Image Title

Search Results for Margaret Thatcher:

Ritika Gunnar, IBM | IBM Data and AI Forum


 

>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>Welcome back to downtown Miami. Everybody. We're here at the Intercontinental hotel covering the IBM data AI form hashtag data AI forum. My name is Dave Volante and you're watching the cube, the leader in live tech coverage. Ritika gunner is here. She's the vice president of data and AI expert labs and learning at IBM. Ritika, great to have you on. Again, always a pleasure to be here. Dave. I love interviewing you because you're a woman executive that said a lot of different roles at IBM. Um, you know, you've, we've talked about the AI ladder. You're climbing the IBM ladder and so it's, it's, it's, it's awesome to see and I love this topic. It's a topic that's near and dear to the cubes heart, not only women in tech, but women in AI. So great to have you. Thank you. So what's going on with the women in AI program? We're going to, we're going to cover that, but let me start with women in tech. It's an age old problem that we've talked about depending on, you know, what statistic you look at. 15% 17% of, uh, of, of, of the industry comprises women. We do a lot of events. You can see it. Um, let's start there. >>Well, obviously the diversity is not yet there, right? So we talk about women in technology, um, and we just don't have the representation that we need to be able to have. Now when it comes to like artificial intelligence, I think the statistic is 10 to 15% of the workforce today in AI is female. When you think about things like bias and ethicacy, having the diversity in terms of having male and female representation be equal is absolutely essential so that you're creating fair AI, unbiased AI, you're creating trust and transparency, set of capabilities that really have the diversity in backgrounds. >>Well, you work for a company that is as chairman and CEO, that's, that's a, that's a woman. I mean IBM generally, you know, we could see this stuff on the cube because IBM puts women on a, we get a lot of women customers that, that come on >>and not just because we're female, because we're capable. >>Yeah. Well of course. Right. It's just because you're in roles where you're spokespeople and it's natural for spokespeople to come on a forum like this. But, but I have to ask you, with somebody inside of IBM, a company that I could say the test to relative to most, that's pretty well. Do you feel that way or do you feel like even a company like IBM has a long way to go? >>Oh, um, I personally don't feel that way and I've never felt that to be an issue. And if you look at my peers, um, my um, lead for artificial intelligence, Beth Smith, who, you know, a female, a lot of my peers under Rob Thomas, all female. So I have not felt that way in terms of the leadership team that I have. Um, but there is a gap that exists, not necessarily within IBM, but in the community as a whole. And I think it goes back to you want to, you know, when you think about data science and artificial intelligence, you want to be able to see yourself in the community. And while there's only 10 to 15% of females in AI today, that's why IBM has created programs such as women AI that we started in June because we want strong female leaders to be able to see that there are, is great representation of very technical capable females in artificial intelligence that are doing amazing things to be able to transform their organizations and their business model. >>So tell me more about this program. I understand why you started it started in June. What does it entail and what's the evolution of this? >>So we started it in June and the idea was to be able to get some strong female leaders and multiple different organizations that are using AI to be able to change their companies and their business models and really highlight not just the journey that they took, but the types of transformations that they're doing and their organizations. We're going to have one of those events tonight as well, where we have leaders from Harley Davidson in Miami Dade County coming to really talk about not only what was their journey, but what actually brought them to artificial intelligence and what they're doing. And I think Dave, the reason that's so important is you want to be able to understand that those journeys are absolutely approachable. They're doable by any females that are out there. >>Talk about inherent bias. The humans are biased and if you're developing models that are using AI, there's going to be inherent bias in those models. So talk about how to address that and why is it important for more diversity to be injected into those models? >>Well, I think a great example is if you took the data sets that existed even a decade ago, um, for the past 50 years and you created a model that was to be able to predict whether to give loans to certain candidates or not, all things being equal, what would you find more males get these loans than females? The inherent data that exists has bias in it. Even from the history based on what we've had yet, that's not the way we want to be able to do things today. You want to be able to identify that bias and say all things being equal, it is absolutely important that regardless of whether you are a male or a female, you want to be able to give that loan to that person if they have all the other qualities that are there. And that's why being able to not only detect these things but have the diversity and the kinds of backgrounds of people who are building AI who are deploying this AI is absolutely critical. >>So for the past decade, and certainly in the past few years, there's been a light shined on this topic. I think, you know, we were at the Grace Hopper conference when Satya Nadella stuck his foot in his mouth and it said, Hey, it's bad karma for you know, if you feel like you're underpaid to go complain. And the women in the audience like, dude, no