs and increasing productivity. It doesn't create a new product, but it makes your business more efficient and more profitable. In the case of GLOBIS, we use AI to assess reports, assess exams, and create curriculum and textbooks—which creates cost reduction and higher profits. All entrepreneurs have to think about offense and defense in terms of AI usage. But offense is more important because defense will make your profit bigger but will not make you win globally. So we should use AI in an offensive way to create new products and new business models.
Jumee Song: Thank you. And Jared, in open source and research environments, how do you actually navigate responsibility? What gets built? What gets released?
Jared Crooks: That's such a good question. And I want to take a step back—I really like that basketball analogy. Go Knicks!
When you think about defense, you think about safety and ethics. So just to give you a grounding here: a frontier company in AI are the companies you're thinking of right now—OpenAI, Anthropic, etc. They're very great and the models they produce, which we use every day, are wonderful, general-purpose models. The challenge is that they are developed as a black box. What that means is that, for proprietary reasons, you don't understand or know the weights or the systems behind how an answer was derived. So you ask it something and it gives you an answer—but how did it arrive at that answer?
For science, this is really important—not the obfuscation of it, but for scientific discovery, it's actually really important for researchers to know how an answer was created, especially as they incorporate AI more into their research. But I could think of other applications, especially in the entrepreneurial world—whether you're creating applications for insurance or healthcare, and you have a consumer-facing product, and you want to know how that insurance company decided not to give a certain rate to a certain individual—you need to be able to investigate that. Which is why open source and open development, from an ethics and safety standpoint, is really important. You can understand from a model perspective how that answer was derived—why did it make that choice? You can really see the weights and the biases that that model uses. We don't necessarily focus on the downstream applications—we're much more fundamental in the framework. But I think that upstream value has a lot of downstream application.
Teaching responsibility
Jumee Song: Thank you. And Josh, in the K12 system that tends to be already overcrowded—teachers are already stretched thin and curriculum is again crowded—what does it mean to teach responsibility?
Joshua Elder: Yeah, I think this is the piece that oftentimes is a worry, because in the education sense, when we think about some of the organizations we're supporting that are focused on education—if they mention the word "responsibility," it gets conflated with being anti-AI or anti-technology. And that's not the case. I think we all agree that we are now living in a world where you have no choice but to be a technologist, because the technology is there whether you like it or not.
Building on what Jared was talking about—being able to ask those questions and understand—if you break it down to the basic sense: a lot of questions around what are we teaching and why are we teaching it. If you think about basic numeracy: if you're teaching students that 2 plus 2 equals 4, and that 2 multiplied by 2 also equals 4, and they apply that same logic and assume 4 multiplied by 4 should also be 8—we know it's not. And why is that? I think that's the piece that's missing. For students who are just told to memorize the answer, that's fine. But understanding and asking why—I think that's what's missing. So when you apply that to emerging technology, it's understanding: where is the data coming from, where's it going, what bias is already built in, and what's the impact it's going to have.
We're also seeing this younger generation is much more focused and concerned about the environmental impacts of AI. So thinking about what are the responsible applications—if we're going to use it, how can we be responsible in the way we're using it, and thinking strategically about what prompts we're going to use? So you're not just throwing "what is 2 plus 2" into ChatGPT, but actually being much more thoughtful about what you're trying to get from it.
The challenge is that a lot of the time, educators and others are not the ones making the decisions. The decisions are coming from the top down—from the government, the state—and they're being told they have to implement the technology because they can fall behind in trends. And the people making the decisions are also not asking the right questions about how we can have responsible use. So as we can get more of the responsibility and ethical considerations built in, it'll have more downstream effects for education.
Songyee Yoon: Yeah—and in addition to that, I think from the educator's perspective, we also have to think about how a lot of the assumptions society has been built upon are changing, and how to prepare the future generation for that.
For example, Jared mentioned that AI was built as a black box. One of the fundamental assumptions that holds democracy together is contestability—we can all have different opinions, but we can trace back why that opinion came about, and we have to be able to challenge those assumptions and come to the same conclusion. Another thing is the role of friction. Technology has been designed to remove all friction. I think you've probably read articles about the concerning phenomenon of young kids who prefer to talk to chatbots instead of their friends—because chatbots are agreeable. They encourage them. They only say the things the kids want to hear. They remove all the frictions they will inevitably experience when talking or playing with friends.
