Lex Fridman (01:15:45):So during the acquisition, the way you knew the people, it’s the right team are the ones that could believe that this consulting business can grow, can integrate with the IBM and all of that.
Ginni Rometty (01:15:57):
Yeah, I was lucky. Look, I did things that helped that. I mean, I knew that people joining us would feel more comfortable if they had people leading it, that they recognized, et cetera. But again, I learned. Those that didn’t then, I eventually had to take some action out. But PWCC had a lot of really dedicated leaders to it. And I give them a lot of credit.
Lex Fridman (01:16:19):
What’s amazing to see a thing that kind of start at that very stressful time, and then it turns out to be a success. Yeah. That’s just beautiful to see. So what about the acquisition itself? Is there something interesting to say about the, like, what you learned about maybe negotiation? Because there’s a lot of money involved too.
Ginni Rometty (01:16:36):To me, it was a win-win. And we both actually cared that customers got value. So there was this, like, third thing that had a benefit. Not them, not us, there was this third thing. And then next to that.
Lex Fridman (01:16:50):I like how you think that people would have the wisdom or what it takes to have great negotiation. But yeah, so it’s a win-win is one of the ways
Ginni Rometty (01:16:57):
you can have successful negotiations. But it’s, like, obvious to even say that, right? I mean, if you can, back to being in service of something, we were both in service of clients. So in and then, you know, I always say, when you have a negotiation with someone, okay, both parties always kind of walk away a little bit. Okay, that’s good. If they both walk away going, yeah, I should have got a little bit more. Okay, but it’s okay if I should have got. Okay, they’re both a little fussy. When one walks away and thinks they did great and the other one did horrible, they’re usually, like, born bad. I mean, because they never worked that way. And I’ve always felt that way with negotiations that you push too far down, you usually will be sorry
Lex Fridman (01:17:38):you did that, you know? So don’t push too far. I mean, that’s ultimately what collaboration and empathy means is you’re interested in the long-term success of everybody together versus, like, your short-term success.
Ginni Rometty (01:17:49):And then you get the discretionary energy from them versus, like, okay, you screwed me here. I’m done, right?
Lex Fridman (01:17:54):So let’s even rewind even back.
Ginni Rometty (01:17:57):No. Oh, no. Do you feel like this is a nostalgia interview?
Lex Fridman (01:18:02):Oh, no. Let me just ask the romantic question. What did you love most about engineering, computer science, electrical engineering, so in those early days, from your degree to the early?
Ginni Rometty (01:18:11):
I just, I love that logic part of it, right? And you do get a sense of completion at some point when you reach certain milestones that, you know, like, yes, it worked, or yes, it, you know, that finite answer to that. So that’s what I loved about it. I loved the problem-solving of it.
Lex Fridman (01:18:26):Computing, what led you down that path? Computing in general, what made you fall in love with computing, with engineering?
Ginni Rometty (01:18:33):
It’s probably that back to that desire, wanting to know how things work, right? And so that’s like a natural thing. You know, math, I loved math for that reason. I always wanted to study how did that, you know, how did it get that to work kind of thing? So it goes back in that time. But I did start, when I went to, when I started at Northwestern, I wasn’t, I was already in the engineering school, but my first thought was to be a doctor, that that was far more noble, that I should be a medical doctor, until I could not pass human reproduction as a course. And I thought the irony that I could not.
Lex Fridman (01:19:01):I’m like, I got all these colored pencils,
Ginni Rometty (01:19:04):
like I don’t have these pictures, this is not working out for me. I’m going to stick to math. It was the only course in my four-year college education I had to take pass-fail, because otherwise I risked impairing my grade point average. Engineering it is, so but.
Lex Fridman (01:19:04):
I’m going to stick to math. It was the only course in my four-year college education I had to take pass-fail, because otherwise I risked impairing my grade point average. Engineering it is, so but. After about 10 years, you jumped from the technical role of systems engineer to management, to a leadership role. Did you miss at that time the sort of the technical direct contribution versus being a leader, a manager?
Ginni Rometty (01:19:30):
That’s an interesting point. Like I say, I’ve always been sort of a doer leader, you know, so. So you never lost that. I never really did, even, you know, and I think this is really important for today. The best way people learn is experientially, I think. Now you may, that’s being a generalization, because there are people can learn all different ways, right? So I’ve done things like with my whole team. They all had to learn how to build cloud applications.