way. And he, he did the right thing. He goes, you know what, you're right. You know, any, any backtrack on that? And that was sort of another inflection point. But you talk about the women in, in AI program. I was at a CDO event one time. It was I and I, an IBM or had started the data divas breakfast and I asked, can I go? They go, yeah, you can be the day to dude. Um, which was, so you're seeing a lot of initiatives like this. My question is, are they having the impact that you would expect and that you want to have? >>I think they absolutely are. Again, I mean, I'll go back to, um, I'll give you a little bit of a story. Um, you know, people want to be able to relate and see that they can see themselves in these females leaders. And so we've seen cases now through our events, like at IBM we have a program called grow, which is really about helping our female lead female. Um, technical leaders really understand that they can grow, they can be nurtured, and they have development programs to help them accelerate where they need to be on their technical programs. We've absolutely seen a huge impact from that from a technology perspective. In terms of more females staying in technology wanting to go in the, in those career paths as another story. I'll, I'll give you kind of another kind of point of view. Um, Dave and that is like when you look at where it starts, it starts a lot earlier. >>So I have a young daughter who a year, year and a half ago when I was doing a lot of stuff with Watson, she would ask me, you know, not only what Watson's doing, but she would say, what does that mean for me mom? Like what's my job going to be? And if you think about the changes in technology and cultural shifts, technology and artificial intelligence is going to impact every job, every industry, every role that there is out there. So much so that I believe her job hasn't been invented yet. And so when you think about what's absolutely critical, not only today's youth, but every person out there needs to have a foundational understanding, not only in the three RS that you and I know from when we grew up have reading, writing and arithmetic, we need to have a foundational understanding of what it means to code. And you know, having people feel confident, having young females feel confident that they can not only do that, that they can be technical, that they can understand how artificial intelligence is really gonna impact society. And the world is absolutely critical. And so these types of programs that shed light on that, that help bridge that confidence is game changing. >>Well, you got kids, I >>got kids, I have daughters, you have daughter. Are they receptive to that? So, um, you know, I think they are, but they need to be able to see themselves. So the first time I sent my daughter to a coding camp, she came back and said, not for me mom. I said, why? Because she's like, all the boys, they're coding in their Minecraft area. Not something I can relate to. You need to be able to relate and see something, develop that passion, and then mix yourself in that diverse background where you can see the diversity of backgrounds. When you don't have that diversity and when you can't really see how to progress yourself, it becomes a blocker. So as she started going to grow star programs, which was something in Austin where young girls coded together, it became something that she's really passionate about and now she's Python programming. So that's just an example of yes, you need to be able to have these types of skills. It needs to start early and you need to have types of programs that help enhance that journey. >>Yeah, and I think you're right. I think that that is having an impact. My girls who code obviously as a some does some amazing work. My daughters aren't into it. I try to send them to coder camp too and they don't do it. But here's my theory on that is that coding is changing and, and especially with artificial intelligence and cognitive, we're a software replacing human skills. Creativity is going to become much, much more important. My daughters are way more creative than my sons. I shouldn't say that, but >>I think you just admitted that >>they, but, but in a way they are. I mean they've got amazing creativity, certainly more than I am. And so I see that as a key component of how coding gets done in the future, taking different perspectives and then actually codifying them. Your, your thoughts on that. >>Well there is an element of understanding like the outcomes that you want to generate and the outcomes really is all about technology. How can you imagine the art of the possible with technology? Because technology alone, we all know not useful enough. So understanding what you do with it, just as important. And this is why a lot of people who are really good in artificial intelligence actually come from backgrounds that are philosophy, sociology, economy. Because if you have the culture of curiosity and the ability to be able to learn, you can take the technology aspects, you can take those other aspects and blend them together. So understanding the problem to be solved and really marrying that with the technological aspects of what AI can do. That's how you get outcomes. >>And so we've, we've obviously talking in detail about women in AI and women in tech, but it's, there's data that shows that diversity drives value in so many different ways. And it's not just women, it's people of color, it's people of different economic backgrounds, >>underrepresented minorities. Absolutely. And I think the biggest thing that you can do in an organization is have teams that have that diverse background, whether it be from where they see the underrepresented, where they come from, because those differences in thought are the things that create new ideas that really innovate, that drive, those business transformations that drive the changes in the way that we do things. And so having that difference of opinion, having