Episode 269

full
Published on:

3rd Apr 2024

Augmenting Artificial Intelligence Through Cross-Functional Perspectives with Varun Grover

This week on the Be Epic podcast, Brent sits down with Varun Grover, Distinguished Professor of Information Systems and George & Boyce Billingsley Endowed Chair in the Sam M. Walton College of Business at the University of Arkansas. They explore the profound effects of AI on individuals, businesses, and society. Varun highlights areas where AI can enhance lives through applications in healthcare, education, and more. However, he cautions that without understanding how AI reaches conclusions, trust remains elusive. Brent and Varun discuss improving AI through specialized models, explainability, richer inputs and contexts. Varun asserts that augmenting human skills rather than automation ensures AI uplifts roles and fuels innovation. Listeners gain insight into AI's trajectory and its role partnering with instead of replacing humans.

Transcript
Varun Grover:

You never have innovation through automation,

Varun Grover:

you will only have innovation if there are ways in which the AI

Varun Grover:

and the technology can work together.

Brent Williams:

Welcome to the Be Epic Podcast brought to you

Brent Williams:

by the Sam M. Walton College of Business at the University of

Brent Williams:

Arkansas. I'm your host, Brent Williams. Together, we'll

Brent Williams:

explore the dynamic landscape of business and uncover the

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strategies, insights and stories that drive business today. Well,

Brent Williams:

today, I'm lucky to have with me Dr. Varun Grover, and Dr.

Brent Williams:

Grover's the George and Boyce Billingsley Endowed Chair and

Brent Williams:

Distinguished Professor of Information Systems in the

Brent Williams:

Walton College. Varun, thank you for joining me today.

Varun Grover:

I'm delighted to be here. Thank you.

Brent Williams:

Well, I think we're going to touch on some

Brent Williams:

interesting topics today. But maybe before we do that, I would

Brent Williams:

love for our audience to get to know you better. I've gotten to

Brent Williams:

know you over the last five years, I think you've been at

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the Walton College since 2017. But tell us a little bit about

Brent Williams:

you your background, and before coming to the Walton College.

Varun Grover:

Sure. So. So I'm a techie at heart in the sense

Varun Grover:

that I did my undergraduate degree in engineering,

Varun Grover:

electrical engineering, and, and that's where my interest in

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technology started coming about. And I had the good fortune of

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getting into a very competitive engineering school that allowed

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me to think systematically about technology. So when I, when I

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graduated, I kind of felt that I was in a very narrow silo, I

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understood technology gyrations I understood, you know,

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technical concepts, but I didn't really understand the world, the

Varun Grover:

broader context. And so I decided to do an MBA and then go

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into my PhD in information systems. And then after that,

Varun Grover:

I've been basically in academic jobs, I was at USC, and then I

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was at Clemson. And my primary goal or responsibility in those

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jobs was to, to build the PhD program, and conduct research

Varun Grover:

and set up centers, and have some outreach, dealing with

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important problems in the Information Systems domain. So

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I've been integrally involved in this in this field, and the

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field has evolved, because the technology catalyst is kind of

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driving changes. So if you think of technology in the 1960s, and

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70s, and 80s 90s, and now, now we're in this digital world,

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that is a lot of people really don't know how to deal with it,

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and companies are still struggling. And now we've got AI

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coming in, that's adding a new wrinkle. And so what I like

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about the field in general, is that we don't have a dearth of

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problems to study, there are lots of challenges faced by by

Varun Grover:

companies faced by individuals, and now the impacts transcend to

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society. So there's a lot of really, really interesting

Varun Grover:

issues. And that keeps me excited about the field.

Brent Williams:

Yeah. Well, you know, Varun, you're, you are a

Brent Williams:

researcher, you're a teacher, you know, you serve the

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University and the College through the normal mechanisms.

Brent Williams:

But you have spent the majority of your career really focused on

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research. And as you say, the your work and PhD programs are

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really advancing the research of these institutions. Just when

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you think about business research, maybe more generally,

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how, how does it impact the world? How does it impact

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others? And how have you viewed that over time?

Varun Grover:

Yeah, that's a really interesting question.