We called it code off. And so, you know, I don’t care what your job is, write code, you know? And I remember when we were trying to get the company to understand AI, we did something called a cognitive jam. Okay, there’s a reason we picked the word cognitive, by the way, instead of AI. Today, we use the word AI. It was really symbolic.
(01:20:18):
It was to mean this is to help you think, not replace your thinking. There was so much in the zeitgeist about AI being a bad thing at that time. So that was why we picked a mouthful of a word like cognitive, and it was like, no, no, this is to help you, actually. So do what, you know, do what you do better or do something you haven’t yet learned. And we did something called the cognitive jam, but the whole point was everybody in the company could volunteer, get on a team. You either had to build something that improved one of our products or did something for a client or did a social, solved a social issue with AI. And again, this goes back now, 10 years, and people did things from bullying applications to, you know, railroad stuff to whatever it was, but it got like 100,000 people to understand, you know, viscerally what is AI. So that’s a long answer to my belief around experiential, and so do you ever give it up? I don’t think so, because I actually think that’s pretty good to get your hands dirty in something. You know, you can’t do it, you know, depending what you’re doing, your effort to do that will be less, but. So even the CEO,
Lex Fridman (01:21:20):tried to get your hands dirty a little bit.
Ginni Rometty (01:21:23):I’ve played, I mean, he’s still, I’m not saying I’m any good at any of it,
Lex Fridman (01:21:27):you know, anymore, but. But to build up into a.
Ginni Rometty (01:21:29):But it’s that, yeah, it’s that really understand, right, and not be afraid of.
Lex Fridman (01:21:35):
Like we mentioned at the beginning, IBM research has helped catalyze some of the biggest accomplishments in computing and artificial intelligence history. So D-Blue, IBM D-Blue versus Kasparov chess match in 96 and 97. Just to ask kind of like what your perception is, what your memory is of it, what is that moment? Like the seminal moment, I believe probably one of the greatest moments in AI history, when the machine first beat a human at a thing that humans thought.
Ginni Rometty (01:22:05):
You make a very interesting point, because it is like one of the first demonstrations of using a game to like bring something to people’s consciousness, right? And to this day, people use games, right, to demonstrate different things. But at the time, it’s funny. I didn’t necessarily think of it so much as AI, and I’ll tell you why. I was, and I’m not a chess player. You might be a chess player, so I’m not expert at it. But I think I understand properly of chess, that chess has got a finite number of moves that can be made.
Therefore, if it’s finite, really what’s a demonstration of a supercomputing, right? It’s about the amount of time and how fast it can crunch through to find the right move. So in some ways, I thought of it as almost a bigger demonstration of that. But it is absolutely, as you said, it was a motivator, one of the big milestones of AI, because it put in your consciousness that it’s man in this other machine, right?
Lex Fridman (01:22:57):
I’m doing something. So you saw it as just a challenging computation problem, and this is a way to demonstrate hardware and software computation at its best. Yes, I did. But the thing is, there is a romantic notion that chess is the embodiment of human intellect, I mean, intelligence, that you can’t build a machine that can beat a chess champion in chess, and the fact that it did.
Ginni Rometty (01:23:18):See, and I was blessed by not being a chess expert.
Lex Fridman (01:23:20):So it wasn’t like college. So it’s just a computation problem, I like it.
Ginni Rometty (01:23:23):It was a computation problem to me.
Lex Fridman (01:23:24):Well, that’s probably required to not be paralyzed by the immensity of the task. So that this is just solvable. But it was a very, I think that was a powerful moment, so speaking just as an AI person, that reinvigorated the dream.
Ginni Rometty (01:23:43):You were a little kid back then, though, right, at 95? You have to be, like, were you,
Lex Fridman (01:23:47):do you remember it, actually, at the moment? Yeah, yeah, yeah, yeah, yeah.
Ginni Rometty (01:23:50):What did you think at the moment about it?
Lex Fridman (01:23:53):
It was awe-inspiring, because especially sort of growing up in the Soviet Union, you think, especially of Garry Kasparov and chess, like, your intuition is weak about those things. I didn’t see it as computation. I thought of it as intelligence, because chess, for a human being, doesn’t feel like computation. It feels like some complicated relationship between memory and patterns and intuition and guts and instinct and all of those, like.
Ginni Rometty (01:24:31):If you watch someone play, that’s what you would conclude, right?
