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Humans will never be more intelligent than AI. There's going to be two types of companies. Those are great at AI and those that went out of business because they weren't. How do we build a future that is human-centered?
I'm Rana Elka Ubi, and on my podcast, Pioneers of AI, we answer that question and so many more. As an AI scientist, entrepreneur, and investor, I know what it takes to build AI that works for everyone. Every week, I sit down with the Pioneers shaping our future, and we take you behind the scenes of the AI that's transforming our lives. Find Pioneers of AI wherever you tune in.
What does an AI-first human-machine interface look like? Right, if you're designing an interface from scratch, is it really going to be like your smartphone, or what else could it be? That's Rana Elka Ubi, a leading innovator in the field of emotion AI, as in how machines can learn to measure and simulate human emotions. She's also my friend and colleague.
AI can unlock human potential, and it can be both massively economically successful and good for people, so it can help us be healthier, more productive, more knowledgeable, good for the planet, and then building empathy into these devices, too. I think that's so important. We often talk about the importance of IQ when it comes to AI, but Rana wants us to also consider EQ. Emotional intelligence is key to making more human-centric AI.
Rana has dedicated her career to this conviction. She co-founded Affectiva, a company building technology to measure complex human emotions. She's also an investor and author of the best-selling memoir, World Decoded. And now she's adding a new title to the list, podcast host.
Pioneers of AI goes behind the scenes of the AI revolution and gives you the tools to understand what's coming next. You've got to have incredible talent at every position. It's like this is a huge push. There are fires burning when you're going home.
You're going to be an idiot. And then you go back to you. This is truly going to be amazing. You're a so real easy way.
So that's right. I have no idea what it is. Sorry, we need to say. You have to find it right.
Oops. We're going to have a free vegetable party. That just seems absolutely. That falls.
Ten years later. Let's not do it. You have to pay just how you do it. This is Masters of Scale.
Rana Elkayubi is a longtime friend of Masters of Scale. Today, we want to reintroduce her and welcome her new show, Pioneers of AI, to the podcast pantheon. And anytime I get to speak with Rana about where AI is headed, especially on the fronts of empathy and emotion, it's a thrill. Let's get to it.
Welcome, Rana Elkayubi, to Masters of Scale. I've been looking forward to this for a while. Me too. Hi, Pete.
Let's do a little bit of the origin story. So say a little bit about your path to becoming an AI academic, like where you grew up and how you chose your PhD and that kind of stuff. Well, let's see. So I was born in Egypt, as you know.
I grew up around the Middle East. Both my parents were technologists, so we were always exposed to a lot of technology early on. I wanted to be an academic, so I decided to study computer science as an undergraduate. Got really fascinated, I still am, by this human-machine touchpoint, the human-machine interfaces, and how it not only affects our communication with technology, but our relationship with one another, too.
So that became my area of focus. And I left Egypt to go do my PhD at Cambridge University in computer vision and machine learning over 25 years ago. So people think AI is this new thing. I'm like, some of us have been doing this for a while.
And pioneered an area or category within AI called emotion recognition or artificial emotional intelligence. Towards the end of my PhD, I met this MIT professor. She was visiting Cambridge University to give a talk. And we clicked, and she invited me to join her as a postdoc at MIT, and that's how I ended up in the U.S.
One of the things that I think is also, for people who want to go deeper into your story, is the memoir, Girl Decoded. Obviously, a great, clever title in lots of different ways. People way under-describe the EQ issues within AI. How much of that understanding, in addition to the path of your life, would people find from the memoir?
Yeah, the memoir is this juxtaposition of my personal journey with the journey of building the technology, because it's so intertwined. So I talk about, okay, why do emotions matter? They influence every aspect of our lives. Everything from our little decisions every day to big decisions we make, how we learn, how we connect with one another.
Sure, and I'm sure our listeners will recognize that it's not just your IQ that matters, right? Your cognitive intelligence, but your emotional intelligence, your ability to tap into other people's emotional experiences, and that's how we motivate behavior change, influence people, persuade people to do things. So people who have higher EQs tend to be just better leaders and better partners. I do believe that's true for technology as well.
