Speaker 1: Hello, Hello, Hello. This is Smart Talks with IBM, a
Speaker 1: podcast from Pushkin Industries, High Heart Media and IBM about
Speaker 1: what it means to look at today's most challenging problems
Speaker 1: in a new way. I'm Malcolm Gladwell. Today I'm chatting
Speaker 1: with a Neil Bout, the senior vice president and Chief
Speaker 1: Technology Officer of Anthem, one of the most prominent health
Speaker 1: insurance companies in the United States. We have been now
Speaker 1: pivoting the more around. Okay, we are building these capabilities,
Speaker 1: we are building these solutions. How are they fundamentally changing
Speaker 1: and improving the lives of our members, our communities and
Speaker 1: really making a difference to the people we saw? And
Speaker 1: Neil has been with Anthem for over thirteen years and
Speaker 1: his spearheaded efforts to improve customer experience and members needs.
Speaker 1: I'll also be chatting with Glenn Finch, Managing Partner of
Speaker 1: Global Business Services at IBM. How you deal with empathy
Speaker 1: in an AI system. It's all based on the choice
Speaker 1: of words that you use and the verbal inflections that
Speaker 1: are present when you have a voice response. Then is
Speaker 1: a twenty five year IBM veteran. His work focuses on
Speaker 1: the most challenging and transformative engagements at IBM. I'm excited
Speaker 1: to share my conversation with the Neil and Glenn about
Speaker 1: artificial intelligence and how it's influencing customers to interact with
Speaker 1: their healthcare in a new way. Al Right, guys, let's
Speaker 1: get started. Hi everyone, Thanks guys for joining me today.
Speaker 1: Why don't we start with the two of you just
Speaker 1: introducing yourself, tell me, tell me what you do as
Speaker 1: great I'm glad to be here today, Thanks for hosting us.
Speaker 1: I basically lead the technology and practice here at Anthem
Speaker 1: as a CTO, managing all the roadmaps for technology, making
Speaker 1: sure that we're building solutions that are meeting our business
Speaker 1: needs on a day to day basis, making sure that
Speaker 1: we are catering to the needs of our members. So
Speaker 1: overall technology roadmap, making sure that we work with partners
Speaker 1: like IBM to bring new technology to the forefront. And
Speaker 1: how how long have you been with Anthem. I've been
Speaker 1: with Anthem for thirteen years actually, and the company has
Speaker 1: evolved while we are in the healthcare business. Our focus
Speaker 1: has been more members centric now, so really understanding how
Speaker 1: a big organization like Anthem can make sure that we
Speaker 1: pivot from being a normal traditional listed company which definitely
Speaker 1: is meeting the expectations of the stockholders, but also catering
Speaker 1: to the need of our members and the communities that
Speaker 1: we serve in. Yeah, why don't you introduce yourself. I'm
Speaker 1: Glenn Finch. I look after data in AI and the
Speaker 1: services side of the IBM company. We take a lot
Speaker 1: of wicked cool technology and bring it to life of
Speaker 1: clients like Anthem and Uh, you know, I get the
Speaker 1: great pleasure of working with a Neil on a daily
Speaker 1: basis to really fundamentally change the member experience using artificial intelligence,
Speaker 1: so usually on the cutting edge of things, and just
Speaker 1: just love coming to work every day. Yeah, so you
Speaker 1: said something. The two of you have been working together
Speaker 1: for some time. When did you guys me me to
Speaker 1: first know each other. As I said, the industry has
Speaker 1: been evolving a lot, Malcolm, So a couple of years back.
Speaker 1: We basically we're kind of figuring out as the consumer
Speaker 1: experience changes, as people get so much used to Netflix
Speaker 1: and Amazon and the way they do their day to
Speaker 1: day shopping, the way they experienced things. We were looking
Speaker 1: for a partner where we could really explore the power
Speaker 1: of AI, really use our data in a way wherein
Speaker 1: we can create these personalized experiences. So that's where Glenn
Speaker 1: and I actually talked a little bit and we figured
Speaker 1: out that there is a possibility of us partnering ib
Speaker 1: AM bringing its UM technology, and basically that's when we
Speaker 1: kind of figure out there's there's a definite role to
Speaker 1: play and partner on this journey together. And it's been great.