Lex Fridman (01:24:33):
So to see a machine be able to beat a human, I mean, you get a little bit of that with Chad G.P.T. now. It’s like, language was to us humans the thing that we kinda, surely the poetry of language is something only humans can really have. It’s going to be very difficult to replicate the magic of a natural language without deeply understanding language. But it seems like Chad G.P.T. can do some incredible things with language. In natural language dialogue. But that was the first moment in AI. Through all the AI winters from the 60s, the promise of the, it was, wow, this is possible for a simple set of algorithms to accomplish something that we think of as intelligence. So that was truly inspiring, that maybe intelligence, maybe the human mind is just algorithms. That was the thought at the time. And of course now, the funny thing, what happens is the moment you accomplish it, everyone says, oh, it’s just brute force algorithms. It’s silly.
(01:25:39):
And this continues. Every single time you pass a benchmark, a threshold to win a game, people say, oh, well, it’s just this. It’s just this. It’s just this. I think that’s funny, and there’s going to be a moment when we’re going to have to contend with AI systems that exhibit human-like emotions and feelings, and you have to start to have some difficult discussions about, well, how do we treat those beings? And what role do they have in society? What are the rules around that? And this is really exciting because that also puts a mirror to ourselves to see, okay, what’s the right way to treat each other as human beings? Because it’s a good test for that.
Ginni Rometty (01:26:22):
And it is, because I always say it’s a reflection of humanity. I mean, it’s taught by what man, bad stuff in the past, you’ll teach it bad stuff for the future, which is why I think efforts to regulate it are a fool’s errand. You need to regulate uses, because it’s not the technology itself is not inherently good or bad, but how it’s used or taught can be good or bad, for sure. And so that’s, to me, will unveil now a whole different way of having to look at technology.
Lex Fridman (01:26:53):Well, what about another magical leap with the early days of Watson with beating the Jeopardy challenge? What was your experience like with Watson? What’s your vision for Watson in general?
Ginni Rometty (01:27:01):
Yeah. What was it? And it was really inspired by first chess, right, and Kasparov, and then you come forward in time. And I think what Watson did, because you used a really important word, AI had kind of waxed and waned in these winters, right? In and out, in and out, popular or not, more money, less money, in and out, confidence, no confidence. And so I think that was one of the first times it brought to the forefront of people like, whoa, like it humanized it. Because here it is playing against these two gentlemen, and as you did lose at first, and then finally won at the end of the day. And what it was doing is making you say, hey, natural language, it’s actually understanding natural language. It’s one of the first demonstrations of natural language support, and a bit of reasoning over lots of data, right? And so that it could have access to a lot of things, come up with a conclusion on it.
(01:27:55):
And to me, that was a really big moment. And I do think it brought to the conscious of the public, and in good ways and bad, because it probably set expectations very high of like, whoa, what this could be. But, and I still do believe that it has got the ability to change and help us, man, make better decisions. That so many decisions are not optimal in this world. Even medical decisions, and it’s right or wrong what took us down a path of healthcare first with our AI.
And we took many pivots, and I think there’s a really valuable lesson in what we learned. One is that, I actually don’t think the challenges are the technology. Yes, those are challenges, but the challenges are the people technologies around this. So do people trust it? How will they use it? I mean, I saw that straight up with doctors and like, meaning they’re so busy in the way they’ve been taught to do something.
(01:28:51):
Do they really have time to learn another way? I saw it was a mistake when you put it on top of processes that didn’t change, kind of like paving a cow path. Didn’t work. I mean, it was all human change management around it that were really its biggest challenges. And another valuable lesson we picked, back to usage, you think of IBM as moonshops, we picked really hard problems to start with.
I think you see a lot of technology now starts with really simple problems. And by that, it probably starts to build trust because I start little. It’s like, oh, I’m not ready to outsource my diagnosis to you, but I’ll get some information here about a test question. So very different thinking. So a lot of things to learn. We were making a market at the time. And when you make a market, choice of problem you work on gets to be very important. When you’re catching up, well, then it’s a scale game. So very different thing. But Watson proved, I think, I mean, I hope I’m not being too…
I think Watson brought AI back out a winner for the world. And that since then there’s just been one company after another and innovations and people working on it. And I have no regrets of anything that we did. We learned so much. I mean, we probably rebuilt it many times over. It made it more modular.
And today, to IBM, a Watson is more about AI inside of a lot of things, if you think of it that way, which is more like an ingredient versus it’s a thing in and of itself. And I think that’s how it’ll bring its real value. You know, more as an ingredient and it’s so badly needed. And even back then the issue was so much data. Like, what do you ever do? You can’t get through it. You can’t use it for anything. You know this well, it’s your profession. So we have to have it. So that’s gonna propel it forward.