So what's your view? What's your view on that? Well, I mean, one of the things that I think is funny is the people who say emotions don't affect how I make decisions, or I think actually, in fact, it affects them a lot, and they just don't have visibility. The question around, like, you know, what words you choose, or how different words, you know, kind of affect you in different ways, even if they have largely similar semantic meaning, the choice of it.
For example, you know, very classically, you might say, like, I think I might have this point of view, versus I have this point of view. Well, very different emotional impacts. But that's not what people typically focus on. Rana believes that AI models need to be designed to pick up on such nuances, models that can understand the difference between a user saying, I think, versus I know.
She sees this as fundamental to AI's development. And while others have ignored emotion in AI, she's dived in headfirst. The company she co-founded, Affectiva, revolutionized emotion AI. Rana has always been a trailblazer.
From academia to entrepreneurship, she's plowed her way in a field where she was often the only woman and the only Muslim in the room. You know, I used to wear the hijab I wore for 12 years, and I put it on willingly, and I took it off when it just didn't feel like me anymore. I also moved to the U.S. with, you know, as a single mom with two young kids.
They were 10 and 4 at the time, and now they're 21 and 15. And so I think I'd like to believe that I've had this entrepreneurial spirit in me. And when I have conviction, I just go for it. And I think one of my core values is having courage to chart a path that maybe hasn't been charted before.
So when it came to Affectiva, so here I am at MIT. You know, I was funded by the National Science Foundation and Ross Picard's lab. But we started to get a lot of commercial interest in our technology, which is the facial expression recognition technology. And all these Fortune 500 companies wanted to use it for a variety of applications.
And so I remember we walked into the Media Lab Director's office at the time. It was Frank Moss. And we said, Frank, we need more dollars to, like, hire more PhD students. And he thought about it for a second.
He said, you know, this is not research anymore. There's a commercialization opportunity here. And my initial reaction was like, whoa, wait, wait, I'm about to fly for faculty. You know, don't mess with my academic plans.
But then I realized, and that was a tipping point for me, and I think that's my message to academics who are listening to this. Entrepreneurship is an amazing path to actually bring your technology to scale, right? Like, you take it from this academic setting where you're publishing papers and maybe 10 people are using it to, like, scaling it worldwide. And that, to me, is what's so magical about starting a business.
That sense of taking insight and thought and research that you get from, you know, the academic side and then applying it to how do you build scale companies, scale technologies, other kinds of things. You don't have to say it wasn't easy, by the way. I want to share a story. Please.
Like, it's more of a confession, really. You know, I'm a first-time founder. When I started Effectiva, it was my first time doing this. And I think I was really, you know, there was a lot of stuff I didn't know.
So, for example, we had one of the investors who was recording us at the time sent us an email, and he said, one line, send me your BS. And I was like, I have no idea what this guy's talking about. Turns out he was asking for a balance sheet, right? Although, like, very early startups.
BS also means the other thing people think. Right, exactly. Yeah, I was like, the only BS I know of, I can't really attach them, you know. But then I was also like, our very first product roadmap, we were like, Q1, we're going to penetrate the advertising research project.
Q2, we're going to do education. Q3, we'll be help. It was so naive, and we had so underestimated how hard it would be. But I actually think that's okay, because that gives you that conviction and that kind of belief that you can go for it is what keeps you going, I think.
I don't know. Do you agree? I mean, I think a lot of the entrepreneurship stuff, you cannot fully prepare. There's no, I prepare everything.
You can prepare some, but you just have to have that chutzpah and grit and, you know, kind of very broad learning capabilities to do that kind of thing. Yeah, that's right. So go into a little bit more depth about both your research on Affectiva and what the shape of that has been. So the core technology we developed at Affectiva was essentially an emotion recognition system that tracked and identified your various facial expressions and then mapped those to any number of emotional states.
