Cannes Round-Up: Rob LoCascio: Modeling Empathy For The Machine

M-A-C-H-I-N-E-Y-E-S-R-X-Y-N-G.

It's Machine Learning from ASSIST. It's a podcast where we think and dream about the future of AI, the talking internet, and how we are reshaping our culture. This chapter is an excerpt from episode 4, a wrap-up of our interviews at the 2018 Cannes Lions International Festival of Creativity. It's where over 10,000 folks from 90 countries meet to hand out awards and chop up the future of brand communication. We used the opportunity to do almost all of our interviews on a boat. But it wasn't just any boat. It was the floating home of LivePerson, one of the true leaders in transforming customer care from voice calls to mobile messaging at scale. They're a huge deal in the conversational commerce world. LivePerson took great care of us and are a true friend of the pod. Coming up, Shane Mac from Assist sits down with Rob Locascio, LivePerson CEO. This is not the same old, same old you get from two technology CEOs. Enjoy.

Why is empathy so important to this? What, what is it specifically that empathy— I mean, empathy is important for everyone to understand what it's like to not be yourself, but how specifically in this space does that play out?

So what is empathy? You know, like, if we start there, it's really that you are engaged with another human being, you are actively listening to that human being, you're not judging them, um, and they are not feeling that they're being judged either. Okay, because we all come with our biases. I see it right now, you're in a t-shirt and you got your sunglasses on, and I could just make a judgment that you're not serious about technology. I just got off a boat, I understand, and it was hot. That's what I'm saying. So, but I'm just saying, like, I could step in and I'm just making a point. Obviously, I know you're serious about technology and you're a great technologist, but we have biases. If I didn't know you, let's say I just sat down, I'm like, this guy's not serious. But so I have that. And then as you started to speak and I listened, I would say, oh wow, you're a serious guy, really. He's running a great company, so forth and so on. And then I let that down. You know that. Yeah, I'm not judging you. And then at that, there's a magic moment where there's empathy. I can relate to you. I can relate to your story. I'm not judging you on my history. Of what I got, who I met, someone like you. Because the brain, the brain does a very funny thing. It tries to optimize for sort of lack of energy, you know.

Say more, what do you mean?

So the brain, you know, when we're, um, about 20% of our energy goes to our brain. So think of our brain is burning 20% of our energy through thought. And so in a day, so our brain is actively trying to do is use its filters to just put you— put things into a box so I don't have to overthink it. You know, when you— if you sat and overthought everything, you'll burn more than 20%.

So bias actually comes from— say it's trying to save energy and not have to think again.

That's it. Wow. So that's the first thing. The second thing bias is, is protecting. I know that you are something, or the, uh, the— our past, and our past is, is thousands of years past. As in, there's a, there's a statistic that like 90% of how we're perceiving things is from a, from our past. Okay, I'm talking about now our past, just I've been around 50 years. I'm talking like from 100,000 years ago.

Like wars. I trusted you because we went to war together and you saved me.

Correct. So our brain has genetic markers all the way through and memories, and then we have our current memories. And then that's what basically what we're doing is saying all of that tells me a bias. You could hurt me, okay? You could hurt me. Like, if you're— if you were— if you were Black, maybe I just have a natural bias because that's what I've had, and that's what's been around for years in the world, you know, or the people in my group of people. I don't know. And I come with that, even if I don't— it's unconscious, even though I don't even know it's there. So that's what bias is about. It's the brain optimizing. It's also trying to protect the the human from, from getting hurt, from getting killed. So that's, that's why it's a very powerful thing.

And when you have that, how do you practice empathy then? How do you make yourself more empathetic?

The best way you can make yourself more empathetic is just put yourself out into things that you don't do. Like, all I can— I can be— I can, I can empathize with you and with your stories if I've had a similar story. So if I've had this life that's fairly limited and I've met— then that's why diversity is very powerful. And I've met a limited set of diverse people. My mind won't expand. Only through diversity do we change. Diversity in our environment, diversity in the people we know. That's why building a great company with diversity, it will help us change. So that's really the important thing.

