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- Okay everyone. I am Karen Bonadio, Senior Director of Alumni Relations, and I'm delighted to welcome you to today's Alumni Talk Policy webinar, Women in Tech. The Alumni Talk Policy webinar series features ÌÇÐÄvlog¹ÙÍø alumni and panel discussions about pressing public issues. This webinar is being recorded and closed captioning is available. I'm happy to introduce the moderator, Kathy Hutson, MPP 2004, Senior Director of Oracle, will kick off today's timely and important discussion. Kathy.

- Thank you, Karen. Hello everyone, and thank you for joining. We are thrilled to welcome a remarkable group of women today to share their valuable insights and experiences. Our distinguished panelists are accomplished female alumni who have been breaking barriers, making a lasting impact, and navigating their careers in technology, business and policy in the public, nonprofit and private sectors. They embody the resilience, the innovation and the determination required to overcome the obstacles women face throughout their careers. I'm so excited for our panelists to share their journeys, and challenges and insights with us. I think their stories are a source inspiration. And I encourage you all to actively engage with our panelists, ask questions and learn from their journeys. Our panelists today are Fei Fei, MPP 2012. She's an Executive Vice President and Chief Strategy officer at LexisNexis. With her is Joyce Hayes. She's a mid-career, 2005. She's the Vice President of Technology Strategy at L3Harris Technologies. And Sarah Spencer, MPP 2006. She's the Director and Founder of DoveTail, and is a regular commentator on the politics of technology, AI, and technology for good. And lastly, Janelle Prevost. She's a Managing Director and Global Head of Investor Solutions at BNY Mellon. Thank you all for joining us. So let's start the discussion with our first question. And I'll start with Fei. Fei, what has been your path to what you do today? And what was the key to making the transition to where you are today from ÌÇÐÄvlog¹ÙÍø?

- Yeah, great question, Kathy. So after I graduated from ÌÇÐÄvlog¹ÙÍø in 2012, I joined the management consulting firm, McKinsey. So from there, you know, I was very interested in technology, so I did a variety of technology related projects and studies including core strategy work, operational efficiencies, sales and marketing, go-to-market, et cetera. And I was lucky enough to have a senior partner who had left McKinsey to join Google, who gave me a call one day when she was at Google, also a woman mentor, and said, "Hey Fei, I've got this really cool role that just opened up, and I think you would be a great fit for it. Do you wanna join me here?" And so that was when I made the transition to join Google. And I was in the core revenue business, which is the advertising business. So I was focusing on go-to-market and product marketing for our ads products. So, very much enjoyed my time there, continuing to focus on technology, and, you know, for personal reasons, my husband was landing a job in Northeast, So I left California, I left Google and joined, we moved to the Northeast and I joined a company called Gartner, which is again, is a very much IT focused research advisory company. About 5 billion in revenue now. And at Garner I held a few different roles. I started in product, helping developing product and improving existing product for our CIO clients. And then moved on to more go-to-market motion, working closely with sales. And from there I transitioned into LexisNexis about a year ago, a little over a year ago, taking a role of executive vice president and chief strategy officer. So my past has been very much in technology, I guess starting from McKinsey when I was a consultant focusing on technology industry 'cause I was very much interested in it. So I think I've been very lucky and having had some really good mentors along the way, and, you know, very, very excited to having this conversation today with all of the women leaders here and with the audience.

- Thanks, Fei. Janelle, how about you?

- Hi, Kathy. Thanks everyone. So my path is a bit different, but certainly listening to what Fei shared, there are some similarities. So what I do today and where I am in terms of having transitioned from technology into where I am today, it rests very much on my parents and on my education. So I'm from a developing country in the Caribbean, a former British colony that is very much rooted in the British education system. And in my final years of high school, you have to do A-level exams, which are foundational for entering university. And so in my country at the time, you could select from the arts, from the social sciences or the sciences, but you couldn't cross over the lines. But I was interested in all three of those. I wanted to do math, I wanted to do French, I wanted to do economics and I wanted to do computer science. And I could not accept that artificial constraint of staying in a single lane. And so I was lucky enough to have parents who went to bat for me and they had tough conversations with the high school principal. and class schedules got rearranged to accommodate me. And that sort of opened the doors, if you will, for others behind me who had interests as well, even at a high school age in technology as well as the arts and social sciences. So from there I went to MIT. I double majored in math and computer science. I chose MIT because of the focus in technology. And at the time I was there, it was the era of the .com boom. And so my summer internships were with the lab for computer science and at startups founded by classmates. And then when I graduated I joined Oracle as an applications engineer. So Kathy, I was there way way earlier than you, and it was a very different company at the time. And I remember the moment at Oracle when I realized that I loved technology, but I didn't want to write code anymore. I was in a code review meeting with my manager and a few teammates and I were literally having a debate about whether the curly brace after an if statement should be on the same line as the if or if it should be on the line below the if. And so that was a pivotal moment for me because I realized that I loved technology, I wanted to leverage technology for the advancement of economies and experiences, but I didn't necessarily want to create it. And so from there I made the decision to expand on my technology based from MIT. This led me to the Kennedy School. I did my MPA. I focused on science and technology there. And then I also pursued my MBA at HBS currently. And then from there I took a similar path to Fei in that, you know, I went to a consulting firm. I was at Booz & Company for a number of years, and then I spent the last 18 years in roles that are, you know, sort of launching from technology, always focused in strategy, transformation and using technology as a fundamental lever. So I spent time, as I said, at Booz & Company. I spent time both in the US and in the Caribbean. I was at Citi, I was at NCB Group and BlackRock, and now I'm at the Bank of New York Mellon and Investor Solutions. So that's sort of the path I've taken. It's sort of starting off in pure technology and sort of transitioning and building on the policy layer from the Kennedy School and the business lay over the last few years in my various roles.