Speaker 1: Over the last two years, we have been able to
Speaker 1: deliver on some great, exceptional experiences for our members and
Speaker 1: and we are now moving beyond to other constituents and
Speaker 1: really making sure that UM we make it awesome for
Speaker 1: for members to connect with us. Yeah, Glenn, had you
Speaker 1: worked with an in an insurance provider before? Yea, So
Speaker 1: we have a variety of clients around the world, so yes,
Speaker 1: but Anthem is special to my heart. We started thinking
Speaker 1: through this because when you work with Anthem, this concept
Speaker 1: of member and member experience, you need to show up
Speaker 1: every day with that front and center in your mind.
Speaker 1: So there are other clients who focus on cost or
Speaker 1: technical debt or something like that, but that's not true
Speaker 1: at Anthem. You need to show up front and center
Speaker 1: every day with how are you going to radically improve
Speaker 1: the member experience first, and fas say, but it's the
Speaker 1: relationship between the two companies and the two of you
Speaker 1: goes back so far that I'm really curious to get
Speaker 1: a sense of how the kinds of questions you've been
Speaker 1: asking and problems you've been trying to solve have evolved
Speaker 1: over that time. Tell me about ten years ago, what
Speaker 1: were you guys talking about. So I think the ten
Speaker 1: years back, the conversation is more and more around Okay,
Speaker 1: how many sellers do we have in our data center,
Speaker 1: how many licensing points that we're going to be spending
Speaker 1: this year? What will be our footprint? What is our
Speaker 1: network speed? Are we able to manage the new capability
Speaker 1: that we're delivering? And it really was very technologically focused
Speaker 1: conversation that we used to have. And what has happened
Speaker 1: over the years, Malcolm, is that you know, we have
Speaker 1: been now pivoting too more around Okay, we are building
Speaker 1: these capabilities, we are building these solutions, how are they
Speaker 1: fundamentally changing and improving the lives of our members, our
Speaker 1: communities and really making a difference to the people we serve.
Speaker 1: So as we looked at technology and engineering, we kind
Speaker 1: of pivoted from that to more platform and a product
Speaker 1: that we are building for our constituents. And as that
Speaker 1: pivot happened, you know, I would say around three or
Speaker 1: four years back, the conversation then evolved to more around Okay,
Speaker 1: how are we improving the experience? How are we making
Speaker 1: sure that we're making it easier for the members? And
Speaker 1: and it pivoted from being reactive and kind of what
Speaker 1: I called sick care management to more wellness oriented conversation
Speaker 1: how do we keep our members healthy? And that's where
Speaker 1: the overall pioneering of personalized experiences, predictive and proactive health
Speaker 1: care management kind of started. And as we had interactive
Speaker 1: that IBM, we knew that they had the technology and
Speaker 1: they had the real backbone, which good. So the needs
Speaker 1: that we wanted to kind of bring forward and talk
Speaker 1: about that pivot. I'm curious what's driving it. Did you
Speaker 1: go to a NIL and say, look, you have an
Speaker 1: opportunity to do so much more here? Does a neil
Speaker 1: come to you and say I don't want to be
Speaker 1: just focused on technology. Are members are telling us X,
Speaker 1: Y and Z or take me back to that transformative
Speaker 1: moment when you start thinking about this project in a
Speaker 1: different way. There's been a a massive shift at the
Speaker 1: IBM company in general to shift away from pure technology
Speaker 1: and move towards technology on behalf of a workflow. When
Speaker 1: you think about artificial intelligence and you are trying to
Speaker 1: have a conversation with someone, right, you don't need just
Speaker 1: deep artificial intelligence programmers. You need to have people attached
Speaker 1: to that that know how to have a conversation with
Speaker 1: people and what sequence some words are gonna elicit a response,
Speaker 1: and how that experience feels. To remember, that's a very
Speaker 1: different type of program then just dropping in a chatbot
Speaker 1: and hoping it works right to answer the twelve questions
Speaker 1: that you get most of the time, right, And you
Speaker 1: mentioned this concept of personalization, right, just making sure we
Speaker 1: put the right people together on the program is half
Speaker 1: the battle, right, And that's a shift that IBM has
Speaker 1: made very consciously, started about five years ago. You know,
Speaker 1: we really in Earnest called out intelligent workflows about two
Speaker 1: or three years ago and that's when we started doing
Speaker 1: this together. M. It was tough, it was ambitious as
Speaker 1: compared to anything else that we had done out here.