And when we first started, it could only recognize a smile and eyebrow raise and brow furrow. But over time, it now has a repertoire of over 40 different emotional states. And the range of applications is numerous. We service about a third of the Fortune 500 companies globally to understand the emotional connection their consumers have with their products and videos and content.
And then a number of years ago, we pivoted to the automotive market where we now build driver monitoring systems and cabin monitoring systems to really understand what's happening in the car and with the driver's driver attentive or they fall asleep and think of it as being a co-pilot to the both driver and also passengers in the vehicle. In 2021, Affectiva was acquired by a company called SmartEye, but the closing of one door meant the opening of the next. Rana has since launched her career as an investor, focusing on companies revolutionizing the field of AI. So I've been investing for the last three years.
I started a fund with a friend of mine, Rob May. We've made 40 investments. And then I'm now partnering with Gabby Ziderveld, who was part of my team at Affectiva. And we were launching Bluetooth adventures to invest in human-centric AI.
So entrepreneurship, again, but in a different form. I just love being in innovation kind of spaces. And I also love supporting founders on their journeys. I found from my experience that some of my investors were so instrumental to our journey at Affectiva, being thought partners, being strategic advisors, being connectors and door openers.
And I want to do the same for founders of early stage companies. I also think it's an amazing time in AI. And actually, you're one of my inspirations and mentors when it comes to that. It's an amazing time to be investing in AI.
It's your early days. I think the next generation AI companies and transformative companies of our generation are being born now. And how cool would it be to play a part in these companies' journeys? Now, part of what we're doing in this podcast is we're going to be introducing another podcast, because in addition to your hats as academic, inventor, entrepreneur, CEO, investor, you're also becoming a podcaster.
And part of what you're going to be doing is pioneers of AI. So say a little bit about what the podcast is, why now, what chart, what path, what journey will the podcast be heading out on? Yeah, it's another kind of entrepreneurial journey, I would say. So pioneers of AI is a guide for all things AI to people who are both experts in the AI space, who kind of just struggle with keeping up with all the innovations and what's happening in AI.
But ideally, one of our goals is to also expand the audience for AI and make AI more inclusive so that you can come to the podcast to understand AI, embrace AI, anticipate what's coming next with AI. We definitely want to take a balanced view on all the potential good that can come out of AI, but we also want to be underscoring and highlighting where things can go wrong, so that hopefully as a society, we can kind of guard against that. We will be featuring AI builders, of course, so those in the kitchen kind of building the next generation of AI technologies and use cases, but also AI thinkers who are particularly thinking about the implications of AI on culture, on society, on our arts, on science, on education, on parenting, right? So we want to be tackling some of these like everyday questions as it relates to, okay, how is AI going to impact my life on a personal and professional level?
I also am very passionate about platforming voices that we don't typically hear from, so that's going to be one of our goals as well. The best AI agent, in my opinion, would be one that knows you really well, and one way to know you really well is, of course, to get access to all of your information and maybe whatever health device you're wearing on your bank account so that it can act on your behalf and whatnot, but another way it gets to really know you is through your emotional experiences and what's your emotional state? Are you stressed? Are you happy?
Are you anxious? So that it can really customize and personalize its interactions, just the way an awesome friend would do. And I think that's still missing from where AI is. And memory plays a big part of that.
How do you build actual models of memory in getting to learn a person? Yeah, because part of how trust is established is that you believe that the person knows you, cares about you, understands, you know, what's kind of good for you and interests and so forth, and will act in those ways. And memory, of course, is essential to all of that, right? Right.
And if it's not there, right, then the interaction suffers, yeah. You know this as deeply as anyone in the world, but like obviously one of the things about this agentic future is going to be kind of establishing trust. So what do you think is going to be important, not just for gaining trust, but actually, in fact, being a faithful holder of trust? I would say like really knowing what's happening to your data, like first of all, understanding who's behind these agentic AIs, like the company that's building these technologies, I think that needs to be trustworthy.