- Great, thank you. How about you, Joyce? Thanks so much. And it's so interesting hearing everybody else's stories. I feel like I'm a bit of a hybrid between Fei and Janelle. I also started off in pure technology. So I grew up in the US and Florida, just north of the Kennedy Space Center, and was enthralled with the space program from day one. I was fortunate like Janelle that had parents who didn't look at me and say, Joyce, you're a little girl, you can't go into engineering. They said, "Go for it. You should totally do it." And so I found myself at Georgia Tech, studied aerospace engineering. And right out of college, actually in college, I was a co-op, I landed my dream job with NASA. I spent the first 20 years of my career at NASA. It was kind of two parts. The first part was hardcore engineering on propulsion systems. I worked on high pressure turbo machinery for the space shuttle main engines, which it's just like about the coolest job you can ever have. And then from there I transitioned from the pure engineering into flight operations. I worked at the Mission Control Center in Houston. I was a guidance and navigation officer as we were building the International Space Station, which was really cool because, A, you're building the International Space Station, but B, every time you launched a new piece, it was like a whole new vehicle. So you had to relearn and it was this constant cycle of learning. It was also a really interesting program too, because we worked very closely with our international partners, strong partnerships on that program. I think there was 21 different countries that had pieces and partnerships on there. So really interesting. And that's what started getting me interested in policy. I was actually on the ground, I was at the time we rotated people, so I had the chance to move to Moscow, Russia, and I was an onsite technical person in the Mission Control Center in Moscow. And I realized we were doing a lot of international relations, and I had no basis in it. So that was interesting. And then 9/11 happened, which was a pretty pivotal moment in my life. And so at that point I had been really narrow and deep, technically focused on human space flight and I decided I wanted to do more national security in the defense world. So combining that with the international relations, that's how I ended up at the Kennedy School where I focused on national security studies when I was there. Kind of did more of Janelle's path of coming out of the Kennedy School, I went into consulting. I consulted to government agencies and aerospace and defense companies trying to help them really develop their technology in a way that could more rapidly deploy it. I spent about 10 years in consulting with a company called PRTM. It was bought by PWC and then roundabout, we ended up buying Booz & Company. And so they all come together at some point. It was a really great insight into how government acquisition works, how companies are trying to deliver technologies. It really was more of a shift to problem solving for a specific mission and then problem solving to help everybody else's companies really be more efficient and more effective in getting technology out. From there, I actually, L3Harris was one of my clients, and just from a work-life balance, it made a little more sense so I moved into this role that I'm in now where I manage our research and development portfolio. We spend around $700 million a year doing research and technology to try to, or research and development to try to field more rapid technologies and ingest commercial technology into the defense world. So that's kind of my path. That's where I am now.

- Thank you, Joyce. It's good to hear some of the commonalities around our paths after the Kennedy School. How about you, Sarah?

- I feel like I have the opposite experience where I started off as like sort of tech neutral or even like tech naive in my career, and now I'm solely tech focused. And maybe that resonates with people on the call. But there is like this really interesting path that a lot of us have been forced into to become interdisciplinary and sort of multi-domain experts. And that speaks to Janelle's experience with the UK education system. My path has been sort of non-linear in so many ways. I spent the first 10 years of my career working with humanitarian agencies and being on the vanguard of response to humanitarian crises. So I was in Goma, Eastern DR Congo, and put on a plane to go and respond to Haiti and then put on a plane to go to and Iraq, and, you know, doing response and humanitarian response in line with the Geneva Conventions and international humanitarian law. And then I sort of fell into working for the British government. I'm a jewel American Britt from birth and at the time just chose the Britts over the Americans for no good real reason. And then spent 10 years working in British foreign policy and national security policy. And I think, you know, Joyce's comments around sort of national security really resonate because there's a lot of national security policy that obviously involves technology, but national security policy in and of itself is a very male dominated arena, as is technology. So the confluence of those two issues was interesting, especially for someone who has an American accent in British national security policy. That always played out in a really interesting way. And, you know, I hope we get to talk about sort of the International Space Station as a national security platform, or not, which is a really interesting angle. But then I was sort of serendipitous to have sort of sabbatical thrust upon me because I have a partner who's also in the diplomatic service. And as it happens when you're sort of coordinating careers, mine was the one that didn't really work out in terms of a being in a very small posting, not the huge amount of opportunities, this is pre COVID, for remote working, and at my level on my track. And I put my head above the parapet and realized that actually there was so much going on in the real world that, you know, went beyond sort of Five Eyes national security policy and conflict and humanitarian work. And in the last five years I've focused almost exclusively on, I think my journey has been sort of huge excitement about the opportunities related to AI and machine learning for humanitarian and forced displacement contexts and thinking we could revolutionize the industry that is sort of operating in 1960s Biafran Civil War and we could just bring it into the 21st century to a current state where I feel like after five years I feel a bit less enthusiastic about that path. I'm not to give a plug for the core curriculum for the MPP, but I do feel like the ethics and the sort of focus on trade-offs in public policy have really helped me in my sort of new technological focus career to think about all of the different angles about where certain policies related to technology and public policy or technology and conflict or national security policy or humanitarian aid has really been brought to bear. And now I am still on sabbatical from the government and I get to focus on, as an independent consultant, a consulting firm, get to focus on supporting nonprofits UN agencies, international organizations, thinking through or navigating the hypes, and the harms and the hopes of AI and machine learning like way down to like thinking about the full stack and like the ethics related to all of that and how to deploy it, and how to design use cases and think about what it means to deploy AI in refugee context in Kenya, for example, where I live.