healthy ways to bring change and to have conflict, absolutely essential for progress to happen. >>So how did you get into the tech business? What was your background? >>So my background was actually, um, a lot in math and science. And both of my parents were engineers. And I have always had this unwavering, um, need to be able to marry business and the technology side and really figure out how you can create the art of the possible. So for me it was actually the creativity piece of it where you could create something from nothing that really drove me to computer science. >>Okay. So, so you're your math, uh, engineer and you ended up in CS, is that right? >>Science. Yeah. >>Okay. So you were coded. Did you ever work as a programmer? >>Absolutely. My, my first years at IBM were all about coding. Um, and so I've always had a career where I've coded and then I've gone to the field and done field work. I've come back and done development and development management, gone back to the field and kind of seen how that was actually working. So personally for me, being able to create and work with clients to understand how they drive value and having that back and forth has been a really delightful part. And the thing that drives me, >>you know, that's actually not an uncommon path for IBM. Ours, predominantly male IBM, or is in the 50 sixties and seventies and even eighties. Who took that path? They started out programming. Um, I just think, trying to think of some examples. I know Omar para, who was the CIO of Aetna international, he started out coding at IBM. Joe Tucci was a programmer at IBM. He became CEO of EMC. It was a very common path for people and you took the same path. That's kind of interesting. Why do you think, um, so many women who maybe maybe start in computer science and coding don't continue on that path? And what was it that sort of allowed you to break through that barrier? >>No, I'm not sure why most women don't stay with it. But for me, I think, um, you know, I, I think that every organization today is going to have to be technical in nature. I mean, just think about it for a moment. Technology impacts every part of every type of organization and the kinds of transformation that happens. So being more technical as leaders and really understanding the technology that allows the kinds of innovations and business for informations is absolutely essential to be able to see progress in a lot of what we're doing. So I think that even general CXOs that you see today have to be more technically acute to be able to do their jobs really well and marry those business outcomes with what it fundamentally means to have the right technology backbone. >>Do you think a woman in the white house would make a difference for young people? I mean, part of me says, yeah, of course it would. Then I say, okay, well some examples you can think about Margaret Thatcher in the UK, Angela Merkel, and in Germany it's still largely male dominated cultures, but I dunno, what do you think? Maybe maybe that in the United States would be sort of the, >>I'm not a political expert, so I wouldn't claim to answer that, but I do think more women in technology, leadership role, CXO leadership roles is absolutely what we need. So, you know, politics aside more women in leadership roles. Absolutely. >>Well, it's not politics is gender. I mean, I'm independent, Republican, Democrat, conservative, liberal, right? Absolutely. Oh yeah. Well, companies, politics. I mean you certainly see women leaders in a, in Congress and, and the like. Um, okay. Uh, last question. So you've got a program going on here. You have a, you have a panel that you're running. Tell us more about. >>Well this afternoon we'll be continuing that from women leaders in AI and we're going to do a panel with a few of our clients that really have transformed their organizations using data and artificial intelligence and they'll talk about like their backgrounds in history. So what does it actually mean to come from? One of, one of the panelists actually from Miami Dade has always come from a technical background and the other panelists really etched in from a non technical background because she had a passion for data and she had a passion for the technology systems. So we're going to go through, um, how these females actually came through to the journey, where they are right now, what they're actually doing with artificial intelligence in their organizations and what the future holds for them. >>I lied. I said, last question. What is, what is success for you? Cause I, I would love to help you achieve that. That objective isn't, is it some metric? Is it awareness? How do you know it when you see it? >>Well, I think it's a journey. Success is not an endpoint. And so for me, I think the biggest thing I've been able to do at IBM is really help organizations help businesses and people progress what they do with technology. There's nothing more gratifying than like when you can see other organizations and then what they can do, not just with your technology, but what you can bring in terms of expertise to make them successful, what you can do to help shape their culture and really transform. To me, that's probably the most gratifying thing. And as long as I can continue to do that and be able to get more acknowledgement of what it means to have the right diversity ingredients to do that, that success >>well Retika congratulations on your success. I mean, you've been an inspiration to a number of people. I remember when I first saw you, you were working in group and you're up on stage and say, wow, this person really knows her stuff. And then you've had a variety of different roles and I'm sure that success is going to continue. So thanks very much for coming on the cube. You're welcome. All right, keep it right there, buddy. We'll be back with our next guest right after this short break, we're here covering the IBM data in a AI form from Miami right back.

