Smart Talks with IBM and Malcolm Gladwell: Can AI be empathetic? Reinventing client experiences

we are building these solutions. How are they fundamentally changing and improving the lives of our members, our communities and really making a difference to the people we saw? And Neil has been with Anthem for over thirteen years and his spearheaded efforts to improve customer experience and members needs. I'll also be chatting with Glenn Finch, Managing Partner of Global Business Services at IBM. How you deal with empathy

in an AI system. It's all based on the choice of words that you use and the verbal inflections that are present when you have a voice response. Then is a twenty five year IBM veteran. His work focuses on the most challenging and transformative engagements at IBM. I'm excited to share my conversation with the Neil and Glenn about artificial intelligence and how it's influencing customers to interact with their healthcare in a new way. Al Right, guys, let's

get started. Hi everyone, Thanks guys for joining me today. Why don't we start with the two of you just introducing yourself, tell me, tell me what you do as great I'm glad to be here today, Thanks for hosting us. I basically lead the technology and practice here at Anthem as a CTO, managing all the roadmaps for technology, making sure that we're building solutions that are meeting our business needs on a day to day basis, making sure that

we are catering to the needs of our members. So overall technology roadmap, making sure that we work with partners like IBM to bring new technology to the forefront. And how how long have you been with Anthem. I've been with Anthem for thirteen years actually, and the company has

evolved while we are in the healthcare business. Our focus has been more members centric now, so really understanding how a big organization like Anthem can make sure that we pivot from being a normal traditional listed company which definitely is meeting the expectations of the stockholders, but also catering to the need of our members and the communities that we serve in. Yeah, why don't you introduce yourself. I'm Glenn Finch. I look after data in AI and the

services side of the IBM company. We take a lot of wicked cool technology and bring it to life of clients like Anthem and Uh, you know, I get the great pleasure of working with a Neil on a daily basis to really fundamentally change the member experience using artificial intelligence, so usually on the cutting edge of things, and just just love coming to work every day. Yeah, so you said something. The two of you have been working together for some time. When did you guys me me to

first know each other. As I said, the industry has been evolving a lot, Malcolm, So a couple of years back. We basically we're kind of figuring out as the consumer experience changes, as people get so much used to Netflix and Amazon and the way they do their day to day shopping, the way they experienced things. We were looking for a partner where we could really explore the power of AI, really use our data in a way wherein

we can create these personalized experiences. So that's where Glenn and I actually talked a little bit and we figured out that there is a possibility of us partnering ib AM bringing its UM technology, and basically that's when we kind of figure out there's there's a definite role to play and partner on this journey together. And it's been great.

Over the last two years, we have been able to deliver on some great, exceptional experiences for our members and and we are now moving beyond to other constituents and really making sure that UM we make it awesome for for members to connect with us. Yeah, Glenn, had you worked with an in an insurance provider before? Yea, So we have a variety of clients around the world, so yes,

but Anthem is special to my heart. We started thinking through this because when you work with Anthem, this concept of member and member experience, you need to show up every day with that front and center in your mind. So there are other clients who focus on cost or technical debt or something like that, but that's not true

at Anthem. You need to show up front and center every day with how are you going to radically improve the member experience first, and fas say, but it's the relationship between the two companies and the two of you goes back so far that I'm really curious to get a sense of how the kinds of questions you've been asking and problems you've been trying to solve have evolved over that time. Tell me about ten years ago, what

were you guys talking about. So I think the ten years back, the conversation is more and more around Okay, how many sellers do we have in our data center, how many licensing points that we're going to be spending this year? What will be our footprint? What is our network speed? Are we able to manage the new capability that we're delivering? And it really was very technologically focused

conversation that we used to have. And what has happened over the years, Malcolm, is that you know, we have been now pivoting too more around Okay, we are building these capabilities, we are building these solutions, how are they fundamentally changing and improving the lives of our members, our communities and really making a difference to the people we serve. So as we looked at technology and engineering, we kind of pivoted from that to more platform and a product

that we are building for our constituents. And as that pivot happened, you know, I would say around three or four years back, the conversation then evolved to more around Okay, how are we improving the experience? How are we making sure that we're making it easier for the members? And and it pivoted from being reactive and kind of what I called sick care management to more wellness oriented conversation