- Great, thank you. And thank you all for sharing your background. I wanna get into a little bit deeper discussion around some of the things that you've worked on, and this area, I think you started the conversation. But I'll start with Joyce on this question in terms of, can you share some examples of decisions or initiatives that you've led that have influenced the development or implementation of technology within the organizations that you've mentioned? I think you're on mute.

- You would think after two and a half years I would not make that mistake. So yeah, I'll start really in my primary role. I'm very fortunate in that, I said we manage a large, I manage a large portfolio of research and development, so I have the opportunity to just constantly scan what new technologies are happening in the broader world, right? And which one of those are relevant in a defense and aerospace context. So I get to help shape the portfolio. We look at tech trends, we look at where we are today, we look at what our customers need and then we try to figure out how to marry that. So I feel like I get to influence that on a daily basis. Kind of playing off something Sarah said though, there is a lot of hype on a lot of technologies, AI being the big one right now when kind of the ChatGPT and the use of the Large Language Models. And that's been a really interesting journey because the problem sets are very different in a defense construct as they are in a commercial construct. So let's go back like say three or four years, and we were partnering with a big tech firm or we were having conversations with one of the big tech firms out on the West Coast and doing machine learning and image recognition, and they said, "Okay, well, what's your a hundred million dollar problem? And we'll come help you figure out how to solve this." And it's like, "Okay, well we're not looking for, is it a black cat or a brown cat, or is this Brie cheese or Camembert. You know, we're looking for, if you're trying to look for a pop-up airstrip in a jungle and you only have one picture that comes three times a week, how do you do AI and machine learning on that?" So it's been really interesting for me kind of helping to shape the thinking on how do you solve these very discreet problems, things like humanitarian aid, things like national defense. It's not a big ubiquitous issue, it's a bunch of little tiny use cases. And so I've been able through my role to kind of help shape our development. We couldn't solve it with the commercial tools that were out there so then we started investing in synthetic training data, right? The AI models are only as good as the data that you train them on. And if you only have 10 data points versus 10 million, then you can't get a good answer, so. So that's kind of how I use technology to sort of shape where we should go next. A little bit of a ramble, so hopefully I was clear on that.

- No, thank you. That was very helpful and very interesting to hear how it's applied in the space that you operate. How about you, Fei? Any examples?

- Let me make sure I unmute myself first. That was a great example, Joyce. So, you know, just building on the AI point, right? A ChatGPT took the world by storm last year and everybody, every industry tries to get on it. I think, you know, nowadays as it should be, any technology implementation or development in any organization should be a collaborative effort, right? There might be a team or leader leading it, but it's really collectively from product organization, technology organization, all the other business units functions that's coming together. And I just went through a perfect example of that. We at LexisNexis, so a background, you know, we provide a sort of online research tools, decision analytics to legal professionals, help lawyers win cases and manage their work more efficiently and serve their clients better and grow their practices. So that's what we do with at the core of LexisNexis. And with generative AI, we just commercial launched after months and months of, you know, incredible effort, we just commercially launched a product called Lexis+ AI. It's designed to transform how legal professionals do their work. So a basis uses our large repository of accurate and exclusive content from LexisNexis that we built over the years and provides results in seconds versus minutes. Some of these, you know, solutions takes minutes to come up with answer. We provide results in seconds featuring, you know, conversational search, intelligent legal drafting, actually helping you coming up with the first draft of a document, insightful summarization and document upload capabilities. So I think that is just a good example of how, you know, we're jumping on generative AI and quickly working in a coordinated fashion and put a commercial product to market and it's gaining a lot of attractions with sort of the early adopters. So I think that's the one example that I wanted to give. Another one from earlier in my career, as you were talking about leading on technology decisions or making technology decisions, as I was working closely with the B2B sales organization, you know, there's a lot of ways to transform, or there was a lot of opportunity to transform how sales do selling using technology, right? It's no longer the traditional picking up the phone, call the prospect, set up a meeting, show up, present the solutions and so on and so forth. There's a lot of technology out there to help transform a sales organization. As an example, you know, Salesforce, which is a mostly commonly used CRM system across many B2B sales organizations. There's a lot of functionalities and you could use to track, gave a 360 view of a client, tracking the interaction with the client, building a pipeline reporting metrics. Another tool that's called SalesLoft, which is helping salespeople doing prospecting better. So they're actually able to look at when they send an email to a prospect, what is the open read, what is the click through, whether or not the prospect click on a link that they send over in the email. What part of the email are they most interested in? There's a lot of sort of intelligence, decision intelligence, attached to a sales tool. So I've done quite a bit of that in my experience working with sales. I think it's tremendous opportunity how much we can use technology today to really transform the way that we work. Whether you're internally working in a sales motion or externally helping our clients was generative AI efforts.

