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Can AI be empathetic? Reinventing client experiences · The Steve Harvey Morning Show

0:05
Speaker 1: Hello, Hello, Hello. This is Smart Talks with IBM, a
0:08
Speaker 1: podcast from Pushkin Industries, iHeartMedia and IBM about what it
0:13
Speaker 1: means to look at today's most challenging problems in a
0:16
Speaker 1: new way. I'm Malcolm Gladwell. Today I'm chatting with Anil Bott,
0:22
Speaker 1: the senior vice president and Chief Technology Officer of Anthem,
0:26
Speaker 1: one of the most prominent health insurance companies in the
0:29
Speaker 1: United States.
0:30
Speaker 2: We have been now pivoting to more around Okay, we
0:34
Speaker 2: are building these capabilities, we are building these solutions. How
0:37
Speaker 2: are they fundamentally changing and improving the lives of our members,
0:41
Speaker 2: our communities and really making a difference to the people
0:44
Speaker 2: we sew?
0:45
Speaker 1: And Neil has been with Anthem for over thirteen years
0:47
Speaker 1: and his spearheaded efforts to improve customer experience and members' needs.
0:53
Speaker 1: I'll also be chatting with Glenn Finch, Managing Partner of
0:56
Speaker 1: Global Business Services at IBM.
1:00
Speaker 3: How you deal with empathy in an AI system. It's
1:05
Speaker 3: all based on the choice of words that you use
1:08
Speaker 3: and the verbal inflections that are present when you have
1:12
Speaker 3: a voice response.
1:14
Speaker 1: Then is a twenty five year IBM veteran. His work
1:17
Speaker 1: focuses on the most challenging and transformative engagements at IBM.
1:25
Speaker 1: I'm excited to share my conversation with Anil and Glenn
1:28
Speaker 1: about artificial intelligence and how it's influencing customers to interact
1:33
Speaker 1: with their healthcare in a new way. All right, guys,
1:37
Speaker 1: let's get started. Hi everyone, Thanks guys for joining me today.
1:52
Speaker 1: Why do we start with the two of you just
1:56
Speaker 1: introducing yourself? Tell me, tell me what you do?
2:00
Speaker 2: Great, I'm glad to be here today. Thanks for hosting us.
2:03
Speaker 2: I basically lead the technology and practice here at Anthem
2:08
Speaker 2: as a CEO, managing all the roadmaps for technology, making
2:11
Speaker 2: sure that we're building solutions that are meeting our business
2:14
Speaker 2: needs on a day to day basis, making sure that
2:16
Speaker 2: we are catering to the needs of our members. So
2:20
Speaker 2: overall technology roadmap, making sure that we work with partners
2:23
Speaker 2: like IBM to bring new technology to the forefront.
2:27
Speaker 1: And how how long have you been with Anthem.
2:29
Speaker 2: I've been with Anthem for thirteen years actually, and the
2:32
Speaker 2: company has evolved. While we are in the healthcare business,
2:36
Speaker 2: our focus has been more member centric now, so really
2:39
Speaker 2: understanding how a big organization like Anthem can make sure
2:43
Speaker 2: that we pivot from being a normal traditional listed company
2:48
Speaker 2: which definitely is meeting the expectations of the stockholders, but
2:51
Speaker 2: also catering to the need of our members and the
2:53
Speaker 2: communities that we serve in.
2:54
Speaker 1: Yeah, Glent, why don't you introduce yourself.
2:57
Speaker 3: I'm Glenn Finch. I look after data and the services
3:01
Speaker 3: side of the IBM company. We take a lot of
3:04
Speaker 3: wicked cool technology and bring it to life at clients
3:08
Speaker 3: like Anthem, and I get the great pleasure of working
3:13
Speaker 3: with a Neil on a daily basis to really fundamentally
3:16
Speaker 3: change the member experience using artificial intelligence. So usually on
3:21
Speaker 3: the cutting edge of things and just just love coming
3:24
Speaker 3: to work every day.
3:25
Speaker 2: Yeah.
3:25
Speaker 1: Yeah, so you said something. The two of you have
3:29
Speaker 1: been working together for some time. When did you guys
3:33
Speaker 1: meet or first know each other?
3:35
Speaker 2: As I said, the industry has been evolving a lot, Malcolm,
3:38
Speaker 2: So a couple of years back, we basically were kind
3:42
Speaker 2: of figuring out as the consumer experience changes, as people
3:46
Speaker 2: get so much used to Netflix and Amazon and the
3:49
Speaker 2: way they do their day to day shopping, the way
3:52
Speaker 2: they experience things. We were looking for a partner where
3:55
Speaker 2: we could really explore the power of AI, really use
3:58
Speaker 2: our data in a way where we can create these
4:01
Speaker 2: personalized experiences. So that's where Glenn and I actually talked
4:05
Speaker 2: a little bit and we figure out that there is
4:08
Speaker 2: a possibility of us partnering ib AM bringing its technology,
4:13
Speaker 2: and basically that's when we kind of figure out there's
4:17
Speaker 2: there's definite role to play and partner on this journey together.