Lex Fridman (01:30:31):So it’s part of the suite of tools that you use when you go to enterprise and you try to solve
Ginni Rometty (01:30:36):
all types of problems. Yeah, so AI for security, AI in automated operations, AI in your robotics, AI on your factory floor. You know what I mean? It’s all part of, and I think, and that’s why even to this day, thousands, I mean thousands and thousands of clients of IBM still have the Watson components that it’s the AI being used. So it became a platform is how I would say it, right? And an ingredient that went inside and consultants, like you said, had to learn. They had to learn, don’t just put it on something. You gotta rethink how that thing should work because with the AI, it could work entirely differently.
And so I also felt it could open up and still will open up jobs to a lot of people because more like an assistant and it could help me be qualified to do something. And we even years ago saw this with the French banks, very unionized, but that idea that you could, in this case, the unions voted for it because it felt people did a better job. And so, and that’s just part about being really dedicated to help it help humanity, not destroy it. Yeah.
Lex Fridman (01:31:38):Speaking of which, a funny side note. So Kubrick’s 2001 Space Odyssey, what do you think about the fact that Hal 9000 was named after IBM?
Ginni Rometty (01:31:52):I really don’t think it was.
Lex Fridman (01:31:53):I know there’s- You don’t think so? I really don’t. It could be more fake news.
Ginni Rometty (01:31:56):It’s more fake news. I have done, I’ve like researched this, tried to find any evidence and people have talked to you. Was it really, you know, one letter, it was one letter- One letter off, so-
Lex Fridman (01:32:03):Off, right? One letter off, so- Off, right? For people that don’t know, H is one letter off of I, A is one letter off of B,
Ginni Rometty (01:32:10):and then L is one letter off of M. I think that’s a solution found afterwards, you know? But here’s what I think it more was. I do think it’s one of the early demonstrations of evil AI. Yeah.
Lex Fridman (01:32:21):
Like can be taught bad. I could push back on that because it’s presented as evil in the movie because it hurts, the AI hurts people, but it’s a really interesting ethical question because the role of HAL 9000 is to carry out a successful mission.
And so the question that is a human question, it’s not an AI question, at what price? Humans wage war, they pay very heavy costs for a vision, for a goal of a future that creates a better world. And so that’s the question, certainly in space. Doctors ask that question all the time, but unlimited resources, who do I allocate my time and money and efforts to?
Ginni Rometty (01:33:02):
I agree. Like I said, I’ve spent a decade talking about this question of AI ethics, right? And that it needs really considerable, not just attention, because otherwise it will mirror everything we love and everything we don’t love. And again, and that’s the beauty in the eye of the holder, right, depending your culture and everything else. With what you’re doing and what you’re gonna do, how do you think about it? Do you think about the AI you’re going to develop as having guardrails dictated by some of your beliefs or?
Lex Fridman (01:33:31):
Yeah, for sure. So there’s so many interesting ways to do this the right way, and I don’t think anyone has an answer. I tend to believe that transparency is really important. So I think some aspect of your work should be open-sourced, or at least have an open-source competitor that creates a kind of forcing function for transparency of how you do things. So the other is, I tend to believe, maybe it’s because of the podcast and I’ve just talked to a lot of people, you should know the people involved.
Ginni Rometty (01:34:03):Yeah. I agree, a hundred percent.
Lex Fridman (01:34:04):
As opposed to hide behind a company wall. Sometimes there’s a pressure, you have a PR team, you have to care for investors and discussions, so on, let’s protect, let’s surely not tweet. And you form this bubble where you have incredible engineers doing fascinating work and also doing work that’s difficult, complex human questions being answered. And we don’t know about any of them as a society, and so we can’t really have that conversation. Even though that conversation would be great for hiring, it would be great for revealing the complexities of what the company is facing, so when the company makes mistakes, you understand that it wasn’t malevolence or half-assedness, and the decision-making is just a really hard problem. And so I think transparency is just good for everybody. And, I mean, in general, just having a lot of public conversations about this is serious stuff
It’s that AI will have a transformative impact on our society, and it might do so very, very quickly through all kinds of ways we’re not expecting, which is social media recommendation systems. They, at scale, have impact on the way we think, on the way we consume news, and our growth, like the kind of stuff we consume to grow and learn and become better human beings, all of that, that’s all AI. And then, obviously, the tools that run companies on which we depend, the infrastructure on which we depend, we need to know all about those AI decisions. And it’s not as simple as, well, we don’t want the AI to say these specific set of bad things. Unfortunately, I don’t believe it’s possible to prevent evil or bad things by creating a set of cold mathematical rules. Unfortunately, it’s all fuzzy and gray areas. It’s all a giant mess.