- Thank you. Sarah, can you share some of your experiences as well?

- Yeah, I mean, I think where I started was really when I wrote a paper, you know, like following on the story I was previously telling where I went on sabbatical, and just wanted to explore the possibilities of new technologies or advanced technologies, but really focus on the AI machine learning for the humanitarian industry. And when I say humanitarian for those who are not humanitarians in the room, I mean, like life saving assistance within 120 hours. It's really not about poverty reduction, it's about, you know, things that are happening in Gaza right now real-time, or in Afghani , most recently with earth earthquake response. And I worked with the Overseas Development Institute, ODI, which a think tank in the UK, and it was 2020 I think, and I said like, "What are we doing on AI in humanitarian aid?" And it was crickets and tumbleweeds. And there wasn't really, they were very keen, but the industry itself, which is 30, 40 billion US a year, lots of agency, lots of people, it was just like maybe the data scientist role, maybe like one person who did data retention and trying to find sort of uptake and interest for some of the research in that paper was low. And what's interesting now in terms of the wake up call for the aid industry, humanitarian industry has been ChatGPT obviously because it's in the papers. And so there's now been this like sort of flurry of emails and calls, and everyone's saying like, "LexisNexis is doing this thing or McKinsey is doing this thing, like what are we missing? What are we missing?" And I think what's interesting about, it's not to say that like I was ahead of the curve at all, but it was more about just like personal interest really, and having the time and space, which is a rare gift for women generally to have time and space to explore a specific issue, in research and then all of a sudden the interest sort of coming home, the chicken's coming home to roost. And I think what has been interesting for the humanitarian sector is not only a conversation about the efficiency and productivity gains that will be leveraged with AI machine learning, which was the sort of the start of the conversation in 2019/2020 with decreasing budgets and pressures on that, now with Ukraine, now with Gaza and everything else, but also should we? Like it is efficiency and productivity gains, are efficiency and productivity gains in the delivery of social services ultimately ethically right? Is that where we should be heading? Because if that holds true for humanitarian aid, it also maybe holds true for the delivery of public and social services in stable low and middle income countries or high income countries as well. So I think the journey, the learning journey for me has been excitement over the ability to reap efficiency and productivity gains for ultimately our clients at the end of the day and do more with the same amount of money or less. And then also the real worries about what that means in terms of arguably the world's most vulnerable people in terms of forcibly displaced and surveilled and forced migrants. The last thing to say about sort of the humanitarian agencies is that they, I mean, for the lawyers in the room, they sit on a lot of the international organizations who are classified as international organizations, sit on a huge amount of personally identifiable information which they use to deliver their services much like the agencies in the US and the Department of Works and Pensions and other agencies in other governments, and they're not subject to the same kinds of regulations 'cause there's a special clause for them. So there is a really weird space for wiggle room for international humanitarian organizations, for international public organizations in this space, and I'm thinking UN agencies and the 37 million people or 40 million people that they hold sort of sensitive information on and how they use that to both power AI and machine learning for really greater efficiency and productivity gains, but equally have they who owns that data and where the power lies and where the agency lies for those people contributing that data to receive aid in public service.

- Great, thank you. It's interesting to hear how the increased use of, or focus and technology, particularly around AI and data begins to lend itself to some of the speak that we have in corporate America around efficiency gains and, you know, KPIs and things like that. And we'll revisit that later in our discussion. But Janelle, would you like to share some initiatives that you've worked on over the course of your career as well?

