>>Hey, everyone. Welcome to the AWS partner, showcase women in tech. I'm Lisa Martin from the cube. And today we're gonna be looking into the exciting evolution of women in the tech industry. I'm going to be joined by Danielle GShock, the ISP PSA director at AWS. And we have the privilege of speaking with some wicked smart women from Teradata NetApp. JFI a 10th revolution group, company and honeycomb.io. We're gonna look at some of the challenges and biases that women face in the tech industry, especially in leadership roles. We're also gonna be exploring how are these tech companies addressing diversity, equity and inclusion across their organizations? How can we get more young girls into stem earlier in their careers? So many questions. So let's go ahead and get started. This is the AWS partner showcase women in tech. Hey, everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about women in tech. Hillary Ashton joins us the chief product officer at Terry data. And Danielle Greshaw is back with us, the ISV PSA director at AWS ladies. It's great to have you on the program talking through such an important topic, Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background, and a little bit about Teradata. >>Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering product management office of the CTO team. Um, at Teradata I've been with Terra data for just about three years and really have spent the last several decades. If I can say that in the data and analytics space, um, I spent time, uh, really focused on the value of, of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's, um, uh, lots of different dimensions and angles of that. Um, at Teradata, we are partnered very deeply with AWS and happy to talk a little bit more about that, um, throughout this discussion as well. >>Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look, Atter data's views of diversity, equity and inclusion. It's a, the, it's a topic that's important to everyone, but give us a snapshot into some of the initiatives that Terra data has there. >>Yeah, I have to say, I am super proud to be working at Teradata. We have gone through, uh, a series of transformations, but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. Um, and we use, uh, data to back that up. Um, in fact, we were named one of the world's most ethical companies for the 13th year in a row. Um, and all of our executive leadership team has taken an oath around D E and I that's available on LinkedIn as well. So, um, in fact, our leadership team reporting into the CEO is just about 50 50, um, men and women, which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a, on a diverse and equitable, uh, team. And I think it really, uh, improves the behaviors that we can bring, um, to our office. >>There's so much value in that. It's I impressive to see about a 50 50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science, or did you have more of a zigzaggy path to where you are now? >>I'm gonna pick door number two and say more zigzaggy. Um, I started off thinking, um, that I started off as a political science major or a government major. Um, and I was probably destined to go into, um, the law field, but actually took a summer course at Harvard. I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how, um, data and analytics can truly provide value and, and outcomes to our customers. Um, and I have been living that life ever since. Um, I graduated from college, so, um, I was very excited and privileged in my early career to, uh, work in a company where I found after my first year that I was managing, um, uh, kids, people who had graduated from Harvard business school and from MIT Sloan school. Um, and that was super crazy, cuz I did not go to either of those schools, but I sort of have always had a natural knack for how do you take technology and, and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help, um, organizations really extract value, um, from the technology that we can create, which I think is fantastic. >>I think there's so much value in having a zigzag path into tech. You bring Danielle, you and I have talked about this many times you bring such breadth and such a wide perspective. That really is such a value. Add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get and under and underrepresented groups as well, to get into stem and stay. >>Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. Um, but for me, it's really been about, uh, looking at that, uh, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that yes, they can do it because oftentimes it's really about believing in themselves and, and realizing that we need folks with all sorts of different perspectives to kind of come in, to be able to help really, um, provide both products and services and solutions for all types of people inside of technology, which requires all sorts of perspectives. >>Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value revenue impact organizations can make by having diversity, especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on de and I at Tarana, but what are, what do you think can be done to encourage, to sorry, to recruit more young women and under groups into tech, any, any carrot there that you think are really important that we need to be dangling more of? >>Yeah, absolutely. And I'll build on what Danielle just said. I think the, um, bringing in diverse understandings, um, of, of customer outcomes, I mean, I, the we've really moved from technology for technology's sake and I know AWS and entirety to have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer centric and technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well, but unless you're really focused on the outcomes and what customers are seeking, um, technology is not hugely valuable. And so I think bringing in people who understand, um, voice of customer who understand those outcomes, and those are not necessarily the, the, the folks who are PhD in mathematics or statistics, um, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and, and how to program, but also the value in outcomes that technology through data and analytics can drive. >>Yeah. You know, we often talk about the hard skills, but this, their soft skills are equally, if not more important that even just being curious, being willing to ask questions, being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for, for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >>That's right. >>What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >>Yeah. I mean, I think first of all, and, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day, day behaviors when it comes to to women in particular. But I'm sure that that is true across all kinds of, of, um, diverse and underrepresented folks in, in the world. And so I think acknowledging that we have bias and actually really learning how, what that can look like, how that can show up. We might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that, um, as you, as you learn more about, um, different types of bias, that actually you do need to kind of, um, account for that and change behaviors. And so I think learning is sort of a fundamental, um, uh, grounding for all of us to really know what bias looks like, know how it shows up in each of us. >>Um, if we're leaders know how it shows up in our teams and make sure that we are constantly getting better, we're, we're not gonna be perfect anytime soon. But I think being on a path to improvement to overcoming bias, um, is really, is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable, um, when things aren't going in, in a, in a Coptic way and being able to talk openly about that, that felt, um, like maybe there was some bias in that interaction and how do we, um, how do we make good on that? How do we change our, our behavior? Fundamentally of course, data and analytics can have some bias in it as well. And so I think as we look at the, the technology aspect of bias, um, looking at at ethical AI, I think is a, a really important, uh, additional area. And I'm sure we could spend another 20 minutes talking about that, but I, I would be remiss if I didn't talk more about sort of the bias, um, and the over the opportunity to overcome bias in data and analytics as well. >>Yeah. The opportunity to overcome it is definitely there you bring up a couple of really good points, Hillary. It, it starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable ourselves, our teammates, that's critical to being able to, to dial that back down, Daniel, I wanna get your perspective on, on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >>I definitely think in both technical and product roles, we definitely have some work to do. And, you know, when I think about, um, our partnership with Teradata, part of the reason why it's so important is, you know, Teradata solution is really the brains of a lot of companies. Um, you know, the what, how, what they differentiate on how they figure out insights into their business. And it's, it's all about the product itself and the data and the same is true at AWS. And, you know, we really could do some work to have some more women in these technical roles, as well as in the product, shaping the products. Uh, just for all the reasons that we just kind of talked about over the last 10 minutes, um, in order to, you know, move bias out of our, um, out of our solutions and also to just build better products and have, uh, better, you know, outcomes for customers. So I think there's a bit of work to do still. >>I agree. There's definitely a bit of work to do, and it's all about delivering those better outcomes for customers at the end of the day, we need to figure out what the right ways are of doing that and working together in a community. Um, we've had obviously a lot had changed in the last couple of years, Hillary, what's your, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro is silver lining the opposite? What are you seeing? >>Yeah, I mean, certainly there's data out there that tells us factually that it has been, um, very difficult for women during COVID 19. Um, women have, uh, dropped out of the workforce for a wide range of, of reasons. Um, and, and that I think is going to set us back all of us, the, the Royal us or the Royal we back, um, years and years. Um, and, and it's very unfortunate because I think we we're at a time when we're making great progress and now to see COVID, um, setting us back in, in such a powerful way. I think there's work to be done to understand how do we bring people back into the workforce. Um, how do we do that? Understanding work life balance, better understanding virtual and remote, working better. I think in the technology sector, um, we've really embraced, um, hybrid virtual work and are, are empowering people to bring their whole selves to work. >>And I think if anything, these, these zoom calls have, um, both for the men and the women on my team. In fact, I would say much more. So for the men on my team, I'm seeing, I was seeing more kids in the background, more kind of split childcare duties, more ability to start talking about, um, other responsibilities that maybe they had, uh, especially in the early days of COVID where maybe daycares were shut down. And, um, you had, you know, maybe a parent was sick. And so we saw quite a lot of, um, people bringing their whole selves to the office, which I think was, was really wonderful. Um, uh, even our CEO saw some of that. And I think, um, that that really changes the dialogue, right? It changes it to maybe scheduling meetings at a time when, um, people can do it after daycare drop off. >>Um, and really allowing that both for men and for women makes it better for, for women overall. So I would like to think that this hybrid working, um, environment and that this, um, uh, whole view into somebody's life that COVID has really provided for probably for white collar workers, if I'm being honest for, um, people who are in a, at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in, um, you know, coming out of the, the old COVID. I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people, um, to transform how we do work, um, leveraging data and analytics, but also, um, overcoming some of the, the disparities that exist for women in particular in the workforce. >>Yeah, I think there's, there's like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately if we're able to have some sort of work life balance, everything benefits, our work or more productive, higher performing teams impacts customers, right? There's so much value that can be gleaned from, from that hybrid model and embracing for humans. We need to be able to, to work when we can, we've learned that you don't have to be, you know, in an office 24, 7 commuting, crazy hours flying all around the world. We can get a lot of things done in a ways that fit people's lives rather than taking command over it. Wanna get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we, we would both agree on like, ask more questions. Don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech >>Oh, inspired and being in tech? You know, I think looking at technology as, in some ways, I feel like we do a disservice to, um, inclusion when we talk about stem, cuz I think stem can be kind of daunting. It can be a little scary for people for younger people. When I, when I go and talk to folks at schools, I think stem is like, oh, all the super smart kids are over there. They're all like maybe they're all men. And so, um, it's, it's a little, uh, intimidating. Um, and stem is actually, you know, especially for, um, people joining the workforce today. It's actually how you've been living your life since you were born. I mean, you know, stem inside and out because you walk around with a phone and you know how to get your internet working and like that is technology right. >>Fundamentally. And so demystifying stem as something that is around how we, um, actually make our, our lives useful and, and, and how we can change outcomes. Um, through technology I think is maybe a different lens to put on it. So, and there's absolutely for, for hard sciences, there's absolutely a, a great place in the world for folks who wanna pursue that and men and women can do that. So I, I don't want to be, um, uh, setting the wrong expectations, but I, I think stem is, is very holistic in, um, in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in, in some of that world change can participate in stem. It just may be through a different, through a different lens than how we classically talk about stem. >>So I think there's great opportunity to demystify stem. I think also, um, what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost, but I think choose the person that you're gonna work for in your first five to seven years. And it might be more than one person, but be, be selective, maybe be a little less selective about the exact company or the exact title. I think picking somebody that, you know, we talk about mentors and we talk about sponsors and those are important. Um, but the person you're gonna spend in your early career, a lot of your day with a lot, who's gonna influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about, um, because that person can set you up for success and give you opportunities and set you on course to be, um, a standout or that person can hold you back. >>And that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can, um, be a little bit picky about who you go and work for. And I would encourage my younger self. I actually, I just lucked out actually, but I think that, um, my first boss really set me, um, up for success, gave me a lot of feedback and coaching. Um, and some of it was really hard to hear, but it really set me up for, for, um, the, the path that I've been on ever since. So it, that would be my advice. >>I love that advice. I it's brilliant. I didn't think it choose your bosses wisely. Isn't something that we primarily think about. I think a lot of people think about the big name companies that they wanna go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice and also more work to do to demystify stem. But luckily we have great family leaders like the two of you helping us to do that. Ladies, I wanna thank you so much for joining me on the program today and talking through what you're seeing in de and I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >>Thank you so much. Great to see you, Danielle. Thank you Lisa, to see you. >>My pleasure for my guests. I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three, with a focus on women in tech. I'm your host, Lisa Martin. I've got two guests here with me, Sue Peretti, the EVP of global AWS strategic alliances at Jefferson Frank, a 10th revolution group company, and Danielle brushoff. One of our cube alumni joins us ISV PSA director, ladies. It's great to have you on the program talking about a, a topic that is near and dear to my heart at women in tech. >>Thank you, Lisa. >>So let's go ahead and start with you. Give the audience an understanding of Jefferson Frank, what does the company do and about the partnership with AWS? >>Sure. Um, so let's just start, uh, Jefferson Frank is a 10th revolution group company. And if you look at it, it's really talent as a service. So Jefferson Frank provides talent solutions all over the world for AWS clients, partners and users, et cetera. And we have a sister company called revelent, which is a talent creation company within the AWS ecosystem. So we create talent and put it out in the ecosystem. Usually underrepresented groups over half of them are women. And then we also have, uh, a company called rubra, which is a delivery model around AWS technology. So all three companies fall under the 10th revolution group organization. >>Got it. Danielle, talk to me a little bit about from AWS's perspective and the focus on hiring more women in technology and about the partnership. >>Yes. I mean, this has definitely been a focus ever since I joined eight years ago, but also just especially in the last few years we've grown exponentially and our customer base has changed. You know, we wanna have, uh, an organization interacting with them that reflects our customers, right. And, uh, we know that we need to keep pace with that even with our growth. And so we've very much focused on early career talent, um, bringing more women and underrepresented minorities into the organization, sponsoring those folks, promoting them, uh, giving them paths to growth, to grow inside of the organization. I'm an example of that. Of course I benefit benefited from it, but also I try to bring that into my organization as well. And it's super important. >>Tell me a little bit about how you benefited from that, Danielle. >>Um, I just think that, um, you know, I I've been able to get, you know, a seat at the table. I think that, um, I feel as though I have folks supporting me, uh, very deeply and wanna see me succeed. And also they put me forth as, um, you know, a, represent a representative, uh, to bring more women into the organization as well. And I think, um, they give me a platform, uh, in order to do that, um, like this, um, but also many other, uh, spots as well. Um, and I'm happy to do it because I feel that, you know, if you always wanna feel that you're making a difference in your job, and that is definitely a place where I get that time and space in order to be that representative to, um, bring more, more women into benefiting from having careers in technology, which there's a lot of value there, >>A lot of value. Absolutely. So back over to you, what are some of the trends that you are seeing from a gender diversity perspective in tech? We know the, the numbers of women in technical positions, uh, right. There's so much data out there that shows when girls start dropping up, but what are some of the trends that you are