Speaker 1: And one thing which Malcolm was very very beautiful and
Speaker 1: and has been very important for us learning on the goal.
Speaker 1: When you have so much data that you're capturing, when
Speaker 1: you have a technology that really can give you in
Speaker 1: a nanosecond the response to what exactly is happening. The
Speaker 1: beauty of it is that you can pivot and kind
Speaker 1: of change on the fly. The agility that you build
Speaker 1: into our system, the agility that you build into our
Speaker 1: operations is a key and that's what we have been
Speaker 1: able to do. And unfortunately at Anthem, we have been
Speaker 1: really at the forefront of that, investing the right dollars
Speaker 1: and bringing the agility, bringing the way we can kind
Speaker 1: of pivot to what is more important to the concerns.
Speaker 1: That has been a great thing that has been happening here.
Speaker 1: Let's go through some some very specific examples. So, I
Speaker 1: am a I'm a member of Anthem, I am on
Speaker 1: your website. I would like to accomplish something. Tell me
Speaker 1: a specific thing that an expectation a member might have,
Speaker 1: and how you have said about trying to satisfy that expectation,
Speaker 1: and let's get let's get super specific. Give me a scenario,
Speaker 1: a tough a tough scenario. Yeah, yeah, well, I think
Speaker 1: I can give you a comparison to the past. Right,
Speaker 1: So when you were enrolled as a member, we probably
Speaker 1: would send you an ID card which was a hard
Speaker 1: piece of paper, a very good piece of paper which
Speaker 1: costs us a lot. Then there was nothing that we
Speaker 1: would let you know other than that, hey, if you
Speaker 1: want a register on our website, please, you're welcome, right,
Speaker 1: And then that's where our first interaction with you as
Speaker 1: a member used to happen. And frankly, there was nothing
Speaker 1: after that. There was a vacuum, and then you would
Speaker 1: probably try to understand your benefits. You will make sure
Speaker 1: that you know what your co pay is, and then
Speaker 1: we will not hear from you for a long time,
Speaker 1: and all of a sudden, someday, unfortunately somebody is tack
Speaker 1: in your family and then you pick up the card,
Speaker 1: go to a provider and basically have a visit um
Speaker 1: there and then you go from there. So that's the
Speaker 1: traditional experience that somebody would have had. Right now we
Speaker 1: have totally revamped that. So as a member, when you
Speaker 1: enrolled with us, we send you a welcome kit which
Speaker 1: sent you a digital well kit. We send you an
Speaker 1: ID card which is available on your phone. We send
Speaker 1: you a link to our Sydney have tapp which basically
Speaker 1: you can download, you can register in a minute, but
Speaker 1: if you've been an existing member, you will get a personalized,
Speaker 1: curated news feed which is specific to you based on
Speaker 1: your prior experience and based on your claims, history and
Speaker 1: other things that we know about you. We work with
Speaker 1: IBM around the AI chat part, which is basically a
Speaker 1: Watson enabled chat board which you can ask the questions
Speaker 1: from what is my copay? You don't have a call us,
Speaker 1: you don't have to send us an email. You can
Speaker 1: really ask a question there itself. You can ask for
Speaker 1: what are the providers near me? And we'll match a
Speaker 1: provider to you based on your past history. And that's
Speaker 1: where AI comes in that what do we think Malcolm's
Speaker 1: age group, Malcolm's prior history tells us who should be
Speaker 1: the right provider for him to take care of things.