4:20
Speaker 2: And it's been great. Over the last two years, we
4:22
Speaker 2: have been able to deliver on some great, exceptional experiences
4:26
Speaker 2: for our members and we are now moving beyond to
4:29
Speaker 2: other constituents and really making sure that we make it
4:33
Speaker 2: awesome for members to connect with us.
4:36
Speaker 1: Yeah, Glenn, had you worked with an insurance provider before?
4:41
Speaker 3: Yeah, So we have a variety of clients around the world,
4:44
Speaker 3: so yes, but Anthem is special to my heart. We
4:49
Speaker 3: started thinking through this because when you work with Anthem,
4:55
Speaker 3: this concept of member and member experience, you need to
4:59
Speaker 3: show up every day with that front and center in
5:02
Speaker 3: your mind. So there are other clients who focus on
5:06
Speaker 3: cost or technical debt or something like that, but that's
5:10
Speaker 3: not true at Anthem. You need to show up front
5:12
Speaker 3: and center every day with how are you going to
5:16
Speaker 3: radically improve the member experience? First?
5:19
Speaker 1: And that's say, but the relationship between the two companies,
5:23
Speaker 1: and the two of you goes back so far that
5:25
Speaker 1: I'm really curious to get a sense of how the
5:28
Speaker 1: kinds of questions you've been asking and problems you've been
5:32
Speaker 1: trying to solve have evolved over that time. Tell me
5:35
Speaker 1: about ten years ago, what were you guys talking about?
5:39
Speaker 2: So I think the ten years back, the conversations more
5:41
Speaker 2: and more around okay, how many severs do we have
5:43
Speaker 2: in our data center? How many licensing points that we
5:47
Speaker 2: are going to be spending this year? What will be
5:49
Speaker 2: our footprint? What is our network speed? Are we able
5:51
Speaker 2: to manage the new capabilities that we are delivering? And
5:54
Speaker 2: it really was very technologically focused conversation that we used
5:58
Speaker 2: to have. What has happened over the years, Malcolm, is
6:02
Speaker 2: that you know, we have been now pivoting to more
6:05
Speaker 2: around okay, we are building these capabilities, we are building
6:09
Speaker 2: these solutions, how are they fundamentally changing and improving the
6:12
Speaker 2: lives of our members, our communities and really making a
6:15
Speaker 2: difference to the people we serve. So as we looked
6:19
Speaker 2: at technology and engineering, we kind of pivoted from that
6:22
Speaker 2: to more a platform and a product that we are
6:25
Speaker 2: building for our constituents. And as that pivot happened, you know,
6:28
Speaker 2: I would say around three four years back. The conversation
6:31
Speaker 2: then evolved to more around Okay, how are we improving
6:34
Speaker 2: the experience? How are we making sure that we're making
6:37
Speaker 2: it easier for the members? And it pivoted from being
6:41
Speaker 2: reactive and kind of what I called sick care management
6:45
Speaker 2: to more wellness oriented conversation how do we keep our
6:48
Speaker 2: members healthy? And that's where the overall pioneering of personalized experiences,
6:54
Speaker 2: predictive and proactive health care management kind of started. And
6:58
Speaker 2: as we had interactive with the IBM, knew that they
7:00
Speaker 2: had the technology and they had the real backbone which
7:03
Speaker 2: could serve the needs that we wanted to kind of
7:06
Speaker 2: bring forward.
7:07
Speaker 1: Then talk about that pivot, I'm curious what's driving it.
7:10
Speaker 1: Did you go to a Neil and say, look, you
7:13
Speaker 1: have an opportunity to do so much more here. Does
7:14
Speaker 1: a Neil come to you and say, I don't want
7:17
Speaker 1: to be just focused on technology. Our members are telling
7:20
Speaker 1: us X, Y and Z, or take me back to
7:22
Speaker 1: that transformative moment when you start thinking about this project
7:25
Speaker 1: in a different way.
7:27
Speaker 3: There's been a massive shift at the IBM company in
7:31
Speaker 3: general to shift away from pure technology and move towards
7:38
Speaker 3: technology on behalf of a workflow. When you think about
7:42
Speaker 3: artificial intelligence and you are trying to have a conversation
7:46
Speaker 3: with someone, right, you don't need just deep artificial intelligence programmers.