Published Date : Oct 22 2019

SUMMARY :

IBM's data and AI forum brought to you by IBM. Ritika, great to have you on. When you think about things like bias and ethicacy, having the diversity in I mean IBM generally, you know, we could see this stuff on the cube because Do you feel that way or do you feel like even a company like IBM has a long way to And I think it goes back to you want to, I understand why you started it started in June. And I think Dave, the reason that's so important is you want to be able to understand that those journeys are So talk about how to address that and why is it important for more it is absolutely important that regardless of whether you are a male or a female, and that you want to have? Um, Dave and that is like when you look at where it starts, out there needs to have a foundational understanding, not only in the three RS that you and I know from when It needs to start early and you I think that that is having an impact. And so I see that as a key component of how coding gets done in the future, So understanding what you And so we've, we've obviously talking in detail about women in AI and women And so having that figure out how you can create the art of the possible. is that right? Yeah. Did you ever work as a programmer? So personally for me, being able to create And what was it that sort of allowed you to break through that barrier? that you see today have to be more technically acute to be able to do their jobs really Then I say, okay, well some examples you can think about Margaret Thatcher in the UK, So, you know, politics aside more women in leadership roles. I mean you certainly see women leaders in a, in Congress and, how these females actually came through to the journey, where they are right now, How do you know it when you see but what you can bring in terms of expertise to make them successful, what you can do to help shape their that success is going to continue.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
IBMORGANIZATION

0.99+

RitikaPERSON

0.99+

Dave VolantePERSON

0.99+

DavePERSON

0.99+

Angela MerkelPERSON

0.99+

10QUANTITY

0.99+

EMCORGANIZATION

0.99+

Ritika GunnarPERSON

0.99+

Rob ThomasPERSON

0.99+

Joe TucciPERSON

0.99+

JuneDATE

0.99+

Satya NadellaPERSON

0.99+

Margaret ThatcherPERSON

0.99+

GermanyLOCATION

0.99+

AustinLOCATION

0.99+

Miami Dade CountyLOCATION

0.99+

AetnaORGANIZATION

0.99+

Omar paraPERSON

0.99+

United StatesLOCATION

0.99+

UKLOCATION

0.99+

Beth SmithPERSON

0.99+

MiamiLOCATION

0.99+

oneQUANTITY

0.99+

Miami, FloridaLOCATION

0.99+

bothQUANTITY

0.99+

15%QUANTITY

0.99+

MinecraftTITLE

0.99+

tonightDATE

0.99+

first yearsQUANTITY

0.99+

PythonTITLE

0.99+

IntercontinentalORGANIZATION

0.98+

todayDATE

0.98+

RetikaPERSON

0.98+

CongressORGANIZATION

0.97+

OneQUANTITY

0.97+

a decade agoDATE

0.97+

first timeQUANTITY

0.96+

Grace HopperEVENT

0.96+

WatsonPERSON

0.96+

firstQUANTITY

0.96+

one timeQUANTITY

0.96+

17%QUANTITY

0.95+

this afternoonDATE

0.94+

DemocratORGANIZATION

0.91+

a yearDATE

0.91+

RepublicanORGANIZATION

0.9+

three RSQUANTITY

0.9+

year and a half agoDATE

0.89+

past decadeDATE

0.89+

IBM DataORGANIZATION

0.87+

Miami DadeORGANIZATION

0.82+

Harley DavidsonORGANIZATION

0.81+

seventiesDATE

0.77+

IBM dataORGANIZATION

0.76+

past few yearsDATE

0.74+

downtown MiamiLOCATION

0.63+

50QUANTITY

0.59+

yearsQUANTITY

0.58+

sixtiesDATE

0.57+

eightiesDATE

0.53+

the panelistsQUANTITY

0.52+

past 50DATE

0.52+

thoseQUANTITY

0.52+