Speaker 1: So that interactive, more personalized, more engaging experience is what
Speaker 1: is different. Let me give you an example. I'd love
Speaker 1: for both of you the way on this. So I'm
Speaker 1: fifty seven years old. It is indicated for someone at
Speaker 1: my age that I get a shingles vaccine. I didn't
Speaker 1: notice never occurred to me. A friend of mine got shingles.
Speaker 1: It was like the worst experience of his life. He
Speaker 1: lost three weeks. It was like so painful, and he's like,
Speaker 1: whatever you do, Malcolm, you need to get a shingles
Speaker 1: vaccine right now. So I went out and got my
Speaker 1: shingles vaccine and then I had to get the booster.
Speaker 1: I remember the booster and blah blah blah. Now when
Speaker 1: you're talking about Sydney and about about drawing on past experience,
Speaker 1: if I was a long time Anthem subscriber, would you
Speaker 1: reach out to me and say, Malcolm, you gotta get
Speaker 1: your shingles vaccine? Would you do? Is that what you're
Speaker 1: thinking about? Exactly? Exactly not only we will tell you
Speaker 1: that you need to take shingles vaccine, will tell you
Speaker 1: exactly which provider probably is the right one for you.
Speaker 1: And that is what the beauty is right now, that
Speaker 1: not to care really that the care gap that we have.
Speaker 1: How does the data tell us that these are the
Speaker 1: care gaps in Malcolm's journey? You know, you you pay
Speaker 1: a lot for your insurance company to take care of you,
Speaker 1: and how do we make sure that we take care
Speaker 1: of you? We be your advocate, We be your journey partners.
Speaker 1: Rather than just allowing for you to come to us
Speaker 1: when you feel that you're sick. So this this AI
Speaker 1: system is called Sydney. First of all, who came up
Speaker 1: with Sydney actually loved the name? But is that who?
Speaker 1: Whose decision was it to call this system Sydney? Actually
Speaker 1: you know, uh, it was it was our team. We
Speaker 1: did some research in terms of what could be a
Speaker 1: very neutral name that we can keep out there. And
Speaker 1: and Malcolm, I can tell you that I love the
Speaker 1: name so much that the beginning of when we had
Speaker 1: COVID hit us, my daughter was asking for a dog
Speaker 1: for a long time and we got a dog, and
Speaker 1: actually we named the dog Sydney. So that's how how
Speaker 1: much how much I care about the name and how
Speaker 1: much I love the name. But thank you very much
Speaker 1: for that's just so we true you Sydney. I'm getting
Speaker 1: the AI assistum, but not your dog, That's all I
Speaker 1: want to be clear. That's what you know we make.
Speaker 1: We may supply you with a picture of Sydney on
Speaker 1: when you when you come to the come to the app,
Speaker 1: but yeah, you're getting the A. Yeah. So what we
Speaker 1: find is that to build trust in AI systems and
Speaker 1: to build the willingness for remember to go along a
Speaker 1: journey experience. There's some things we have to do at
Speaker 1: the table stakes level, at the grassroots level, that we
Speaker 1: have to get right inexorably. And I'm going to go
Speaker 1: back to a Neil's comment about the I D card.
Speaker 1: What happens if you've lost your I D card. You
Speaker 1: don't want to wait on the phone for anybody to
Speaker 1: get a replacement a D card. You'd like to be
Speaker 1: able to do that once and done on the web
Speaker 1: or the mobile. Might have to ask a couple of
Speaker 1: questions and have it done lights out right. So there's
Speaker 1: this combination of doing the more routine things with absolute
Speaker 1: decision writes out complete ease of member, and then that
Speaker 1: builds this trust to have this more longitudinal journey to
Speaker 1: answer your questions or to recommend to you about shingles,
Speaker 1: vaccine right, or a variety of other things based on
Speaker 1: you know your your health challenges. So it's a it's
Speaker 1: kind of a double edged sort of taking care of
Speaker 1: the table stakes and taking people along the journey. Your
Speaker 1: point is you start with the very prosaic stuff and
Speaker 1: you build a trust in the system, and then you
Speaker 1: can move to the more high end stuff. Tell me
Speaker 1: about how you build an AI system like this. This
Speaker 1: is not a trivial accomplishment. What went into building Sydney. Yeah,
Speaker 1: so I think you know, Malcolm, Traditionally, we have a
Speaker 1: lot of data over the years that we have accumulated
Speaker 1: for every member, and we have eighty million lives, multiple
Speaker 1: petabytes of data which is sitting on our systems, and
Speaker 1: that data basically allows us to learn. You know, the
Speaker 1: data is data. As long as you don't touch it,
Speaker 1: you don't do anything. But once you start really using
Speaker 1: technologies and and when when we call AI, these are
Speaker 1: mathematical models that you can run on this data to
Speaker 1: give you insights. And those insights are the key at
Speaker 1: the end of the day. And as we get those insights,
Speaker 1: we have to make sure that we have a way
Speaker 1: to use those insights to make a difference in the
Speaker 1: in the life of any member that we have or
Speaker 1: any constant. Actually, you know, our sales experience for our
Speaker 1: brokers are providers. Getting to know exactly what they need
Speaker 1: to know is very very important. So we are making
Speaker 1: sure that this data and the minding of this data
Speaker 1: is constant. So when we talk about the partnership with IBM.