7:53
Speaker 3: You need to have people attached to that that know
7:57
Speaker 3: how to have a conversation with people and what sequence
8:00
Speaker 3: of words are going to elicit a response, and how
8:03
Speaker 3: that experience feels to a member. That's a very different
8:08
Speaker 3: type of program than just dropping in a chatbot and
8:12
Speaker 3: hoping it works right to answer the twelve questions that
8:15
Speaker 3: you get most of the time right, And you mentioned
8:17
Speaker 3: this concept of personalization right, just making sure we put
8:21
Speaker 3: the right people together on the program is half the battle, right,
8:24
Speaker 3: And that's a shift that IBM has made very consciously
8:29
Speaker 3: started about five years ago. You know, we really in
8:31
Speaker 3: earnest called out intelligent workflows about two or three years ago,
8:36
Speaker 3: and that's when we started doing this together.
8:41
Speaker 2: It was tough, it was ambitious as compared to anything
8:43
Speaker 2: else that we had done out here. And one thing
8:48
Speaker 2: which Malcolm was very very beautiful and has been very
8:51
Speaker 2: important for us, learning on the goal when you have
8:54
Speaker 2: so much data that you're capturing, when you have a
8:56
Speaker 2: technology that really can give you in a nanosecond the
9:00
Speaker 2: response to what exactly is happening. The beauty of it
9:03
Speaker 2: is that you can pivot and kind of change on
9:05
Speaker 2: the fly. The agility that you build into our system,
9:08
Speaker 2: the agility that you build into our operations is a
9:11
Speaker 2: key and that's what we have been able to do.
9:13
Speaker 2: And fortunately at Anthem we have been really at the
9:16
Speaker 2: forefront of that, investing the right dollars and bringing the agility,
9:19
Speaker 2: bringing the way we can kind of pivot to what
9:23
Speaker 2: is more important to the concerns. That has been a
9:26
Speaker 2: great thing that has been happening.
9:28
Speaker 3: Here.
9:28
Speaker 1: Let's go through some very specific examples. So I am,
9:35
Speaker 1: I'm a member of Anthem. I am on your website.
9:39
Speaker 1: I would like to accomplish something. Tell me a specific
9:42
Speaker 1: thing that an expectation a member might have, and how
9:47
Speaker 1: you have set about trying to satisfy that expectation, and
9:51
Speaker 1: let's get let's get super specific. Give me a scenario,
9:55
Speaker 1: a tough, a tough scenario.
9:57
Speaker 2: Yeah, yeah, Well, I think I can give you a
9:58
Speaker 2: comparison to the past. So when you were enrolled as
10:02
Speaker 2: a member, we probably would send you an ID card,
10:05
Speaker 2: which was a hard piece of paper, a very good
10:08
Speaker 2: piece of paper which costs us a lot. Then there
10:11
Speaker 2: was nothing that we would let you know other than that, hey,
10:14
Speaker 2: if you want a register on our website, please be welcome, right,
10:18
Speaker 2: And then that's where our first interaction with you as
10:21
Speaker 2: a member used to happen. And frankly, there was nothing
10:25
Speaker 2: after that. There was a vacuum, and then you would
10:28
Speaker 2: probably try to understand your benefits. You will make sure
10:31
Speaker 2: that you know what your cope is, and then we'll
10:35
Speaker 2: not hear from you for a long time, and all
10:37
Speaker 2: of a sudden, someday, unfortunately somebody is sick in your family,
10:41
Speaker 2: and then you pick up the card, go to a
10:43
Speaker 2: provider and basically have a visit there and then you
10:47
Speaker 2: go from there. So that's the traditional experience that somebody
10:51
Speaker 2: would have had. Right now we have totally revamped that.
10:55
Speaker 2: So as a member, when you enroll with us, we
10:57
Speaker 2: send you a welcome kit which send you a digital weal.
11:00
Speaker 2: We send you an ID card which is available on
11:03
Speaker 2: your phone. We send you a link to our Sydney
11:06
Speaker 2: Halt app which basically you can download. You can register
11:09
Speaker 2: in a minute, but if you've been an existing member,
11:12
Speaker 2: you will get a personalized curated news feed which is
11:15
Speaker 2: specific to you based on your prior experience and based
11:19
Speaker 2: on your claims, history and other things that we know
11:22
Speaker 2: about you. We work with IBM around the AI chatbot,
11:25
Speaker 2: which is basically a Watson enabled chatbot which you can
11:29
Speaker 2: ask the questions from what is my copy? You don't
11:31
Speaker 2: have to call us, you don't have to send us
11:33
Speaker 2: an email. You can really ask a question there itself.
11:36
Speaker 2: You can ask for what are the providers near me?
11:39
Speaker 2: And we'll match a provider to you based on your
11:42
Speaker 2: past history. And that's where AI comes in that what
11:45
Speaker 2: do we think Malcolm's age group, Malcolm's prior history tells
11:49
Speaker 2: us who should be the right provider for him to
11:52
Speaker 2: take care of things. So that interactive, more personalized, more
11:56
Speaker 2: engaging experience is what is different.