Ginni Rometty (01:35:59):
It is, I mean, you think about it like a knife. A knife can do good, and a knife can do bad, okay? You can’t, it’s very hard. You can’t ban knives. You can’t ban knives. And that, this is, I think back, it was probably 20, I don’t know, 15, 16, we did principles of trust and transparency. Notice the word transparency. That belief that with AI, it should be explainable. You should know who taught it. You should know the data that went into training it. You should know how it was written. If it’s being used, you have a right to know these things. And I think those are pretty, to this day, really powerful principles to be followed, right? And part of it, we ended up writing, because here we were, when we were working on particularly healthcare, like, okay, you care who trained it and what, and where did, and that’s sort of simple, you know, that comes to your mind, and you’re like, yeah, that makes a lot of sense for something important like that. But it just, in general, people won’t trust the technologies, I don’t think, unless they have transparency into those things. In the end, they won’t really trust it.
Lex Fridman (01:36:55):
I think a lot of people would like to know sort of, because a lot of us, I certainly do, suffer from imposter syndrome, that self-critical brain. So, you know, taking that big step into leadership, did you at times suffer from imposter syndrome? Like, how did I get here? Do I really belong here? Or were you able to summon the courage and sort of the confidence to really step up?
Ginni Rometty (01:37:22):
I think that’s very natural for someone. Like, no matter, like, the bigger the job gets, you turn and you look to the left and the right, and you see people around you, and you think, what am I doing here, right? But then you remember what you do, and there’s no one else doing it, and so you get that confidence. So, I do hear a lot of people talk about imposter syndrome, right?
And I kind of, actually, this past year, I’ve spent some time helping people on that topic. And part of the stress, you have to believe you have a right to be like anyone else does if you’ve prepared for that moment, you know? And so, it’s a bit more of a, I know it’s hard to say it, like a confidence thing more than anything else. So, yes, there are times I look around, but then I think, wow, I’m in a position to make something change. So, I can’t say I have ever really dwelled on that feeling for long.
Lex Fridman (01:38:20):So, I guess you just focus on the work. I have an opportunity, I’m gonna stop propagating.
Ginni Rometty (01:38:22):You know, it’s good or bad, I just focus on the work. Yeah, good or bad, yeah.
Lex Fridman (01:38:26):
One important lesson you said you learned from your mom is never let anyone else define you. Only you define who you are. So, what’s the trajectory, let’s say, of your self-definition journey, of you discovering who you are from having that very difficult upbringing?
Ginni Rometty (01:38:47):
You know they say pivotal moments happen and you don’t realize it when they’re happening? So, most of my, I feel like most of my self-discovery, it’s been like something happens in a year or two or some number later, I look back on it and say, you know, I learned this from that. It’s like not in the moment always with me. That could just be how I am. So, I feel like it’s been, know yourself, it’s a good thing, right? I’ve actually heard you say that on a different podcast when you ask people questions. You’re like, well, it depends, you know, like know yourself a bit, right? And, uh.
Lex Fridman (01:39:20):
But to know who you are, though, there’s a lot of things, like you said, Nick. Like, for me, there’s moods when you’re super self-critical, sometimes you’re super confident, and there’s many, sometimes you’re emotional, sometimes you’re cool under pressure, and all those are the same human being. Yeah, and I think that’s fine.
Ginni Rometty (01:39:39):Self-awareness, that’s different.
Lex Fridman (01:39:41):Was there societal expectations and norms regarding gender that you felt in your career? You’ve spoken to that a little bit, but was there some aspect of that that was constraining, empowering, or both?
Ginni Rometty (01:39:56):
You know, I chose to never look at it, okay? Now, whether that is right or wrong, and again, I’m a product of the 70s, and 70s and the 80s, where I think I was surrounded, all the other women around me viewed our way to get ahead was just to work hard. Work hard, work hard, and that was the way you differentiated yourself. And that’s obvious it did help. I mean, there’s no doubt about it. You were always, you know, you learned a lot of things, which qualified opened up another door, opened up another door. I’m very remindful that I have worked for companies that are very steeped in those values of equal opportunity. And so nothing remarkable about that. And I mean, when I was a wee kid, I’m taught hire a diverse team.
