 Live from Stanford University in Palo Alto, California. It's theCUBE. Covering Women in Data Science Conference 2018. Brought to you by Stanford. Welcome to theCUBE. We are live at Stanford University. I'm Lisa Martin, and we are at the third annual Women in Data Science Conference, or WIDS. WIDS, if you're not familiar, is a one day technical conference that has keynote speakers, technical vision talks, as well as a career panel. And we are fortunate to have guests from all three today. It's also an environment, it's really a movement that's aimed at inspiring and educating data scientists globally and supporting women in the field. This event is remarkable. In its third year, they're expecting to reach, sit down for this 100,000 people today. We're here at Stanford. This is the main event in person, but there's over 150 plus regional events around the globe in 50 plus countries. And I think those numbers will shift up during the day and I'll be sure to brief you on that. We're excited to be joined by one of the speakers featured on main stage this morning. Not only a CUBE alum not returning to us, but also the first ever female president of Harvey Mudd College, Dr. Maria Clavey. Maria, welcome back to theCUBE. Thank you, it's great to be here again. It's so exciting to have you here. I love you representing with your t-shirt there. I mentioned you are the first ever female president of Harvey Mudd. You've been in this role for about 12 years and you've made some pretty remarkable changes there, in supporting women in technology. You gave some stats this morning in your talk a few minutes ago. Share with us what you've done to improve the percentages of females in faculty positions as well as in this student body. Well, the first thing I should say is, as president, I do nothing. Nothing. You've done a good job. Yeah, exactly. The whole thing that makes it work at Harvey Mudd is we are a community that's committed to diversity and inclusion. And so everything we do, we try to figure out ways that we will attract people who are underrepresented. So that's women in areas like computer science and engineering physics. It's people of color in all areas of science and engineering. And it's also LGBTQ plus. I mean, it's, you know, it's Muslims. It's just like all kinds of things. And our whole goal is to show that it doesn't matter what race you are. It doesn't matter what gender or anything else. If you bring hard work and persistence and curiosity, you can succeed. I love that, especially the curiosity part. One of the things that you mentioned this morning was that for people, don't worry about the things that you might think you're not good at. I thought that was a very important message as well as something that I heard you say previously on theCUBE as well. And that is the best time that you found to reach women, young women, to get them interested in STEM as even a field of study is the first semester in college. And I shared with you off camera. That was when I found STEM and biology. Tell me a little bit more about that and what are some of the key elements that you find about that time in a university career that are so, I guess, ripe for inspiration? So I think the thing is that when you're starting in college, if somebody can introduce you to something you find fun, engaging, and if you can really discover that you can solve major issues in the world by using these ideas, these concepts, the skills, you're probably gonna stay in that and graduate in that field. Whereas if somebody does that to you when you're in middle school, there's still lots of time to get put off. And so our whole idea is that we emphasize creativity, teamwork, and problem solving. And we do that whether it's in math or in engineering or computer science or biology. We just, in all of our fields. And when we get young women and young men excited about these possibilities, they stick with it. And I love that you mentioned the word fun and curiosity. I can remember exactly where I was in Bio 101 and I was suddenly, I liked biology, but never occurred to me that I would ever have the ability to study it. And it was a teacher that showed me this is fun. And also, and I think you probably do this too, showed that you believe in someone. You've got talent here. And I think that inspiration coming from a mentor, whether you know it's a mentor or not is a key element there that is one that I hope all of the viewers today and the women that are participating in woods have the chance to find. So one of the things every single one of us can do in our lives is encourage others. And it's amazing how much impact you can have. I met somebody who's now a faculty person at Stanford. She did her PhD in mechanical engineering. Her name is Allison Marsden. I hadn't seen her for, I don't know, probably almost 12 years. And she said, she came up to me and she said, I met you just as I was finished my PhD and you gave me a much needed pep talk. And you know, that is so easy to do. Believing in people, encouraging them and it makes so much difference. It does, I love that. So woods is, as I mentioned, in the third annual and the growth that they have seen is unbelievable. I've not seen anything quite like it in tech, in terms of events. It's aimed at inspiring not just women in data science, but data science in general. What is it about woods that attracted you and what are some of the key things that you shared this morning in your opening remarks? Well, so the thing that attracts me about woods is the following, data science is growing exponentially in terms of the job opportunities in terms of the impact on the world. And what I love about woods is that they had the insight, this flash of genius, I think, that they would do a conference where all the speakers would be women. And just that they would show that there are women all over the world who are contributing to data science who are loving it, who are being successful. And it's the craziest thing, because in some ways it's really easy to do, but nobody had done it. And it's so clear that there's a need for this when you think about all of the different locations around the world that are doing a woods version in Nigeria, in Mumbai, in London, in just all across the world there are people doing this. So the things I shared are number one, oh my goodness, this is a great time to get into data science. It's just, there's so many opportunities in terms of career opportunities, but there's so many opportunities to make a difference in the world, and that's really important. Number two, I shared that it's you're never too old to learn math and CS. And my example is my younger sister who's 63 and who's learning math and computer science at the Northern Alberta Institute of Technology, NAIT. All the other students are 18 to 24. She suffers from fibromyalgia. She walks with a walker. She's quite disabled. She's getting A's and