seeing? >>So it's, that's a really interesting question. And, and Lisa, I had a whole bunch of data points that I wanted to share with you, but just two weeks ago, uh, I was in San Francisco with AWS at the, at the summit. And we were talking about this. We were talking about how we can collectively together attract more women, not only to, uh, AWS, not only to technology, but to the AWS ecosystem in particular. And it was fascinating because I was talking about, uh, the challenges that women have and how hard to believe, but about 5% of women who were in the ecosystem have left in the past few years, which was really, really, uh, something that shocked everyone when we, when we were talking about it, because all of the things that we've been asking for, for instance, uh, working from home, um, better pay, uh, more flexibility, uh, better maternity leave seems like those things are happening. >>So we're getting what we want, but people are leaving. And it seemed like the feedback that we got was that a lot of women still felt very underrepresented. The number one thing was that they, they couldn't be, you can't be what you can't see. So because they, we feel collectively women, uh, people who identify as women just don't see enough women in leadership, they don't see enough mentors. Um, I think I've had great mentors, but, but just not enough. I'm lucky enough to have a pres a president of our company, the president of our company, Zoe Morris is a woman and she does lead by example. So I'm very lucky for that. And Jefferson, Frank really quickly, we put out a hiring a salary and hiring guide a career and hiring guide every year and the data points. And that's about 65 pages long. No one else does it. Uh, it gives an abundance of information around, uh, everything about the AWS ecosystem that a hiring manager might need to know. But there is what, what I thought was really unbelievable was that only 7% of the people that responded to it were women. So my goal, uh, being that we have such a very big global platform is to get more women to respond to that survey so we can get as much information and take action. So >>Absolutely 7%. So a long way to go there. Danielle, talk to me about AWS's focus on women in tech. I was watching, um, Sue, I saw that you shared on LinkedIn, the Ted talk that the CEO and founder of girls and co did. And one of the things that she said was that there was a, a survey that HP did some years back that showed that, um, 60%, that, that men will apply for jobs if they only meet 60% of the list of requirements. Whereas with females, it's far, far less, we've all been in that imposter syndrome, um, conundrum before. But Danielle, talk to us about AWS, a specific focus here to get these numbers up. >>I think it speaks to what Susan was talking about, how, you know, I think we're approaching it top and bottom, right? We're looking out at what are the, who are the women who are currently in technical positions and how can we make AWS an attractive place for them to work? And that's all a lot of the changes that we've had around maternity leave and, and those types of things, but then also, um, more flexible working, uh, can, you know, uh, arrangements, but then also, um, early, how can we actually impact early, um, career women and actually women who are still in school. Um, and our training and certification team is doing amazing things to get, um, more girls exposed to AWS, to technology, um, and make it a less intimidating place and have them look at employees from AWS and say like, oh, I can see myself in those people. >>Um, and kind of actually growing the viable pool of candidates. I think, you know, we're, we're limited with the viable pool of candidates, um, when you're talking about mid to late career. Um, but how can we, you know, help retrain women who are coming back into the workplace after, you know, having a child and how can we help with military women who want to, uh, or underrepresented minorities who wanna move into AWS, we have a great military program, but then also just that early high school, uh, career, you know, getting them in, in that trajectory. >>Sue, is that something that Jefferson Frank is also able to help with is, you know, getting those younger girls before they start to feel there's something wrong with me. I don't get this. Talk to us about how Jefferson Frank can help really drive up that in those younger girls. >>Uh, let me tell you one other thing to refer back to that summit that we did, uh, we had breakout sessions and that was one of the topics. What can cuz that's the goal, right? To make sure that, that there are ways to attract them. That's the goal? So some of the things that we talked about was mentoring programs, uh, from a very young age, some people said high school, but then we said even earlier, goes back to you. Can't be what you can't see. So, uh, getting mentoring programs, uh, established, uh, we also talked about some of the great ideas was being careful of how we speak to women using the right language to attract them. And some, there was a teachable moment for, for me there actually, it was really wonderful because, um, an African American woman said to me, Sue and I, I was talking about how you can't be what you can't see. >>And what she said was Sue, it's really different. Um, for me as an African American woman, uh, or she identified, uh, as nonbinary, but she was relating to African American women. She said, your white woman, your journey was very different than my journey. And I thought, this is how we're going to learn. I wasn't offended by her calling me out at all. It was a teachable moment. And I thought I understood that, but those are the things that we need to educate people on those, those moments where we think we're, we're saying and doing the right thing, but we really need to get that bias out there. So here at Jefferson, Frank, we're, we're trying really hard to get that careers and hiring guide out there. It's on our website to get more women, uh, to talk to it, but to make suggestions in partnership with AWS around how we can do this mentoring, we have a mentor me program. We go around the country and do things like this. We, we try to get the education out there in partnership with AWS. Uh, we have a, a women's group, a women's leadership group, uh, so much that, that we do, and we try to do it in partnership with AWS. >>Danielle, can you comment on the impact that AWS has made so far, um, regarding some of the trends and, and gender diversity that Sue was talking about? What's the impact that's been made so far with this partnership? >>Well, I mean, I think just being able to get more of the data and have awareness of leaders, uh, on how <laugh>, you know, it used to be a, a couple years back, I would feel like sometimes the, um, uh, solving to bring more women into the organization was kind of something that folks thought, oh, this is Danielle is gonna solve this. You know? And I think a lot of folks now realize, oh, this is something that we all need to solve for. And a lot of my colleagues who maybe a couple years ago, didn't have any awareness or didn't even have the tools to do what they needed to do in order to improve the statistics on their, or in their organizations. Now actually have those tools and are able to kind of work with, um, work with companies like Susan's work with Jefferson Frank in order to actually get the data and actually make good decisions and feel as though, you know, they, they often, these are not lived experiences for these folks, so they don't know what they don't know. And by providing data and providing awareness and providing tooling and then setting goals, I think all of those things have really turned, uh, things around in a very positive way. >>And so you bring up a great point about from a diversity perspective, what is Jefferson Frank doing to, to get those data points up, to get more women of, of all well, really underrepresented minorities to, to be able to provide that feedback so that you can, can have the data and gleamy insights from it to help companies like AWS on their strategic objectives. >>Right? So as I, when I go back to that higher that, uh, careers in hiring guide, that is my focus today, really because the more data that we have, I mean, the, and the data takes, uh, you know, we need people to participate in order to, to accurately, uh, get a hold of that data. So that's why we're asking, uh, we're taking the initiative to really expand our focus. We are a global organization with a very, very massive database all over the world, but if people don't take action, then we can't get the right. The, the, the data will not be as accurate as we'd like it to be. Therefore take better action. So what we're doing is we're asking people all over the, all over the world to participate on our website, Jefferson frank.com, the se the high, uh, in the survey. So we can learn as much as we can. >>7% is such a, you know, Danielle and I we're, we've got to partner on this just to sort of get that message out there, get more data so we can execute, uh, some of the other things that we're doing. We're, we're partnering in. As I mentioned, more of these events, uh, we're, we're doing around the summits, we're gonna be having more ed and I events and collecting more information from women. Um, like I said, internally, we do practice what we preach and we have our own programs that are, that are out there that are within our own company where the women who are talking to candidates and clients every single day are trying to get that message out there. So if I'm speaking to a client or one of our internal people are speaking to a client or a candidate, they're telling them, listen, you know, we really are trying to get these numbers up. >>We wanna attract as many people as we can. Would you mind going to this, uh, hiring guide and offering your own information? So we've gotta get that 7% up. We've gotta keep talking. We've gotta keep, uh, getting programs out there. One other thing I wanted to Danielle's point, she mentioned, uh, women in leadership, the number that we gathered was only 9% of women in leadership within the AWS ecosystem. We've gotta get that number up, uh, as well because, um, you know, I know for me, when I see people like Danielle or, or her peers, it inspires me. And I feel like, you know, I just wanna give back, make sure I send the elevator back to the first floor and bring more women in to this amazing ecosystem. >>Absolutely. That's not that metaphor I do too, but we, but to your point to get that those numbers up, not just at AWS, but everywhere else we need, it's a help me help use situation. So ladies underrepresented minorities, if you're watching go to the Jefferson Frank website, take the survey, help provide the data so that the woman here that are doing this amazing work, have it to help make decisions and have more of females and leadership roles or underrepresented minorities. So we can be what we can see. Ladies, thank you so much for joining me today and sharing what you guys are doing together to partner on this important. Cause >>Thank you for having me, Leah, Lisa, >>Thank you. My pleasure for my guests. I'm Lisa Martin. You're watching the cubes coverage of the AWS partner showcase. Thanks for your time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. We've got two female rock stars here with me next. Stephanie Curry joins us the worldwide head of sales and go to market strategy for AWS at NetApp and Danielle GShock is back one of our QM ISV PSA director at AWS. Looking forward to a great conversation, ladies, about a great topic, Stephanie, let's go ahead and start with you. Give us an overview of your story, how you got into tech and what inspired you. >>Thanks so much, Lisa and Danielle. It's great to be on this show with you. Um, thank you for that. Uh, my name's Stephanie cur, as Lisa mentioned, I'm the worldwide head of sales for, uh, AWS at NetApp and run a global team of sales people that sell all things AWS, um, going back 25 years now, uh, when I first started my career in tech, it was kind of by accident. Um, I come from a different background. I have a business background and a technical background from school, um, but had been in a different career and I had an opportunity to try something new. Um, I had an ally really that reached out to me and said, Hey, you'd be great for this role. And I thought, I'd take a chance. I was curious. Um, and, uh, it, it turned out to be a 25 year career, um, that I'm really, really excited about and, and, um, really thankful for that person, for introducing me to the, to the industry >>25 years in counting. I'm sure Danielle, we've talked about your background before. So what I wanna focus on with you is the importance of diversity for high performance. I know what a machine AWS is, and Stephanie'll come back to you with the same question, but talk about that, Danielle, from your perspective, that importance, um, for diversity to drive the performance. >>Yeah. Yeah. I truly believe that, you know, in order to have high performing teams, that you have to have people from all different types of backgrounds and experiences. And we do find that oftentimes being, you know, field facing, if we're not reflecting our customers and connecting with them deeply, um, on, on the levels that they're at, we, we end up missing them. And so for us, it's very important to bring people of lots of different technical backgrounds experiences. And of course, both men, women, and underrepresented minorities and put that forth to our customers, um, in order to make that connection and to end up with better outcomes. So >>Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity for creating highly performant teams and organizations. >>I really aligned with Danielle on the comment she made. And in addition to that, you know, just from building teams in my, um, career know, we've had three times as many women on my team since we started a year ago and our results are really showing in that as well. Um, we find the teams are stronger, they're more collaborative and to Danielle's point really reflective, not only our partners, but our customers themselves. So this really creates connections, which are really, really important to scale our businesses and, and really, uh, meet the customer where they're at as well. So huge proponent of that ourselves, and really finding that we have to be intentional in our hiring and intentional in how we attract diversity to our teams. >>So Stephanie let's stay with you. So a three X increase in women on the team in a year, especially the kind of last year that we've had is really incredible. I, I like your, I, your thoughts on there needs to be a, there needs to be focus and, and thought in how teams are hired. Let's talk about attracting and retaining those women now, especially in sales roles, we all know the number, the percentages of women in technical roles, but what are some of the things that, that you do Stephanie, that NetApp does to attract and retain women in those sales roles? >>The, the attracting part's really interesting. And we find that, you know, you, you read the stats and I'd say in my experience, they're also true in the fact that, um, a lot of women would look at a job description and say, I can't do a hundred percent of that, that, so I'm not even going to apply with the women that we've attracted to our team. We've actually intentionally reached out and targeted those people in a good way, um, to say, Hey, we think you've got what it takes. Some of the feedback I've got from those women are, gosh, I didn't think I could ever get this role. I didn't think I had the skills to do that. And they've been hired and they are doing a phenomenal job. In addition to that, I think a lot of the feedback I've got from these hires are, Hey, it's an aggressive sales is aggressive. Sales is competitive. It's not an environment that I think I can be successful in. And what we're showing them is bring those softer skills around collaboration, around connection, around building teams. And they do, they do bring a lot of that to the team. Then they see others like them there and they know they can be successful cuz they see others like them on the team, >>The whole concept of we can't be what we can't see, but we can be what we can't see is so important. You said a couple things, Stephanie, that really stuck with me. And one of them was an interview on the Cub I was doing, I think a couple weeks ago, um, about women in tech. And the stat that we talked about was that women will apply will not apply for a job unless they meet 100% of the skills and the requirements that it's listed, but men will, if they only meet 60. And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. It's a huge challenge, but the softer skills, as you mentioned, especially in the last two years, plus the ability to communicate, the ability to collaborate are incredibly important to, to drive that performance of any team of any business. >>Absolutely. >>Danielle, talk to me about your perspective and AWS as well for attracting and retaining talent. And, and, and particularly in some of those challenging roles like sales that as Stephanie said, can be known as aggressive. >>Yeah, for sure. I mean, my team is focused on the technical aspect of the field and we definitely have an uphill battle for sure. Um, two things we are focused on first and foremost is looking at early career women and that how we, how can we bring them into this role, whether in they're in support functions, uh, cl like answering the phone for support calls, et cetera, and how, how can we bring them into this organization, which is a bit more strategic, more proactive. Um, and then the other thing that as far as retention goes, you know, sometimes there will be women who they're on a team and there are no other women on that team. And, and for me, it's about building community inside of AWS and being part of, you know, we have women on solution architecture organizations. We have, uh, you know, I just personally connect people as well and to like, oh, you should meet this person. Oh, you should talk to that person. Because again, sometimes they can't see someone on their team like them and they just need to feel anchored, especially as we've all been, you know, kind of stuck at home, um, during the pandemic, just being able to make those connections with women like them has been super important and just being a, a long tenured Amazonian. Um, that's definitely one thing I'm able to, to bring to the table as well. >>That's so important and impactful and spreads across organizations in a good way. Daniel let's stick with you. Let's talk about some of the allies that you've had sponsors, mentors that have really made a difference. And I said that in past tense, but I also mean in present tense, who are some of those folks now that really inspire you? >>Yeah. I mean, I definitely would say that one of my mentors and someone who, uh, ha has been a sponsor of my career has, uh, Matt YK, who is one of our control tower GMs. He has really sponsored my career and definitely been a supporter of mine and pushed me in positive ways, which has been super helpful. And then other of my business partners, you know, Sabina Joseph, who's a cube alum as well. She definitely has been, was a fabulous partner to work with. Um, and you know, between the two of us for a period of time, we definitely felt like we could, you know, conquer the world. It's very great to go in with a, with another strong woman, um, you know, and, and get things done, um, inside of an organization like AWS. >>Absolutely. And S I've, I've agreed here several times. So Stephanie, same question for you. You talked a little bit about your kind of, one of your, uh, original early allies in the tech industry, but talk to me about allies sponsors, mentors