Noelle Russell recounts her 20‑year tech career—from IBM to Red Hat, VMware, Amazon Alexa, and Microsoft Azure AI—highlighting how her identity as a Latina, a woman, and a mother of a child with Down syndrome shaped her perspective on technology. She describes early work on Alexa, where she built mindfulness and kindness skills despite being the only person of her demographic on the team, and how that experience revealed the need for inclusive product design. At Microsoft she coined the "baby tiger" metaphor to illustrate the immature, uncontrolled nature of early AI models that are cute but lack safeguards. This led her to found the AI Leadership Institute and author Scaling Responsible AI, advocating for a shift from AI enthusiasm to responsible execution. She introduces the SAT framework—Security, Accuracy, Trust—as the core pillars for responsible AI, emphasizing the necessity of designing the human‑AI experience. Throughout, she urges technologists to bring diverse, lived‑experience perspectives to AI development, arguing that inclusion, not the technology itself, is the true driver of innovation. The talk concludes with a motivational call to teach machines not only to talk but to listen.
Chapters
So 12 years ago, I was a principal cloud architect at AWS, or Amazon Web Services. And I, well, took a while to get there. I actually started my career at IBM. I was there like 12 years, but I started there during a time you might remember, the first time the world was gonna end, Y2K. You remember, right? Yeah, we saved the world that night, by the way. You're welcome. And I got very excited because I was like, oh, this tech stuff's pretty cool. I went on from there to Red Hat, open source capital of the world, went on from there to VMware virtualization. Eventually Amazon was like, you should come build virtualization here. And I was like, you're right. So I joined that team. Fast forward, I'm there a couple months and Jeff Bezos sends out an email. I get an email in my inbox from Mr. Bezos himself and I'm like, I was like, oh my gosh. And in this email, he invites me to become part of a brand new team. And this team was gonna be the team that built the Star Trek computer. We had a motto, work hard, have fun, make history. And I was all about it. I was like, let's go. Now, the challenge of course is that I did find out later it wasn't written by Jeff Bezos. It was like a recruiter that wrote that email. But I felt like he was speaking to me. And I took that chance. I became an early member of the Amazon Alexa team. I built in the first year over 100 applications, had 10% of the entire codebase that I built. But it's kind of funny because I built it maybe in an unconventional way. It was a struggle, honestly, in those early days of Amazon Alexa because I was the only person who looked like me. I was the only woman on my team for almost 2 years. I was the only Latina. Unfortunately, that is still the case today on the teams that I am on. But what was maybe more unique is that I was the only mom on the team. I was the only one taking care of my dad. I'm a mom of 6 kids today, but then my firstborn son, his name is Max, he was born with a condition known as Down syndrome. And it, no one knew it, I wasn't saying it, but it was really the motivation for like, wait a second, I can help build tech you can talk to? That means that all I have to do is teach my son to talk and the world opened up for him, and it changed my entire perspective. After I joined the team and I realized I was a little bit alone in the direction I wanted to go, I started building applications that my teammates did not understand. I was building mindfulness. If you go to Alexa and ask for mindfulness, that's me. Or daily affirmation, kindness, Christmas kindness, corporate kindness, you get the idea. Like, and everyone was like, "No one needs kindness in the kitchen." And I was like, "Just you wait." But they weren't pairing parents yet, right? They didn't have the stresses of being what I call the sandwich generation. So I got very excited about this because I realized that my unique perspective was not only changing the life for the people that I work with, for the people in my own home, but it was actually changing the product for everyone. And that unless so many more people started providing this unique perspective, the product wouldn't serve everyone. So I Then 4 years later, got recruited by Microsoft to help launch what today is known as Azure AI Services or Cognitive Services. But back then they were just baby little AI models. I was hired to help researchers productize their AI to go from a world where they could basically just ask any question and test out answers to a world where they had service level agreements and deadlines. They needed someone like me, an excited person, very positive to say, It's gonna be okay. And we productized 17 research models into production. But I, I used to say I heard cats. Have you heard that term before? Like, I used to say that, but I realized in the world of AI, it's not really cats at all. It's more like baby tigers, right? It's like little baby tigers. And so I had all these little baby tigers around me. And you might remember this moment, your baby tiger moment, when you started using ChatGPT or Claude or Google AI mode and you gave it a question