- Sure, sure thing. So I mentioned earlier that in my career since leaving the Kennedy School and HBS I've worked in management consulting and within financial services firms advising, developing or implementing strategy and transformation efforts with digital and technology as a core foundational pillar. And so in financial services like many other industries, there's been this digital transformation underway for more than a decade. And so the considerations I take into account for growing or transforming the organizations I've worked in, have been centered around a very simple framework: people, process, footprint and technology. And I've seen technology become more and more of a horizontal in that framework, cutting broadly across the people, process, and footprint vectors rather than being a parallel or standalone vector. But the example I actually wanted to share was from earlier in my career from my days as a student at the Kennedy School. So I spent this summer between my first and second years at the Kennedy School as an intern with the UN, UNDP, to be specific. And the initiative I worked on was the creation and launch of internet community centers, this was back in my home country, and it was focused on launching these internet community centers in rural areas which had little to no access to the internet. And so my role was to conduct a survey. So I went door to door in the various communities. But it was really around how we use the results to help in the design of the centers and in coming up with what technology should or should not be made available, whether it was desktops, or laptops or printers. Like that was the power I think of the initiative. because we left there with an understanding of, or the work I did led to an understanding of what technology should we be providing. We left also with an understanding of how access to the internet, or how access to information would be helpful to members of that community who were largely farmers and fishermen. And so the people side of things, what did they need, what skills and learnings did they need to sort of ramp up in. That was the people side of things. And we also had an understanding from the survey of what they were doing today, where they needed information, and what processes they were using on a day-to-day basis for their basic communication or for learning about their trades. And so that was the process side of things. And lastly, we were able to use the survey information to align on the best location for the centers, particularly those centers that needed to serve multiple communities. So that was where the footprint aspect came in. And I was reflecting on this, and again, this is way earlier in my career, but it's the same framework around technology, it's implementation and the adoption of it. It applies whether you're working in large corporates like what I'm doing today, or in small communities that have a need for access to information, that have a need for transformation, and that have a need for sort of advancing learnings and using tools in order to advance, whether it's an economy or a PNL. So that's what I wanted to share with the group today.

- Thank you. That's fantastic. And I just wanna stay with you for our next question in terms of, you know, we're all here, we've all worked across technology. As I mentioned in my intro, you're all trailblazers in your own right in terms of the things that you've been able to accomplish and the spaces that you've been able to occupy, so to speak. So can you share personal anecdote or experience that highlights the importance of women's voices in technology?

- Yes, happy to. So I was fortunate to grow up in a place where the leaders in business, and government and society all looked like me. So my country had the first female prime minister in the Caribbean from 1980 to 1995. I had a mother who was an attorney. She had her own practice and she held leadership roles in the National Council of Women. And in addition to that, I had a father who was a relentless advocate for me and my sisters. And when he entered electoral office, he continued his advocacy for women on a broader scale. So I had early and consistent exposure to voices of women in leadership and supportive voices of men helping women advance into leadership. So I think the first thing is, at least for me, exposure matters or exposure mattered, and especially exposure at an early age. For me, it's critical for young girls to see women as creators and adopters of technology so that they can also visualize themselves in that space. And so there's an aspect of exposure, early exposure, but there's also an aspect of diversity and diversity mattering, especially in the realm of technology, which is the alpha and omega powering business, government and society. And we talked about it, I think all of my colleagues already talked about it, how critical technology is as an anchor for problem solving. And diversity goes hand in hand with that, diversity of thought, diversity of experience, diversity of gender, both the visible and invisible elements of diversity. All of these are critical in getting to the best digital experience for investors, mitigating risk, reducing complexity and processes, identifying patterns in data. And so in my career I've seen this diversity within technology translate to better decision-making, happier customers and a workplace environment that truly focuses on team. So for me it's, I think the two elements of why women's voices in this space are important. For me it's about sort of having that early exposure and then having that diversity because that creates value across the board.

- Great, thank you. How about you, Joyce?

- So it's interesting, I had strong family support, but, you know, if I look back, I think Sarah mentioned in the defense and aerospace sector, it's 10 to 20% women, max. I remember I played tennis in high school, and I was telling a senior, "Oh, I'm gonna go to Georgia Tech and study aerospace engineering," and he looked at me and said, "You can't do that, you're a girl," and I was like, "Watch me." So I think there's a bit of feistiness that you have to have. I mean, I had strong family support, and I was bright and I knew that I could do it. But people threw a lot of roadblocks. Even I was going in after the Challenger accident, so the aerospace industry was shrinking. I got a letter from Georgia Tech saying, "You're accepted into aerospace engineering, but just so you know, there's not a lot of jobs coming out the other end." So there was roadblock after roadblock just saying, hey, are you really sure you wanna do this? So I had to have a really strong sense of this is my passion, this is what I wanna do. I think that that's really important. Because of those challenges, I have always found my voice. I am not afraid to stand up and say, this is right or we should do it this way, or yeah, you know, I'm not comfortable with that. I think that willingness to stand up and say your opinion, even if it doesn't fit with the prevailing winds in the room, it's important to have that voice. And I see that making an impact. I was at NASA in flight control when we lost the Columbia vehicle. And if you ever look at problem resolution and decision-making, there's a Columbia Accident Investigation Board Report, which is very well written, but the role that I was in as a flight controller, our job was to surface issues and solve them. And it was your obligation, if you told somebody there was an issue and they didn't listen to you, it was your obligation to go around. That didn't happen in Columbia. And it's really interesting, one of the key findings was you have to have a diverse team and you have to have a space for somebody to say something different. And I think in technology above all, that's got to be a key player as we're fielding solutions so that you don't have, you know, these inherent biases coming out in the software that are just there because nobody thought anything different. So I cannot tell you how important I think it is having that voice.

- Thank you, Joyce. Fei, how about you?