Speaker 1: We're talking about ability for us to mind this data
Speaker 1: on the fly at a very very quick speed, and
Speaker 1: that is what is key. Then we're able to use
Speaker 1: AI in a different text. And I'm going to give
Speaker 1: you example of something that really we're bringing to the
Speaker 1: forefront of of what we call as a nutrition tracker.
Speaker 1: So imagine that you have your phone in front of you,
Speaker 1: You have a plate of food that came in front
Speaker 1: of you, and you can open Sydney and show the
Speaker 1: food of plate to Sydney. Sydney can tell you based
Speaker 1: on what it plate. You take a picture of the
Speaker 1: photo and Sydney looks at the photo and says, why
Speaker 1: are you loading up on carbs? I mean, is that
Speaker 1: what we're talking about exactly? That's what I'm talking about.
Speaker 1: So you know, this is a great partnership we have
Speaker 1: with one of our ecosystem partners. And actually this isn't
Speaker 1: pilot with our house account, which is eighty thousand members
Speaker 1: right now, and it can tell you. It can you
Speaker 1: can show it a cup and it can tell you
Speaker 1: this is a coffee with no milk, and it's going
Speaker 1: to be seventy calories and it keeps track of what
Speaker 1: you're eating and basically that's how we build the healthy
Speaker 1: habits out there. So the advancement in the in the
Speaker 1: field of technology and how do we make sure that
Speaker 1: we move away from that leg thee information technology to
Speaker 1: really the exponential technology that is in front of us
Speaker 1: is the key. We needed to take all of that
Speaker 1: AI and persist a conversation with a member, right And
Speaker 1: and that's where Watson came in to help Sydney persist
Speaker 1: conversations with members, right Because crunching through data and and
Speaker 1: knowing about your claim is one thing, but being able
Speaker 1: to talk to you about that claim and understand your
Speaker 1: responses back, whether you're on a keyboard, whether you're speaking,
Speaker 1: whether you're doing whatever. That's kind of where Watson came
Speaker 1: in to help augment Sydney and again designing those conversations.