12:03
Speaker 1: Let me give you an example. I'd love for both
12:05
Speaker 1: you to weigh on this. So I'm fifty seven years old.
12:08
Speaker 1: It is indicated for someone of my age. Did I
12:10
Speaker 1: get a shingles vaccine? I didn't notice, never occurred to me.
12:14
Speaker 1: Friend of mine got shingles. It was like the worst
12:17
Speaker 1: experience of his life. He last three weeks. It was
12:20
Speaker 1: like so painful and he's like whatever, you do, Malcolm,
12:23
Speaker 1: you need to get a shingles vaccine right now. So
12:26
Speaker 1: I went out and got my shingles vaccine and then
12:28
Speaker 1: I had to get the booster. I remember the booster
12:29
Speaker 1: and blah blah blah. Now, when you're talking about Sydney
12:33
Speaker 1: and about drawing on past experience, if I was a
12:36
Speaker 1: long time Anthem subscriber, would you reach out to me
12:41
Speaker 1: and say, Malcolm, you got to get your shingles vaccine?
12:44
Speaker 1: Would you do? Is that what you're thinking about?
12:46
Speaker 2: Exactly? Exactly, Not only we will tell you that you
12:49
Speaker 2: need to take shingles vaccine, we'll tell you exactly which
12:52
Speaker 2: provider probably is the right one for you. And that
12:55
Speaker 2: is what the beauty is. Right now, the nuts took
12:57
Speaker 2: care really the care gap that we have? How does
13:01
Speaker 2: the data tell us that these are the care gaps
13:03
Speaker 2: in Malcolm's journey? You know, you pay a lot for
13:07
Speaker 2: your insurance company to take care of you. And how
13:09
Speaker 2: do we make sure that we take care of you?
13:11
Speaker 2: We be your advocate, We be your journey partners, rather
13:14
Speaker 2: than just allowing you to come to us when you
13:18
Speaker 2: feel that you're sick.
13:20
Speaker 1: So this AI system is called Sydney. First of all,
13:23
Speaker 1: who came up with Sydney actually love the name. But
13:25
Speaker 1: is that whose decision was it to call this system Sydney.
13:29
Speaker 2: Actually, you know it was our team. We did some
13:35
Speaker 2: research in terms of what could be a very neutral
13:37
Speaker 2: name that we can keep out there, and Malcolm, I
13:40
Speaker 2: can tell you that I love the name so much
13:42
Speaker 2: that beginning of twenty twenty when we had COVID hit us,
13:45
Speaker 2: my daughter was asking for a dog for a long
13:47
Speaker 2: time and we got a dog, and actually we named
13:50
Speaker 2: the dog Sydney. So that's how much I care about
13:54
Speaker 2: the name and how much I love the name. But
13:56
Speaker 2: thank you very much for that.
13:57
Speaker 1: Just so way through with you, Sydney, I'm getting the
13:59
Speaker 1: AI system and not your dog. That's all I want
14:01
Speaker 1: to be clear.
14:03
Speaker 2: What you we may we may supply you with the
14:06
Speaker 2: picture of Sydney on to the come to the app,
14:09
Speaker 2: but yeah, you're getting the AI.
14:11
Speaker 3: Yeah. So what we find is that to build trust
14:15
Speaker 3: in AI systems and to build the willingness form a
14:19
Speaker 3: member to go along a journey experience, there's some things
14:24
Speaker 3: we have to do at the table stakes level, at
14:27
Speaker 3: the grassroots level that we have to get right inexorably,
14:30
Speaker 3: and I'm going to go back to Anil's comment about
14:33
Speaker 3: the ID card. What happens if you've lost your ID card.
14:37
Speaker 3: You don't want to wait on the phone for anybody
14:41
Speaker 3: to get a replacement a D card. You'd like to
14:43
Speaker 3: be able to do that once and done on the
14:46
Speaker 3: web or the mobile. Might have to ask a couple
14:49
Speaker 3: of questions and have it done lights out right. So
14:53
Speaker 3: there's this combination of doing the more routine things with
14:58
Speaker 3: absolute decision, lights out, complete ease of member, and then
15:04
Speaker 3: that builds this trust to have this more longitudinal journey
15:09
Speaker 3: to answer your questions or to recommend to you about shingles,
15:13
Speaker 3: vaccine right, or a variety of other things based on
15:17
Speaker 3: you know, your your health challenges. So it's a it's
15:19
Speaker 3: kind of a double edged sort of taking care of
15:22
Speaker 3: the table stakes and taking people along the journey.
15:25
Speaker 1: Your point is you start with the very prosaic stuff
15:29
Speaker 1: and you build a trust in the system, and then
15:32
Speaker 1: you can move to the more high end stuff. Tell
15:36
Speaker 1: me about how you build an AI system like this.
15:39
Speaker 1: This is not a trivial accomplishment. What went into building Sydney.