- Yeah, incredible stories from Janelle and Joyce. I think my family support and then the environment around me, unfortunately is probably opposite to both of you. So I have a TED Talk where I talk about resilience. And in the beginning of the TED Talk that I talk about the story where I was, you know, born under the one-child policy in China in 1980s and when my parents had to go to the hospital, to give birth to me, well, because of one-child policy, you know, a lot of couples in China wanted their only chance to be a boy. So when my parents were in the hospital, they found out that my mom needed a C-section to give birth. And during that time in my hometown, you know, C-section was considered still quite risky, so a nurse handed a form to my dad and one of the questions on the form said, you know, if the baby and the mom are both in danger and we can only save one, who would you like us to save? And even though my dad didn't have any education, could barely read, you know, through the help of the nurse, he understood the question and he scribbled on the paper, if the baby is a boy, save the baby, otherwise save the mom. So that story was later told to me by my grandparents. And unfortunately, you know, I was born and my mom and I were both okay. But that would just, you know, give you a view of how boy was very much preferred than a girl in the time that I was born and in my region in northeast China. So, you know, growing up there were two expectations for me. One was get a job working on the local assembly lines in the local factory, and two, was find a good husband. You know, so fast forward and that even though the latter is true, fortunately the former is far from reality. So I'm thankful every day to sort of all the amazing colleagues that I work with, all the mentors I've had through the years. You know, talking about, a little bit to Joyce's point around, you know, how people tell you you can't do things and make you wanna do it more and make you succeed. I was reading this new book that came out on Elon Musk, he's a sort of authorized biography by Walter Isaacson. And I'm just getting into it, but in the beginning I talked about how Elon, and I'm by no means comparing myself to anybody like that, but I'm just talking about how when he was growing up in South Africa as a child, he was really bullied, like he was bullied into the point where, you know, his brother couldn't recognize his face. And that along with some other challenges he faced as a child, just propelled him to really work hard and wanna succeed and want to get out of that situation. So I think sometimes adversity actually helps you for women and men. I think, you know, there's just so much progress that has been made in organizations on helping women succeed and there's so much more that could happen. I remember when I first joined McKinsey, there was this retreat that you bring your partner, you know, you plus one, and sort of they wine you and dine you in a nice hotel for a couple days or a weekend, couple days. And I was remembering the consultants being in the ballroom for a whole morning talking about, you know, business trend, firm values and so on and so forth. And the spouses, so the plus ones, had their own activities. And so by lunchtime I was chatting with my husband, I was like, "Oh, so how was your morning?" My husband said, "How was your morning?" I said, "It was great, how was yours?" And he said, "Well, I just was in my hotel room watching TV all day." "Like, what? I thought they had activities for you." Well, he said, "Well, the activities were either a spa or facial, I wasn't really interested in any of any of that." So it turns out because of the overwhelming number of men as consultants, you know, most of the partners were women and so they didn't really think about having something different than a spa or a facial. Now, that was many years ago. The activities look very, very different now. And I, you know, love my experience at McKinsey to death, but I was just one instance of how sort of unconscious bias, how we should really think about and inclusive from working to sort of these fun activities retreats, how inclusive we could all be. McKinsey just published the Women in the Workplace study, 2023, just this month, early October. And it talks about how women is now consist of 28% of C-suites, which is still low, but significant progress compared to many years ago. And out of that, only 6% were women of color in the C-suites. You know, 28% of women total, 6% are women of color. So just tremendous progress that's been made, but a lot more opportunities for us all, you know, to do better. You know, things like formulating official mentorship programs for women, you know, really track the diversity metrics across all levels from junior level to manager level to senior leadership level, and how do you have transparency and visibility into all those metrics and therefore, you know, organizations can work towards goal to get to a better number. So I think that's again, societal effort that demands not just women but mostly men as well demands it from all of us.

- Thank you so much. How about you, Sarah?