I get evaluated for it. I get evaluated if my team has built up their skills. So this is, you know, when you’re really formative, you’re in a culture that that’s what it’s valuing, right? So it becomes part of you. So I say sometimes to chagrin, did I ever feel I was held back for that reason? No, were there plenty of times when, you know, I write about a few of the stories in the book, I’m laying cables at night and the guys are at the bar. Now, I didn’t really wanna go with them to the bar anyways. They’d be like, we’ll be back to get you, you know, bye. And I’m like, okay.
(01:41:08):
I mean, I learned a lot. So it didn’t. Now, all that said, back to my earlier story about being a role model, you know, it would be foolish to not believe that there were times that that mattered. And I would say two things, even not that long ago, you know, a colleague called me and I was talking about media and about women CEOs and said, do you notice that sometimes when it’s a woman CEO, they call the person by name.
And when it’s a man, they call the company out, not the person’s name exactly associated with the issue. And I said, yeah, well, I think you have to just understand much of what you do, it will be magnified because there are so few of you. And sometimes it will be, you know, really can be blown out of proportion, right? And so that can happen and you get to learn in which way. Now, all that said, on gender, it is an interesting thing with the book as I’ve talked to, you know, having a book. Even some of my best friends, the first reaction is, I can’t wait for my daughter to read it. I say, well, that’s interesting. Do you think you could read it?
Lex Fridman (01:42:17):Yeah, it’s fascinating.
Ginni Rometty (01:42:17):
It’s an interesting reaction. And here I am 40 years later, that’s an interesting reaction, right? And I say, no, the book, I really worked hard to write it for everyone. I just happened to be a woman, right? But there’s still that there. And so, look, until I think people see and never feel that they have a, it doesn’t even matter whether there’s a woman, could be another diverse group that feels it. It’s okay to ask those questions. And that’s why actually I’m okay talking about it because there were times I felt it, right? There were times in my life on my looks or my weight or my clothing or endless numbers of things that people would comment on that they would not have commented on if it was someone else.
Now, on the other hand, when there’s so few of you and, you know, there’s good and bad. I mean, there’s benefit to that too, right? If you do good work, it’s easier to be recognized. And so, a pro and a con, and I think I’ve just grown up believing my advice to young women, go into engineering. Not because you’re gonna be an engineer. It teaches you to solve problems. And anything new job you do is gonna be solving problems. Things like that are what I take away from that in that journey.
Lex Fridman (01:43:28):
It is interesting that I hear from women that even on this podcast, when I talk to incredible women like yourself, it is inspiring to young women to hear. I mean, you like to see, you talk to somebody from Turkey and then Turkish people all get excited. It’s so true. So you get like somebody that looks like you, somebody that, and the category could be tiny, it could be, it can be huge. That’s just the reality of the world.
Ginni Rometty (01:43:57):
It is the reality of the world. And the work I do now to put this group called 110, put 1 million black employees into the middle class without college degrees. Get them the right skills, upwardly mobile jobs. So one of my last years we had been working on, it just did regular leadership session at IBM and had our black colleagues. We’re talking about what did it feel like to be a black leader? And here, these are extremely accomplished people. And I can remember very well one telling a story about, look, I felt if I failed or succeeded, it’s not just me. It came from a country in Africa. I feel like the whole country is on my shoulder, my success or failure. That’s a burden. I mean, like, I don’t feel that burden. Not true. As a woman CEO, I did feel like, even the headlines when I was named said, her appointment will either, her success or failure will be a statement for the whole gender kind of thing.
And I didn’t dwell on it, but I could see how people, like you said, it could be a small group, could be whatever. And so that is a lot of pressure on people and they need role models. You are a role model for people. Look at what you’re able to do. You do these podcasts, you understand your science very well, you’re very well prepared, your ability to translate it to people. That’s not an insignificant thing. And you may think, oh, is that about the power of me? Not really, right? And you obviously believe, you don’t do this because you just like sitting at a microphone. You do it because you think, okay, if I can get people to say things that are really valuable to other people, they’re gonna learn something. I assume that is, I mean, you never told me, my interpretation is, that’s why you do this podcast. That you feel like in service of other people that you can bring them something unique by the way you do this.
Now, I should ask you, why do you do it? That’s my impression.