Varun Grover:

Because even business research has has evolved. If you think

Varun Grover:

about in the 1950s, business research was not much of

Varun Grover:

anything, it was more, you know, go out maybe some outreach and

Varun Grover:

case studies that you did with with businesses, but then the

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scientific aspect of business research came in the 1960s,

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1970s. And we kind of went overboard with the concepts,

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scientific concepts of theory and became somewhat

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disassociated with practice. So my thinking is that in in a, in

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an applied business discipline, it's really important that we

Varun Grover:

create interventions to practice. Any research that we

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do, should not be esoteric and isolated from the real world.

Varun Grover:

And so when we talk about when we think about research

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projects, traditionally our approach would be, you know,

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look for research gaps in the literature and then try and fill

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those gaps. I think the more productive approach is to To

Varun Grover:

identify real problems faced by practice, and then to convert

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those practical problems into research problems. So it's more

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like engaged scholarship, you engage with practice at a deeper

Varun Grover:

level, and try and look at their problems, and then translate

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those problems into research problems so that you can create

Varun Grover:

interventions, as a result of your research that actually make

Varun Grover:

a difference in practice.

Brent Williams:

That's right, what a good way to explain that

Brent Williams:

I just couldn't agree more about at least in my own research that

Brent Williams:

that's where the research questions that I've been most

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interested in then that ultimately, I think the research

Brent Williams:

that has the biggest impact for my own career comes from same

Brent Williams:

for you.

Varun Grover:

Absolutely

Brent Williams:

Well, I'll, I'll brag on you a minute, because I

Brent Williams:

don't think you would brag on yourself in this way. A couple

Brent Williams:

of the interesting statistics about you as a researcher, I

Brent Williams:

think you've published more than 400 articles in your career,

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over 100 in the top journals, and you are listed as one of the

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100 most cited, not just information systems, but

Brent Williams:

business researchers in the world, what an accomplishment.

Brent Williams:

And so you have truly over a career made a real impact in the

Brent Williams:

academy and in practice.

Varun Grover:

Thank you. Thank you Brent.

Brent Williams:

Well your research, yeah, I told you this

Brent Williams:

before, I'm kind of borrowing from your bio here. But you

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know, at a real broad level, you know, as I saw it described

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focuses on the effects of digitization on individuals on

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businesses and organizations and even society, tell us a little

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more of a high level before we get into some of the more

Brent Williams:

detailed questions.

Varun Grover:

So I've always been interested in how

Varun Grover:

technology creates value. And information technology is

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particularly of interest to me. So when we look at computing

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technologies, in a business context, what are the aspects of

Varun Grover:

these technologies? And the and the context around them, that

Varun Grover:

lead to value value at the individual level? So how can

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technology enhance individual productivity? How the value at

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the group level, value at the organizational level? How do you

Varun Grover:

actually create competitive advantage through these

Varun Grover:

technologies? How do you create greater profitability, more

Varun Grover:

revenues? And then at the market level? And that is how do you

Varun Grover:

make markets more efficient through technology. And then now

Varun Grover:

even more so at the societal level. So with technology, and

Varun Grover:

particularly digital technologies, penetrating every

Varun Grover:

aspect of what we do, there are issues of value, and the value

Varun Grover:

could be positive or negative. So now we are seeing you know,

Varun Grover:

this, there's two phases of technology, you have the

Varun Grover:

intended consequences to create positive value for companies.

Varun Grover:

And then you have sometimes unintended consequences that

Varun Grover:

create problems for society. So I like to study at every one of

Varun Grover:

these levels, I like to study different questions regarding

Varun Grover:

the value proposition of digital technologies.

Brent Williams:

Well, this has to bring probably to anyone's

Brent Williams:

mind, you know, when you talk about the enter the the

Brent Williams:

intersection of society and digital technology, as we sit

Brent Williams:

here today, the conversation around artificial intelligence,

Brent Williams:

AI, is everywhere. All right, you know when chat GPT popped on

Brent Williams:

the scene, it really just brought it to the consciousness,

Brent Williams:

even though this has been developing for years, if not

Brent Williams:

decades, it really brought it to the consciousness. You're not an

Brent Williams:

AI researcher, I know. But but I do think that you're probably in

Brent Williams:

a unique position to think about this intersection between this

Brent Williams:

technology, and people, businesses and society. So maybe

Brent Williams:

just I'll just I'll stop right there and kind of say, all

Brent Williams:

right, as you're observing this phenomenon of AI, what's kind of

Brent Williams:

going through your mind and what are the observations and

Brent Williams:

questions that that are becoming apparent to you?