Speaker 1: I don't know if you've been in a in a
Speaker 1: situation where you're sitting next to somebody and they're talking
Speaker 1: and you say, oh my god, I can't believe they
Speaker 1: said that. Well, you have to engineer that out of
Speaker 1: the conversations that you have with members so that you know,
Speaker 1: all of the members are delighted and one of the
Speaker 1: things I'm proudest of is when by our work together,
Speaker 1: we have members that are thanking Sydney when we're working
Speaker 1: with them with artificial intelligence, responding to their questions, just
Speaker 1: as if Sydney was a fully human worker, right, And
Speaker 1: that that's what I get delight from is when we've
Speaker 1: been able to change a member experience and work through
Speaker 1: that all of the things members might ask, Now, are
Speaker 1: you taking real life conversations, looking at them and feeding
Speaker 1: them to Sydney and saying okay? In the last two years,
Speaker 1: these are all the These are all the phone conversations
Speaker 1: we've had with our members. These are the kinds of
Speaker 1: things they ask. Is that where it starts? We build
Speaker 1: what we call the anthology of the conversations? You know,
Speaker 1: how are we making sure that as we get the
Speaker 1: interactions noted down for our members or provide us into
Speaker 1: our system, whether it's a phone call, whether it's a chat,
Speaker 1: whether it's basically even they came to the website and
Speaker 1: they clicked through specific things, right, so we are noting
Speaker 1: those down. We are kind of creating a what we
Speaker 1: call a graph model and a flow of When a
Speaker 1: member asked this, the next question possible level, it's going
Speaker 1: to be this. If you give up yes to that
Speaker 1: answer or not to that answer, they're gonna probably ask
Speaker 1: you this. So that kind of slow Sydney can be
Speaker 1: thinking two in three steps ahead exactly. So Sydney is
Speaker 1: thinking two or three steps ahead and making sure that
Speaker 1: the anticipation of what you're going to be doing and
Speaker 1: and beyond. Sydney, our overall system is thinking two or
Speaker 1: three systems steps ahead and predicting proactively those conversations as
Speaker 1: well as those interventions that we need to give to
Speaker 1: the members. So really using ai UM you know Watson
Speaker 1: as a back backbone to this, Sydney is basically what
Speaker 1: we call the human centered, designed, focused Interaction and Engagements
Speaker 1: system that sits on top of the backbone of the
Speaker 1: AI as the data at the bottom, So that basically
Speaker 1: is layered away. How Sydney is able to answer the
Speaker 1: question that we have it aspects you of what type
Speaker 1: of question it is because our intology of the data
Speaker 1: as well as the AIS that we have built is
Speaker 1: very very dock solid. And that is and the good
Speaker 1: thing is that it's it's a gift that keeps giving
Speaker 1: because the more data we collect, the more the system
Speaker 1: it gets Yeah, wait, can you Stumps, Sydney, can you
Speaker 1: ask it a question? You can? I'm sure it's possible too.
Speaker 1: And then you know, when we when we get into
Speaker 1: that situation, what we want to do is we want
Speaker 1: to bring the member to a human agent so that
Speaker 1: the member satisfied seamlessly right, so that there's there's no
Speaker 1: daylight at all regardless of how the member has wants
Speaker 1: to connect with the human agent. A lot of members,
Speaker 1: you know, are are dealing with time challenges and they
Speaker 1: don't want to call up anymore. They just want somebody
Speaker 1: to you know, be able to chat with. We try
Speaker 1: and respond to all that, and then if if somebody
Speaker 1: needs a human agent, then we go there. Yeah. Yeah,
Speaker 1: what's what did your what did your members tell you about,
Speaker 1: either explicitly or implicitly about what they wanted? You know,
Speaker 1: we've been through this. We've just been through a year
Speaker 1: and a half of craziness, you know, where everything is
Speaker 1: being turned upside down. I'm curious, what have you what
Speaker 1: have you learned from them over the last stretch is
Speaker 1: what a member wants today very different than it was
Speaker 1: two years ago. Definitely, Malcolm. If you look at that,
Speaker 1: you know, the terms that you use in healthcare are
Speaker 1: very very complex, and it's very difficult for people to
Speaker 1: understand what my cope is. What is an out of network,
Speaker 1: what is it in network? What does a claim uh
Speaker 1: that that needs a pre authoriation mean to me? So
Speaker 1: if you look at the conversation that we were having before,
Speaker 1: they were really very hardcore health care oriented conversations and
Speaker 1: and the transparency to to what I'm going to pay
Speaker 1: was not there. So this was this was industry where
Speaker 1: in you know, you're going to buy insurance and you're
Speaker 1: going to buy a product without really understanding what I'm
Speaker 1: going to get. At the end of the day, what
Speaker 1: we did and basically what our customers actually demanded from
Speaker 1: us is that irrespect you of the channel that they
Speaker 1: come to us. Um what we call here at Anthem
Speaker 1: connected experiences. We want to build the connected experiences, whether
Speaker 1: they come to us from a phone call, whether they're
Speaker 1: chatting with us, they're having a web in traction, whether
Speaker 1: they're in the provider's office. How do we make sure
Speaker 1: that we connect the experience end to end. Now, once
Speaker 1: we connect the experience, we want to make sure that
Speaker 1: we are building a very human centered design way of
Speaker 1: answering their questions. So it is as simple as making
Speaker 1: sure that we provide them a nudge on probably this
Speaker 1: is what you're looking for, and that clicks with them
Speaker 1: and they say, yeah, that's what I was looking for.