15:44
Speaker 2: Yeah, so I think you know, Malcolm, Traditionally we have
15:49
Speaker 2: a lot of data over the years that we have
15:51
Speaker 2: accumulated for every member, and we have you know, eighty
15:56
Speaker 2: million lives, multiple petabytes of data which is sitting on
16:00
Speaker 2: our systems, and that data basically allows us to learn.
16:04
Speaker 2: You know, the data is data. As long as you
16:07
Speaker 2: don't touch it, you don't do anything. But once you
16:09
Speaker 2: start really using technologies and when we call AI, these
16:14
Speaker 2: are mathematical models that you can run on this data
16:18
Speaker 2: to give you insights. And those insights are the key
16:21
Speaker 2: at the end of the day. And as we get
16:24
Speaker 2: those insights, we have to make sure that we have
16:26
Speaker 2: a way to use those insights to make a difference
16:29
Speaker 2: in the life of any member that we have or
16:32
Speaker 2: any constituent. Actually, you know, our sales experience for our
16:35
Speaker 2: brokers are providers. Getting to know exactly what they need
16:39
Speaker 2: to know is very very important. So we are making
16:42
Speaker 2: sure that this data and the mining of this data
16:44
Speaker 2: is constant. So when we talk about the partnership with IBM,
16:49
Speaker 2: we are talking about ability for us to mine this
16:51
Speaker 2: data on the fly at a very very quick speed,
16:55
Speaker 2: and that is what is key. Then we are able
16:58
Speaker 2: to use AI in a different content text And I'm
17:00
Speaker 2: going to give you example of something that really we're
17:02
Speaker 2: bringing to the forefront of what we call as a
17:05
Speaker 2: nutrition tracker. So imagine that you have your phone in
17:09
Speaker 2: front of you, you have a plate of food that
17:13
Speaker 2: came in front of you, and you can open Sydney
17:16
Speaker 2: and show the food of plate to Sydney. Sydney can
17:20
Speaker 2: tell you based on what is plate.
17:22
Speaker 1: You take a picture of the photo and Sydney looks
17:24
Speaker 1: at the photo and says, why are you loading up
17:27
Speaker 1: on carbs? I mean, is that what you're talking about?
17:29
Speaker 2: Exactly? That's what I'm talking about. So you know, this
17:31
Speaker 2: is a great partnership with we have with our one
17:33
Speaker 2: of our ecosystem partners and actually this isn't pilot with
17:36
Speaker 2: our house account, which is eighty thousand members right now,
17:39
Speaker 2: and it can tell you. It can you can show
17:42
Speaker 2: it a cup and it can tell you this is
17:44
Speaker 2: a coffee with no milk and it's going to be
17:47
Speaker 2: seventy calories and it keeps track of what you're eating.
17:51
Speaker 2: And basically that's how we build the healthy habits out there.
17:53
Speaker 2: So the advancement in the field of technology and how
17:57
Speaker 2: do we make sure that we move away from that
17:59
Speaker 2: legac information technology world to really the exponential technology that
18:04
Speaker 2: is in front of us is the key.
18:09
Speaker 3: We needed to take all of that AI and persist
18:13
Speaker 3: a conversation with a member, right. And that's where Watson
18:17
Speaker 3: came in to help Sydney persist conversations with members, right,
18:23
Speaker 3: Because crunching through data and knowing about your claim is
18:26
Speaker 3: one thing. But being able to talk to you about
18:29
Speaker 3: that claim and understand your responses back, whether you're on
18:33
Speaker 3: a keyboard, whether you're speaking, whether you're doing whatever. That's
18:36
Speaker 3: kind of where Watson came in to help augment Sidney
18:39
Speaker 3: and again, designing those conversations. I don't know if you've
18:43
Speaker 3: been in a situation where you're sitting next to somebody
18:45
Speaker 3: and they're talking and you say, oh my god, I
18:48
Speaker 3: can't believe they said that. Well, you have to engineer
18:52
Speaker 3: that out of the conversations that you have with members
18:57
Speaker 3: so that you know all of the members are delighted.
19:00
Speaker 3: And one of the things I'm proud oft of is
19:03
Speaker 3: when by our work together, we have members that are
19:07
Speaker 3: thanking Sydney when we're working with them with artificial intelligence,
19:13
Speaker 3: responding to their questions just as if Sydney was a
19:18
Speaker 3: fully human worker, right. And that that's what I get
19:22
Speaker 3: delight from is when we've been able to change a
19:25
Speaker 3: member experience and work through that.
19:31
Speaker 1: All of the things members might ask, Now, are you
19:35
Speaker 1: taking real life conversations, looking at them and feeding them
19:40
Speaker 1: to Sydney and saying okay, in the last two years,
19:42
Speaker 1: these are These are all the phone conversations we've had
19:45
Speaker 1: with our members. These are the kinds of things they ask.