who have, and continue to make a difference in your life. >>Yeah. And, you know, I think it's a great differentiation as well, right? Because I think that mentors teach us sponsors show us the way and allies make room for us at the table. And that is really, really key difference. I think also as women leaders, we need to make room for others at the table too, and not forget those softer skills that we bring to the table. Some of the things that Danielle mentioned as well about making those connections for others, right. And making room for them at the table. Um, some of my allies, a lot of them are men. Brian ABI was my first mentor. Uh, he actually is in the distribution, was in distribution, uh, with advent tech data no longer there. Um, Corey Hutchinson, who's now at Hashi Corp. He's also another ally of mine and remains an ally of mine, even though we're not at the same company any longer. Um, so a lot of these people transcend careers and transcend, um, um, different positions that I've held as well and make room for us. And I think that's just really critical when we're looking for allies and when allies are looking for us, >>I love how you described allies, mentors and sponsors Stephanie. And the difference. I didn't understand the difference between a mentor and a sponsor until a couple of years ago. Do you talk with some of those younger females on your team so that when they come into the organization and maybe they're fresh outta college, or maybe they've transitioned into tech so that they can also learn from you and understand the importance and the difference between the allies and the sponsors and the mentors? >>Absolutely. And I think that's really interesting because I do take, uh, an extra, uh, approach an extra time to really reach out to the women that have joined the team. One. I wanna make sure they stay right. I don't want them feeling, Hey, I'm alone here and I need to, I need to go do something else. Um, and they are located around the world, on my team. They're also different age groups, so early in career, as well as more senior people and really reaching out, making sure they know that I'm there. But also as Danielle had mentioned, connecting them to other people in the community that they can reach out to for those same opportunities and making room for them >>Make room at the table. It's so important. And it can, you never know what a massive difference and impact you can make on someone's life. And I, and I bet there's probably a lot of mentors and sponsors and allies of mine that would be surprised to know, uh, the massive influence they've had Daniel back over. Let's talk about some of the techniques that you employ, that AWS employees to make the work environment, a great place for women to really thrive and, and be retained as Stephanie was saying. Of course that's so important. >>Yeah. I mean, definitely I think that the community building, as well as we have a bit more programmatic mentorship, um, we're trying to get to the point of having a more programmatic sponsorship as well. Um, but I think just making sure that, um, you know, both everything from, uh, recruit to onboard to ever boarding that, uh, they they're the women who come into the organization, whether it's they're coming in on the software engineering side or the field side or the sales side that they feel as that they have someone, uh, working with them to help them drive their career. Those are the key things that were, I think from an organizational perspective are happening across the board. Um, for me personally, when I run my organization, I'm really trying to make sure that people feel that they can come to me at any time open door policy, make sure that they're surfacing any times in which they are feeling excluded or anything like that, any challenges, whether it be with a customer, a partner or with a colleague. Um, and then also of course, just making sure that I'm being a good sponsor, uh, to, to people on my team. Um, that is key. You can talk about it, but you have to start with yourself as well. >>That's a great point. You you've got to, to start with yourself and really reflect on that. Mm-hmm <affirmative> and look, am I, am I embodying what it is that I need? And not that I know they need that focused, thoughtful intention on that is so importants, let's talk about some of the techniques that you use that NetApp uses to make the work environment a great place for those women are marginalized, um, communities to really thrive. >>Yeah. And I appreciate it and much like Danielle, uh, and much like AWS, we have some of those more structured programs, right around sponsorship and around mentorship. Um, probably some growth there, opportunities for allies, because I think that's more of a newer concept in really an informal structure around the allies, but something that we're growing into at NetApp, um, on my team personally, I think, um, leading by example's really key. And unfortunately, a lot of the, um, life stuffs still lands on the women, whether we like it or not. Uh, I have a very, uh, active husband in our household, but I still carry when it push comes to shove it's on me. Um, and I wanna make sure that my team knows it's okay to take some time and do the things you need to do with your family. Um, I'm I show up as myself authentically and I encourage them to do the same. >>So it's okay to say, Hey, I need to take a personal day. I need to focus on some stuff that's happening in my personal life this week now, obviously to make sure your job's covered, but just allowing some of that softer vulnerability to come into the team as well, so that others, um, men and women can feel they can do the same thing. And that it's okay to say, I need to balance my life and I need to do some other things alongside. Um, so it's the formal programs, making sure people have awareness on them. Um, I think it's also softly calling people out on biases and saying, Hey, I'm not sure if you know, this landed that way, but I just wanted to make you aware. And usually the feedback is, oh my gosh, I didn't know. And could you coach me on something that I could do better next time? So all of this is driven through our NetApp formal programs, but then it's also how you manifest it on the teams that we're leading. >>Absolutely. And sometimes having that mirror to reflect into can be really eye-opening and, and allow you to, to see things in a completely different light, which is great. Um, you both talked about, um, kind of being what you, uh, can see, and, and I know both companies are upset customer obsessed in a good way. Talk to me a little bit, Danielle, go back over to you about the AWS NetApp partnership. Um, some of that maybe alignment on, on performance on obviously you guys are very well aligned, uh, in terms of that, but also it sounds like you're quite aligned on diversity and inclusion. >>Well, we definitely do. We have the best partnerships with companies in which we have these value alignments. So I think that is a positive thing, of course, but just from a, from a partnership perspective, you know, from my five now plus years of being a part of the APN, this is, you know, one of the most significant years with our launch of FSX for NetApp. Um, with that, uh, key key service, which we're making available natively on AWS. I, I can't think of a better Testament to the, to the, um, partnership than that. And that's doing incredibly well and it really resonates with our customers. And of course it started with customers and their need for NetApp. Uh, so, you know, that is a reflection, I think, of the success that we're having together. >>And Stephanie talk to, uh, about the partnership from your perspective, NetApp, AWS, what you guys are doing together, cultural alignment, but also your alignment on really bringing diversity into drive performance. >>Yeah, I think it's a, a great question. And I have to say it's just been a phenomenal year. Our relationship has, uh, started before our first party service with FSX N but definitely just, um, uh, the trajectory, um, between the two companies since the announcement about nine months ago has just taken off to a, a new level. Um, we feel like an extended part of the family. We worked together seamlessly. A lot of the people in my team often say we feel like Amazonians. Um, and we're really part of this transformation at NetApp from being that storage hardware company into being an ISV and a cloud company. And we could not do this without the partnership with AWS and without the, uh, first party service of Fs XM that we've recently released. Um, I think that those joint values that Danielle referred to are critical to our success, um, starting with customer obsession and always making sure that we are doing the right thing for the customer. >>We coach our team teams all the time on if you are doing the right thing for the customers, you cannot do anything wrong. Just always put the customer at the, in the center of your decisions. And I think that there is, um, a lot of best practice sharing and collaboration as we go through this change. And I think a lot of it is led by the diverse backgrounds that are on the team, um, female, male, um, race and so forth, and just to really, uh, have different perspectives and different experiences about how we approach this change. Um, so we definitely feel like a part of the family. Uh, we are absolutely loving, uh, working with the AWS team and our team knows that we are the right place, the right time with the right people. >>I love that last question for each of you. And I wanna stick with you Stephanie advice to your younger self, think back five years. What advice would you seen what you've accomplished and maybe the thet route that you've taken along the way, what would you advise your youngest Stephanie self. >>Uh, I would say keep being curious, right? Keep being curious, keep asking questions. And sometimes when you get a no, it's not a bad thing, it just means not right now and find out why and, and try to get feedback as to why maybe that wasn't the right opportunity for you. But, you know, just go for what you want. Continue to be curious, continue to ask questions and find a support network of people around you that wanna help you because they are there and they, they wanna see you be successful too. So never be shy about that stuff. >><laugh> absolutely. And I always say failure does not have to be an, a bad F word. A no can be the beginning of something. Amazing. Danielle, same question for you. Thinking back to when you first started in your career, what advice would you give your younger self? >>Yeah, I think the advice I'd give my younger self would be, don't be afraid to put yourself out there. Um, it's certainly, you know, coming from an engineering background, maybe you wanna stay behind the scenes, not, not do a presentation, not do a public speaking event, those types of things, but back to what the community really needs, this thing. Um, you know, I genuinely now, uh, took me a while to realize it, but I realized I needed to put myself out there in order to, um, you know, allow younger women to see what they could be. So that would be the advice I would give. Don't be afraid to put yourself out there. >>Absolutely. That advice that you both gave are, is so fantastic, so important and so applicable to everybody. Um, don't be afraid to put yourself out there, ask questions. Don't be afraid of a, no, that it's all gonna happen at some point or many points along the way. That can also be good. So thank you ladies. You inspired me. I appreciate you sharing what AWS and NetApp are doing together to strengthen diversity, to strengthen performance and the advice that you both shared for your younger selves was brilliant. Thank you. >>Thank you. >>Thank you >>For my guests. I'm Lisa Martin. You're watching the AWS partner showcase. See you next time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. I've got two female rock stars joining me. Next Vero Reynolds is here engineering manager, telemetry at honeycomb, and one of our cube alumni, Danielle Ock ISV PSA director at AWS. Join us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. >>Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years. Um, but yeah, I started in tech in 2012. Um, I was an engineer for most of that time. Uh, and just recently as a March, switched to engineering management here at honeycomb and, um, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different, um, companies and products. And I've done things from web development to mobile to platforms. Um, it would be apt to call me a generalist. Um, and in the more recent years I was sort of gravitating more towards developer tool space. And for me that, uh, came in the form of cloud Foundry circle CI and now honeycomb. Um, I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. >>Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right, uh, for your career. And so I was like, who is this person? I really like her, uh, found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, uh, found a lot of talks about the product. And on the one hand they really spoke to me as the solution. They talked about developers owning their coding production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from, uh, an amazing woman <laugh>, which I haven't seen before. Uh, so I came across charity majors again, Christine Y our other founder, and then Liz Jones, who's our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You're two leaders. You mentioned that you like the technology, but you were also attracted because you saw females in the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically, um, we have tried not to over index on that because there was this, uh, maybe fear awareness of, um, it taking away from our legitimacy as an engineering organization, from our success as a company. Um, but I'm seeing that, uh, rhetoric shift recently because we believe that with great responsibility, uh, with great power comes great responsibility, and we're trying to be more intentional as far as using that attribute of our company. Um, so I would say that for me, it was, um, a choice between a few offers, right. And that was a selling point for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Um, even me being here and me moving into management, I think were both, um, ways in which they really put a lot of trust and support in me. And so, um, I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you there talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. Um, so honeycomb is an observability tool, uh, that enables engineers to answer questions about the code that runs in production. And, um, we work with a number of various customers. Some of them are Vanguards, slack. Hello, fresh, just to name a couple, if you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because, uh, APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. >>What I mean by rich data is, um, something that has a lot of attributes. So for example, when an error happens, knowing who it happened to, which user ID, which, um, I don't know, region, they were in, um, what, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You can do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ality and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query the data. We can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using comb to understand and observe their system. >>And they get a report that a user is experiencing a slowdown or something's wrong. They can go into comb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out, um, under your data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. Uh, and we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that real time visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important, uh, segment in the cloud space, very important to AWS, um, because a lot of all of our customers, uh, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. Um, they've been working with us for quite some time and they have a, uh, their solution is listed on the marketplace. Um, definitely something that we see a lot of demand with our customers and they have many integrations, uh, which, you know, we've seen is key to success. Um, being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS, uh, things in that area as well. And so, uh, very important partner in the observa observability market that we have >>Back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. Um, I know this predates me to some extent, but I know for a long time, AWS and honeycomb has really pushed the envelope together. And, um, I think it's a beneficial relationship for both ends. There's kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does so in a pretty Orthodox way. So we've had a longstanding conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use this technology in a way that works for us and hopefully will work for other customers of theirs as well. Um, that also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out, um, in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year we built a tool, um, based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that telemetry data out of their applications and into honeycomb. And it man was win, win. >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in, let's talk about how honeycomb supports D and I across its organization. And how is that synergistic with AWS's approach? Yeah, >>Yeah, absolutely. So I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. Um, but again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that, and we're doing a few things differently, um, that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Um, some examples would be after tech hu Latinas in tech among, um, a number of others. And another initiative is DEI head start. That's something that is an internal, um, practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is will lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it, um, with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect, uh, the customers that we have. And I think, you know, working with, uh, a company like honeycomb that is looking to differentiate in a space, um, by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. Um, and you know, it's one of, one of our leadership principles, uh, is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives. Uh, and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, um, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them, um, to do what they need to do in their unique, um, environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI head start program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand, um, and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities, and that can involve partnering with the organizations that I mentioned or reaching out to our internal network, um, and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tag, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate, uh, being able to share this. So I started as a software engineer, uh, back actually in the late nineties, uh, during the, the first.com bubble and, uh, have, have spent quite a long time actually as an individual contributor, um, probably working in software engineering teams up through 2014 at a minimum until I joined AWS, uh, as a customer facing solutions architect. Um, I do think spending a lot of time, hands on definitely helped me with some of the imposter syndrome, um, issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teams at AWS since 2015. Um, so it's really been a great ride. Um, and like I said, I'm very happy to see all of our engineering teams change, uh, as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice, your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual positions and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career, uh, direction, um, and