But having good friction is a kind of necessary evil for society. In democracy, we live in friction—we live in a world we didn't necessarily vote for. If more people voted for a different set of rules, that's part of the social contract that society is built upon. How are you going to introduce the necessary friction, and learn to live with it, when there's a tendency toward technology that eliminates all friction? That's going to be very important for holding society together. Those are fundamental questions we have to raise as educators to prepare the future generation who are going to live in this new world and new norms.
Joshua Elder: And I just want to add one piece on that—as you talk about friction and the narrative shifting. Something else that I think in education we are not doing a great job of is: there's a fear that leveraging AI is also increasing cognitive offloading. I think there's an opportunity to counter that narrative. If we actually talked about—going back to the 2 plus 2 example—cognitive offloading: we were doing that with a calculator, right? We've been taught, you can get the sum there. But if we are leveraging technology in responsible ways, we can actually increase the cognitive skills and critical thinking skills we're trying to develop, especially in K12. But I don't think we're doing a great job of knowing how to do that, and then actually telling the story and the narrative. Because right now we're just seeing students who want AI to write their paper or do their problems for them, as opposed to thinking about critical and responsible ways that it is actually aiding them to think more critically.
Prioritizing speed versus ethics
Jumee Song: Great. I really appreciate that, and in my attempt to add friction to this conversation, I would like to ask each of you a very frank question. Josh, starting with you—would you prioritize speed of innovation or getting it right ethically?
Joshua Elder: As I'm sitting in between two VC people—maybe not the right answer—but first and foremost, if we think about education, education is human-centered. I think we have to be clear that no matter the advancements in technology, we've seen this with the emergence of educational technology—we were told that was going to be a game-changer. We're seeing that now with AI. You look at standardized test scores, whether you're looking at PISA or others—everyone is still struggling with basic literacy and numeracy skills. And I think in terms of education, I'm going to answer it both ways: we have to move slow to move fast. Because if we don't get it right in education, we are going to do severe harm.
We've done a lot of harm in the education system that is going to have exponential impact, and we're already seeing that. That being said, I don't think we can let the past dictate where the future's going to go. Oftentimes in education, we want to be as risk-averse and safe as possible, and then usually that leads to analysis paralysis—we're constantly asking questions, constantly trying to figure out whether we should do this, and then we don't do anything. And that's equally as harmful.
So we have to figure out how we can move in a deliberate fashion, going back to being responsible, making sure that we are keeping students and educators at the center of what we're doing. But at the same time, what we've been doing in the past hasn't worked. So we've got to be creative and innovative to think about how we are going to adjust a system that is slow to change—and usually allergic to change—but that change is needed if we're actually going to set these students up for success, to not just be consumers of technology, but to actually be the creative developers and innovators that are going to be needed to take society to the next stage.
Jumee Song: Great. From your lens, Yoshito—does slowing down actually hurt innovation?
Yoshito Hori: So I understand the question as: is it either ethics or speed? I would say ethics is the most important thing of all—there's no question. Because if you do unethical things in your company or in your educational institution, two things happen: internally, you yourself feel guilty, you make harm to your society, and also to your organization and the people. And at the same time, if you do unethical things externally, it will go viral and backlash you and blow up afterward. We are living in a very ethical society in a way—everything you do has to be ethical because people will be watching and media will criticize you. Therefore, ethical conduct is the most important thing of all.
But at the same time, you don't have to go slow—you have to go fast. I think it's not a trade-off between ethics and speed. You have to do both. Ethical is the common standard—everybody has to do it. But speed is what is needed to become stronger in this market.
As a venture capitalist, I always watch two things: the speed of the revenue growth—topline growth—and gross margin. And maybe one more thing: satisfaction of customers. If the topline is growing, gross margin is still there, and customers are satisfied, even though you are making a big loss, eventually you will break even. So ethics is always given—everybody has to take it into consideration. At the same time, you have to go faster in speed and use technovate. By the way, "technovate" is a trademark—I invented the word, but you can use it.