Speaker 1: So that input, simple interaction really helps to make sure
Speaker 1: that you make the member feel good. Having the ability
Speaker 1: to text, having an ability to get dancers while you're
Speaker 1: cooking your dinner and you can text and say that, hey,
Speaker 1: could you please tell me what will cope for the
Speaker 1: next visit? I have a daughter X And you go
Speaker 1: ahead and start cooking your dinner and when you come back,
Speaker 1: you have a text back out there which tells you
Speaker 1: exactly what it is. And the beauty of it is
Speaker 1: that we had a very constant loop out there, you know,
Speaker 1: the technologies that we use that that allowed us to
Speaker 1: have a constant feedback on those complex interactions that we
Speaker 1: were having. And that's where IBM team and we work
Speaker 1: together and kind of figured out, Okay, what will be
Speaker 1: our game plan. What did you learn from working with
Speaker 1: other people on the Watson platform that helped a Neil
Speaker 1: and Anthem? What did you bring to them? So from
Speaker 1: what you've learned from others. So what we what we've
Speaker 1: tried to do with Watson, Well, Watson first started, we
Speaker 1: thought that everybody wanted of a spoke suit, and so
Speaker 1: we kind of go on a journey together to make
Speaker 1: up a spoke suit. And what what we found the
Speaker 1: clients really wanted was well, look, I want you to
Speaker 1: show up with the suit partially done to answer some
Speaker 1: of the basic things, and then I want to make
Speaker 1: it my own, right, So so show up ready to
Speaker 1: go so that we can get into production answering questions
Speaker 1: in a few months, and then we will work together
Speaker 1: to radically customize and taylor that experience. That's been my
Speaker 1: biggest learning, right, So whether it was UM in financial services,
Speaker 1: or healthcare or Telco or you know, there's about seven
Speaker 1: or eight dominant industries. UM. We tried to make a
Speaker 1: series of industry specific cartridges so that Watson came kind
Speaker 1: of pre trained, right, so that we were ready to
Speaker 1: go quickly. And then the second learning was we needed
Speaker 1: to show up with the right people because remember you're
Speaker 1: creating a conversational interaction with someone, right, so you've got
Speaker 1: to make sure that people are designing the words correctly
Speaker 1: and the user experience right. Those are the two things
Speaker 1: I think that you know, we brought that tried to
Speaker 1: help Anthem accelerate. I mean, and Neil said something that
Speaker 1: I thought was fascinating. You're talking about designing a system
Speaker 1: with empathy, and I'm curious what does First of all,
Speaker 1: what does empathy look like in an AI system? And
Speaker 1: b have you has anyone ever, has any non healthcare
Speaker 1: player ever asked you, Glenn to put empathy in the system. UM.
Speaker 1: Clients outside of healthcare are less focused on empathy. They
Speaker 1: are focused more on making sure to get UM, you know,
Speaker 1: the information out there correctly, especially in highly regulated industries. Right.
Speaker 1: How you deal with empathy in an AI system, it's
Speaker 1: all based on the choice of words that you use
Speaker 1: and the verbal inflections that are present when you have
Speaker 1: a voice response, right, and you you and I UM
Speaker 1: when we're talking right now, was Malcolm with Annal with whomever.
Speaker 1: We can just by the words that somebody chooses, we
Speaker 1: can know whether it matters to them about what we're
Speaker 1: talking about, right, And so we try and build a
Speaker 1: lot of those human characteristics into all the responses as
Speaker 1: compared to just getting the information right. Just what's you know?
Speaker 1: Usn't just telling people you're sorry, right, Those are the
Speaker 1: types of things that you have to engineer in as
Speaker 1: compared to just being flawlessly precise about the answer. Yeah.