Varun Grover:

Yeah. As many people are fascinated by AI, so

Varun Grover:

am I, as it's not, it's not my primary area of research, but

Varun Grover:

clearly it falls within the domain of digital technologies.

Varun Grover:

And like you said, ChatGPT came on the scene and it blew away

Varun Grover:

people because not because it wasn't necessarily the most

Varun Grover:

accurate or more most interesting output, but it gave

Varun Grover:

people the sense of the possible if this is the starting point,

Varun Grover:

and it can generate such interesting outputs, then where

Varun Grover:

is the world going. And I remember the first time I played

Varun Grover:

around with GPT, I asked it to write a story, I said, you know,

Varun Grover:

here's a little girl walking up a hill, and there's a, there's a

Varun Grover:

big rock at the top of the hill, write a story for a five year

Varun Grover:

old. And it wrote a pretty compelling story that I actually

Varun Grover:

read to a five year old. And then I said, okay, redo the

Varun Grover:

story for a 10 year old and it reformulated the story, change

Varun Grover:

the language, and again, fairly compelling story for a 10 year

Varun Grover:

old, then I asked her to do one for an adult, and it did it. And

Varun Grover:

then I pushed it to be more creative, in the ending, make it

Varun Grover:

more interesting, make it more controversial, make it more

Varun Grover:

enigmatic. And every time I did it, it came up with interesting

Varun Grover:

changes. And I said, wow, you know, this is actually doing it

Varun Grover:

from the corpus of data it's been trained on, and yet, it has

Varun Grover:

this layer of creativity that we don't quite understand how it's

Varun Grover:

getting there. And this was the early version of ChatGPT. More

Varun Grover:

recently, I was playing around with now there's many, many of

Varun Grover:

these chatbots, AI based chatbots. And I noticed one of

Varun Grover:

the differences. So I was playing around with a chatbot

Varun Grover:

called Pie, which now I believe has been acquired by Microsoft.

Varun Grover:

And it I found it to be extremely conversational. And

Varun Grover:

what was different about the earlier versions in this version

Varun Grover:

is that it had empathy. It actually could relate to me, and

Varun Grover:

it was taking cues from my text, and putting that emotional

Varun Grover:

response back to me.

Varun Grover:

And that was very interesting. So it's like, it's

Brent Williams:

Interesting.

Brent Williams:

Interesting. Well, you mentioned profound and scary. You also,

Brent Williams:

almost like we're coding emotions into these training

Brent Williams:

sets. Now, to provide far more conversational far more personal

Brent Williams:

AI, personal intelligence reactions. And I stopped

Brent Williams:

thinking about this, it is absolutely fascinating where

Brent Williams:

this can go. Because if you can have that level of

Brent Williams:

you talked about a wide potential set of potential

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interactivity, and conversational and empathy with

Brent Williams:

with individuals, you can put this front end on pretty much

Brent Williams:

any intelligence, and you can access the world. So customer

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interfaces, so providing excellent customer service, that

Brent Williams:

impacts on people business society at large. I'll, I'll

Brent Williams:

make it make it conversational, so you can align with what the

Brent Williams:

customer wants. Personal learning it for in the education

Brent Williams:

sphere, companionship for old people, you know, if you

Brent Williams:

actually put a physical manifestation, like a robot, and

Brent Williams:

kind of dive into two and ask you a question. So you mentioned

Brent Williams:

then you have this AI back back end, you can you can maybe

Brent Williams:

alleviate some loneliness in the world. And then so clearly,

Brent Williams:

there's this tremendous implications. And then you see

Brent Williams:

the applications of AI. Some of the things that we've often

Brent Williams:

wealth management, and you mentioned health care. And as I

Brent Williams:

talked about is in the medical field, in the medical field, you

Brent Williams:

can feed in radiology reports, and it can find abnormalities,

Brent Williams:

that's kind of low hanging fruit. But then when you have

Brent Williams:

this kind of conversational AI, you can put that in front of

Brent Williams:

was sitting here listening, I was thinking, oh, those are two

Brent Williams:

medical knowledge and you have a doc in a box. And when you are

Brent Williams:

considered the shortage of primary care physicians, this

Brent Williams:

would be a very interesting way to layer our medical

Brent Williams:

interactions, where you have the first layer of interaction where

Brent Williams:

pretty personal topics to me, like, one, you know, how am I

Brent Williams:

you can feel comfortable talking, even though it's not a

Brent Williams:

person, you can talk talk to the box, and that can do a diagnosis

Brent Williams:

and write up a report. And then it can go to the next level for

Brent Williams:

verification with a human and then go to the next level for a

Brent Williams:

managing my money and two managing my health? And I know

Brent Williams:

referral to a specialization. It can change the medical field

Brent Williams:

quite quite significantly. And we've seen applications of AI in

Brent Williams:

supply chain and manufacturing with robotics, in the financial

Brent Williams:

sector with wealth planning. And so when you have these

Brent Williams:

that I think that a lot of your research in digitization and how

Brent Williams:

interfaces, you basically can interact and get it more aligned

Brent Williams:

with what you want in terms of your wealth goals. And, and

Brent Williams:

recently, I was reading an article that described IBM's

Brent Williams:

Watson that was working with a fashion house, and they actually

Brent Williams:

trained the AI on videos of models walking down runways, and

Brent Williams:

it affects people in organizations and society looked

Brent Williams:

social media included, and the AI was quite adept at

Brent Williams:

identifying fashion trends, and new fashion clothing designs,

Brent Williams:

based on what they observed through this corpus of data. So

Brent Williams:

at least at trust at some level. So what have you learned about

Brent Williams:

it's remarkable at the diversity of areas that AI can have have

Brent Williams:

an impact, which is why it's so profound. And in some sense,

Brent Williams:

also a little scary.

Brent Williams:

the way that trust, I don't know, I don't know if it

Brent Williams:

mediates those two. Tell me what you've learned and how you think

Brent Williams:

that that's going to play out with AI?

Brent Williams:

Yeah, this is a really interesting question of trust.

Brent Williams:

Because historically, when we looked at information systems,

Brent Williams:

we programmed these systems, we could actually code them, we

Brent Williams:

said, so if we had a, we had to make a computer play chess, we'd

Brent Williams:

say, okay, this is the way the queen moves. This is the way the

Brent Williams:

bishop moves. These are the rules of chess, we put it into a

Brent Williams:

program, and then it will play chess. So the earlier AI systems

Brent Williams:

were actually programmed systems, they will rule based

Brent Williams:

systems. So there was AI in the 1970s. But it was usually

Brent Williams:

referred to as a snake oil of the 1970s and 80s. Because it

Brent Williams:

over promised and under delivered, you could only have

Brent Williams:

some gaming applications. So yes, you had medical diagnostic

Brent Williams:

systems, but they were based on rules, the rules were coded in.

Brent Williams:

So if a patient had temperature over 98.6, the patient had

Brent Williams:

fever, if their white blood cell was over a certain level they

Brent Williams:

had an infection, and it would, you'd kind of give it the

Brent Williams:

symptoms, and it will pull out the rules and come up with the

Brent Williams:

diagnosis. What's changed now is we have had the perfect storm of

Brent Williams:

processing power. With these GPUs, graphic processing units,

Brent Williams:

Navidia is the big player there, we have massive amounts of data,

Brent Williams:

and low cost of data storage. And we have with this process of

Brent Williams:

processing power and data, we can kind of look for patterns in

Brent Williams:

the data that are and, and identify these patterns and make

Brent Williams:

predictions based on these patterns. So the large language

Brent Williams:

models that we see of today, are really next word predictors, if

Brent Williams:

they although now, we can actually feed them videos and

Brent Williams:

images. So they're multimodal models. But the language models

Brent Williams:

are, really next word predictor, so they don't have any raw

Brent Williams:

intelligence of their own. But they're kind of looking for

Brent Williams:

these patterns in the data. And so while the old systems were

Brent Williams:

programmed, the newer systems are digging out these patterns,

Brent Williams:

almost like your neurological connections in the brain. It's

Brent Williams:

actually creating these connections. But we don't really

Brent Williams:

understand how they're creating these connections. It's almost

Brent Williams:

like asking a person, say, How did you come up with that

Brent Williams:

decision? Yeah, and what what neurons were connected in your

Brent Williams:

brain to come up with that decision. So we don't really

Brent Williams:

understand it. And so if we don't fully understand it, it's

Brent Williams:

like Warren Buffett says, Never invest in anything you don't

Brent Williams:

understand. So here, we are relying on the outputs. And we

Brent Williams:

don't really understand how the outputs came to into existence.

Brent Williams:

It's massive amounts of data, millions of parameters in the

Brent Williams:

model. And so without understanding it, why should we

Brent Williams:

trust it? And if we can't trust it, then why should we use it?