you will always be able to find women like you, you have to maybe just work a little bit harder, uh, to join, have community, uh, in that. But then as a leader, um, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead, love that there. Same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Um, Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask, uh, questions and don't be afraid to kind of show a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or, uh, in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed, there's a million outta people in the room that probably has the, have the same question and because of imposter syndrome, don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is, um, one of the best things. Raise your hand, ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D E and I, we appreciate your insights. Thank you so much for having us great talking to you. My pleasure, likewise for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in check. Welcome to the AWS partner showcase I'm Lisa Martin, your host. This is season one, episode three, and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Shaw, the ISV PSA director at AWS, and the sponsor of this fantastic program. Danielle, it's great to see you and talk about such an important topic. >>Yes. And I will tell you, all of these interviews have just been a blast for me to do. And I feel like there has been a lot of gold that we can glean from all of the, um, stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. So >>I agree. And we're gonna get to set, cuz advice is one of the, the main things that our audience is gonna hear. We have Hillary Ashton, you'll see from TETA there, Reynolds joins us from honeycomb, Stephanie Curry from NetApp and Sue Paris from Jefferson Frank. And the topics that we dig into are first and foremost, diversity equity and inclusion. That is a topic that is incredibly important to every organization. And some of the things Danielle that our audiences shared were really interesting to me. One of the things that I saw from a thematic perspective over and over was that like D Reynolds was talking about the importance of companies and hiring managers and how they need to be intentional with de and I initiatives. And that intention was a, a, a common thing that we heard. I'm curious what your thoughts are about that, that we heard about being intentional working intentionally to deliver a more holistic pool of candidates where de I is concerned. What are your, what were some of the things that stuck out to you? >>Absolutely. I think each one of us is working inside of organizations where in the last, you know, five to 10 years, there's been a, you know, a strong push in this direction, mostly because we've really seen, um, first and foremost, by being intentional, that you can change the, uh, the way your organization looks. Um, but also just that, you know, without being intentional, um, there was just a lot of, you know, outcomes and situations that maybe weren't great for, um, you know, a healthy, um, and productive environment, uh, working environment. And so, you know, a lot of these companies have made a big investments and put forth big initiatives that I think all of us are involved in. And so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how, you know, these align with our values. So >>Yeah, that, that value alignment mm-hmm <affirmative> that you bring up is another thing that we heard consistently with each of the partners, there's a cultural alignment, there's a customer obsession alignment that they have with AWS. There's a D E and I alignment that they have. And I, I think everybody also kind of agreed Stephanie Curry talked about, you know, it's really important, um, for diversity on it, on, on impacting performance, highly performant teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in >>This. Absolutely. And I absolutely, and I definitely even feel that, uh, with their studies out there that tell you that you make better products, if you have all of the right input and you're getting all many different perspectives, but not just that, but I can, I can personally see it in the performing teams, not just my team, but also, you know, the teams that I work alongside. Um, arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities. Tech is a little bit behind, but we're trying really hard to bring that forward as well to in technical roles. Um, but you can just see the difference in the outcomes. Uh, at least I personally can just in the adjacent teams of mine. >>That's awesome. We talked also quite a bit during this episode about attracting women and underrepresented, um, groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that, um, you know, some of the guests talked about in terms of retention? >>Yeah. I think especially, uh, speaking with Hillary and hearing how, uh, Teradata is thinking about different ways to make hybrid work work for everybody. I think that is definitely when I talk to women interested in joining AWS, oftentimes that might be one of the first, uh, concerns that they have. Like, am I going to be able to, you know, go pick my kid up at four o'clock at the bus, or am I going to be able to, you know, be at my kids' conf you know, conference or even just, you know, have enough work life balance that I can, um, you know, do the things that I wanna do outside of work, uh, beyond children and family. So these are all very important, um, and questions that especially women come and ask, but also, um, you know, it kind of is a, is a bellwether for, is this gonna be a company that allows me to bring my whole self to work? And then I'm also gonna be able to have that balance that I need need. So I think that was something that is, uh, changing a lot. And many people are thinking about work a lot differently. >>Absolutely. The pandemic not only changed how we think about work, you know, initially it was, do I work from home or do I live at work? And that was legitimately a challenge that all of us faced for a long time period, but we're seeing the hybrid model. We're seeing more companies be open to embracing that and allowing people to have more of that balance, which at the end of the day, it's so much better for product development for the customers, as you talked about there's, it's a win-win. >>Absolutely. And, you know, definitely the first few months of it was very hard to find that separation to be able to put up boundaries. Um, but I think at least I personally have been able to find the way to do it. And I hope that, you know, everyone is getting that space to be able to put those boundaries up to effectively have a harmonious, you know, work life where you can still be at home most of the time, but also, um, you know, have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >>Yeah, absolutely. And a lot of that from a work life balance perspective leads into one of the next topics that we covered in detail with, and that's mentors and sponsors the differences between them recommendations from, uh, the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that, that Hillary said that I thought was fantastic, advice were mentors and sponsors are concerned is, is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks. I shouldn't say that that are attracted to a company it's brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way. But I thought that was really poignant advice that Hillary provided something that I'm gonna take into consideration myself. >>Yeah. And I honestly hadn't thought about that, but as I reflect through my own career, I can see how I've had particular managers who have had a major impact on helping me, um, with my career. But, you know, if you don't have the ability to do that, or maybe that's not a luxury that you have, I think even if you're able to, you know, find a mentor for a period of time or, um, you know, just, just enable for you to be able to get from say a point a to point B just for a temporary period. Um, just so you can grow into your next role, have a, have a particular outcome that you wanna drive, have a particular goal in mind find that person who's been there and done that and can really help you get through. If you don't have the luxury of picking your manager mentor, who can help you get to the next step. >>Exactly. That, that I thought that advice was brilliant and something that I hadn't really considered either. We also talked with several of the women about imposter syndrome. You know, that's something that everybody, I think, regardless of gender of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real. This is, this is how it happened to me. This is I navigated around or got over it. I think there's some great advice there for the audience to glean as well about how to dial down the imposter syndrome that they might be feeling. >>Absolutely. And I think the key there is just acknowledging it. Um, but also just hearing all the different techniques on, on how folks have dealt with it because everybody does, um, you know, even some of the smartest, most confident men I've, I've met in, uh, industry still talk to me about how they have it and I'm shocked by it oftentimes, but, um, it is very common and hopefully we, we talk about some good techniques to, to deal with that. >>I think we do, you know, one of the things that when we were asking the, our audience, our guests about advice, what would they tell their younger selves? What would they tell young women or underrepresented groups in terms of becoming interested in stem and in tech and everybody sort of agreed on me, don't be afraid to raise your hand and ask questions. Um, show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader, I, I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives. And that's just, don't be afraid to ask questions. You never know, oh, how can people have the same question sitting in the room? >>Well, and also, you know, for folks who've been in industry for 20, 25 years, I think we can just say that, you know, it's a, it's a marathon, it's not a sprint and you're always going to, um, have new things to learn and you can spend, you know, back to, we talked about the zing and zagging through careers, um, where, you know, we'll have different experiences. Um, all of that kind of comes through just, you know, being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, I don't know all the answers, but I wanna learn is a key thing, uh, especially culturally at AWS, but I'm sure with all of these companies as well, >>Definitely I think it sounded like it was really ingrained in their culture. And another thing too, that we also talked about is the word, no, doesn't always mean a dead end. It can often mean not right now or may, maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is gonna learn is that, you know, failure is not necessarily a bad F word. If you turn it into opportunity, no isn't necessarily the end of the road. It can be an opener to a different door. And I, I thought that was a really positive message that our guests, um, had to share with the, the audience. >>Yeah, totally. I can, I can say I had a, a mentor of mine, um, a very, uh, strong woman who told me, you know, your career is going to have lots of ebbs and flows and that's natural. And you know that when you say that, not right now, um, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes, when you can. <laugh> >>Exactly. Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary Vera, Stephanie Sue, and you so much valuable content in here. We hope you enjoy this partner showcase season one, episode three, Danielle, thanks so much for helping >>Us with it's been a blast. I really appreciate it >>All audience. We wanna enjoy this. Enjoy the episode.

>>Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host. Lisa Martin. I've got two female rock stars joining me. Next Vera Reynolds is here engineering manager, telemetry at honeycomb, and one of our Cub alumni, Danielle GShock ISV PSA director at AWS joins us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years, but yeah, I started in tech in 2012. I was an engineer for most of that time. And just recently, as of March switched to engineering management here at honeycomb and, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different companies and products, and I've done things from web development to mobile, to platforms. It would be apt to call me a generalist. And in the more recent years, I was sort of gravitating more towards developer tool space. And for me, that came in the form of cloud Foundry circle CI, and now honeycomb. I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right for your career. >>And so I was like, who is this person? I really like her found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, found a lot of talks about the product. And on the one hand, they really spoke to me as the solution. They talked about developers owning their coding in production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from an amazing woman, which I haven't seen before. So I came across charity majors again, Christine Young, who's our other founder. And then Liz Frank Jones, who's our, our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You two leaders, you mentioned that you liked the technology, but you were also attracted because you saw females and the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically we have tried not to over index on that because there was this maybe fear or rareness of it taking away from our legitimacy as an engineering organization, from our success as a company. But I'm seeing that rhetoric shift recently because we believe that with great responsibility with great power comes great responsibility. And we're trying to be more intentional as far as using that attribute of our company. So I would say that for me, it was a choice between a few offers, right. And that was a selling point, for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Even me being here and me moving into management, I think were both ways in which they really put a lot of trust and support in me. And so I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you here, talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. So honeycomb is an observability tool that enables engineers to answer questions about the code that runs in production. And we work with a number of various customers. Some of them are Vanguards, slack. Hello, fresh. Just to name a couple. If you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. What I mean by rich data is something that has a lot of attributes. >>So for example, when an error happens, knowing who it happened to, which user ID, which I don't know region, they were in, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You could do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ity and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query this data and we can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using honeycomb to understand and observe their system. And they get a report that a user is experiencing a slowdown or something's wrong. >>They can go into honeycomb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out under data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. And we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that realtime visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important segment in the cloud space, very important to AWS, because a lot of all of our customers, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. They've been working with us for quite some time and they have a, their solution is listed on the marketplace. Definitely something that we see a lot of demand with our customers, and they have many integrations, which, you know, we've seen is key to success. Being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS things in that area as well. And so very important partner in the observa observability market that we have >>You back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. I know that this predates me to some extent, but I know for a long time, AWS and honeycomb has really pushed the envelope together. And I think it's a beneficial relationship for both ends. There is kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does so in a pretty Orthodox way. So we've had a long standing conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use the technology in a way that works for us and hopefully will work for other customers of theirs as well. That also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year we built a tool based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that tele, telemetry data out of their applications and into honeycomb and it land was win-win >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in. Let's talk about how honeycomb supports D and I across its organization. And how is that synergistic with AWS's approach? Yeah, >>Yeah, absolutely. So I, I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. But again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that, and we're doing a few things differently that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Some examples would be after tech hu Latinas in tech among a number of others. And another initiative is DEI head start. That's something that is an internal practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is we'll lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect the customers that we have. And I think, you know, working with a company like honeycomb that is looking to differentiate in a space by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. And, you know, it's one of, one of our leadership principles is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them to do what they need to do in their unique environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI headstart program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities. And that can involve partnering with the organizations that I mentioned or reaching out to our internal network and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tech, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate being able to share this. So I started as a software engineer back actually in the late nineties during the, the first.com bubble and have, have spent quite a long time actually as an individual contributor, probably working in software engineering teams up through 2014 at a minimum until I joined AWS as a customer facing solutions architect. I do think spending a lot of time, hands on, definitely helped me with some of the imposter syndrome issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teens at AWS since 2015. So it's really been a great ride. And like I said, I'm very happy to see all of our engineering teams change as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice or your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual contributor positions and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career direction and you will always be able to find women like you, you have to maybe just work a little bit harder to join, have community in that. But then as a leader, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead, love it there. Same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask questions and don't be afraid to kind of show a, a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed. There's a million other people in the room that probably has the, have the same question. And because of imposter syndrome, don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is one of the best things. Raise your hand, ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D and I, we appreciate your insights. >>Thank you so much for having us great talking to you. >>My pleasure, likewise for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in check.

