 Live from Anaheim, California. It's theCUBE, covering Nutanix.next 2019. Brought to you by Nutanix. Welcome back everyone to theCUBE's live coverage of Nutanix.next here in Anaheim, California. I'm your host, Rebecca Knight, along with my co-host, John Furrier. We are joined by Dr. Ayanna Howard. She is a professor and chair of the School of Interactive Computing in the College of Computing at Georgia Institute of Technology. Welcome, Dr. Howard to theCUBE. Thank you, thank you. I'm excited about this conversation. Yeah, so you're a fascinating person. You, when you were a little girl watching Bionic Woman, you said, I want to be a scientist. You started your career at NASA. Correct. You are an entrepreneur, a researcher. Tell us what you're doing today. So what I'm doing today, and what I'm really excited about, is bringing robots into the home of children with special needs. So one of the things about kids, and those that may have a developmental disability, is that there's not enough contact hours with human clinicians. And so how do you augment that in the home environment? How do you bring technology into the home to do therapy with them, to do even education? And so that's what I focus on. So we want to hear so much more about that, but what are you going to be talking about at this conference? It's the future of AI and robots. Yeah, so I'm going to talk about the things that make my robots work. And so the future of AI and robotics and where it leads is a combination of things like wearables. So if you think about all the data around us, we have wearables with our phones and our smartwatches. All that data that's being collected about us allows our machines to do very interesting personalized things with us and for us. The other thing is that if you think about collaborative AI, collaborative machines, we're going to the place where the workforce and how you do your work, you are going to have an AI as a companion, a robot as an assistant. So you might not be sitting next to a human, you might be sitting next to a robot. And so what does that look like? And then of course, emotional AI. And so yes, machines do have emotions, which counts kind of weird, but in order for us to work with others, we typically have a bond. So why not have a bond with our machines? What's the software look like? I'm riffing in my mind here, just thinking about, I want to write some software that be dynamic, a neural network, these kinds of words been kicked around in the industry. How do you make software have emotion in AI? Because it has to be random, but yet not, it has to be programmable. It does, but think about it. Emotions are not necessarily random. Emotions are pretty repetitive. I.e., if you're hurt, what do you do? If you're young, you cry. If you're older, you hide the cry, right? I mean, it's very repetitive. If you're happy, there's a certain emotion and what makes you happy? There are certain things that we can all say, if I suddenly woke up and I won a prize, I'd be happy. Emotions are actually very predictable. They're not that hard to model. And the data sources could be coming off my Fitbit, facial recognition, you know, the morning. Well, facial recognition, you can see it in the face. In fact, your pulse, and you sweat a little bit when your emotion changed. You remember the mood rings back in the day? Sure. Okay, those were fake, but still, their concept about them was that, you know, your body gives a response based on the emotions inside. Yeah, it's so cool. So what's the state of the art? If you had to, you know, look at bleeding edge and state of the art kind of mainstream, where are people with the software, machine learning, AI? What's some of the things that are notable to you that are important to highlight? Yeah, so I think that the two areas that are the furthest ahead is, one is facial recognition and emotion detection. And it's because the applications that are out there, as an example, airports are putting in these systems. So imagine, I mean, the positive is, is that you don't have to book or print out your ticket, right? You just walk into the airport, you walk through security, you don't get padded down, and you walk to your gate and get on the plane. I mean, just imagine that, and you're like, well, how would you do that? Well, if I know who you look like and I can model you and I grab your wearable and your data, I know who you are. So I don't have to make sure that you are who you are. I know. I mean, so that's kind of the benefit. Of course, there's some negatives that you won't talk about. But that's one area, this facial recognition aspect. The other, I think, is in healthcare. I think it's in the fact that our data and about us, about our health, it's so much there, and as we mine it, we just get better. There's, for example, some research that shows stress can be detected. And I can then have a, think about it, I can have an AI that if I know you're stressed, like, I'm not going to send you that email. I'm going to halt a little bit until I realize that your stress level is a little bit better. And then I will give you the bad news, right? Like, because we don't want to be stressed. But that's a manager with really good intentions. I mean, you can really see the perils of this going. No, that's the negative. That's the aspect of all these things are really have good return on investment, good quality. But the negatives are is that if you have a nefarious manager or an organization's like, I just want to make money, money, money, you can sway that. And I think, though, that most organizations are thinking about this. I think there's this push now to do things like regulations to basically protect us, but still ensure that we have a positive relationship with AI and robotics. What's the coolest thing you've seen or built recently that could tie into the robotics? So I will personally say it's one of our machines that has, it emotionally responds to you based on what you're doing. And so what does this mean? It means I have robots that are just looking so cute, right? You look at them and anyone looks at them and it's just, it's like, it's real, it's intelligent, it like understands me. Of course it's programmed based on modeling, but it's just as fascinating. And I watch people interact with the robots and it's like, oh my gosh, like this person, this individual is really engaged with my robot recreation. And you mean in conversation or just in feeling the camaraderie? Conversation and interaction. And the robots, they have a limited script, but people will adapt to that, right? And they will, it's just like when you talk to your phone, have you noticed that when your phone doesn't understand you, what do you do? You speak a little slower. You might choose different words, right? I see that with the robots. You change your behavior based on the limitations. You're speaking with someone who doesn't speak your language natively. Correct, correct. Same thing with robots. So describe what you see, returning to the beginning of our conversation, talking in particularly with kids with special needs. Describe what you see, the changes in the child who is developing a relationship, a bond with a robot. Yeah, so what we've actually shown, not just see and observed is that when we have a child interacting with the robot there, and what we call whatever milestones we're doing, so maybe it's movement therapy, which means I want them to say move a little faster than their normal space of moving. What I see is with the robot there as