Speaker 1: Um wait, one last question for for both of has
Speaker 1: been such a fun conversation. We talked about ten years
Speaker 1: ago when you guys started talking and then this sort
Speaker 1: of this transition moment five years ago. Now let's go
Speaker 1: five years in the future. So let's imagine it's twenty
Speaker 1: and we're three of us are talking again. I want
Speaker 1: to know what problems you're trying to solve. Then the
Speaker 1: problems we're trying to solve at that time would would
Speaker 1: would definitely be much different on where we are. But
Speaker 1: what I can tell you before I get there is
Speaker 1: that you know, we want to make sure that in
Speaker 1: the next five years, anthem Is is treated like a
Speaker 1: platform company which is focused on creating these solutions with
Speaker 1: the help of our partners that really meet the need
Speaker 1: of the members in the journey that they have from
Speaker 1: a healthcare perspective, and we do want to pivot from
Speaker 1: a from a sick care to more proactive and predictive
Speaker 1: care and wellness for members. So we're gonna will down
Speaker 1: and keep working on that because it's a it's something
Speaker 1: that never ends and it's going to keep keep going
Speaker 1: in the years to come. I'm still processing this fantastic
Speaker 1: idea about taking a photo of your meal, if your
Speaker 1: plate of food, and getting instantent feedback and analysis on that.
Speaker 1: So Sydney starts gets all these pictures of my food,
Speaker 1: gets it gets a sense of what I'm eating over
Speaker 1: the course of the given day. Is the idea that
Speaker 1: so I'm thinking about this five year from now conversation.
Speaker 1: So five years from now I might be taking a
Speaker 1: photo of everything, and then at the end of every day,
Speaker 1: Sydney text me and says, Malcolm, you should be aware
Speaker 1: of the fact that you're nutritional patterns of the last
Speaker 1: few days. You need to eat a few more vegetables
Speaker 1: or you'll be useful to have some. Is that what
Speaker 1: we're talking about here? But I think this idea is
Speaker 1: fantastic because there is no we have no way of
Speaker 1: making any nutritional sense of the stuff we unless you
Speaker 1: spend two hours on a on Google before you make
Speaker 1: your dinner. How do you know whether the sum total
Speaker 1: of the things you eat in a given day is
Speaker 1: going to be um is optimum? I love this. I
Speaker 1: want this with this now? Can I do I have
Speaker 1: to wait five years? Can I have? Guys, It's been
Speaker 1: a really, really fun conversation. I really appreciate you taking
Speaker 1: the time, Neil Glenn have a wonderful day, and that
Speaker 1: the future cannot come fast enough, at least for me,
Speaker 1: So bring it on. I'm waiting for it. Thank you
Speaker 1: very much for Malcolm. Oh yeah, awesome, Thanks Malcolm. Bye, guys.
Speaker 1: Understanding customer needs has become even more important in the
Speaker 1: wake of COVID nineteen. Companies like IBM and Anthem are
Speaker 1: learning to leverage technology to deliver a more personal experience,
Speaker 1: a crucial part of our evolving healthcare system. Thanks again
Speaker 1: to a Neil Bot and Glenn Finch for talking king
Speaker 1: with me, I learned a lot Smart Talks with IBM
Speaker 1: is produced by Emily Rosteck with Carlie Migliori, edited by
Speaker 1: Karen Shakergee engineering by Martin Gonzalez, mixed and mastered by
Speaker 1: Jason Gambrell and Ben Tolliday. Music by Granmoscope. Special thanks
Speaker 1: to Molly Sosha, Andy Kelly Mia, Label, Jacob Weisberg, Heather Faine,
Speaker 1: Eric Sandler, and Maggie Taylor and the teams at eight
Speaker 1: Bar and IBM. Smart Talks with IBM is a production
Speaker 1: of Pushkin Industries and I Heart Media. You can find
Speaker 1: more Pushkin podcasts on the i Heart Radio app, Apple Podcasts,
Speaker 1: or wherever you like to listen. I'm Malcolm Gladwell, See
Speaker 1: you next time.