I founded Lucky Fest, a music festival, four years ago. It made a big loss, but the topline growth was fast, gross margin was good, and customer satisfaction was high. So I think it's both: ethical at the same time as speed and technovate, and at the same time satisfaction is needed—you have to be more passionate about that. Jared, do you have any comments?
Jared Crooks: Yeah, it was such a great question, and I want to give humankind maybe a little bit of grace—not permission, but grace. When we discovered fire, it took us maybe some decades to go from being warm around the fire to actually utilizing it to cook food or mix metals. And the speed at which technological advances have typically happened—they've usually happened over generations or decades. So that's why I'm giving us some grace. It took maybe 70 years to go from the last horse and buggy to landing on the moon. My friend Steve Weiss in his talk yesterday was talking about how folks were learning how to code using punch cards and slide rules. Now a new AI model is coming out once every six months—it'll probably get much faster, once every three months. So I'm giving us grace in the fact that society has not had time to catch up ethically toward some of these innovations.
But to answer your question: the ethics have to be embedded. The ethics have to be embedded into the actions and the innovation of what we're doing. Otherwise, we fail ourselves, we fail society—all for the sake of progress, which is fantastic, but it won't be sustainable.
Jumee Song: Songyee, I want to hear more about embedded ethics—but also in the context that as an investor, there is pressure to generate capital and make money. So realistically, in real time, is there room to slow down?
Songyee Yoon: I work in Silicon Valley, and Silicon Valley is full of extremists. You often times meet people who say any regulation is evil, it prevents innovation and the progression of technology. But I disagree. I think it really depends on what innovation you're talking about, and there are many examples in the past where good innovation actually accelerated the adoption of the technology and the progression of the business.
In Korea, we talk a lot about positive regulation versus negative regulation. I think it's really hard to come up with all the positive regulations in an environment where technology is advancing and changing at such a rapid pace. So we may have to think about new frameworks to come up with the right type of guardrails that set the right boundaries. But it doesn't mean that we don't need any regulation. In the case of the food industry, regulation actually helped the creativity, innovation, and adoption of technology. Think about the list of ingredients you can find on the back of a food package—because of that disclosure of what's inside, people with all kinds of allergies feel comfortable consuming that product. Without it, they'll just avoid it. So that regulation actually helped the adoption of the product and gave more comfort to end users and consumers.
I don't think it's an either/or. We can do both, and that's very important for building the foundation for sustainable innovation.
Embedded ethics is something being implemented at higher education institutions across the US. When we talk about AI in particular, we talk about alignment: ethics and alignment have to be aligned with human values. But often times, as those who studied political science know, there's no such thing as alignment. If there is human alignment, there will be no war. We all think differently. So it's really hard to come up with a single "human value vs. AI value"—accepting the differences is part of the ethical framework. Being responsible is about how we can be more transparent, how we can intentionally not leave people behind, how we can accept differences and opinions and build a platform large enough to include all of these different perspectives.
So asking the right questions is becoming more important than coming up with one right value, because that doesn't exist in our society. Embedded ethics is a movement in many different schools—when they're teaching computer science, they ask students to think about: who are the stakeholders, why are you making these assumptions, what kind of data are you selecting to train these models, what are the unintentional exclusions of viewpoints and representation in doing so? So instead of teaching what is right or wrong, we teach them to ask the questions, think about them, and embrace it as part of their responsibility. I could talk more about embedded ethics, but I think we don't have much time.
Audience Q&A
Jumee Song: Oh thank you. At this time I'd love to open it up to the audience—if there are any questions, we're here.
First audience member: Hi, my name is Bridget, and I'm from the Asia New Zealand Foundation. I just had a question for Songyee, but happy to hear from anyone else. You mentioned that knowledge is becoming less important than creativity in an AI world. I love creativity—it's a beautiful word, but often a vague one. So what specifically should universities and graduate programs be teaching under that banner of creativity?
Songyee Yoon: I think you're right, and I've thought about this for a while because there are many aspects to it. First of all, as you mentioned, there's no good definition of creativity. If you look at the creativity literature, there are notions of "big-C" and "small-C" creativity. Big-C is the creativity of artists like Van Gogh or Mozart—they can come up with beautiful masterpieces, but that's not what we're talking about. We don't expect everyone to be those artists. We're talking about small-C.