19:47
Speaker 1: Is that where it starts?
19:50
Speaker 2: We build what we call the antology of the conversations.
19:53
Speaker 2: You know, how are we making sure that as we
19:56
Speaker 2: get the interactions noted down for our members or providers
20:01
Speaker 2: into our system, whether it's a phone call, whether it's
20:03
Speaker 2: a chat, whether it's basically even they came to the
20:06
Speaker 2: website and they clicked through specific things, right, so we
20:10
Speaker 2: are noting those down. We are kind of creating what
20:13
Speaker 2: we call a graph model and a flow of when
20:16
Speaker 2: a member asked this, the next question possibly, well, it's
20:19
Speaker 2: going to be this. If you give a yes to
20:22
Speaker 2: that answer or not to that answer, they're going to
20:24
Speaker 2: probably ask you this. So that kind of flow is.
20:26
Speaker 1: Sydney can be thinking two and three steps ahead exactly.
20:30
Speaker 2: So Sydney is thinking two or three steps ahead and
20:33
Speaker 2: making sure that the anticipation of what you're going to
20:35
Speaker 2: be doing and beyond, Sydney, our overall system is thinking
20:38
Speaker 2: two or three system steps ahead and predicting proactively those
20:44
Speaker 2: conversations as well as those interventions that we need to
20:47
Speaker 2: give to the members. So really using AI, you know,
20:51
Speaker 2: Watson as a backbone to this, Sydney is basically what
20:55
Speaker 2: we call the human centered, designed, focused interaction and Engagements
21:00
Speaker 2: system that sits on top of the backbone of the
21:02
Speaker 2: AI as the data at the bottom, so that basically
21:05
Speaker 2: is layered away. How Sydney is able to answer the
21:08
Speaker 2: question that we have It expects you of what type
21:11
Speaker 2: of question it is because our intology of the data
21:14
Speaker 2: as well as the AI that we have built is
21:17
Speaker 2: very very rock solid. And that is and the good
21:20
Speaker 2: thing is that it's it's a gift that keeps giving
21:23
Speaker 2: because the more data we collect, the more the system
21:27
Speaker 2: it gets.
21:28
Speaker 1: Yeah, wait, can you stumps Sydney. Can you ask Sydney
21:32
Speaker 1: a question you can.
21:32
Speaker 3: About I'm sure it's possible to. And then you know,
21:35
Speaker 3: when we when we get into that situation, what we
21:38
Speaker 3: want to do is we want to bring the member
21:41
Speaker 3: to a human agent so that the members satisfied seamlessly right,
21:47
Speaker 3: so that there's there's no daylight at all regardless of
21:50
Speaker 3: how the member has wants to connect with a human agent.
21:54
Speaker 2: A lot of.
21:55
Speaker 3: Members, you know, are dealing with time challenges and they
21:59
Speaker 3: don't want to call up anymore. They just want somebody
22:02
Speaker 3: to you know, be able to chat with. We try
22:04
Speaker 3: and respond to all that, and then if somebody needs
22:07
Speaker 3: a human agent, then we go there.
22:10
Speaker 2: Yeah.
22:11
Speaker 1: Yeah, what's what did your what did your members tell
22:15
Speaker 1: you about, either explicitly or implicitly about what they wanted?
22:22
Speaker 1: You know, we've been through this. We've just been through
22:24
Speaker 1: a year and a half of craziness, you know, where
22:27
Speaker 1: everything's being turned upside down. I'm curious, what have you
22:31
Speaker 1: what have you learned from them over the last stretch?
22:34
Speaker 1: Is what a member wants today very different than it
22:37
Speaker 1: was two years ago.
22:38
Speaker 2: I definitely, Malcolm, if you look at that, you know,
22:42
Speaker 2: the terms that we use in healthcare are very very complex,
22:45
Speaker 2: and it's very difficult for people to understand what my
22:47
Speaker 2: cope is. What is an out of network? What is
22:49
Speaker 2: that in network? What does a claim that that it
22:54
Speaker 2: needs a pre authorization mean to me? So if you
22:57
Speaker 2: look at the conversation that we were having before. They
23:01
Speaker 2: were really very hardcore healthcare oriented conversations, and the transparency
23:07
Speaker 2: to what I'm going to pay was not there. So
23:11
Speaker 2: this was an industry wherein you know, you're going to
23:15
Speaker 2: buy insurance and you're going to buy a product without
23:18
Speaker 2: really understanding what I'm going to get. At the end
23:20
Speaker 2: of the day, what we did and basically what our
23:23
Speaker 2: customers actually demanded from us, is that irrespect you of
23:26
Speaker 2: the channel that they come to us, what we call
23:29
Speaker 2: here at Anthem connected Experiences. We want to build the
23:32
Speaker 2: connected experiences, whether they come to us from a phone call,
23:35
Speaker 2: whether they're chatting with us, they're having a web interaction,
23:39
Speaker 2: whether they're in the provider's office. How do we make
23:42
Speaker 2: sure that we connect the experience end to end. Now,
23:45
Speaker 2: once we connect the experience, we want to make sure
23:47
Speaker 2: that we are building a very human centered design way
23:51
Speaker 2: of answering their questions. So it is as simple as
23:54
Speaker 2: making sure that we provide them a nudge on probably
23:58
Speaker 2: this is what you're looking for, and that clicks with
24:01
Speaker 2: them and they say, yeah, that's what I was looking for.