Brent Williams:

And so I think it's a fundamental question of

Brent Williams:

technology and value, which is my major stream, that we need to

Brent Williams:

be able to trust these systems. Because another way to think

Brent Williams:

about this is typically, if you look at scientific research, the

Brent Williams:

idea of actually looking at patterns from data was

Brent Williams:

considered voodoo science for many years.

Brent Williams:

Yeah

Varun Grover:

This induction you don't look for patterns.

Brent Williams:

Yeah

Varun Grover:

You come up with a theory or a statement and then

Varun Grover:

you go on to get data and test it.

Brent Williams:

Yeah, that's right.

Varun Grover:

But what are large language models doing? What is

Varun Grover:

Yeah. So it's just thinking exactly the same question.

Varun Grover:

AI doing? It is really creating and testing theory

Varun Grover:

simultaneously without any scientific underlay. So when I

Varun Grover:

think about this, I think, you know, I've always grown up

Varun Grover:

through my information systems career, thinking about data,

Varun Grover:

information and knowledge as a trichotomy. So you have data,

Varun Grover:

which are raw facts. And then you put the data together, and

Varun Grover:

you get information which informs you. So you get

Varun Grover:

interesting reports that reduce uncertainty or informs you. And

Varun Grover:

then when you apply it, and you use organize the information,

Varun Grover:

with experience, you get knowledge. What we've done with

Varun Grover:

AI, is we've removed the middle layer, we've gone data is

Varun Grover:

knowledge. And so we're basically taking massive amounts

Varun Grover:

of data about the world. And we are proclaiming that this is

Varun Grover:

actually creating knowledge. So we don't really need to

Varun Grover:

understand the world to know it. It's like we're just take, so

Varun Grover:

that layer has gone. So that's why this idea of trust is so

Varun Grover:

fundamental, because we don't really understand how these

Varun Grover:

connections are made. And so I I was thinking about, you know, as

Varun Grover:

you why do people trust other people?

Varun Grover:

And so so and do the others elements actually translate to

Brent Williams:

Well, that's what I was gonna ask you, you

Brent Williams:

AI. And I think people trust other people, because they may

Brent Williams:

have a connection with them, they actually relate to them,

Brent Williams:

they have empathy, or they relate at some subliminal level.

Brent Williams:

know, how do you see that changing and evolving? The one

Brent Williams:

So they say I trust you. People may trust people, because they

Brent Williams:

understand where they're coming from. So if they make a

Brent Williams:

decision, if you talk to someone, they make a decision,

Brent Williams:

that I could see that you just mentioned. Well, the model is

Brent Williams:

you can ask them. Okay, what's the basis of this decision? And

Brent Williams:

do I trust you to explain to me how you came up with this

Brent Williams:

decision. People trust people, because they are predictable,

Brent Williams:

getting more reliable, let's say less erratic. That one may

Brent Williams:

they are reliable, they may give accurate outputs. So if someone

Brent Williams:

is erratic, we probably won't trust them. But if someone is

Brent Williams:

more stable and predictable, and comes up with good, good

Brent Williams:

change, you know, but and you even mentioned the ability of,

Brent Williams:

outputs, we tend to trust them. And people trust people because

Brent Williams:

we might share the same social experiences. So I think these

Brent Williams:

elements of we trust people, because we can connect with them

Brent Williams:

or relate to them. We trust people because we can understand

Brent Williams:

of maybe I don't think you said it this way. I think you were

Brent Williams:

where they're coming from, we can ask them, we trust people

Brent Williams:

because they're reliable and not erratic. And we trust people,

Brent Williams:

because we have a shared social world, is generally why people

Brent Williams:

mentioning Pie, the the product you were working with, that it

Brent Williams:

trust people. These elements are not very prominent in AI. And

Brent Williams:

so, so I think that's why trust is a kind of an important issue.

Brent Williams:

Although they're changing.

Brent Williams:

had a feel of empathy, which might mean you could emotionally

Brent Williams:

connect to it more easily. So some of these things seem to be evolving,

Varun Grover:

I think so I think that from whatever little

Varun Grover:

observation I've had over the last year and a half, it's not

Varun Grover:

been that long since ChatGPT was removed, released. But this

Varun Grover:

idea, I can see improvement in empathy, I think that element is

Varun Grover:

there. So we are starting in on that trajectory in terms of

Varun Grover:

understandability, there is a whole field or subfield of AI.