how do we keep our members healthy? And that's where the overall pioneering of personalized experiences, predictive and proactive health care management kind of started. And as we had interactive that IBM, we knew that they had the technology and they had the real backbone, which good. So the needs that we wanted to kind of bring forward and talk about that pivot. I'm curious what's driving it. Did you go to a NIL and say, look, you have an

opportunity to do so much more here? Does a neil come to you and say I don't want to be just focused on technology. Are members are telling us X, Y and Z or take me back to that transformative moment when you start thinking about this project in a different way. There's been a a massive shift at the IBM company in general to shift away from pure technology

and move towards technology on behalf of a workflow. When you think about artificial intelligence and you are trying to have a conversation with someone, right, you don't need just deep artificial intelligence programmers. You need to have people attached to that that know how to have a conversation with people and what sequence some words are gonna elicit a response,

and how that experience feels. To remember, that's a very different type of program then just dropping in a chatbot and hoping it works right to answer the twelve questions that you get most of the time, right, And you mentioned this concept of personalization, right, just making sure we put the right people together on the program is half the battle, right, And that's a shift that IBM has

made very consciously, started about five years ago. You know, we really in Earnest called out intelligent workflows about two or three years ago and that's when we started doing this together. M. It was tough, it was ambitious as compared to anything else that we had done out here. And one thing which Malcolm was very very beautiful and and has been very important for us learning on the goal.

When you have so much data that you're capturing, when you have a technology that really can give you in a nanosecond the response to what exactly is happening. The beauty of it is that you can pivot and kind of change on the fly. The agility that you build into our system, the agility that you build into our operations is a key and that's what we have been

able to do. And unfortunately at Anthem, we have been really at the forefront of that, investing the right dollars and bringing the agility, bringing the way we can kind of pivot to what is more important to the concerns. That has been a great thing that has been happening here. Let's go through some some very specific examples. So, I am a I'm a member of Anthem, I am on

your website. I would like to accomplish something. Tell me a specific thing that an expectation a member might have, and how you have said about trying to satisfy that expectation, and let's get let's get super specific. Give me a scenario, a tough a tough scenario. Yeah, yeah, well, I think I can give you a comparison to the past. Right, So when you were enrolled as a member, we probably would send you an ID card which was a hard piece of paper, a very good piece of paper which

costs us a lot. Then there was nothing that we would let you know other than that, hey, if you want a register on our website, please, you're welcome, right, And then that's where our first interaction with you as a member used to happen. And frankly, there was nothing after that. There was a vacuum, and then you would

probably try to understand your benefits. You will make sure that you know what your co pay is, and then we will not hear from you for a long time, and all of a sudden, someday, unfortunately somebody is tack in your family and then you pick up the card, go to a provider and basically have a visit um there and then you go from there. So that's the traditional experience that somebody would have had. Right now we

have totally revamped that. So as a member, when you enrolled with us, we send you a welcome kit which sent you a digital well kit. We send you an ID card which is available on your phone. We send you a link to our Sydney have tapp which basically you can download, you can register in a minute, but if you've been an existing member, you will get a personalized, curated news feed which is specific to you based on your prior experience and based on your claims, history and

other things that we know about you. We work with IBM around the AI chat part, which is basically a Watson enabled chat board which you can ask the questions from what is my copay? You don't have a call us, you don't have to send us an email. You can really ask a question there itself. You can ask for what are the providers near me? And we'll match a

provider to you based on your past history. And that's where AI comes in that what do we think Malcolm's age group, Malcolm's prior history tells us who should be the right provider for him to take care of things. So that interactive, more personalized, more engaging experience is what is different. Let me give you an example. I'd love for both of you the way on this. So I'm fifty seven years old. It is indicated for someone at my age that I get a shingles vaccine. I didn't

notice never occurred to me. A friend of mine got shingles. It was like the worst experience of his life. He lost three weeks. It was like so painful, and he's like, whatever you do, Malcolm, you need to get a shingles vaccine right now. So I went out and got my shingles vaccine and then I had to get the booster.

I remember the booster and blah blah blah. Now when you're talking about Sydney and about about drawing on past experience, if I was a long time Anthem subscriber, would you reach out to me and say, Malcolm, you gotta get your shingles vaccine? Would you do? Is that what you're thinking about? Exactly? Exactly not only we will tell you that you need to take shingles vaccine, will tell you exactly which provider probably is the right one for you.