Knowing where and how your data is being used, that's so important. So I think a certain level of transparency around that is important and also control over that. The relationship between a person and their AI agents is so important. How much autonomy do you want to give your AI agents and does that build over time as you trust them more and more, question mark?
So there's a lot of questions that we ought to be asking kind of as design decisions when we're building these AI agents. I'm so looking forward to Rana's podcast conversations on Pioneers of AI. She's just getting started. And when we come back from a break, Rana takes the mic and asks me a few of her questions about AI.
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I hope to see you there. We're back with a special Masters of Scale introduction for Pioneers of AI with AI scientist, entrepreneur and investor, Rana El-Kalubi. You can find this interview on the Masters of Scale YouTube channel and more about the new show at PioneersOf.ai. We're going to switch hosts and you're now the host for the second half of this podcast.
So I am handing the mic over to you. So exciting. And I will start by saying you also have a new podcast joining our network. Share a bit about Possible.
What's it about? So one of the things I think is a great disservice to humanity that's happening across media, across government discussions and so forth is a fear and dystopia approach to technology first versus a possibility and a creation. And it doesn't mean that it needs to be blind, you know, optimism or blind utopic because, you know, navigating how you get the good is really important. Like, for example, when you're driving somewhere, you don't get somewhere by going, I'm first going to figure out all the things that go wrong before I get in the car, right?
Like, I'm going to go, well, I could spin out of control. I could hit a tree. You got to start driving towards location and you have to have someplace you're going, right? You can't just go, well, if I eliminate all the bad, then the good will happen.
That's not actually, in fact, how a journey and a creation happens. It's going towards something. So the real question is, what should you shake towards? And part of the reason I decided to add possible into the Pantheon.
So we have master scale for scale companies and entrepreneurs and journey and impact. And then possible is, okay, what could possibly go right? Yeah, of course. But like, what should we be building towards?
It's definitely positive, but it's positive in a, you know, how do you chart the journey? How do you navigate? And that's why I added it in to the Pantheon podcast. I love that because sometimes you need to create the possibility, like literally for people.
And then you plant that idea or you create that image or picture of the future and then people can work towards it. But right now there is so much here. So you talk a lot about AI unlocking human potential. What do you mean by that?
So last year I published the first book on AI, co-written with AI. My co-writer was GPT-4. And what I wanted to do is I wanted to show where I understand why, you know, John McCarthy at all, you know, called it artificial intelligence, especially back then. But, you know, it actually now has a little bit of a misnomer.
And so I call it, you know, implication intelligence because it's an amplifier of human capabilities. And that doesn't mean that just like, you know, kind of other technologies, sometimes parts of it so outstrip human that the technology just does it itself. I mean, like for example, we don't have humans plowing farm fields anymore. So it's like any bit of technology kind of moves this and it changes that landscape.
But in the change of the landscape, part of, of course, the discourse has been kind of almost like the movie Idiocracy. Like is AI going to be doing everything and we're going to be sitting on the couches, you know, drinking Gatorade and watching numbing Aldous Huxley, Brave New World, you know, becoming just kind of sensate, you know, bundles of emphatic, lymphatic response. And I just think that it's just not very likely. You have all these discussions about like, well, like you could just, you know, farm a marketing department, use GPT-4.
It's like, well, no, you can't. By the way, marketing is a competition between multiple organizations. And of course, if you're not using GPT-4, you know, and other AI tools in your marketing today, you're falling behind. You're not using key tool sets, but it's human beings doing it and being amplified.
You should be looking at what are the ways in this human competition, just like, for example, I use really good running shoes or I use, you know, flippers or I use scuba tanks or I use, you know, da, da, da. What's the way that I can be deploying this technology to be furthering, you know, my human objectives, my humanist objectives, my business objectives. So that's what the unlocking human potential. And by the way, AI and the application, it brings, we'll have some of those challenges for people full stop and we need to help and be more sympathetic, but ultimately better for your children, better for society, better for industry.