>>Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host. Lisa Martin. I've got two female rock stars joining me. Next Vera Reynolds is here engineering manager, telemetry at honeycomb, and one of our Cub alumni, Danielle GShock ISV PSA director a at AWS joins us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years, but yeah, I started in tech in 2012. I was an engineer for most of that time. And just recently, as of March switched to engineering management here at honeycomb and, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different companies and products. And I've done things from web development to mobile, to platforms. It would be apt to call me a generalist. And in the more recent years, I was sort of gravitating more towards developer tool space. And for me, that came in the form of cloud Foundry circle CI, and now honeycomb. I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right for your career. >>And so I was like, who is this person? I really like her found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, found a lot of talks about the product. And on the one hand, they really spoke to me as the solution. They talked about developers owning their coding in production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from an amazing woman, which I haven't seen before. So I came across charity majors again, Christine yen, who our other founder, and then Liz Frank Jones, who our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You're two leaders. You mentioned that you like the technology, but you were also attracted because you saw females in the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically we have tried not to over index on that because there was this maybe fear or rareness of it taking away from our legitimacy as an engineering organization, from our success as a company. But I'm seeing that rhetoric shift recently because we believe that with great responsibility with great power comes great responsibility. And we're trying to be more intentional as far as using that attribute of our company. So I would say that for me, it was a choice between a few offers, right. And that was a selling point, for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Even me being here and me moving into management, I think were both ways in which they really put a lot of trust and support in me. And so I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you here, talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. So honeycomb is an observability tool that enables engineers to answer questions about the code that runs in production. And we work with a number of various customers. Some of them are Vanguard, slack. Hello, fresh. Just to name a couple. If you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. What I mean by rich data is something that has a lot of attributes. >>So for example, when an error happens, knowing who it happened to, which user ID, which I don't know region, they were in, what, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You can do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ity and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query this data and we can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using comb to understand and observe their system. And they get a report that a user is experiencing a slowdown or something's wrong. >>They can go into honeycomb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out under data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. And we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that real time visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important segment in the cloud space, very important to AWS, because a lot of all of our customers, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. They've been working with us for quite some time and they have a, their solution is listed on the marketplace. Definitely something that we see a lot of demand with our customers, and they have many integrations, which, you know, we've seen is key to success. Being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS things in that area as well. And so very important partner in the observa observability market that we have. >>Vera a back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. I Don know that this Predates me to some extent, but I Don know for a long time, AWS and honeycomb has really pushed the envelope together. And I think it's a beneficial relationship for both ends. There's kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does also in a pretty unorthodox way. So we've had a long standing conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use the technology in a way that works for us and hopefully will work for other customers of theirs as well. That also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year, we built a tool based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that tele telemetry data out of their applications and into honeycomb and demand was win-win >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in. Let's talk about how honeycomb supports D E and I across its organization. And how is that synergistic with AWS's approach Vera? >>Yeah, absolutely. So I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. But again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that end, we're doing a few things differently that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Some examples would be Africa, tech hu Latinas in tech among a number of others. And another initiative is DEI head start. That's something that is an internal practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is will lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect the customers that we have. And I think, you know, working with a company like honeycomb that is looking to differentiate in a space by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. And, you know, it's one of, one of our leadership principles is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them to do what they need to do in their unique environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI head start program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities. And that can involve partnering with the organizations that I mentioned or reaching out to our internal network and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tech, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate being able to share this. So I started as a software engineer back actually in the late nineties during the, the first.com bubble and have, have spent quite a long time actually as an individual contributor, probably working in software engineering teams up through 2014 at a minimum until I joined AWS as a customer facing solutions architect. I do think spending a lot of time, hands on, definitely helped me with some of the imposter syndrome issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teen at AWS since 2015. So it's really been a great ride. And like I said, I'm very happy to see all of our engineering teams change as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice, your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual contributor positions, and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career direction and you will always be able to find women like you, you have to maybe just work a little bit harder to join, have community in that. But then as a leader, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead. Love that various same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask questions and don't be afraid to kind of show a bit, a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed. There's a million outta people in the room that probably has the, have the same question and because an imposter syndrome don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is one of the best things. Raise your hand and ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D E and I, we appreciate your insights. >>Thank you so much for having us talking to >>My pleasure. Likewise, for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in.

(upbeat music) >> Hey everyone. Welcome to theCUBE's coverage of Women In Tech, International Women's Day 2022. I'm your host, Lisa Martin. I have two guests from AWS here with me. Carolina Pina joins us, the head of Enterprise Enablement for LATAM and Laura Alvarez Modernel is here as well, Public Sector Programs Manager at AWS. Ladies, it's great to have you on theCUBE. >> Nice to meet you. >> Thank you for having us. >> Carolina, let's start with you. Talk to me a little bit about your role, what it is that you're doing there. >> So my role in AWS is to actually create mechanisms of massive training to try to close the talent gap that we have in the region. And when I mentioned talent gap, I'm talking about obviously digital and cloud-computing skills. So that's, that's, in a nutshell what my role entails. >> Lisa: Got it. How long have you been in that role? Just curious. >> So I've been at AWS a little bit over, over two years. I was actually in the public sector team when I joined, leading the education vertical for Latin American Canada. And I recently joined the commercial sector now leading these massive training efforts for the region for LATAM. >> And Laura, you're in public sector. Talk to me a little bit about your role. >> Yes, I'm in public sector. I'm also based in Buenos Aires, Argentina. So yeah, I'm from Latin America, and I lead educational and community impact programs in the Southern cone of Latin America. I also lead diversity, equity and inclusion efforts and I'm part of the Women at Amazon global board. That's our affinity group to make sure we make efforts towards building a more equal world. And on a personal note I'm really passionate about the topic of gender equality because I truly think it affects us all as women and as Latins. So that's something that I'm always interested in collaborating with. >> Lisa: Excellent. Carolina back to you. If we think about from an enablement perspective how is AWS partnering with its customers and its partners to train and employ women particularly in technology? >> Oh, sure. Lisa, so it's not a surprise. We, like I mentioned, you know we have a big cloud skills, talent gap in the region. In fact, you know, 69% of companies have reported talent shortages and difficulty hiring. So, and this represents a 15 year high. So, many of these companies are actually, you know, our own commercial customers. So they approach us saying, you know, asking for for support training and developing their talent. So like I mentioned, in my role I create massive training efforts and initiatives. So we always take into consideration women, minorities, underrepresented community, and not just for the current talent, meaning like the people that are currently employed, but also to ensure that we are proactively implementing initiatives to develop a talent of younger you know, a younger generation and a talent. So we can, you know, to inspire them and, and ensure that they, that we're seeing them represented in companies like AWS, you know and our customers, and in our partners. And obviously we, when we sit down with customers to craft these massive trainings you know, leveraging their ecosystems and communities, we actually try to use all our AWS training and certification portfolio which includes, you know, in live in class with live in structures, in classroom trainings. We also have our AWS Skill Builder platform which is the platform that allows us to, you know to reach a broader audience because it has, you know over 500 free and on-demand classes. And we also have a lot of different other programs that touches in different audiences. You know, we have AWS re/Start for underrepresented, and underemployed minorities. We also have AWS Academy, which is the program that we have for higher education institutions. And we have AWS, you know, Educate which also touches, you know, cloud beginners. So in every single of these programs, we ensure that we are encompassing and really speaking to women and developing training and developing women. >> Lisa: That's a great focus there. Laura, talk to me about upskilling. I know AWS is very much about promoting from within. What are some of the things that it's doing to help women in Latin America develop those tech skills and upskill from where, maybe where they are now? >> Well, Lisa, I think that is super interesting because there's definitely a skills gap problem, right? We have all heard about. And what's funny is also that we have this huge opportunity in Latin America to train people and to help further develop the countries. And we have the companies that need the talent. So why is there still a gap, right? And I think that's because there's no magic solution to solving this problem. No, like epic Hollywood movie scene that it's going to show how we close the gap. And it takes stepping out of our comfort zone. And as Carolina mentioned, collaborating. So, we at AWS have a commitment to help 29 million people globally to grow their technical skills with free cloud-computing skills training by 2025. I know that sounds a lot through educational programs but we do have as Carolina mentioned, a Skill Builder you can go into the website for free, enter, choose your path, get trained. We have Academy that we implement with universities. Re/Start that is a program that's already available in Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Costa Rica. So there are a lot of opportunities, but you also mentioned something else that I would like to dive a bit deeper that is Latin American women. And yesterday we had the opportunity to record a panel about intersectionality with three amazing Latin women. And what we have to learn from that is that these are two minorities that intersect, right. We're talking about females that are minority. Latinas are minority. And in tech, that is also something that is even bigger minority. So there are more difficulties there and we need to make sure that we are meeting that talent that is there that is in Latin America, that exists. We know for sure we have unicorns in Latin America that are even AWS customers like Mercado Libre, and we have to meet them with the opportunities. And that's why we created a program that came from identifying how this problem evolves in Latin America, that there is a lack of confidence in women also that they don't feel prepared or equipped. There is a cultural component why we don't choose tech careers. And we partner with universities, more than 12 universities in Latin America with the International American Development Bank as well to create tech skills that's a free five weeks program in order to get students and get female in Latin America, into the tech world. And we also have them with mentorship. So I think that is an opportunity to truly collaborate because we as AWS are not going to solve these by ourselves, right? We need everyone pitching in on that. >> Lisa: Right. It's absolutely a team effort. You mentioned something important in terms of helping women, and especially minorities get out of their comfort zone. Carolina, I'm curious when you're talking with women and getting them into the program and sharing with them all of the enablement programs that you have, how do you help them be confident to get out of that comfort zone? That's a hard thing to do. >> Yeah, no, for sure. For sure, Lisa, well, I, you know, a lot of times actually I use myself as an example because, you know, I studied engineering and industrial systems engineering many years ago. And you know, a lot of my career has been in in higher education and innovation and startups. And as I mentioned in the intro I've been at AWS for a little bit over two years. So I, my career has not been in cloud and I recently joined the cloud. So I actually had to go through our own trainings and get our own certifications. So I, that's, you know a lot of times I actually, I use my own example, so people understand that you don't have to come from tech, you don't have to come, you can actually be a non-tech person and, and also see the the benefits of the cloud. And you don't have to only, you know, learn cloud if you're in the IT department or in an IT team. So sometimes, I also emphasize that the cloud and the future is absolutely the cloud. In fact, the world economic foreign, you know teaches us that cloud-computing is that the technology that's going to be mostly adopted by 2025. So that's why we need to ensure that every single person, women and others are really knowledgeable in the cloud. So that's why, you know, technical and untechnical. But I, you know, I use myself as an example for them to say, you know, you can actually do it. And obviously also I collaborate with Laura and a lot of the women at Amazon Latin America Group to also you know, ensure that we're doing webinars and panels. So we show them ourselves as role model like, Laura is an incredible role model for our community. And so it's also to to show examples of what the possibilities are. And that's what we do. >> Lisa: I love that you're sharing >> And can I make a note there also? >> Please, yes. >> To add to that. I think it also requires the companies and the, and the private sector to get out of their comfort zone, right? Because we are not going to find solutions doing what we are already doing. We truly need to go and get near these persons with a new message. Their interest is there in these programs we have reached more than 3,000 women already in Latin America with tech skills. So it's not that women are not interested. It's like, how do we reach them with a message that resounds with them, right? Like how we can explain the power of technology to transform the world and to actually improve their communities. I think there's something there also that we need to think further of. >> It's so important. You know, we say often when we're talking about women in tech, that she needs to see what she can be or if she can't see it, she can't be it. So having those role models and those mentors and sponsors is absolutely critical for women to get, I call it getting comfortably uncomfortable out of that comfort zone and recognizing there's so many opportunities. Carolina, to your point, you know, these days every company is a tech company, a data company whether you're talking about a car dealer, a grocery market. So your point about, you know, and obviously the future being cloud there's so much opportunity that that opens up, for everybody really, but that's an important thing for people to recognize how they can be a part of that get out of their comfort zone and try something that they maybe hadn't considered before. >> Yes. And, actually, Lisa I would love to share an example. So we have a group, O Boticário, which is one of our customers one of the, the lead retails in Brazil. And they've been a customer of AWS since 2013 when they realized that, you know the urgency and the importance of embracing state of the art technology, to your point, like, you know this is a retail company that understands that needs to be, you know embrace digital transformation, especially because, you know they get very busy during mother's days and other holidays during the year. So they realized that they, instead of outsourcing their IT requirements to technology experts they decided to actually start developing and bringing the talent, you know within itself, within, you know, technology in-house. So they decided to start training within. And that's when we, obviously we partnered with them to also create a very comprehensive training and certification plan that started with, you know a lot of the infrastructure and security teams but then it was actually then implemented in the rest of the company. So going back to the point like everybody really needs to know. And what we also love about O Boticário is they they really care about the diversion and inclusion aspect of this equation. And we actually collaborated with them as well through this program called Desenvolve