- That's so fascinating, all these stories, and I just feel like I'm saying a lot of quiet amens in the backgrounds in my office of one, but I sort of wanna say that as the mother of three boys, which is like God's joke for a 21st century feminist, when I go to H&M and all the NASA T-shirts, and this is a Joyce, all the NASA T-shirts and the boys section and not in the girls section. How is that still happening in like 2023? Like this is a problem, right? And there are subtle directions that we're giving to girls and women about the roles that are appropriate for them. I also, to Fei's point, like my spouse also works in foreign policy and national security space, and the roles that I've been given, I mean, in the British government I think ambassadors weren't allowed to, I can't remember it, I mean it's being recorded so I can't officially say what the policy was, but it was something like up until 1980, women couldn't be ambassadors because who would serve tea, which is a real thing. And then like fast forward to that, it was sort of like, what's really confusing, 'cause what's the man can do as a training passed for a female ambassador? So like both in foreign policy and national security, that's been a real challenge. But I wanted to not share a personal anecdote. I wanted to share Diane Forsyth's, who's a sort of famed anthropologist in a machine learning and AI, her experience trying to interpret or understand the culture of data science and machine learning in the '90s. She sadly died, like, from a tragic sort of hiking accident in Alaska in late '90s, 2000s. But she had done some really interesting anthropological work around data science and machine learning, and one of these guys come in saying, "We are gonna find the best algorithm to deduce why people have migraines and we're gonna source the domain expertise from only the doctors." And all the doctors were male and they precluded, discounted all the information coming from nurses, all the information coming from migraine sufferers themselves. They didn't ask them any of those questions. I'm sure it was really interesting sort of anthropological discourse and lots of other things around the culture of technology and the sort of anthropological culture of technology. And what she surfaced was that actually nurses and clients coming in for treatment of migraines, many of the women who were coming in also had sort of correlating like correlations with intimate partner violence and gender-based violence, which was not being surfaced in the research because domain expertise rested with the doctor, like the top of the pyramid in this machine learning engineers design, so they only went to the doctors. And at that point in the '90s, it was really only men that could do it. And so if you fail to exclude or to account for the variety of voices and if you fail to account for user experiences, and any of these things, you just don't make a good product. So whether you're like, man, the public sector and like thinking about impact on society, that's obviously harmful. If you're thinking about corporate profitability, your deliverable is crap, right? Like, it's just not gonna deliver for the client because you're failing to meet the whole range of, of like use cases or of like needs that the user might present. And I also think the last thing to say that Joyce mentioned about roadblocks, like who's giving you those roadblocks, and why are they? I mean, in sort of the foreign policy and national security world, you always think about incentives and why someone's saying something that they are. And I just think as a woman or as anyone who is an unrepresented voice in a space related to technology or national security or underrepresented field, you have to always question why people are trying to block you or your voice from that space. And some of them go back decades and centuries, millennia. But it's really important to challenge those roadblocks. And you may be the lone force and you may have the time where you think I'm the only one, you said the awkward thing that no one wants to hear in a private classified space, but I said it, I said it and I'm walking away and I feel okay about it.

- Great, thank you so much for your remarks. I wanna leave some time for questions. So I'll hold the last prepared question that we have. I'll come back to it if we have time, but I wanna open up the discussion now for the participants. Just a reminder to everyone who wants to ask a question that it's being recorded and will be posted online. To ask a question, we ask participants to raise their hands. Kristen will notify when it's your turn to speak. We would appreciate it, and this is with love from the Kennedy School, "We would appreciate if you could state your name, degree and year before asking your question. And please remember that all questions end in a question mark." So I think we have our first question from Andel. Sorry, yeah, Andel.

- Yes. Hi, Andel Koester, MPP, 2011. Thank you all for your time. Several of you mentioned starting your careers in sort of a technical capacity and finding your way into policy later. For those of us who have started our careers, or in my case are many years underway on the policy and program design side, but have often been in the technology adjacent space, what would you recommend is the right way in or the right balance of technical expertise and sort of that higher level policy understanding of some of the problems that you're tackling?

- Anyone, who wants to take it?

- I mean, I'll start and maybe somebody could add on. I think, I think in the technology space you'll find that engineers and technologists tend to be quirky and very detail-oriented and focused on knowing what they know. And so one of the strategies that I've used is, and I did not take Ron Heifer's class, but he uses this, I would zoom in and understand the technology at a way to talk level, right? Like, I'm not getting into the bits and bites, but I can understand the application of the technology and then zoom out and set it in context. And I find, because I deal with a lot of really detailed, now really detailed technologists, if I can go in and empathize with them and say, yeah, I understand that that's a really hard problem and you guys are solving it this way, but now let's talk about how it has to work, what price point you have to hit, you know, how it needs to be available. I think that zooming in and zooming out is a strategy that's been effective for me.

- I think, Joyce, I would absolutely echo what you mentioned there around, I think part of the power, if you will, of having that training from the Kennedy School is the ability you get or the training you get that forces you to analyze across different dimensions: business, government, society, right? I think the other point I would add, Andel, for you is if you're looking to make a transition, I think network, use your network, that's probably like, have conversations one-on-ones like this with people within the Kennedy School community who are doing the kinds of things or who are in the kinds of roles that you'd be interested in. I know we always talk about it, at least as students way back when we would always talk about the power of the network, it is true. And so leverage the privilege you have being part of the Harvard community, get those conversations going. Leverage LinkedIn and make your way. And have those sort of safe conversations with whether it's people like us or others within this space, that's really, I think probably one of the most powerful tools you could leverage that's within your reach.

- I would agree with that. I think I was gonna say the network point, but just the, you know, the education is really not even about what you learn, but how you learn. I think your training from the Kennedy School that gives you the ability to sort of both go deep in the problem, solve it with your technical skills, but also really take a step back and look at a holistic picture, look at an intersection between public sector, nonprofit, you know, private sector, all of the skills just go with you and it comes in handy as you really any area you're trying to get into. So I think think about that and utilize that, and again, to echo what Janelle saying, the more people that you talk to on your specific question that you're trying to do, the more ideas you get and the more focused you will be. So I think, you know, the point around talking to your network, reaching out to people you know and reaching out people that you don't know. The more people that you talk to the more just ideas that you would get that will help.

