VOICE Round-Up: Google’s Cathy Pearl explains Actions on Google and the social nature of voice assistants

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

It's Machine Yearning from Assist. It's a podcast where we think and dream about the future of AI, the talking internet, and how we're reshaping our culture. This chapter is an excerpt from our interview with Google's Cathy Pearl at the 2018 Voice Summit. the largest gathering of the conversational technology world. Cathy is one of the many folks we interviewed, people who are thriving at the front edge of brand, UX, research, and design. At Google, Cathy is helping people and brands figure out how to integrate voice assistants into their larger strategies. She has the perspective that only comes after you've worked your way through an incredibly diverse swath of projects, user needs, and clients. She's done voice assistants for auto, healthcare, and even fashion advice, and got us to think in new ways about the social nature of voice assistants. This is just a taste, so make sure you grab the full episode and subscribe so you never miss a single Machine Yearning. Cathy Pearl.

Let's talk about that very interesting title that you have. Like, what's the, what's the outreach part of conversational design?

So the main point of outreach is conversation design is one of those things that if you talk to somebody about it, they'll say, "Oh yeah, yeah, definitely we need— that's important." But when it comes to practice, it doesn't always get invoked. So conversation design is the concept that whenever you're creating one of these conversational experiences, whether it's a voice assistant or whether you're typing, you have to spend time iterating and thinking about the user experience, the interaction with the user. Because a lot of people just jump in with a couple developers and say, "We're going to build this cool thing." And then they find that actually a lot of people won't use it, it's very difficult to use, and it isn't successful. So my goal is to get everybody on board with this idea that you need to involve somebody who's got experience in designing these systems and spend the time working on that to really have a great system.

Is that about building cross-functional teams that go beyond just technologists?

For sure. A lot of conversation designers come from from writing backgrounds, psychology backgrounds, linguistic backgrounds, and the real key is the understanding of human conversation. A lot of people say to me, "Why do I need a conversation designer? I know how to talk." And we've all been talking since we were very young, but there's an art to fitting in the rules of human conversation with the technical constraints that we have and building within that to be able to leverage these human ways we speak to each other, but in a way that we can actually work with.

It's so funny how these conversations repeat and don't change. So in the early days of digital graphic design, it was this— and the joke that everybody told was, "Well, you can cut your own hair too, but we don't advise it." Exactly.

I think the same thing with website design. When you could first start building websites in the mid-'90s, everybody was throwing up their GeoCities site with their blinking, you know, "under construction" graphic and all that stuff. And now I think we've realized that, well, you should really You'd probably hire somebody who has expertise in this area if you're a company and you want a really awesome website. So similarly, if you're building an Actions on Google or any conversational experience, you gotta get somebody who knows how to apply these principles.

So let's talk about the nut of that, like Actions on Google. Define that space. Define that work group. What are you trying to accomplish with that?

With Actions on Google, we're trying to extend the capabilities of the Google Assistant to incorporate all kinds of things. So whether you're a restaurant or you want to build a game or you want to have a branded experience for your company, We want to allow lots and lots of people out there and companies out there to add their stuff to the Google Assistant so that it's not just a locked ecosystem. We want people to have access to all these different types of services, entertainment, news, everything through the Google Assistant.

Are you seeing patterns now of sort of the major requests that are coming in? Like, what are the big demands that are coming in to you at this phase for activities that people want to be developing for?

It's a good question. Honestly, there's a lot of experimentation right now. So we see things in all different domains. We see a lot of games and entertainment. We see stuff for kids is certainly very, very popular. A lot of parents feel that time with a voice assistant is healthier than screen time. So they'd rather their kid maybe play a game that way because— and this is something I believe in strongly— voice allows you to get away from the screen and be more social. So, for example, at our house, dinner, we don't have devices on the table, but sometimes we have questions. So we might turn and say, "Hey Google, what's the longest bridge in the world?" or whatever. And the thing I like about that is that it joins the conversation. We all hear the question. We all hear the response. Instead of it's like, "I'm going to look that up," and you look at your phone and you're gone, right? You've disappeared from the world. And there was a statistic that came out from the NPR and Edison study saying that over 50% of the time people are using voice assistants, it's with someone else. So I really like that community aspect that these things bring.