with the Brazilian government. And Desenvolve means developing Portuguese and they this program really ensures that we are also closing that gender and that race gap and ensuring that they're actually, you know, developing talent in cloud for Brazil. So we, you know, obviously have been very successful with them and we will continue to do even more things with them particular for this topic. >> Lisa: I've always known how customer focused AWS is every time we get to go to re:Invent or some of the events but it's so nice to hear these the educational programs that you're doing with customers to help them improve DEI to help them enable their own women in their organizations to learn skills. I didn't realize that. I think that's fantastic very much a symbiotic part of AWS. If we think about the theme for this year's International Women's Day, Breaking The Bias I want to get both of your opinions and Laura we'll start with you, what that means to you, and where do you think we are in Latin America with breaking the bias? >> Well, I think breaking the bias is the first step to truly being who we are every day and being able to bring that to our work as well. I think we are in a learning curve of that. The companies are changing culturally, as Carolina mentioned we have customers that are aware of the importance of having women. And as we say at AWS not only because there is a good business reason because there is, because there are studies that show that we can increase the country's CPD, but also because it's important and it's the right thing to do. So in terms of breaking the bias I think we are learning and we have a long way to go. I talked a bit earlier about intersectionality and that is something that is also important to highlight, right? Because we are talking about females but we are also talking about another minorities. We're talking about underrepresented communities, Indigenous People, Latins. So when these overlap, we face even bigger challenges to get where we want to get, right? And to get to decision making places because technology is transforming the ways we take decisions, we live, and we need someone like us taking those decisions. So I think it's important at first to be aware and to see that you can get there and eventually to start the conversation going and to build the conversation, not to just leave it but to make sure we hear people and their input and what they're going through. >> Lisa: Yes. We definitely need to hear them. Carolina, what's your take on breaking the bias and where do you from your experience, where do you think we are with it? >> Yeah, no, I'm as passionate as Laura on this topic. And that's why we, you know we're collaborating in the Women at Amazon Latin America Chapter, because we're both very, I think breaking the bias starts with us and ourselves. And we are very proactive within AWS and externally. And I feel it's also, I mean, Lisa, what we've been doing is not only, obviously gathering you know, the troops and really making sure that, that we have very aggressive goals internally, but also bringing you know, bringing our male counterparts, and other, you know, other members of the other communities, because the change, we're not going to make it alone. Like the change where it is not women only talking to women is going to make the change. We actually need to make sure the male and other groups are represented. And the dialogue that they're that we're very conscious about that. And I feel like we're seeing more and more that the topic is becoming more of a priority not only within AWS and Amazon but we also see it because now that I meet with when I meet with customers around the region they really want to see how we can collaborate in these diversion and inclusion initiatives. So I think we are breaking the bias because now this topic is more top of mind. And then we are being more proactively addressing it and and training people and educating people. And I feel we're really in a pivoted point where the change that we've really been wanting to we will see in the next you know, few years which is very exciting. >> Lisa: Excellent, and we'll see that with the help of women like you guys. Thank you so much for joining me today, talking about what you're doing, how you're helping organizations across AWS's ecosystem, customers, partners, and helping, of course, folks from within you, right. It's a holistic effort, but we are on our way to breaking that bias and again, I thank you both for your insights. >> Thank you. >> Thank you, Lisa, for the opportunity. >> My pleasure. For Carolina Pina and Laura Alvarez Modernel, I'm Lisa Martin. You're watching theCUBE's coverage of Women in Tech, International Women's Day 2022. (upbeat music)

>>Hey, everyone. Welcome to the cubes coverage of women in data science, 2022. I'm Lisa Martin. And I'm here with one of the key featured keynotes for this year is with events. So the Aragon, the professor and department of human centered design and engineering at the university of Washington Cecilia, it's a pleasure to have you on the cube. >>Thank you so much, Lisa Lisa, it's a pleasure to be here as well. >>You got an amazing background that I want to share with the audience. You are a professor, you are a data scientist, an aerobatic pilot, and an author with expertise in human centered, data science, visual analytics, aviation safety, and analysis of extremely large and complex data sets. That's quite the background. >>Well, thank you so much. It's it's all very interesting and fun. So, >>And as a professor, you study how people make sense of vast data sets, including a combination of computer science and art, which I love. And as an author, you write about interesting things. You write about how to overcome fear, which is something that everybody can benefit from and how to expand your life until it becomes amazing. I need to take a page out of your book. You were also honored by president Obama a few years back. My goodness. >>Thank you so much. Yes. I I've had quite a journey to come here, but I feel really fortunate to be here today. >>Talk about that journey. I'd love to understand if you were always interested in stem, if it was something that you got into later, I know that you are the co-founder of Latinas in computing, a passionate advocate for girls and women in stem. Were you always interested in stem or was it something that you got into in a kind of a non-linear path? >>I was always interested in it when I was a young girl. I grew up in a small Midwestern town and my parents are both immigrants and I was one of the few Latinas in a mostly white community. And I was, um, I loved math, but I also wanted to be an astronaut. And I remember I, when we were asked, I think it was in second grade. What would you like to be when you grow up? I said, oh, I want to be an astronaut. And my teacher said, oh, you can't do that. You're a girl pick something else. And um, so I picked math and she was like, okay. >>Um, so I always wanted to, well, maybe it would be better to say I never really quite lost my love of being up in the air and potentially space. But, um, but I ended up working in math and science and, um, I, I loved it because one of the great advantages of math is that it's kind of like a magic trick for young people, especially if you're a girl or if you are from an underrepresented group, because if you get the answers right on a math test, no one can mark you wrong. It doesn't matter what the color of your skin is or what your gender is. Math is powerful that way. And I will say there's nothing like standing in a room in front of a room of people who think little of you and you silence them with your love with numbers. >>I love that. I never thought about math as power before, but it clearly is. But also, you know, and, and I wish we had more time because I would love to get into how you overcame that fear. And you write books about that, but being told you can't be an astronaut. You're a girl and maybe laughing at you because you liked Matt. How did you overcome that? And so nevermind I'm doing it anyway. >>Well, that's a, it's a, okay. The short answer is I had incredible imposter syndrome. I didn't believe that I was smart enough to get a PhD in math and computer science. But what enabled me to do that was becoming a pilot and I B I learned how to fly small airplanes. I learned how to fly them upside down and pointing straight at the ground. And I know this might sound kind of extreme. So this is not what I recommend to everybody. But if you are brought up in a way where everybody thinks little of you, one of the best things you can possibly do is take on a challenge. That's scary. I was afraid of everything, but by learning to fly and especially learning to fly loops and rolls, it gave me confidence to do everything else because I thought I appointed the airplane at the ground at 250 miles an hour and waited, why am I afraid to get a PhD in computer science? >>Wow. How empowering is that? >>Yeah, it really was. So that's really how I overcame the fear. And I will say that, you know, I encountered situations getting my PhD in computer science where I didn't believe that I was good enough to finish the degree. I didn't believe that I was smart enough. And what I've learned later on is that was just my own emotional, you know, residue from my childhood and from people telling me that they, you know, that they, that I couldn't achieve >>As I look what, look what you've achieved so far. It's amazing. And we're going to be talking about some of the books that you've written, but I want to get into data science and AI and get your thoughts on this. Why is it necessary to think about human issues and data science >>And what are your thoughts there? So there's been a lot of work in data science recently looking at societal impacts. And if you just address data science as a purely technical field, and you don't think about unintended consequences, you can end up with tremendous injustices and societal harms and harms to individuals. And I think any of us who has dealt with an inflexible algorithm, even if you just call up, you know, customer service and you get told, press five for this press four for that. And you say, well, I don't fit into any of those categories, you know, or have the system hang up on you after an hour. I think you'll understand that any type of algorithmic approach, especially on very large data sets has the risk of impacting people, particularly from low income or marginalized groups, but really any of us can be impacted in a negative way. >>And so, as a developer of algorithms that work over very large data sets, I've always found it really important to consider the humans on the other end of the algorithm. And that's why I believe that all data science is truly human centered or should be human centered, should be human centered and also involves both technical issues as well as social issues. Absolutely correct. So one example is that, um, many of us who started working in data science, including I have to admit me when I started out assume that data is unbiased. It's scrubbed of human influence. It is pure in some ways, however, that's really not true as I've started working with datasets. And this is generally known in the field that data sets are touched by humans everywhere. As a matter of fact, in our, in the recent book that we're, that we're coming out with human centered data science, we talk about five important points where humans touch data, no matter how scrubbed of human influence it's support it's supposed to be. >>Um, so the first one is discovery. So when a human encounters, a data set and starts to use it, it's a human decision. And then there's capture, which is the process of searching for a data set. So any data that has to be selected and chosen by an individual, um, then once that data set is brought in there's curation, a human will have to select various data sets. They'll have to decide what is, what is the proper set to use. And they'll be making judgements on this the time. And perhaps one of the most important ways the data is changed and touched by humans is what we call the design of data. And what that means is whenever you bring in a data set, you have to categorize it. No, for example, let's suppose you are, um, a geologist and you are classifying soil data. >>Well, you don't just take whatever the description of the soil data is. You actually may put it into a previously established taxonomy and you're making human judgments on that. So even though you think, oh, geology data, that's just rocks. You know, that's soil. It has nothing to do with people, but it really does. Um, and finally, uh, people will label the data that they have. And this is especially critical when humans are making subjective judgments, such as what race is the person in this dataset. And they may judge it based on looking at the individual skin color. They may try to apply an algorithm to it, but you know what? We all have very different skin colors, categorizing us into race boxes, really diminishes us and makes us less than we truly are. So it's very important to realize that humans touch the data. We interpret the data. It is not scrubbed of bias. And when we make algorithmic decisions, even the very fact of having an algorithm that makes a judgment say on whether a prisoner's likely to offend again, the judge just by having an algorithm, even if the algorithm makes a recommended statement, they are impacted by that algorithms recommendation. And that has obviously an impact on that human's life. So we consider all of this. >>So you just get given five solid reasons why data science and AI are inevitably human centric should be, but in the past, what's led to the separation between data science and humans. >>Well, I think a lot of it simply has to do with incorrect mental models. So many of us grew up thinking that, oh, humans have biases, but computers don't. And so if we just take decision-making out of people's hands and put it into the hands of an algorithm, we will be having less biased results. However, recent work in the field of data science and artificial intelligence has shown that that's simply not true that algorithmic algorithms reinforce human biases. They amplify them. So algorithmic biases can be much worse than human biases and can greater impact. >>So how do we pull ethics into all of this data science and AI and that ethical component, which seems to be that it needs to be foundational. >>It absolutely has to be foundational. And this is why we believe. And what we teach at the university of Washington in our data science courses is that ethical and human centered approaches and ideas have to be brought in at the very beginning of the algorithm. It's not something you slap on at the end or say, well, I'll wait for the ethicists to weigh in on this. Now we are all human. We can all make human decisions. We can all think about the unintended consequences of our algorithms as we develop them. And we should do that at the very beginning. And all algorithm designers really need to spend some time thinking about the impact that their algorithm may have. >>Right. Do you, do you find that people are still in need of convincing of that or is it generally moving in that direction of understanding? We need to bring ethics in from the beginning, >>It's moving in that direction, but there are still people who haven't modified their mental models yet. So we're working on it. And we hope that with the publication of our book, that it will be used as a supplemental textbook in many data science courses that are focused exclusively on the algorithms and that they can open up the idea that considering the human centered approaches at the beginning of learning about algorithms and data science and the mathematical and statistical techniques, that the next generation of data scientists and artificial intelligence developers will be able to mitigate some of the potentially harmful effects. And we're very excited about this. This is why I'm a professor, because I want to teach the next generation of data scientists and artificial intelligence experts, how to make sure that their work really achieves what they intended it to, which is to make the world a better place, not a worse place, but to enable humans to do better and to mitigate biases and really to lead us into this century in a positive way. >>So the book, human centered data science, you can see it there over Sicily, his right shoulder. When does this come out and how can folks get a copy of it? >>So it came out March 1st and it's available in bookstores everywhere. It was published by MIT press, and you can go online or you can go to your local independent bookstore, or you can order it from your university bookstore as well. >>Excellent. Got to, got to get a copy of, get my hands on that. Got cut and get a copy and dig into that. Cause it sounds so interesting, but also so thoughtful and, um, clear in the way that you described that. And also all the opportunities that, that AI data science and humans are gonna unlock for the world and humans and jobs and, and great things like that. So I'm sure there's lots of great information there. Last question I mentioned, you are keynoting at this year's conference. Talk to me about like the top three takeaways that the audience is going to get from your keynote. >>So I'm very excited to have been invited to wins this year, which of course is a wonderful conference to support women in data science. And I've been a big fan of the conference since it was first developed here, uh, here at Stanford. Um, the three, the three top takeaways I would say is to really consider the data. Science can be rigorous and mathematical and human centered and ethical. It's not a trade-off, it's both at the same time. And that's really the, the number one that, that I'm hoping to keynote will bring to, to the entire audience. And secondly, I hope that it will encourage women or people who've been told that maybe you're not a science person or this isn't for you, or you're not good at math. I hope it will encourage them to disbelieve those views. And to realize that if you, as a member of any type of unread, underrepresented group have ever felt, oh, I'm not good enough for this. >>I'm not smart enough. It's not for me that you will reconsider because I firmly believe that everyone can be good at math. And it's a matter of having the information presented to you in a way that honors your, the background you had. So when I started out my, my high school didn't have AP classes and I needed to learn in a somewhat different way than other people around me. And it's really, it's really something. That's what I tell young people today is if you are struggling in a class, don't think it's because you're not good enough. It might just be that the teacher is not presenting it in a way that is best for someone with your particular background. So it doesn't mean they're a bad teacher. It doesn't mean you're unintelligent. It just means the, maybe you need to find someone else that can explain it to you in a simple and clear way, or maybe you need to get some scaffolding that is Tate, learn extra, take extra classes that will help you. Not necessarily remedial classes. I believe very strongly as a teacher in giving students very challenging classes, but then giving them the scaffolding so that they can learn that difficult material. And I have longer stories on that, but I think I've already talked a bit too long. >>I love that. The scaffolding, I th I think the, the one, one of the high level takeaways that we're all going to get from your keynote is inspiration. Thank you so much for sharing your path to stem, how you got here, why humans, data science and AI are, have to be foundationally human centered, looking forward to the keynote. And again, Cecilia, Aragon. Thank you so much for spending time with me today. >>Thank you so much, Lisa. It's been a pleasure, >>Likewise versus silly Aragon. I'm Lisa Martin. You're watching the cubes coverage of women in data science, 2022.