a partner, encouraging, guiding, providing them input on how well they're doing or in terms of correcting, the child improves their behavior. And so between day zero and day in, the child has gotten better. We see that, we have the data that shows that. Incredible. I want to also ask about women in technology. And this is really a theme at every single tech conference you go to because it's such a problem. It's such an issue that is finally getting the attention it deserves. We know about the dearth of women leaders, the dearth of underrepresented minorities, particularly in management leadership positions. What do you see as your role in tackling this problem? Yes. As the head of an important department in technology, and also as a woman of color. Yeah, so I think there's always been kind of two dilemmas. One is what they call the pipeline, which is now the pathway. Like how do you get women to come into STEM? And the data has shown that it's not that girls are not interested in STEM, is that they lose interest because of their society, right? So that's one thing. It's like make sure that where they are and the society is encouraging. The other is that when you get older, you look up and you're like, okay, there's no one there. Obviously I'm not supposed to be here or when things get tough, it's like, okay, I need to move out. And so the other is, is how do you do mentorship and sponsorship so that women are pushed forward as managers and supervisors? So those are kind of the two things. And so as a, and I consider myself a leader in this space, I actually feel it's my duty to be upfront and be a mentor and be a lead and actually be vocal and make others realize like if I'm in a room and we're deciding on a student or a candidate and there is no representation, I'm comfortable enough to say, hey, I should not be the one that says this, right? And eventually what you see is that people start looking and thinking about this at every instance of time. Do you feel like it's getting better? I do, it's getting better. And it's not perfect, but it's getting better. Like if I look at my in the classrooms or I look in like the computer science curriculums, I see more female students coming in and lasting and then going into corporate America and continue on to grad school. I see it being better. Of course it's not on parity, but it is better. That's awesome. And the technology has shifted the definition. It's not programming or electrical engineering. The surface area for tech is gaming to analytics, data science is a huge- Human-centered interaction. This new artistry around it. So I think it's a great surface area. It is. And I think one of the reasons why it's so important is that the world is diverse. I mean, in terms of all the different aspects. And so if you're going to create products for a diverse world, you should have individuals that are also diverse creating them for everyone and so that there is some equality in the process. As the analog world connects with the digital world. Fascinating, we're talking before we came on camera around the technology and digital. So the human experience from whether having robots detecting emotion and having some sort of new kinds of notifications like, hey, you know, cheer up or do something clever is that you can now immerse. So augmented reality has been the first killer app before virtual reality, but gaming is an indicator of what's happening on screen. So the on-screen digital realm is intersecting with our lives. It is. What's your view on this? Because this is an area that's new. It's cutting edge. It's a first generation problem, opportunity. Opportunity. I think this blending of the, I would say, even I will say the blending of the digital and the physical and the gamification aspects is really going to enhance two areas. One is education and the retraining. And so what does that mean? It means that, you know, instead of me having to, you know, not to say go to college for four years, but instead of me trying to study everything in this one semester course, it's like I just need some basic knowledge and I can then work in the field and I have my augmented reality. And so I see things and there's some scaffolding. There's some indication of here's the step one, here's step two. You did that step two a little bit wrong. Let's revise it. You saw you learn with real-time training and that's with doctors, well, except for live patients, but, you know, with doctors or residents or factory workers or even teachers, teachers who are teaching, say, calculus that may have an English background. That's where it is. So the progressions are not linear, like they used to be. They're different and now you have data and instrumentation with on-demand digital robots, agents. Agents, adaptation, taking things from other places. So if I, for example, learn the best way to provide information to this human and this factory, well, guess what? I can take that information, connect to the cloud, connect to the data centers and apply that information to another worker in a different factory but very similar characteristics. And so you have this transfer of knowledge as well. So education was one, what's the other one, healthcare? Of course it's healthcare, of course. As someone who is immersed in it and a believer in technology, what do you do to disconnect? Well, first of all, do you disconnect? Do you worry about our over-reliance on these little devices in our pockets? And what do you do to sort of leave the digital world behind for a while? Yeah, so I do worry about our over-reliance because we've shown, and other researchers have shown, that there's actually an over-trust factor. We will use devices and of course these devices, they have errors, right? Even if it's 1% of the time. And that 1% of the time when they have errors, we find that a lot of individuals will trust those errors because they're over-reliant. And they kind of go in zone mode and they're like, it worked all this time so that 1% they just don't question. It must be real news. It's, but it's scary, right? It's scary. I do worry about that. And we're thinking about ways to try to mitigate that because that does worry me. How do I disconnect? I think that with anything, mind, body and soul, so I love listening to music, although that's not disconnecting from technology because I'm using technology to listen, but it's this zone period exercise. I think most of us think about exercise. I'm fairly religious even when I'm traveling, like, okay, I'm going to find the gym and at least walk on the treadmill because we do have to have that combination in order to be healthier cells. Finally, for the little girl, the little girl, you, who is watching Bionic Women, I think that's the thing. We need more shows like that to get kids interested. Well, exactly, exactly. What would be your advice to the smaller you who says, I want to be a scientist someday? So I would, and this is like some advice that people told me as I was growing up, and I didn't realize I had really good mentors, is one is don't listen to the naysayers, i.e. believe in yourself, right? And I think that's the one thing we sometimes forget to do, like believe in that dream, even if others say that it's not possible. And it's like, no, everything is possible if you believe in yourself. Words to live by. Thank you so much for coming on the show. This was great conversation. Awesome. I'm Rebecca Knight for John Fourier. We will be back here tomorrow with more from Nutanix.next. We hope to see you then.