Yeah.

Yeah.

I would love to hear how this experience ports through your eyes. So rebooking a ticket on Amtrak, but was in a noisy train station at night using a voice prompt system that— and we just got caught in an awful loop. So you take that kind of a problem back to your team. You say, how do we unpack this and how do we start to evaluate solutions for that? How does that conversation unfold?

We think a lot about the user's context. Where are they? Are they driving? Are they in a noisy environment? Are they at home in their kitchen? Are there other people around? And my motto is that you want to give the user alternatives. So if they are in a noisy train station and they're trying to use voice only, that is going to be challenging. And so sometimes we want to have what we call back-off strategies, where perhaps if they're really struggling and you know that they're having problems, maybe you even back off to DTMF to press, you know, press 1 or 2. Just because you don't want them to be suffering. So you want to give alternatives. And we want to meet the user where they're at.

Very helpful. Talk to us a little bit about disambiguation.

That is one of my favorite topics. So disambiguation refers to the fact that sometimes we need to ask follow-up questions because we might not have understood you. So for example, if you say you want to hear the song "Hello," do you mean Lionel Richie or Adele? And so in certain situations, we definitely want to follow up. Now disambiguation, it's not a hard and fast rule. For example, let's talk about weather. If I say, "What's the weather in Belmont?" I don't want it to say, "Do you mean Belmont, California or Belmont, Canada?" I live in California. It knows that. There's no reason to ask a follow-up question. But if I ask for the weather in Springfield, which one? You know, I don't live near one. So we want to make sure that we ask a follow-up question just in the right time and A lot of times I think some people err on the side of, oh, we just want to give someone information as quickly as possible. And if we get it wrong, that's OK. They can start over. But sometimes asking a follow-up question is much more satisfying for a user. Speed is not always the most delightful experience. Sometimes it's like one or two follow-up questions gets me exactly what I want. And people can be happier with that.

To be successful with that, it means having access to an enormous amount of data.

It does help. A lot of this is aggregated data. Certainly we don't have to have individualized data to make these decisions, but we can use things like an aggregation of when somebody requested something that was perhaps ambiguous, how many times did they ask again in a different way? Well, that's probably a signal to us that we didn't get it right. So, but we can look at that as a large group of data. It's like, you know, 90% of the time when somebody asks this question, they said it again in another way, hey, that's probably a good case for disambiguation.

Paul heard you say yesterday, "Often we think of solving big problems, but we need to remember that little things can bring dignity to people's lives." Can you expand on that?

Yeah, one of the things that I really like about these voice assistants is hearing stories of people who perhaps have some sort of maybe a physical limitation or something that it's giving them back their independence. And one of the stories I told yesterday was about my grandmother, who's 104. And I brought a smart speaker to her to try out. And I said, "Grandma, you can ask anything you want," because I was just curious. I thought she would ask maybe, you know, who was president in 1930, or maybe to hear a song from her youth. But she asked very localized, personal questions like, "What am I having for dinner?" and "Who gave me these flowers?" She had told me that the hardest part about being over 100 for her is that she no longer can walk on her own. So if it's not within the radius of her chair, she can't, you know, do it. She has to call a caregiver. And the voice assistants bring back a lot of this independence for some of these smaller tasks that maybe we don't even think are that important, but in fact bring a lot of feelings of independence and dignity to people who were struggling.

Thank you very much, Callie.

Thank you. My pleasure.

Thanks for listening, and we hope you'll take a second and share this episode with other members of your team. And make sure you check out the other chapters from this week's episode. We have an interview with Bree Glaser from the Mars Agency, and these two conversations show us a lot about the role of deep consumer insight in the design, build, and integration of voice products. Actually, make it easy on yourself. Just subscribe so you never miss an episode or a chapter. That way you can be the first to stay on top of this field and help shape the conversation at your company. 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 Chufo and Michael Elsesser for Limon House. Have a great day.