>>Yeah, yeah. >>Welcome back. I'm so excited to introduce our next session empowerment through inclusion, reimagining society and technology. This is a topic that's personally very near and dear to my heart. Did you know that there's only 2% of Latinas in technology as a Latina? I know that there's so much more we could do collectively to improve these gaps and diversity. I thought spot diversity is considered a critical element across all levels of the organization. The data shows countless times. A diverse and inclusive workforce ultimately drives innovation better performance and keeps your employees happier. That's why we're passionate about contributing to this conversation and also partnering with organizations that share our mission of improving diversity across our communities. Last beyond, we hosted the session during a breakfast and we packed the whole room. This year, we're bringing the conversation to the forefront to emphasize the importance of diversity and data and share the positive ramifications that it has for your organization. Joining us for this session are thought spots Chief Data Strategy Officer Cindy Housing and Ruhollah Benjamin, associate professor of African American Studies at Princeton University. Thank you, Paola. So many >>of you have journeyed with me for years now on our efforts to improve diversity and inclusion in the data and analytic space. And >>I would say >>over time we cautiously started commiserating, eventually sharing best practices to make ourselves and our companies better. And I do consider it a milestone. Last year, as Paola mentioned that half the room was filled with our male allies. But I remember one of our Panelists, Natalie Longhurst from Vodafone, suggesting that we move it from a side hallway conversation, early morning breakfast to the main stage. And I >>think it was >>Bill Zang from a I G in Japan. Who said Yes, please. Everyone else agreed, but more than a main stage topic, I want to ask you to think about inclusion beyond your role beyond your company toe. How Data and analytics can be used to impact inclusion and equity for the society as a whole. Are we using data to reveal patterns or to perpetuate problems leading Tobias at scale? You are the experts, the change agents, the leaders that can prevent this. I am thrilled to introduce you to the leading authority on this topic, Rou Ha Benjamin, associate professor of African studies at Princeton University and author of Multiple Books. The Latest Race After Technology. Rou ha Welcome. >>Thank you. Thank you so much for having me. I'm thrilled to be in conversation with you today, and I thought I would just kick things off with some opening reflections on this really important session theme. And then we could jump into discussion. So I'd like us to as a starting point, um, wrestle with these buzzwords, empowerment and inclusion so that we can have them be more than kind of big platitudes and really have them reflected in our workplace cultures and the things that we design in the technologies that we put out into the world. And so to do that, I think we have to move beyond techno determinism, and I'll explain what that means in just a minute. Techno determinism comes in two forms. The first, on your left is the idea that technology automation, um, all of these emerging trends are going to harm us, are going to necessarily harm humanity. They're going to take all the jobs they're going to remove human agency. This is what we might call the techno dystopian version of the story and this is what Hollywood loves to sell us in the form of movies like The Matrix or Terminator. The other version on your right is the techno utopian story that technologies automation. The robots as a shorthand, are going to save humanity. They're gonna make everything more efficient, more equitable. And in this case, on the surface, he seemed like opposing narratives right there, telling us different stories. At least they have different endpoints. But when you pull back the screen and look a little bit more closely, you see that they share an underlying logic that technology is in the driver's seat and that human beings that social society can just respond to what's happening. But we don't really have a say in what technologies air designed and so to move beyond techno determinism the notion that technology is in the driver's seat. We have to put the human agents and agencies back into the story, the protagonists, and think carefully about what the human desires worldviews, values, assumptions are that animate the production of technology. And so we have to put the humans behind the screen back into view. And so that's a very first step and when we do that, we see, as was already mentioned, that it's a very homogeneous group right now in terms of who gets the power and the resource is to produce the digital and physical infrastructure that everyone else has to live with. And so, as a first step, we need to think about how to create more participation of those who are working behind the scenes to design technology now to dig a little more a deeper into this, I want to offer a kind of low tech example before we get to the more hi tech ones. So what you see in front of you here is a simple park bench public bench. It's located in Berkeley, California, which is where I went to graduate school and on this particular visit I was living in Boston, and so I was back in California. It was February. It was freezing where I was coming from, and so I wanted to take a few minutes in between meetings to just lay out in the sun and soak in some vitamin D, and I quickly realized, actually, I couldn't lay down on this bench because of the way it had been designed with these arm rests at intermittent intervals. And so here I thought. Okay, the the armrest have, ah functional reason why they're there. I mean, you could literally rest your elbows there or, um, you know, it can create a little bit of privacy of someone sitting there that you don't know. When I was nine months pregnant, it could help me get up and down or for the elderly, the same thing. So it has a lot of functional reasons, but I also thought about the fact that it prevents people who are homeless from sleeping on the bench. And this is the Bay area that we were talking about where, in fact, the tech boom has gone hand in hand with a housing crisis. Those things have grown in tandem. So innovation has grown within equity because we haven't thought carefully about how to address the social context in which technology grows and blossoms. And so I thought, Okay, this crisis is growing in this area, and so perhaps this is a deliberate attempt to make sure that people don't sleep on the benches by the way that they're designed and where the where they're implemented and So this is what we might call structural inequity. By the way something is designed. It has certain effects that exclude or harm different people. And so it may not necessarily be the intense, but that's the effect. And I did a little digging, and I found, in fact, it's a global phenomenon, this thing that architects called hostile architecture. Er, I found single occupancy benches in Helsinki, so only one booty at a time no laying down there. I found caged benches in France. And in this particular town. What's interesting here is that the mayor put these benches out in this little shopping plaza, and within 24 hours the people in the town rallied together and had them removed. So we see here that just because we have, uh, discriminatory design in our public space doesn't mean we have to live with it. We can actually work together to ensure that our public space reflects our better values. But I think my favorite example of all is the meter bench. In this case, this bench is designed with spikes in them, and to get the spikes to retreat into the bench, you have to feed the meter you have to put some coins in, and I think it buys you about 15 or 20 minutes. Then the spikes come back up. And so you'll be happy to know that in this case, this was designed by a German artists to get people to think critically about issues of design, not just the design of physical space but the design of all kinds of things, public policies. And so we can think about how our public life in general is metered, that it serves those that can pay the price and others are excluded or harm, whether we're talking about education or health care. And the meter bench also presents something interesting. For those of us who care about technology, it creates a technical fix for a social problem. In fact, it started out his art. But some municipalities in different parts of the world have actually adopted this in their public spaces in their parks in order to deter so called lawyers from using that space. And so, by a technical fix, we mean something that creates a short term effect, right. It gets people who may want to sleep on it out of sight. They're unable to use it, but it doesn't address the underlying problems that create that need to sleep outside in the first place. And so, in addition to techno determinism, we have to think critically about technical fixes that don't address the underlying issues that technology is meant to solve. And so this is part of a broader issue of discriminatory design, and we can apply the bench metaphor to all kinds of things that we work with or that we create. And the question we really have to continuously ask ourselves is, What values are we building in to the physical and digital infrastructures around us? What are the spikes that we may unwittingly put into place? Or perhaps we didn't create the spikes. Perhaps we started a new job or a new position, and someone hands us something. This is the way things have always been done. So we inherit the spike bench. What is our responsibility when we noticed that it's creating these kinds of harms or exclusions or technical fixes that are bypassing the underlying problem? What is our responsibility? All of this came to a head in the context of financial technologies. I don't know how many of you remember these high profile cases of tech insiders and CEOs who applied for Apple, the Apple card and, in one case, a husband and wife applied and the husband, the husband received a much higher limit almost 20 times the limit as his wife, even though they shared bank accounts, they lived in Common Law State. And so the question. There was not only the fact that the husband was receiving a much better interest rate and the limit, but also that there was no mechanism for the individuals involved to dispute what was happening. They didn't even know what the factors were that they were being judged that was creating this form of discrimination. So in terms of financial technologies, it's not simply the outcome that's the issue. Or that could be discriminatory, but the process that black boxes, all of the decision making that makes it so that consumers and the general public have no way to question it. No way to understand how they're being judged adversely, and so it's the process not only the product that we have to care a lot about. And so the case of the apple cart is part of a much broader phenomenon of, um, racist and sexist robots. This is how the headlines framed it a few years ago, and I was so interested in this framing because there was a first wave of stories that seemed to be shocked at the prospect that technology is not neutral. Then there was a second wave of stories that seemed less surprised. Well, of course, technology inherits its creator's biases. And now I think we've entered a phase of attempts to override and address the default settings of so called racist and sexist robots, for better or worse. And here robots is just a kind of shorthand, that the way people are talking about automation and emerging technologies more broadly. And so as I was encountering these headlines, I was thinking about how these air, not problems simply brought on by machine learning or AI. They're not all brand new, and so I wanted to contribute to the conversation, a kind of larger context and a longer history for us to think carefully about the social dimensions of technology. And so I developed a concept called the New Jim Code, which plays on the phrase Jim Crow, which is the way that the regime of white supremacy and inequality in this country was defined in a previous era, and I wanted us to think about how that legacy continues to haunt the present, how we might be coding bias into emerging technologies and the danger being that we imagine those technologies to be objective. And so this gives us a language to be able to name this phenomenon so that we can address it and change it under this larger umbrella of the new Jim Code are four distinct ways that this phenomenon takes shape from the more obvious engineered inequity. Those were the kinds of inequalities tech mediated inequalities that we can generally see coming. They're kind of obvious. But then we go down the line and we see it becomes harder to detect. It's happening in our own backyards. It's happening around us, and we don't really have a view into the black box, and so it becomes more insidious. And so in the remaining couple minutes, I'm just just going to give you a taste of the last three of these, and then a move towards conclusion that we can start chatting. So when it comes to default discrimination. This is the way that social inequalities become embedded in emerging technologies because designers of these technologies aren't thinking carefully about history and sociology. Ah, great example of this came Thio headlines last fall when it was found that widely used healthcare algorithm affecting millions of patients, um, was discriminating against black patients. And so what's especially important to note here is that this algorithm healthcare algorithm does not explicitly take note of race. That is to say, it is race neutral by using cost to predict healthcare needs. This digital triaging system unwittingly reproduces health disparities because, on average, black people have incurred fewer costs for a variety of reasons, including structural inequality. So in my review of this study by Obermeyer and colleagues, I want to draw attention to how indifference to social reality can be even more harmful than malicious intent. It doesn't have to be the intent of the designers to create this effect, and so we have to look carefully at how indifference is operating and how race neutrality can be a deadly force. When we move on to the next iteration of the new Jim code coded exposure, there's attention because on the one hand, you see this image where the darker skin individual is not being detected by the facial recognition system, right on the camera or on the computer. And so coated exposure names this tension between wanting to be seen and included and recognized, whether it's in facial recognition or in recommendation systems or in tailored advertising. But the opposite of that, the tension is with when you're over included. When you're surveiled when you're to centered. And so we should note that it's not simply in being left out, that's the problem. But it's in being included in harmful ways. And so I want us to think carefully about the rhetoric of inclusion and understand that inclusion is not simply an end point. It's a process, and it is possible to include people in harmful processes. And so we want to ensure that the process is not harmful for it to really be effective. The last iteration of the new Jim Code. That means the the most insidious, let's say, is technologies that are touted as helping US address bias, so they're not simply including people, but they're actively working to address bias. And so in this case, There are a lot of different companies that are using AI to hire, create hiring software and hiring algorithms, including this one higher view. And the idea is that there there's a lot that AI can keep track of that human beings might miss. And so so the software can make data driven talent decisions. After all, the problem of employment discrimination is widespread and well documented. So the logic goes, Wouldn't this be even more reason to outsource decisions to AI? Well, let's think about this carefully. And this is the look of the idea of techno benevolence trying to do good without fully reckoning with what? How technology can reproduce inequalities. So some colleagues of mine at Princeton, um, tested a natural