24:03
Speaker 2: So that input, simple interaction really helps to make sure
24:07
Speaker 2: that you make the member feel good having the ability
24:09
Speaker 2: to text, having an ability to get dancers while you're
24:13
Speaker 2: cooking your dinner and you can text and say that, hey,
24:16
Speaker 2: could you please tell me what will make copey for
24:18
Speaker 2: the next visit I have with doctor X. And you
24:20
Speaker 2: go ahead and start cooking your dinner, and when you
24:22
Speaker 2: come back, you have a text back out there which
24:24
Speaker 2: tells you exactly what it is. And the beauty of
24:27
Speaker 2: it is that we had a very constant loop out there.
24:30
Speaker 2: You know, the technologies that we use that allowed us
24:34
Speaker 2: to have a constant feedback on those complex interactions that
24:37
Speaker 2: we were having. And that's where IBM team and we
24:40
Speaker 2: work together and kind of figured out, Okay, what will
24:42
Speaker 2: be our game plan?
24:43
Speaker 1: What did you learn from working with other people on
24:47
Speaker 1: the Watson platform that helped aneil an anthem? What did
24:51
Speaker 1: you bring to them? So from what you've learned from others.
24:54
Speaker 3: So what we've tried to do with Watson. And when
24:58
Speaker 3: Watson first started, we thought that everybody wanted a spoke suit,
25:04
Speaker 3: and so we'd kind of go on a journey together
25:08
Speaker 3: to make up a spoke suit. And what we found
25:11
Speaker 3: the clients really wanted was, well, look, I want you
25:15
Speaker 3: to show up with the suit partially done to answer
25:20
Speaker 3: some of the basic things, and then I want to
25:24
Speaker 3: make it my own, right, So so show up ready
25:27
Speaker 3: to go so that we can get into production answering
25:31
Speaker 3: questions in a few months, and then we will work
25:35
Speaker 3: together to radically customize and tailor that experience. That's been
25:40
Speaker 3: my biggest learning, right, So, whether it was in financial services,
25:46
Speaker 3: or healthcare or telco or you know, there's about seven
25:49
Speaker 3: or eight dominant industries. We tried to make a series
25:54
Speaker 3: of industry specific cartridges so that Watson came kind of
25:58
Speaker 3: pre trained, right, so that we were ready to go quickly.
26:03
Speaker 3: And then the second learning was we needed to show
26:07
Speaker 3: up with the right people because remember you're creating a
26:11
Speaker 3: conversational interaction with someone, right, so you got to make
26:15
Speaker 3: sure that people are designing the words correctly and the
26:18
Speaker 3: user experience right. Those are the two things I think
26:20
Speaker 3: that you know, we brought that tried to help Anthem accelerate.
26:26
Speaker 1: I mean, and Neil said something that I thought was fascinating,
26:29
Speaker 1: you talking about designing a system with empathy, and I'm curious,
26:34
Speaker 1: what does First of all, what does empathy look like
26:37
Speaker 1: in an AI system? And b have you has anyone
26:42
Speaker 1: ever has any non healthcare player ever asked you, Glenn,
26:48
Speaker 1: to put empathy in the system.
26:51
Speaker 3: Clients outside of healthcare are less focused on empathy. They
26:56
Speaker 3: are focused more on making sure to get you know,
27:01
Speaker 3: the information out there correctly, especially in highly regulated industries. Right.
27:07
Speaker 3: How you deal with empathy in an AI system is
27:13
Speaker 3: based on the choice of words that you use and
27:17
Speaker 3: the verbal inflections that are present when you have a
27:20
Speaker 3: voice response, right, and you and I when we're talking
27:25
Speaker 3: right now with Malcolm, with an Eil, with whomever, we
27:28
Speaker 3: can just by the words that somebody chooses, we can
27:31
Speaker 3: know whether it matters to them about what we're talking about, right,
27:36
Speaker 3: And so we try and build a lot of those
27:38
Speaker 3: human characteristics into all the responses as compared to just
27:42
Speaker 3: getting the information right. Just what's you know us just
27:47
Speaker 3: telling people you're sorry? Right, Those are the types of
27:50
Speaker 3: things that you have to engineer in as compared to
27:53
Speaker 3: just being flawlessly precise about the answer.