and it gave you an answer and you're like, well, that's not terrible. Like that's its whole job is just to get you to be like, well, that's not terrible. What else can I ask? It doesn't know what truth is or humanity or fairness. It's just trying to get you to say, well, that's not half bad. And that's what baby tiger mode is. But my job was to be like, okay, cute little baby tiger. I see you, you're fluffy, I like it. But look at these paws. How big are you going to be? Razor-sharp teeth at birth. What do you eat? How much do you eat? Where are you going to live? What happens when I don't want you anymore? It became shocking to me. I mean, I should tell you, in addition to being a mom and, you know, a caregiver, being a Latina and a woman, I was also, wait for it, a cat owner. Hugely divergent at Amazon. Like, they were like, "Who is this woman?" But it taught me that like in this mode, in this baby tiger mode, no one's asking these super important questions. And it came from my lived experience that those questions were born. So at Microsoft, I became known as that person, you know, that person in the room who's like, "Heh heh." Can I ask you a question? And that question was always around, have we thought about what the future looks like? Optimistically, yes. But also, what's the worst thing that can happen? In baby tiger mode, everyone is always enamored with how this goes. They're always like, oh my gosh, it's adorable. Oh my gosh, I love it. No one wants to be the one that kind of kills— they call me buzzkill for a long time at Amazon. Because I'd be the one who was like, let's think about this. Now, from there, right, I got this opportunity to now become this person. I, I decided, you know what, the world needs to know this. It's when I shifted my focus from helping build technology products to helping teach the world to actually listen to the problems in the world and build AI that responds to those problems. So I decided to start a company, the AI Leadership Institute. That was in 2016. I then, though, also decided to write a book. Took a lot longer, actually, but I wrote a book called Scaling Responsible AI: From Enthusiasm to Execution. And what I learned in that process is that most people are stuck, if you will, enamored by baby tiger mode, enamored by what AI can do. It is amazing. But now what I've found out is that in the new world, AI leadership When you get a new job, when you start a new company, you might never hire a human, you might never manage a human, but you will definitely be leading machines. And in that change, you now have to have the number one skill as an AI leader. The number one skill to manage a machine is clarity of thought that you need to really think about what you want, articulate what you want with words that a machine can understand. And here's the sad news. Over the last 10 years, we've gotten further and further away from that clarity of knowing who we are and how do we wanna say things. We use emojis and LOLs, right? We use these short words and truncations. And now these machines are counting on us to be clearly, definitively identifying what we wanna do and how we wanna build it. So as I, you know, moved into this direction, I started working with all the major brands in the world, airlines, manufacturing companies. They were all like, what is this AI stuff? Do we need to use it? And they were already like, we got AI, we have baby tigers everywhere. And I'm like, yay, this is awesome. So my goal was to walk in and help them harness, right, those baby tigers, ask these questions, But I found out that there's a pattern. If you look long enough at anything, you'll find. And there are 3 things that every company ended up struggling with. And if I tell you this now, you can be the voice in the room that raises their hand and goes, "Eh, have we thought about this?" The first one, well, I'll just give you an acronym. I grew up at IBM. Sorry, SAT, right? It's a test I aced in high school, but it's also a really nice acronym for the most important concepts in artificial intelligence. Number 1, security. There's 2 lenses, not just how do you secure the data you're using to build your AI model, but also how do you manage the attack surface that's coming in an expanding world of AI. Number 2, A, accuracy. Do you know that it is actually possible to build a model that never lies? You just have to design it that way. It takes a human to do that work. And T, trust, the most human thing that you can do. You are going to have to design how humans and AI work together. It's called the human AI experience. We used to build UX, right? User experiences, designed user interfaces. Well, now we're gonna have to design how AI will participate with humans. And that is 100% you. You with the 20 years of experience, You who have done this job forever, this is not a time where you are going to be opted out. It is the very most important moment where you opt in. One thing I'll share with you as I close is this phrase I heard. It's in my most favorite musical, Hamilton. We, we can win. I know that greatness lies in you. But remember, from here on in, history has its eyes on you. We are the first generation to teach machines to talk. We might be the last generation that can teach it to listen. Thank you for having me. I'm Noelle Russell.