Lex Fridman (01:45:38):
By the way, can I just comment on the fact that you keep asking me really hard questions? I really, I appreciate it, I love this. I’m really honored by it. As a fan of podcasts myself, what I hope is to talk to people like you and to show that you are a fascinating and beautiful human being outside of your actual accomplishments also. So sometimes people are very focused on very specific things about, like you said, science, like what the actual work is, whether it’s nuclear fusion or it’s GIGPT.
I just wanna show that it’s, because I see it at MIT and everywhere, it’s just human beings trying their best, they’re flawed, but just realizing that all of these very well accomplished people are all the same. Yeah, that’s a very good, well said. And then so then regular people and young people, they’re able to see, you know, I can do this too, I can have a very big impact. No imposter syndrome, right? Yeah, exactly. It’s like we’re all kind of imposters. We’re all like trying to figure it out on our own.
Ginni Rometty (01:46:42):To a certain degree. Yeah. To a certain degree.
Lex Fridman (01:46:45):
So let me just ask you about family. You wrote that my family still jokes that the reason I never had children on my own was because I had already raised my family. They’re right. So this is talking to you about upbringing, but in general, what was your, you know, leading a giant company, what was the right place to find a work-life balance for you to have time for family, have time for away from work and be successful?
Ginni Rometty (01:47:13):
So I had to learn that and I might have said, you know, you’re the only one that can determine your own work-life balance. Companies are innate things. I mean, they will take everything they can from you and it’s not a bad thing. They just will, as will bosses. I mean, you give it, they’ll take it. And when people ask for, you know, I need a roof, I’m like, okay. I had to come to terms with the criminal was me if I needed that balance. I had to set those boundaries. And so when I comment about a family, because I am in extreme awe of people with children who work, it is a extremely hard thing to do. I watch my siblings. I love my nieces and nephews.
And you know, A, the emotional, their pain is your pain every minute of a day. And then you still have a job on top of it. And so when my mom had to go back to school and had to work, I was the one. And so when she couldn’t go to the teacher meeting, I went to the teacher meeting. And so in some ways, there’s an age gap between my brother and I and my other two sisters. And so I’m still, they still call me mama bear even. I mean, I’m extremely protective of all of them. And it is as if I had raised them and my mom did a great job raising them. I didn’t, but I was there. And so when it came time to have children and my husband came from a family where his father died and was raised by a single mother, very similar end point, different reasons why he ended up, you know, his father did not abandon them. And I don’t want people to believe to do my job, you can have no children. That is not right. I know other great women CEOs, Marilyn Hewson, who ran Lockheed Martin, extremely technical company, Mary Barra, who runs General Motors, Ellen Coleman, who run DuPont. These are all my friends to this day.
(01:49:01):
And they’ve been fantastic mothers and husbands, good parents, right? And so I talk about it because it was a choice we made. And so, you know, we both felt, look, we’d reached a point where for his reasons, what he had to do, I’d already felt that way. And that we were comfortable just being great aunts and uncles. And I’m a great aunt, you know? Well, I like to think that for my little guys and they’re older now, but lots of them. And there’s no doubt though, the choices we made, Mark and I, that that made it easier for me to focus on work. I mean, it’s just math, you know, when you’ve got less people to have to take care of.
And so I’m very considerate of that. And I think much of it informed many of the policies I put into because I had such great empathy for those who then still had these other responsibilities. And I desperately wanted them all to stay in the workforce. So I can remember, and my siblings have been more successful than I, by the way, I mean, to my mother’s credit.
And my one sister who, you know, went to Northwestern, has an MBA, built some of the most sophisticated systems. She spent her whole career at Accenture and just recently retired as the chief executive of all of consulting. But at one point she took off time to spend with her family and then went to go back to work. She’s talking to me and she’s like, I don’t know if I should go back to work. You know, maybe life’s path, you know, technology goes so fast, it’s been a few years.
(01:50:29):
I’m sitting there like, what are you talking about? I’m like, you know, look at her credentials. They’re far outstanding. I’m like, and I thought to myself, like, ding, one of those moments. If my own sister feels that way with all her credentials, I’ll bet I went back to work the next day and I said, hey, pull for me. All the people who’ve left for parental reasons and, or whatever, family reasons, didn’t come back. And it began a program of returnships. And I can’t tell you how many, in men and women, was because they didn’t feel confident to come back. They thought technology passed them by. Okay, we said, it’s three months. You could stay one month, three months, doesn’t matter. Well, a lot of people, like one day, they’re like, you’re right, not that much happened. It happened, but I caught up.
Lex Fridman (01:51:11):Actually, no more than I think, you know?