27:56
Speaker 1: Yeah. Wait, one last question for both The has been
28:00
Speaker 1: such a fun conversation We talked about ten years ago
28:04
Speaker 1: when you guys started talking, and then the sort of
28:08
Speaker 1: this transition moment five years ago. Now, let's go five
28:10
Speaker 1: years in the future. So let's imagine it's twenty twenty
28:15
Speaker 1: six and where three of us are talking again. I
28:18
Speaker 1: want to know what problems you're trying to solve.
28:21
Speaker 2: Then the problems we are trying to solve at that
28:25
Speaker 2: time would definitely be much different than where we are.
28:29
Speaker 2: But what I can tell you before I get there
28:31
Speaker 2: is that you know, we want to make sure that
28:34
Speaker 2: in the next five years, Anthem is treated like a
28:39
Speaker 2: platform company which is focused on creating these solutions with
28:44
Speaker 2: the help of our partners that really meet the need
28:47
Speaker 2: of the members in the journey that they have from
28:50
Speaker 2: a healthcare perspective, and we do want to pivot from
28:53
Speaker 2: a sick care to more proactive and predictive care and
28:57
Speaker 2: wellness for members. So we're going to down and keep
29:01
Speaker 2: working on that because it's a it's something that never
29:04
Speaker 2: ends and it's going to keep going in the years
29:07
Speaker 2: to come.
29:09
Speaker 1: I'm still processing this fantastic idea about taking a photo
29:13
Speaker 1: of your meal, if your plate of food, and getting
29:18
Speaker 1: instant feedback and analysis on that. So so Sydney starts
29:22
Speaker 1: gets all these pictures of my food, gets a sense
29:25
Speaker 1: of what I'm eating over the course of the given day.
29:28
Speaker 1: Is the idea that. So I'm thinking about this five
29:30
Speaker 1: year from now conversation. So five years from now I
29:34
Speaker 1: might be taking a photo of everything and then at
29:36
Speaker 1: the end of every day, Sydney texts me and says, Malcolm,
29:42
Speaker 1: you should be aware of the fact that your nutritional
29:46
Speaker 1: patterns of the last few days you need to eat
29:48
Speaker 1: a few more vegetables or you'd be useful to have some.
29:51
Speaker 1: Is that what we're talking about here? But I think
29:53
Speaker 1: this idea is fantastic because there is no we have
29:56
Speaker 1: no way of making any nutritional sense of the stuff
29:59
Speaker 1: we unless you spend two hours on a on Google
30:03
Speaker 1: before you make your dinner. How do you know whether
30:06
Speaker 1: the sum total of the things you eat in a
30:08
Speaker 1: given day is going to be is optimum? I love this,
30:12
Speaker 1: I want this thing with this now? Can I do
30:15
Speaker 1: I have to wait five years? Can I have?
30:17
Speaker 3: No?
30:19
Speaker 1: Guys, it's been a really, really fun conversation. I really
30:22
Speaker 1: appreciate you taking the time and Neil Glenn have a
30:24
Speaker 1: wonderful day. And the future cannot come fast enough, at
30:29
Speaker 1: least for me, So bring it on. I'm waiting for it.
30:33
Speaker 2: Thank you very much for having Malcolm.
30:35
Speaker 3: Oh yeah, awesome, Thanks Malcolm. Bye.
30:37
Speaker 2: Guys.
30:41
Speaker 1: Understanding customer needs has become even more important in the
30:44
Speaker 1: wake of COVID nineteen. Companies like IBM and Anthem are
30:48
Speaker 1: learning to leverage technology to deliver a more personal experience,
30:52
Speaker 1: a crucial part of our evolving healthcare system. Thanks again
30:57
Speaker 1: to A Neil Bot and Glenn Finch for talking with me,
31:00
Speaker 1: I learned a lot. Smart Talks with IBM is produced
31:05
Speaker 1: by Emily Rostek with Carl Migliori, edited by Karen Schakerjee,
31:10
Speaker 1: engineering by Martin Gonzalez, mixed and mastered by Jason Gambrell
31:14
Speaker 1: and Ben Tolliday. Music by Gramoscope. Special thanks to Molly Sosha,
31:20
Speaker 1: Andy Kelly Mia, Label, Jacob Weisberg, Heather Fein, Eric Sandler,
31:24
Speaker 1: and Maggie Taylor, and the teams at eight Bar and IBM.
31:29
Speaker 1: Smart Talks with IBM is a production of Pushkin Industries
31:32
Speaker 1: and iHeartMedia. You can find more Pushkin podcasts on the
31:36
Speaker 1: iHeartRadio app, Apple Podcasts, or wherever you like to listen.
31:40
Speaker 1: I'm Malcolm Gladwell, See you next time.