And that is what the beauty is right now, that not to care really that the care gap that we have. How does the data tell us that these are the care gaps in Malcolm's journey? You know, you you pay a lot for your insurance company to take care of you, and how do we make sure that we take care of you? We be your advocate, We be your journey partners. Rather than just allowing for you to come to us when you feel that you're sick. So this this AI system is called Sydney. First of all, who came up

with Sydney actually loved the name? But is that who? Whose decision was it to call this system Sydney? Actually you know, uh, it was it was our team. We did some research in terms of what could be a very neutral name that we can keep out there. And and Malcolm, I can tell you that I love the name so much that the beginning of when we had COVID hit us, my daughter was asking for a dog for a long time and we got a dog, and

actually we named the dog Sydney. So that's how how much how much I care about the name and how much I love the name. But thank you very much for that's just so we true you Sydney. I'm getting the AI assistum, but not your dog, That's all I want to be clear. That's what you know we make. We may supply you with a picture of Sydney on when you when you come to the come to the app,

but yeah, you're getting the A. Yeah. So what we find is that to build trust in AI systems and to build the willingness for remember to go along a journey experience. There's some things we have to do at the table stakes level, at the grassroots level, that we have to get right inexorably. And I'm going to go back to a Neil's comment about the I D card. What happens if you've lost your I D card. You don't want to wait on the phone for anybody to

get a replacement a D card. You'd like to be able to do that once and done on the web or the mobile. Might have to ask a couple of questions and have it done lights out right. So there's this combination of doing the more routine things with absolute decision writes out complete ease of member, and then that builds this trust to have this more longitudinal journey to answer your questions or to recommend to you about shingles, vaccine right, or a variety of other things based on

you know your your health challenges. So it's a it's kind of a double edged sort of taking care of the table stakes and taking people along the journey. Your point is you start with the very prosaic stuff and you build a trust in the system, and then you can move to the more high end stuff. Tell me about how you build an AI system like this. This

is not a trivial accomplishment. What went into building Sydney. Yeah, so I think you know, Malcolm, Traditionally, we have a lot of data over the years that we have accumulated for every member, and we have eighty million lives, multiple petabytes of data which is sitting on our systems, and that data basically allows us to learn. You know, the data is data. As long as you don't touch it,

you don't do anything. But once you start really using technologies and and when when we call AI, these are mathematical models that you can run on this data to give you insights. And those insights are the key at the end of the day. And as we get those insights, we have to make sure that we have a way to use those insights to make a difference in the in the life of any member that we have or any constant. Actually, you know, our sales experience for our

brokers are providers. Getting to know exactly what they need to know is very very important. So we are making sure that this data and the minding of this data is constant. So when we talk about the partnership with IBM. We're talking about ability for us to mind this data on the fly at a very very quick speed, and that is what is key. Then we're able to use

AI in a different text. And I'm going to give you example of something that really we're bringing to the forefront of of what we call as a nutrition tracker. So imagine that you have your phone in front of you, You have a plate of food that came in front of you, and you can open Sydney and show the food of plate to Sydney. Sydney can tell you based on what it plate. You take a picture of the photo and Sydney looks at the photo and says, why are you loading up on carbs? I mean, is that

what we're talking about exactly? That's what I'm talking about. So you know, this is a great partnership we have with one of our ecosystem partners. And actually this isn't pilot with our house account, which is eighty thousand members right now, and it can tell you. It can you can show it a cup and it can tell you this is a coffee with no milk, and it's going to be seventy calories and it keeps track of what you're eating and basically that's how we build the healthy

habits out there. So the advancement in the in the field of technology and how do we make sure that we move away from that leg thee information technology to really the exponential technology that is in front of us

is the key. We needed to take all of that AI and persist a conversation with a member, right And and that's where Watson came in to help Sydney persist conversations with members, right Because crunching through data and and knowing about your claim is one thing, but being able to talk to you about that claim and understand your responses back, whether you're on a keyboard, whether you're speaking,

whether you're doing whatever. That's kind of where Watson came in to help augment Sydney and again designing those conversations. I don't know if you've been in a in a situation where you're sitting next to somebody and they're talking and you say, oh my god, I can't believe they

said that. Well, you have to engineer that out of the conversations that you have with members so that you know, all of the members are delighted and one of the things I'm proudest of is when by our work together, we have members that are thanking Sydney when we're working with them with artificial intelligence, responding to their questions, just as if Sydney was a fully human worker, right, And that that's what I get delight from is when we've