Varun Grover:

That is called Explainable AI. How do you get take this neural

Varun Grover:

connections? And how do you actually convert it into a

Varun Grover:

language that humans can understand so they can explain

Varun Grover:

the rationale for their decisions? Now, it may not be

Varun Grover:

that important for radiology reports. But if we're dealing

Varun Grover:

with a business discipline, you know, often you want to

Varun Grover:

understand the rationale for the decision. So Explainable AI is

Varun Grover:

actually being worked on. And and it's important, and it's

Varun Grover:

it's particularly important because AI is all about data and

Varun Grover:

connections and patterns. AI is not particularly good at

Varun Grover:

reasoning. So if we tell an AI that Look, if they're looking at

Varun Grover:

a pattern, x is the parent of y, it will not naturally infer from

Varun Grover:

there or deduce from there, that y is the child of x. That

Varun Grover:

reasoning ability will only come about if it's in the corpus of

Varun Grover:

data. So the question then becomes, you know, how do you

Varun Grover:

get this reasoning out of the AI, and that's where a lot of

Varun Grover:

the research on Explainable AI is, give you another example. We

Varun Grover:

can put millions of chess games played by world chess champions

Varun Grover:

and feed it into the AI and it'll figure out the rules of

Varun Grover:

chess and what works and what doesn't work. So that it will

Varun Grover:

basically be a really good chess player. But if we change the

Varun Grover:

board from an eight by eight board to a nine by nine board,

Varun Grover:

then the training doesn't really help because it needs more than

Varun Grover:

that it needs some kind of reasoning ability to play chess

Varun Grover:

well on a nine by nine input. So I think that that idea of how do

Varun Grover:

you get that reasoning to come into you know, the box or the

Varun Grover:

corpus of intelligence of AI is is something that is being

Varun Grover:

worked on through Explainable AI. So empathy? Yes, we're

Varun Grover:

seeing improvement there. Explainable AI, we're not quite

Varun Grover:

there. But there's certainly a direction there. And like you

Varun Grover:

said, absolutely the corpus of training data. So most of the

Varun Grover:

models, we had an AI foundational models, like from

Varun Grover:

open AI. And from Google and Microsoft, these models are

Varun Grover:

trained on massive corpus of data from the internet, the

Varun Grover:

internet data is noisy. And it is, you know, it has a lot of a

Varun Grover:

lot of problems, which means it can be a pretty good general, it

Varun Grover:

can provide general advice on a lot of things. But if you're

Varun Grover:

looking for very specialized advice, sometimes these models

Varun Grover:

hallucinate and create these arbitrary outcomes, because

Varun Grover:

they're not fully trained in those specialized areas. So I

Varun Grover:

think one of the trends is how do you actually curate data for

Varun Grover:

training and make these models more accurate and better? And

Varun Grover:

how do you move away from the big tech companies which have

Varun Grover:

the resources to train these large foundational models, to

Varun Grover:

smaller models that are done through open source where you

Varun Grover:

can, individual companies may not have to invest millions of

Varun Grover:

dollars in training these models, but they can train them

Varun Grover:

on their own data,

Brent Williams:

Right.

Varun Grover:

And, and become, it can become more more

Varun Grover:

personalized and more accurate within that domain. So I think

Varun Grover:

that's the third component of trust, where these models are

Varun Grover:

being trained on better data. And sometimes even instead of

Varun Grover:

the large models, we're getting smaller and more specialized

Varun Grover:

models that are more accurate. And I think that's a trajectory

Varun Grover:

that will improve trust. And finally, in terms of context. So

Varun Grover:

I think that context is also improving, because the earlier

Varun Grover:

models had very little that you could put into the model in

Varun Grover:

terms of input. Now, some of the newer models, you can put entire

Varun Grover:

books and and say, you know, so your context window, the number

Varun Grover:

of tokens that go into the context is becoming larger and

Varun Grover:

larger, which means you can provide a richer context to your

Varun Grover:

decision making. And then you can have conversations to get

Varun Grover:

the alignment of get what you want from the AI. And so that

Varun Grover:

alignment can continue by probing and interacting with the

Varun Grover:

AI. So I think on the third aspect, the context aspect,

Varun Grover:

we're also seeing improvements. So I will trust the box, because

Varun Grover:

I can connect with it. I can trust the box, because I know

Varun Grover:

where it's coming from. It can explain its reasoning to me, I

Varun Grover:

can trust the box. Because it gives me good outputs, accurate

Varun Grover:

outputs, and I can trust the box because it's grounded in my

Varun Grover:

world. And so all those aspects are advancing. And so I think

Varun Grover:

that on the technological front, we are seeing a trajectory

Varun Grover:

that's positive for trust.