learning processing algorithm and was looking to see whether it exhibited the same, um, tendencies that psychologists have documented among humans. E. And what they found was that in fact, the algorithm associating black names with negative words and white names with pleasant sounding words. And so this particular audit builds on a classic study done around 2003, before all of the emerging technologies were on the scene where two University of Chicago economists sent out thousands of resumes to employers in Boston and Chicago, and all they did was change the names on those resumes. All of the other work history education were the same, and then they waited to see who would get called back. And the applicants, the fictional applicants with white sounding names received 50% more callbacks than the black applicants. So if you're presented with that study, you might be tempted to say, Well, let's let technology handle it since humans are so biased. But my colleagues here in computer science found that this natural language processing algorithm actually reproduced those same associations with black and white names. So, too, with gender coded words and names Amazon learned a couple years ago when its own hiring algorithm was found discriminating against women. Nevertheless, it should be clear by now why technical fixes that claim to bypass human biases are so desirable. If Onley there was a way to slay centuries of racist and sexist demons with a social justice box beyond desirable, more like magical, magical for employers, perhaps looking to streamline the grueling work of recruitment but a curse from any jobseekers, as this headline puts it, your next interview could be with a racist spot, bringing us back to that problem space we started with just a few minutes ago. So it's worth noting that job seekers are already developing ways to subvert the system by trading answers to employers test and creating fake applications as informal audits of their own. In terms of a more collective response, there's a federation of European Trade unions call you and I Global that's developed a charter of digital rights for work, others that touches on automated and a I based decisions to be included in bargaining agreements. And so this is one of many efforts to change their ecosystem to change the context in which technology is being deployed to ensure more protections and more rights for everyday people in the US There's the algorithmic accountability bill that's been presented, and it's one effort to create some more protections around this ubiquity of automated decisions, and I think we should all be calling from more public accountability when it comes to the widespread use of automated decisions. Another development that keeps me somewhat hopeful is that tech workers themselves are increasingly speaking out against the most egregious forms of corporate collusion with state sanctioned racism. And to get a taste of that, I encourage you to check out the hashtag Tech won't build it. Among other statements that they have made and walking out and petitioning their companies. Who one group said, as the people who build the technologies that Microsoft profits from, we refuse to be complicit in terms of education, which is my own ground zero. Um, it's a place where we can we can grow a more historically and socially literate approach to tech design. And this is just one, um, resource that you all can download, Um, by developed by some wonderful colleagues at the Data and Society Research Institute in New York and the goal of this interventionist threefold to develop an intellectual understanding of how structural racism operates and algorithms, social media platforms and technologies, not yet developed and emotional intelligence concerning how to resolve racially stressful situations within organizations, and a commitment to take action to reduce harms to communities of color. And so as a final way to think about why these things are so important, I want to offer a couple last provocations. The first is for us to think a new about what actually is deep learning when it comes to computation. I want to suggest that computational depth when it comes to a I systems without historical or social depth, is actually superficial learning. And so we need to have a much more interdisciplinary, integrated approach to knowledge production and to observing and understanding patterns that don't simply rely on one discipline in order to map reality. The last provocation is this. If, as I suggested at the start, inequity is woven into the very fabric of our society, it's built into the design of our. Our policies are physical infrastructures and now even our digital infrastructures. That means that each twist, coil and code is a chance for us toe. We've new patterns, practices and politics. The vastness of the problems that we're up against will be their undoing. Once we accept that we're pattern makers. So what does that look like? It looks like refusing color blindness as an anecdote to tech media discrimination rather than refusing to see difference. Let's take stock of how the training data and the models that we're creating have these built in decisions from the past that have often been discriminatory. It means actually thinking about the underside of inclusion, which can be targeting. And how do we create a more participatory rather than predatory form of inclusion? And ultimately, it also means owning our own power in these systems so that we can change the patterns of the past. If we're if we inherit a spiked bench, that doesn't mean that we need to continue using it. We can work together to design more just and equitable technologies. So with that, I look forward to our conversation. >>Thank you, Ruth. Ha. That was I expected it to be amazing, as I have been devouring your book in the last few weeks. So I knew that would be impactful. I know we will never think about park benches again. How it's art. And you laid down the gauntlet. Oh, my goodness. That tech won't build it. Well, I would say if the thoughts about team has any saying that we absolutely will build it and will continue toe educate ourselves. So you made a few points that it doesn't matter if it was intentional or not. So unintentional has as big an impact. Um, how do we address that does it just start with awareness building or how do we address that? >>Yeah, so it's important. I mean, it's important. I have good intentions. And so, by saying that intentions are not the end, all be all. It doesn't mean that we're throwing intentions out. But it is saying that there's so many things that happened in the world, happened unwittingly without someone sitting down to to make it good or bad. And so this goes on both ends. The analogy that I often use is if I'm parked outside and I see someone, you know breaking into my car, I don't run out there and say Now, do you feel Do you feel in your heart that you're a thief? Do you intend to be a thief? I don't go and grill their identity or their intention. Thio harm me, but I look at the effect of their actions, and so in terms of art, the teams that we work on, I think one of the things that we can do again is to have a range of perspectives around the table that can think ahead like chess, about how things might play out, but also once we've sort of created something and it's, you know, it's entered into, you know, the world. We need to have, ah, regular audits and check ins to see when it's going off track just because we intended to do good and set it out when it goes sideways, we need mechanisms, formal mechanisms that actually are built into the process that can get it back on track or even remove it entirely if we find And we see that with different products, right that get re called. And so we need that to be formalized rather than putting the burden on the people that are using these things toe have to raise the awareness or have to come to us like with the apple card, Right? To say this thing is not fair. Why don't we have that built into the process to begin with? >>Yeah, so a couple things. So my dad used to say the road to hell is paved with good intentions, so that's >>yes on. In fact, in the book, I say the road to hell is paved with technical fixes. So they're me and your dad are on the same page, >>and I I love your point about bringing different perspectives. And I often say this is why diversity is not just about business benefits. It's your best recipe for for identifying the early biases in the data sets in the way we build things. And yet it's such a thorny problem to address bringing new people in from tech. So in the absence of that, what do we do? Is it the outside review boards? Or do you think regulation is the best bet as you mentioned a >>few? Yeah, yeah, we need really need a combination of things. I mean, we need So on the one hand, we need something like a do no harm, um, ethos. So with that we see in medicine so that it becomes part of the fabric and the culture of organizations that that those values, the social values, have equal or more weight than the other kinds of economic imperatives. Right. So we have toe have a reckoning in house, but we can't leave it to people who are designing and have a vested interest in getting things to market to regulate themselves. We also need independent accountability. So we need a combination of this and going back just to your point about just thinking about like, the diversity on teams. One really cautionary example comes to mind from last fall, when Google's New Pixel four phone was about to come out and it had a kind of facial recognition component to it that you could open the phone and they had been following this research that shows that facial recognition systems don't work as well on darker skin individuals, right? And so they wanted Thio get a head start. They wanted to prevent that, right? So they had good intentions. They didn't want their phone toe block out darker skin, you know, users from from using it. And so what they did was they were trying to diversify their training data so that the system would work better and they hired contract workers, and they told these contract workers to engage black people, tell them to use the phone play with, you know, some kind of app, take a selfie so that their faces would populate that the training set, But they didn't. They did not tell the people what their faces were gonna be used for, so they withheld some information. They didn't tell them. It was being used for the spatial recognition system, and the contract workers went to the media and said Something's not right. Why are we being told? Withhold information? And in fact, they told them, going back to the park bench example. To give people who are homeless $5 gift cards to play with the phone and get their images in this. And so this all came to light and Google withdrew this research and this process because it was so in line with a long history of using marginalized, most vulnerable people and populations to make technologies better when those technologies are likely going toe, harm them in terms of surveillance and other things. And so I think I bring this up here to go back to our question of how the composition of teams might help address this. I think often about who is in that room making that decision about sending, creating this process of the contract workers and who the selfies and so on. Perhaps it was a racially homogeneous group where people didn't want really sensitive to how this could be experienced or seen, but maybe it was a diverse, racially diverse group and perhaps the history of harm when it comes to science and technology. Maybe they didn't have that disciplinary knowledge. And so it could also be a function of what people knew in the room, how they could do that chest in their head and think how this is gonna play out. It's not gonna play out very well. And the last thing is that maybe there was disciplinary diversity. Maybe there was racial ethnic diversity, but maybe the workplace culture made it to those people. Didn't feel like they could speak up right so you could have all the diversity in the world. But if you don't create a context in which people who have those insights feel like they can speak up and be respected and heard, then you're basically sitting on a reservoir of resource is and you're not tapping into it to ensure T to do right by your company. And so it's one of those cautionary tales I think that we can all learn from to try to create an environment where we can elicit those insights from our team and our and our coworkers, >>your point about the culture. This is really inclusion very different from just diversity and thought. Eso I like to end on a hopeful note. A prescriptive note. You have some of the most influential data and analytics leaders and experts attending virtually here. So if you imagine the way we use data and housing is a great example, mortgage lending has not been equitable for African Americans in particular. But if you imagine the right way to use data, what is the future hold when we've gotten better at this? More aware >>of this? Thank you for that question on DSO. You know, there's a few things that come to mind for me one. And I think mortgage environment is really the perfect sort of context in which to think through the the both. The problem where the solutions may lie. One of the most powerful ways I see data being used by different organizations and groups is to shine a light on the past and ongoing inequities. And so oftentimes, when people see the bias, let's say when it came to like the the hiring algorithm or the language out, they see the names associated with negative or positive words that tends toe have, ah, bigger impact because they think well, Wow, The technology is reflecting these biases. It really must be true. Never mind that people might have been raising the issues in other ways before. But I think one of the most powerful ways we can use data and technology is as a mirror onto existing forms of inequality That then can motivate us to try to address those things. The caution is that we cannot just address those once we come to grips with the problem, the solution is not simply going to be a technical solution. And so we have to understand both the promise of data and the limits of data. So when it comes to, let's say, a software program, let's say Ah, hiring algorithm that now is trained toe look for diversity as opposed to homogeneity and say I get hired through one of those algorithms in a new workplace. I can get through the door and be hired. But if nothing else about that workplace has changed and on a day to day basis I'm still experiencing microaggressions. I'm still experiencing all kinds of issues. Then that technology just gave me access to ah harmful environment, you see, and so this is the idea that we can't simply expect the technology to solve all of our problems. We have to do the hard work. And so I would encourage everyone listening to both except the promise of these tools, but really crucially, um, Thio, understand that the rial kinds of changes that we need to make are gonna be messy. They're not gonna be quick fixes. If you think about how long it took our society to create the kinds of inequities that that we now it lived with, we should expect to do our part, do the work and pass the baton. We're not going to magically like Fairy does create a wonderful algorithm that's gonna help us bypass these issues. It can expose them. But then it's up to us to actually do the hard work of changing our social relations are changing the culture of not just our workplaces but our schools. Our healthcare systems are neighborhoods so that they reflect our better values. >>Yeah. Ha. So beautifully said I think all of us are willing to do the hard work. And I like your point about using it is a mirror and thought spot. We like to say a fact driven world is a better world. It can give us that transparency. So on behalf of everyone, thank you so much for your passion for your hard work and for talking to us. >>Thank you, Cindy. Thank you so much for inviting me. Hey, I live back to you. >>Thank you, Cindy and rou ha. For this fascinating exploration of our society and technology, we're just about ready to move on to our final session of the day. So make sure to tune in for this customer case study session with executives from Sienna and Accenture on driving digital transformation with certain AI.