been able to change a member experience and work through that all of the things members might ask, Now, are you taking real life conversations, looking at them and feeding them to Sydney and saying okay? In the last two years, these are all the These are all the phone conversations we've had with our members. These are the kinds of things they ask. Is that where it starts? We build

what we call the anthology of the conversations? You know, how are we making sure that as we get the interactions noted down for our members or provide us into our system, whether it's a phone call, whether it's a chat, whether it's basically even they came to the website and they clicked through specific things, right, so we are noting those down. We are kind of creating a what we call a graph model and a flow of When a member asked this, the next question possible level, it's going

to be this. If you give up yes to that answer or not to that answer, they're gonna probably ask you this. So that kind of slow Sydney can be thinking two in three steps ahead exactly. So Sydney is thinking two or three steps ahead and making sure that the anticipation of what you're going to be doing and and beyond. Sydney, our overall system is thinking two or three systems steps ahead and predicting proactively those conversations as well as those interventions that we need to give to

the members. So really using ai UM you know Watson as a back backbone to this, Sydney is basically what we call the human centered, designed, focused Interaction and Engagements system that sits on top of the backbone of the AI as the data at the bottom, So that basically is layered away. How Sydney is able to answer the question that we have it aspects you of what type of question it is because our intology of the data as well as the AIS that we have built is

very very dock solid. And that is and the good thing is that it's it's a gift that keeps giving because the more data we collect, the more the system it gets Yeah, wait, can you Stumps, Sydney, can you ask it a question? You can? I'm sure it's possible too.

And then you know, when we when we get into that situation, what we want to do is we want to bring the member to a human agent so that the member satisfied seamlessly right, so that there's there's no daylight at all regardless of how the member has wants to connect with the human agent. A lot of members, you know, are are dealing with time challenges and they don't want to call up anymore. They just want somebody

to you know, be able to chat with. We try and respond to all that, and then if if somebody needs a human agent, then we go there. Yeah. Yeah, what's what did your what did your members tell you about, either explicitly or implicitly about what they wanted? You know, we've been through this. We've just been through a year and a half of craziness, you know, where everything is

being turned upside down. I'm curious, what have you what have you learned from them over the last stretch is what a member wants today very different than it was two years ago. Definitely, Malcolm. If you look at that, you know, the terms that you use in healthcare are very very complex, and it's very difficult for people to understand what my cope is. What is an out of network, what is it in network? What does a claim uh

that that needs a pre authoriation mean to me? So if you look at the conversation that we were having before, they were really very hardcore health care oriented conversations and and the transparency to to what I'm going to pay was not there. So this was this was industry where in you know, you're going to buy insurance and you're going to buy a product without really understanding what I'm

going to get. At the end of the day, what we did and basically what our customers actually demanded from us is that irrespect you of the channel that they come to us. Um what we call here at Anthem connected experiences. We want to build the connected experiences, whether they come to us from a phone call, whether they're chatting with us, they're having a web in traction, whether they're in the provider's office. How do we make sure

that we connect the experience end to end. Now, once we connect the experience, we want to make sure that we are building a very human centered design way of answering their questions. So it is as simple as making sure that we provide them a nudge on probably this is what you're looking for, and that clicks with them and they say, yeah, that's what I was looking for. So that input, simple interaction really helps to make sure

that you make the member feel good. Having the ability to text, having an ability to get dancers while you're cooking your dinner and you can text and say that, hey, could you please tell me what will cope for the next visit? I have a daughter X And you go ahead and start cooking your dinner and when you come back, you have a text back out there which tells you

exactly what it is. And the beauty of it is that we had a very constant loop out there, you know, the technologies that we use that that allowed us to have a constant feedback on those complex interactions that we were having. And that's where IBM team and we work together and kind of figured out, Okay, what will be our game plan. What did you learn from working with other people on the Watson platform that helped a Neil and Anthem? What did you bring to them? So from

what you've learned from others. So what we what we've tried to do with Watson, Well, Watson first started, we thought that everybody wanted of a spoke suit, and so we kind of go on a journey together to make

up a spoke suit. And what what we found the clients really wanted was well, look, I want you to show up with the suit partially done to answer some of the basic things, and then I want to make it my own, right, So so show up ready to go so that we can get into production answering questions in a few months, and then we will work together

to radically customize and taylor that experience. That's been my biggest learning, right, So whether it was UM in financial services, or healthcare or Telco or you know, there's about seven or eight dominant industries. UM. We tried to make a series of industry specific cartridges so that Watson came kind of pre trained, right, so that we were ready to

go quickly. And then the second learning was we needed to show up with the right people because remember you're creating a conversational interaction with someone, right, so you've got to make sure that people are designing the words correctly and the user experience right. Those are the two things I think that you know, we brought that tried to help Anthem accelerate. I mean, and Neil said something that