It's everyday creativity: asking questions, challenging the status quo. Those are the kinds of habits we have to instill in our students so they can navigate a changing world where the new tools are doing a lot of the things that memorized knowledge used to do. How we train that and nurture it in students through education is another matter.
For example, if you think about brain development—a brain develops over time, from the moment you are born until you become an adult. Just like your muscles develop when you learn tennis—you practice certain strokes and your muscle develops—your brain is full of sensory systems, motor systems, cognitive systems, a prefrontal cortex. All of those areas develop with a rich set of stimulation. That's one of the reasons why we often say traveling the world is the best present we can give to our children. When they travel overseas, they see different colors, they smell different things, they taste different things. All of that becomes rich stimulation that helps with brain development.
But those are expensive forms of education. Many underprivileged students in particular have to depend on the public education system. We don't have that luxury. So that's why we have to think more critically about how we can bring that type of stimulation education intentionally into the classroom so that they can all benefit from this new technology development.
Jumee Song: Oh yes, the gentleman.
Second audience member: Warm greetings and thank you to the panel. In the indigenous and native tongue of New Zealand—and also here with the Asia New Zealand Foundation, the other half of this colorful duo. For quick context: earlier today, former Congresswoman Edwards spoke about putting the human back in humanity. Professor Park talked about humanizing the energy transition and the importance of that.
My question is a human one. While I drink from the Kool-Aid in terms of the importance of progression and moving forward with technology—as this exciting thing to help us create future skills—how do we make sure we don't leave the humans or the human component behind? There are a number of disadvantaged and excluded communities all around the world who we are, at times, as philanthropies, guilty of going into and saying "this is the best thing for you, jump on board"—when they may not value education, or may be worried about other things like putting food on the table. How do we bring them along on this journey?
Jared Crooks: It's a great question. I'll just jump in quickly here because I know there are other thoughts. One of the most interesting things I've seen—especially in the advancement of technology, be it AI or anything else, when you're trying to make impact in society—is that the best solutions come from the communities themselves. The top-down approach can be quite challenging because it creates a sort of power imbalance: "We know what's best. We will create this and you will use it." That's not necessarily a sustainable solution—or as sustainable as the solution that comes from the community themselves. But how you get them involved is a different question.
I've seen really interesting models where you create a small council—invite folks from the community into the actual development of the product or the technology itself. Doesn't have to be everybody. But if you have certain representatives from that community who understand the problems, and who can also help develop—they don't have to be the coders, they don't have to be the solution-makers, but they give voice to the development of that technology—I think that's one of the best approaches. It takes time, it takes effort, you have to gather collective feedback. But overall, over time, it's worth it—it's much more worth it than a top-down structure.
And I know we're over time—from the philanthropic standpoint, something we've been trying to do at Siegel as well is: philanthropy in general has to do a better job to make sure we're not imposing our values on the community. Just because we are tech-forward and we're all in on thinking about the impact of tech on society doesn't mean all communities have to be. And the approach we've been taking—a lot of people have heard of the "techno-optimist" approach: give us any problem, technology can solve it. We have really focused on a "techno-pragmatist" approach: what is your problem, let's unpack it, can technology solve it—if so, how, or why not—and in particular if AI can help, why or why not. And I think that's really helped us to understand what we're solving for, and what the communities we're supporting want to solve for, and how we can push for co-creation as opposed to a predetermined solution that may or may not fit the context of that community.
Future readiness and agency
Jumee Song: One takeaway I've heard today from all these wonderful insights is that future readiness is not simply about technical competence. It's about agency—the ability to learn continuously, to collaborate, think ethically, and to shape technology rather than to simply react to it. Thank you so much to all of our wonderful panelists, and thank you for your time. Thank you.
Cite this post
@misc{crooks2026_preparing_for_the_ai_future_with_ethics_in_mind,
author = {Crooks, Jared},
title = {Preparing for the AI Future with Ethics in Mind},
year = {2026},
month = {jun},
howpublished = {\url{https://www.openathena.ai/blog/preparing-for-the-ai-future-with-ethics-in-mind/}},
note = {Open Athena Blog}
}