Ginni Rometty (01:51:13):
Yeah. And I, so it was a long answer to your question about, I didn’t, but I am so empathetic and I am in awe of what they are able to do. So, and it made me then, I think, more empathetic to the policies and the like around that topic, so you could keep great people in the workforce.
Lex Fridman (01:51:30):So you mentioned your friends with Mayabara, the CEO of GM. I didn’t mean to name drop. So don’t, I didn’t mean it that way. No, I love her, she’s amazing. So I just wanted to, I’m just curious.
Ginni Rometty (01:51:40):I’ll tell Mary she should do your podcast. We’ll make it happen, but. She’s a great leader. She’s amazing. I tell Mary what I think of her is, I think she’s one of the most authentic leaders out there.
Lex Fridman (01:51:49):Most authentic. I mean, just very different companies, huge challenge.
Ginni Rometty (01:51:53):
I worked there first, though, remember, right? So I’m very, you know, in some ways I’m very beholden, right, you know, I’m very appreciative of what they did. I mean, Mary and I are circa the same, well, I’m a bit older, so, but circa that genre.
Lex Fridman (01:52:05):Do you exchange wisdoms?
Ginni Rometty (01:52:06):
Oh yeah, yeah. When you do anything hard, it takes time and perseverance, like we talked about. And you can get that, where do you get the fuel for it? You can either get it from your attitude, or you can get it from your network or your relationships. And I’m a firm believer relationships are from what you give, not what you get. Meaning, you give, trust me, they will come back at the time they need to come back to you at these moments in life. If you focus on, how can I bring Lex value? There’ll be a day I need Lex, and he will be back. And so, to those women, to me, relationships are not transactional.
And it’s a proof that to this day, even though I’m no longer still active as a CEO, these are all still my friends. And they’re, we are friends, all of us. And I can remember some of them, when I first became a CEO, calling me and saying, hey, it’s a little lonely here, so let me talk to you. And then when they became, I did the same for them. And then they remember, and they do for the next generation. And so, it’s a very supportive, almost to a T, any of the women you could name who have been CEOs, I would say, almost to a T, have all been very supportive. In fact, a number of us work on a little, another non-for-profit right now called Journey, which some women who had started, the Fortune’s Most Powerful Women had started, which was, could we get more women, particularly diverse women, but women in general, to more quickly be into positions of leadership and power? And so, many of the women you named and more, we all dedicate time mentoring in kind of creating this little group of fellows every year to do this.
Lex Fridman (01:53:44):
Friendship and love is core to this whole thing, not just the success, but just the whole human condition. Let me ask one last question. Advice for young people. You’ve had a difficult upbringing, a difficult life, and you’ve become one of the most successful human beings in history. What advice would you give to young people, or just people in general who are struggling a bit, trying to figure out how they can have a career they can be proud of, or maybe a life they can be proud of?
Ginni Rometty (01:54:12):
I feel like a life you can be proud of is just one if you leave something a little bit better. It doesn’t have to be big, you know? That’s a life well-lived, right? It was Churchill who said, you might remember it better than I. You make a living by what you get, and you live a life by what you give, something to that effect. But my advice would probably, when I’m asked this, I would tell them to ask more questions than give answers.
Just focus on being a sponge. It’s funny, I asked my husband the same question the other day. I said, hey, we’re talking to somebody, and people were asking this, and he sort of paused for a while, and he said, I tell them, patience. I said, what do you mean? And he said, I see so many young people, they’re in such a hurry to somewhere, I don’t know where, and that if they just had patience and let life unfold, I think they may be surprised where they ended up. And actually, I think that’s a really good answer,
Lex Fridman (01:55:13):to be honest. Along the way, keep asking questions, keep that childlike curiosity.
Ginni Rometty (01:55:18):I know, it sounds so easy to say, it’s just so, you know.
Lex Fridman (01:55:23):
Yeah, like you said, the obvious things, I think they tend to be the most profound. Jeannie, you’re an incredible human being. You’re an inspiration to so many. Thank you for helping run and contribute to one of the great companies that brings so much good power to the world, and thank you for putting in the hard work of putting it all in the great book, and thank you for talking today.
Ginni Rometty (01:55:47):This was a huge honor. Thank you for doing it. You did a lovely job.
Lex Fridman (01:55:50):
Thanks for listening to this conversation with Jeannie Rometty. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Eleanor Roosevelt. Do what you feel in your heart to be right, for you’ll be criticized either way. Thank you for listening, and hope to see you next time.