I thought was fascinating. You're talking about designing a system with empathy, and I'm curious what does First of all, what does empathy look like in an AI system? And b have you has anyone ever, has any non healthcare player ever asked you, Glenn to put empathy in the system. UM. Clients outside of healthcare are less focused on empathy. They are focused more on making sure to get UM, you know, the information out there correctly, especially in highly regulated industries. Right.

How you deal with empathy in an AI system, it's all based on the choice of words that you use and the verbal inflections that are present when you have a voice response, right, and you you and I UM when we're talking right now, was Malcolm with Annal with whomever. We can just by the words that somebody chooses, we can know whether it matters to them about what we're talking about, right, And so we try and build a lot of those human characteristics into all the responses as

compared to just getting the information right. Just what's you know? Usn't just telling people you're sorry, right, Those are the types of things that you have to engineer in as compared to just being flawlessly precise about the answer. Yeah. Um wait, one last question for for both of has been such a fun conversation. We talked about ten years ago when you guys started talking and then this sort of this transition moment five years ago. Now let's go

five years in the future. So let's imagine it's twenty and we're three of us are talking again. I want to know what problems you're trying to solve. Then the problems we're trying to solve at that time would would

would definitely be much different on where we are. But what I can tell you before I get there is that you know, we want to make sure that in the next five years, anthem Is is treated like a platform company which is focused on creating these solutions with the help of our partners that really meet the need of the members in the journey that they have from a healthcare perspective, and we do want to pivot from a from a sick care to more proactive and predictive

care and wellness for members. So we're gonna will down and keep working on that because it's a it's something that never ends and it's going to keep keep going in the years to come. I'm still processing this fantastic idea about taking a photo of your meal, if your plate of food, and getting instantent feedback and analysis on that. So Sydney starts gets all these pictures of my food, gets it gets a sense of what I'm eating over

the course of the given day. Is the idea that so I'm thinking about this five year from now conversation. So five years from now I might be taking a photo of everything, and then at the end of every day, Sydney text me and says, Malcolm, you should be aware of the fact that you're nutritional patterns of the last few days. You need to eat a few more vegetables or you'll be useful to have some. Is that what

we're talking about here? But I think this idea is fantastic because there is no we have no way of making any nutritional sense of the stuff we unless you spend two hours on a on Google before you make your dinner. How do you know whether the sum total of the things you eat in a given day is going to be um is optimum? I love this. I want this with this now? Can I do I have to wait five years? Can I have? Guys, It's been

a really, really fun conversation. I really appreciate you taking the time, Neil Glenn have a wonderful day, and that the future cannot come fast enough, at least for me, So bring it on. I'm waiting for it. Thank you very much for Malcolm. Oh yeah, awesome, Thanks Malcolm. Bye, guys. Understanding customer needs has become even more important in the wake of COVID nineteen. Companies like IBM and Anthem are learning to leverage technology to deliver a more personal experience,

a crucial part of our evolving healthcare system. Thanks again to a Neil Bot and Glenn Finch for talking king with me, I learned a lot Smart Talks with IBM is produced by Emily Rosteck with Carlie Migliori, edited by Karen Shakergee engineering by Martin Gonzalez, mixed and mastered by Jason Gambrell and Ben Tolliday. Music by Granmoscope. Special thanks to Molly Sosha, Andy Kelly Mia, Label, Jacob Weisberg, Heather Faine, Eric Sandler, and Maggie Taylor and the teams at eight

Bar and IBM. Smart Talks with IBM is a production of Pushkin Industries and I Heart Media. You can find more Pushkin podcasts on the i Heart Radio app, Apple Podcasts, or wherever you like to listen. I'm Malcolm Gladwell, See you next time.