A pluses. It's so cool. And I think for every single person in the world, there's an opportunity to learn something new. And the most important thing is hard work and perseverance. That is so much more important than absolutely anything else. I agree with that so much. It's such an inspiring time, but I think that you said there's clearly a demand for this. What Woods has done in such a short time period demonstrates massive demand. The stats that I was reading the last couple of days that show that women with STEM degrees, only 26% of them are actually working in STEM fields. That's very low. And it even can start from things like how companies are recruiting talent and the messages that they're sending may be the right ones, maybe not so much. So I have a great example for you about companies recruiting talent. So about three years ago, I was, no, actually almost four years ago now, I was talking at a conference called HR50. And it's a conference that's aimed at the chief human resource officers of 50 multinationals. And my talk, I was talking for 25 minutes on how to recruit and retain women in tech careers. And afterwards, the chief HR officer from Accenture came up to me and she said, we hire 17,000 software engineers a year just in India. 17,000. And she said, we've been coming in at 30% female and I want to get that up to 45. She said, you told me some really good things I could use. She said, you told me how to change the way we advertise jobs, change the way we interview for jobs. Four months later, her name is Ellen Schuch. Ellen comes up to me at another conference, this happens to be the most powerful women's summit that's run by Fortune Magazine every year. And she comes up and she says, Maria, I implemented different job descriptions. We changed the way we interview and I also, we started actually recruiting at women's college, engineering colleges in India as well as co-ed ones. She said, we came in at 42% female. From 30 to 42, just making those changes. And I went, Ellen, you owe me, you're joining my board. And she did. And Accenture has now set a goal of being at 50-50 in technical roles by 2025. They've continued to come in all around the world, they're coming in at over 40%. And then they've started really looking at how many women are being promoted to partners and they've moved that number up to 30% in the most recent year. So, you know, it's such a great example of a company that just decided we're going to think about how we advertise, we're going to think about how we interview, we're going to think about how we do promotions and we're going to make it equitable. And from a marketing perspective, those aren't massive, massive changes. No, it wasn't expensive. It's quite simple, exactly. Yeah, these are, so the thing I think about, so when I look at what's happened at Harvey Mudd and how we've gotten more women into computer science, engineering, physics, into every discipline, it's really all about encouragement and support. It's about believing in people. It's about having faculty who, when they start teaching a class, that perhaps is technically very rigorous, they might say, this is a really challenging course. Every student in this course who works hard is going to succeed. It's setting that expectation that everyone can succeed. It's so important. I think back to physics and college and how the baseline was probably 60% in terms of grade scoring and you went in with intimidation. I don't know if I can do this. And it sounds like, again, such a simple yet revolutionary approach that you're taking. Let's make things simple, but let's be supportive and encouraging. And hopefully, these people will gain enough confidence that they'll be able to sustain that even within themselves as they graduate and go into careers. Whether they stay in academia or go in industry, and I know you've got great experiences in both. I have, so I've been very lucky and I've been able to work both in academia and in industry. I will say, so I worked for IBM Research for eight years early in my career and I attribute a lot of my success as a leader since then to the kind of professional development that I got as a manager at IBM Research. And what I think is that there's not that much difference between creating a great learning environment and a great work environment. And one of the interesting results that came out of a study at Google, sometime in the last few months, is they looked at what made senior engineering managers successful. And the least important thing was their knowledge of engineering. Of course they all have good knowledge of engineering, but it was empathy, ability to mentor, communication skills, ability to encourage, all of these kinds of things that we think of as quote, unquote soft skills, but that actually changed the world. And on those soft skills, we hear a lot about the hard skills if we're thinking about data scientists from a role perspective, statistical analysis, et cetera, but those soft skills, empathy, and also the ability to kind of bring in different perspectives for analyzing data can really have a major impact on every sector and socially in the world today. And that's why we need women and people of color and people who are not well represented in these fields because data science is changing everything in the world. And if we want those changes to be for the better, we really need diverse perspectives and experiences influencing things that get made because algorithms can be hostile and negative as well as positive and good for the world and you need people who actually will raise the questions about the ethics of algorithms and how it gets used. There's a great book about how math can be used for the bad of humanity as well as the good of humanity. And until we get enough people with different perspectives into these roles, nobody's going to be asking those questions. Right, right. Well, I think with the momentum that we're feeling in this movement today and it sounds like what you're being able to influence greatly at Med for the last 12 years plus, there are foundations that are being put in place with not just on the education perspective but on the personal perspective and inspiring the next generation, giving them, helping them, I should say, achieve the confidence that they need to sustain them throughout their career. So Maria, thank you so much for finding the time to join us this morning on theCUBE. It's great to have you back and we can't wait to talk to you next year and hear what great things you've influenced in the next 12 months. Well, it's wonderful to have a chance to talk with you as well. Thank you so much. Excellent. You've been watching theCUBE. We're live at Stanford University for the third annual Women in Data Science WIDS Conference. Join the conversation, hashtag WIDS 2018. I'm Lisa Martin. Stick around, I'll be right back with my next guest after a short break.