And if you keep a learning and evolving mindset, it can be better for you too. So for some of our listeners who are listening to this conversation and they're still kind of weary of AI, what are some of the applications of AI that you're most excited about? Well, part of when I'm talking to government folks who are like, you know, press is telling me that my primary job is to limit big tech. And part of the problem, of course, is a lot of the driver of AI of this new industrial, this cognitive industrial revolution we're getting is emerging from big tech.
And I say, well, actually, in fact, while this is what everyone's kind of singing the song you should be doing, I have an alternative vision, which is we have a line of sight. We could construct in a small number of months, a medical assistant that is as capable as kind of call it, you know, an average GP or better that could run for a small number of dollars per hour. How do you get that to be made and available to everybody? And then, you know, everybody who has access to a smartphone and then you have a medical assistant for the billions of people in the world who do not have access to a doctor.
And by the way, even here in the US, there are millions of people who do not really have access to a doctor other than an ER room and they may not even have access to an ER room. So that's one. And that will require some modifications of liability laws, some incentives and other things. The second one, which I also think is super important, is a tutor on every skill, every capability, every subject for every age, infinitely patient.
Again, runnable on a smartphone. Wealthy people have always been able to afford tutors for themselves for kids. Now it can be everybody. Yeah.
I love that you've highlighted those two applications in particular. I'm passionate about both of them. It's this idea of democratizing access to quality health and quality education around the world. It's very possible.
Like back to your new podcast, it is so possible. Like the data is there. You can create these like co-pilots for health and co-pilot, career coaches, right? That can be kind of learning companions and career companions.
It's so exciting. What are some of the things that concern you when it comes to AI? Look, it is definitely possible that bad things can happen. Now, one of the reasons why I kind of advocate very strongly against the existential risk that robots are coming, you know, Terminator movie, et cetera, is because most of the real bad things to focus on are AI in the hands of, you know, kind of bad human beings, whether it's criminals, you know, cybercrime, terrorists, a variety of things, rogue states, you know, interference with elections, you know, all of this kind of stuff in the hands of human beings with bad intense because we have those two are the top concerns I have.
Now, you know, again, a little bit of the tech lash is people tend to say, well, you know, but what about like, for example, things like hallucination or, you know, perpetuating a racial stereotype? And shouldn't we like not launch until there was zero of that? And I was like, well, I tend to have the same view that I have on most things, which is you can never get all these things in these complicated systems to zero. So the better thing is make sure that you've got baseline good and then be improving constantly on that.
So you launch anyway. You know, one of the things I've helped set up with various 51c3s is, you know, hosted conversations across all the major tech developers to talk about, you know, what kind of things go wrong and what are safety cases and what should be on a test safety thing. So like people who are obviously don't have visibility naturally get some. And facial eyes, right?
And look, having no visibility, a fear response is not irrational, right? Like, what are you guys doing? Are you just trying to build an AI that's just kind of trying to manipulate you by things I don't know and I want or, you know, or get really angry so I spend a bunch of time on social media. So those are all definitely in the concerns, but there's the concerns that you go, let's steer right now before and then let's, what are the ones that are dynamic and iterating?
And the list of dynamic and iterating is very long. And the list of prevent before it could ever launch is compact and fixed. I'm hearing you also say that there just needs to be a lot of intentionality about how we're building these technologies and kind of thinking ahead of time about what are the unintended consequences? Like what could potentially go wrong, but not letting us stop our innovation for that.
So let's switch to investor mode. The next million dollar company is going to be AI first and it's being born now. You've been investing in AI for many, many years. In fact, I believe you're one of the early investors in open AI.
What do you look for when you are vetting these AI startups? Because every startup today is an AI startup, right? So how do you truly vet what's going to be transformative? Yeah, and I did actually lead the first kind of commercial round into open AI.