In the bot space specifically, and AI, I would say, is also relevant. Because I agree with you on the negative tech narrative that it's going to take all our jobs, kill all the people, and take over the world. What are you most optimistic about?

I, I don't think it's going to do that. I, I think actually, first of all, I don't believe that AI should be replicating human intelligence nor consciousness. The human brain is just a tool that's being used to paint reality. That's what it does. And it paints reality based on a set of inputs it's getting from the world around us. Okay, even color, you know, we're seeing color, that's light reflecting off of an object, then my eye interpreting that. I'm saying like our brain is just doing this interpretive thing all day. Why replicate that? Yeah, I don't, I don't get that. Like, it's pretty good. The problem that it has is that the, the inputs it gets, sometimes it, it makes a false connection to something from the past, like we're saying in this bias. If the machine could provide me with another set of realities, you know, another, a better way to do things. For instance, maps are great, like Google Maps. Before there was Google Maps, I may have had a bias. Like, what do you mean? I, maybe I went down a road, I see this in New York City all the time. I'll be, I'll go in a taxi and the guy will go take a route and I'm like, why are you taking that route? And he's like, because this, the route that I'm taking has less traffic. And I will know that I take the other route all the time. It never has traffic. I've seen this all the time and I'm like, the guy's like, but because sometime in his past he hit traffic in that one area, so he figures traffic will be there. You open Google Maps, it says it's green, I'm going. Sometimes it says red, sometimes it says make a right, left, right, left to get around things. That's, that made my reality in the world I'm living in much easier. Like Maps also allowed me to discover things. I can find restaurants, I can find things. So Maps and Google Maps is, is when you think about machine learning, And the data, what they've done is make my— the way my brain is processing reality better. I can better get from point A to point B. And that's what we want is more maps created around us.

That's a great example. That's one of those ones where I think 50% of my childhood parents' fights were around directions to places.

Yeah.

Like that is a— that hits a trigger in me of like remembering always like, no, I know which way. Go left. It's not left.

It's right. Yeah. I remember every time we got stuck in traffic up in the Bronx coming back from New Jersey, my dad was convinced that a game let out at Yankee Stadium. It was like if there was traffic, it was a game in Yankee— even if the Yankee— it was wintertime, the Yankees weren't playing. He's like, a game must have let out. It was like, 'cause he had something that happened in his past where a game let out and he was in traffic, you know? And 60 years later, the game had left out. So you're right.

That's also a great example of people trusting the machine enough. And once it got there, 'cause I remember even in— I would go back to the Midwest and I would have Google Maps open And even 2 or 3 years ago, people would be like, no, I know how to get there faster. And I'm like, it literally says, like, I know all 3 routes and exactly how fast.

Um, so, so we'll trust the machine. This goes back to, back to building bots. We'll trust the machines when they start to paint a, a reality that makes life easier for us and how we think, which is not hard because most of us do trust Google Maps. Like I said, some people but most of the world are trusting electronic maps now.

You know what's fascinating about what you just said though? I never thought about this way. I think it's a really good analogy for bots where you have to let people see where they're going, point A to point B, know there's other routes, but to get to the same end goal. And then you know the friction or speed or steps in which it's going to take to get there. Like maps is actually maybe a great analogy for bot building.

Yes, because in the end, Even with maps, we have human choice.

Exactly.

I'm not being forced. My car's not autonomous yet where I'm forced to go and take a route because of it is I have choice. And so I think people still want to feel, um, that power and they want to feel that they're going to have that choice as they live their life.

Thank you.

Thank you. All right.

Thanks for listening. And thanks once again Thank you again to the folks at LivePerson for their support in making the Machine Learning CAN episodes possible. Get in touch on Twitter @assist. DMs are open. We're super interested to hear who you think should appear on the podcast. Machine Learning is made by Paul Ciuffo and Michael Alsesser for Lumina House. Have a great day.