- I'm gonna say it quick 60 seconds. On the non-tech person who's leaning into the tech world is that I find that the real hardcore techies really don't value non-tech experience, and it's very difficult. And this is where Diana Forsyth bit on domain expertise, right? I have a bit of COVID, sorry. And I would say that the same thing that applies with trying to understand, like to Joyce's point about understanding how a car works, but not the inner, like, functionings of an engine are really important. So you can like zoom in and zoom out, but also push back on that, right? There is a lot of people who now value, economically value machine learning expertise and data scientists and AI engineers because that's where the money is. And so therefore anyone who's not a technical expert doesn't necessarily have voice. And I say this from friends who are at OpenAI right now who are saying like, "We're at the bottom of the totem pole, not necessarily because our views aren't are valued, but because their views are." So, it's not that you're being discounted, it's that their views are so much more valuable. So push on them. So push on them. Because actually to be fair, regulation and public policy around new technologies is so needed. And so all of us need to upskill who are the non-technologists in the room, to help our government or think tanks or other people sort of get to the place where they need to be. So push for it.

- Thank you so much, and thank you, Andel, for your question. So we have about three minutes left and I wanna give the panelists an opportunity for some final thoughts before we end the webinar. So I'll ask the question and anyone can feel free to chime in. In terms of our last prepared question was around how do we ensure that innovation and technological advancements are balanced with ethical considerations, especially when our decisions have an impact on the public and the society as a whole? So we'll leave your thoughts on that question as our closing statements, so to speak. Sarah, if you wanna start or Joyce, or Fei or Janelle.

- I can jump in really quickly and say, but I think in that question, the difference between innovation and ethics is a missing piece related to regulation, and in the design of corporations and their teams, we need to figure out where ethics happens, especially for AI. And sometimes it's part with corporate and legal affairs, sometimes it's part with product development, very rarely, but sometimes it is. And none of these corporations, as far as I can tell, have figured out where ethics actually sits in the design process and development process. But also whose ethics, right? I live in Kenya, I live in Nairobi. Whose ethics? Who are we consulting? For what our ethical principles are and how we sort of like roll out general principles related to ethics and ethical development of product. And I think all of that sort of shapes both regulation and innovation. And there is a wider geopolitical contest that's happening right now, and particularly in the US there is a, who's the tail and who's the dog and who's wagging who with regards to technology leaders and the US government and intelligence committee, you know, and how they're using those narratives to .

- So I echo the point on regulation. I also think with, especially with AI, is so new and involving so much, so quickly, I think regulation also needs to evolve over time, which regulation is usually not evolving very quickly and it's, you know, the government and business leaders really need to establish clear guidelines and make their policy and regulation evolve with technology over time. Also establish really clear oversight and educate all the various parties involved. I think education is key here. You know, bring awareness to the possibilities to what's going on, what could happen. Data privacy I think is another key point. You know, how do we protect data that, again, going back to AI, how do we make sure the data that's being used to train these Large Language Models are, you know, regulated and following certain guidelines and rules. I think all of those are sort of getting into new territory, I mean, the problem deserves a new territory, all of these things that we talk about are not new territories. We know how to work together in general, we just have to, you know, do it even better.

- So I'll jump in. Ethics and AI is actually a pretty hot topic in the defense world in the US because there's such a bush for ethics. The US Department of Defense actually came out with 10 guiding principles for how to employ AI. Internally, we actually look at, it is kind of a double-edged sword, right? We've drafted a policy internally on how to do ethical AI for our engineers and our developers, and then kind of we're piloting a procedure because we have to strike the balance of make sure that you get that thinking out there and that we're being thoughtful, but we don't have requirements for the customer. So we have to make sure that we're still responsive and not slowing things down. So we've taken the tact of putting out a draft policy, starting the procedures, and seeing how they work and then adjusting them before we implement. But the thing for us is that it, particularly in the defense world when you're thinking about the decisions that could be made, our customers don't trust it, right? So we are trying to figure out how to build a parallel system that shows what's happening on the inside so that we can help our customers gain trust that in all of these crazy edge cases that you're gonna come up with, that the software will ultimately project an answer within the right ethical standards. So it's a very complex problem, and so we're attacking it through a bunch of different ways, but it is definitely a work in process. But I will say from my view, our US defense customers are very, very concerned about it. And, you know, trying to put the right things in place. It's a big, giant machine. It's slow, it's not all happening in the right place, but we're marching towards that.

- Thank you. Thank you so much for all of your insights and for sharing your experiences. I know I've definitely walk away from this webinar being even more inspired than I have been before. So thank you again. And I'm going to turn it over to Karen to wrap up. I think we can have another hour talking about these topics. But again, thank you so much.

- Yes, I just wanna echo Kathy, thank you to all the panelists for dynamic discussion. And for all the alumni who joined today, we hope you enjoyed the discussion. Our next ATP will take place on November 30th and will focus on climate change. For the most up-to-date school news and events, please visit the ÌÇÐÄvlog¹ÙÍø Alumni website. We look forward to keeping you engaged in the future months. Enjoy the rest of the day. Thanks again.