So you look for a set of characteristics, which are sufficient, you know, knowledge of technology, an understanding at least of what problems they're going to need to be solving. They may not have the solutions yet, but what problems are and they have a good map. So part of the investor dialogue with them is, you know, how do you see your game? How do you see what the challenge of this is?
And, you know, another thing that is kind of a classic regular entrepreneur failure is I just build a great product and it all works out and you have to have a good market strategy, distribution strategy, you know, which is as important as your product in most cases, sometimes even more. One of the definitions I read about entrepreneurs, oh gosh, 20 years ago, is an entrepreneur makes plans and outstrip their current resources. That is a truth. It isn't the only thing about entrepreneur, but it's like the, okay, I'm going to have to be acquiring capital and talent and customers and the market.
So you have to do all of those kinds of things. So all of that characteristic within the founding teams, kind of general across a lot of these things, although some of them tie in the specifics of what the game looks like now. One of the things I love about entrepreneurship and technology is the game changes on a very fast time period. So, so an answer now evolves and changes.
One of the things about entrepreneurship that's underdescribed is what you're really seeking is to be competitively strong, which means competing against either non-existent competition or weak competition. And if you're jumping into a field where there's like multiple really strong startup competitors, it's much, much harder, right? Like, for example, I'm a little bit more cautious about people coming in and saying, I've got a new chatbot idea. It's like, well, there's a lot of chatbot ideas going for a few years now.
So you really have to have something that that's an interesting, you know, kind of play. But to look at, you know, kind of like, what are other areas that could be really interesting? And also, like, when you're charting the path ahead, you know, you're skating to where the puck is moving towards and where you're building it towards, not to where the puck is today. Do you have a good vision of that?
So I tend to look for things that are not as populated, right? And it's one of the reasons why I led the Series A and Airbnb, you know, and I was, you know, the first money in along with Peter Thiel into Facebook. And part of the reason why, you know, I did the angel investment in PayPal and joined as an executive. Like in a venture thing, what you're kind of ideally looking for is that day one of the investment, everyone thinks you're a little crazy.
And then like year two, it's like, oh, yeah, that's credible. And at year three to five, it's obvious. Amazing. All right, we could go on forever, but I'm going to wrap up our interview together.
So if you could have AI do anything for you, what would that be? I love Ethan Mullick's line, you know, today's AI is the worst AI you're ever going to use. And so this answer should change on a regular basis. Today, what I would love AI to do, and I don't think it's quite there yet, I would love it to be a front end to my complete communications inbox.
Everything from email to, you know, signal and WhatsApp and like intelligently triage that so that I go, okay, like, for example, I wake up in the morning, I don't have to check my email first thing because I'll go, I just, you know, talk to the assistant, the assistant, go, these three things that you really probably need to know right now, first thing in the morning before you get your coffee. Love that. Love that. You know, and by the way, here's 10 things that I might be able to craft good responses to.
Here's to ask, what do you think, right, with that kind of thing to facilitate that communication. Because again, that's amplification of human potential. And the idea is that still keep me very centrally in the loop, but to give me superpowers. Love that.
Well, thank you so much for joining us. Well, it's a pleasure. I'm looking forward to becoming a deeply intrigued listener and, you know, occasional participant. So this is awesome.
While we still have you, search for Pioneers of AI wherever you're listening and subscribe. You can find the first episode. It's right there in the feed. It features Dr.
Joy Bullamini, who's one of the world's leading experts in algorithmic bias. This is a must listen for anyone concerned about how to make safe AI that benefits all of us. Masters of Scale is a Witwet original. Our executive producer is Eve Tro.
Our senior producer is Trisha Bobita. Rachel Ishikawa produced this episode with help from Jordan Smart. They're the ace Pioneers of AI team. The production team for Masters of Scale includes Tucker Ligurski, Masha Makhachanina, Brandon Klein, and Timothy Lou Lee.
Our senior talent executive is Stephanie Stern. Mixing and mastering by Aaron Bastinelli and Ryan Pugh. Original music by Ryan Holiday. Our head of podcast is The Tall Malad.
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