Brent Williams:

I'm gonna I'm gonna ask you about to human.

Brent Williams:

Maybe let's start in the business context, right. So

Brent Williams:

let's say the models are improving, they're becoming more

Brent Williams:

trustworthy. They're certainly becoming more commonplace.

Brent Williams:

They're still probably some of the like, there's the

Brent Williams:

excitement. There's some of those some people who think it's

Brent Williams:

scary. Probably each of us land somewhere on that continuum

Brent Williams:

differently. But in the business world, you know, the role of the

Brent Williams:

human in business, does it, change it slightly? Does it

Brent Williams:

change? Fundamentally? You have any thoughts to share on that?

Varun Grover:

Yeah I think that's, that's, that's a million

Varun Grover:

dollar question, or maybe a billion dollar question. or now

Varun Grover:

given, given the market of AI, maybe a trillion question.

Brent Williams:

If you can answer this, we can raise a lot

Brent Williams:

of money for the Walton College.

Varun Grover:

But I think I so, how should AI, so if if we are

Varun Grover:

using AI, to automate jobs, if we're using AI to, to automate

Varun Grover:

and replace jobs, so you can, you know, you can do an

Varun Grover:

accounting job better, or you can do a legal job better. Then

Varun Grover:

what is essentially happening is we are devaluing labor. We're

Varun Grover:

devaluing human skills and labor, because we're essentially

Varun Grover:

replacing labor with the technology. And that's going to

Varun Grover:

bring the cost of labor down. So substitution of jobs with

Varun Grover:

technology is probably not the most innovative direction, it's

Varun Grover:

probably appropriate. And probably the incentives for

Varun Grover:

corporations to make money are in the cost cutting sphere. So

Varun Grover:

we're certainly going to see a lot of that. But I think that

Varun Grover:

where we're going to see the human and, and the technology

Varun Grover:

work better is through augmentation. You never have

Varun Grover:

innovation through automation, you will only have innovation,

Varun Grover:

if there are ways in which the AI and the technology can work

Varun Grover:

together. So if you automate a lot, you're basically devaluing

Varun Grover:

the human if you augment you're up valuing the human, because

Varun Grover:

when you when you automate, your competition is between the AI

Varun Grover:

and the human, when you augment your competition is between the

Varun Grover:

human with the AI, and the human without the AI.

Brent Williams:

Right.

Varun Grover:

And so you're upskilling. So I think that we

Varun Grover:

are at a point of inflection, where we are making 1000s of

Varun Grover:

decisions regarding AI. And it's really important that if

Varun Grover:

corporations are going to invest in AI, they should consciously

Varun Grover:

think about how to augment human skills through AI, rather than

Varun Grover:

only automation. Because automation will probably give

Varun Grover:

you the short term bang for the buck in terms of reduction in

Varun Grover:

costs. But the longer term impact on innovation will only

Varun Grover:

take place if you give people the discretion to leverage AI

Varun Grover:

and become and use it innovatively. So if there's

Varun Grover:

there's a series of tasks in your job, and there's a few that

Varun Grover:

can be automated, that's fine. But then think about what are

Varun Grover:

the tasks in your jobs that can be augmented. That's where the

Varun Grover:

innovation comes in. And that's where the value is created.

Brent Williams:

Well, Varun, thank you. Thank you for sharing

Brent Williams:

your knowledge and that knowledge that comes from

Brent Williams:

decades of work and research and I know I learned a lot and I'm

Brent Williams:

sure our audience did as well. So thank you for joining me

Brent Williams:

today.

Varun Grover:

Thank you, Brent for having me.

Brent Williams:

On behalf of the Walton College thank you for

Brent Williams:

joining us for this captivating conversation. To stay connected

Brent Williams:

and never miss an episode, simply search for Be Epic on

Brent Williams:

your preferred podcast service.

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About the Podcast

Be EPIC Podcast
Welcome to the Be Epic Podcast featuring Brent Williams, interim dean of the Sam M. Walton College of Business at the University of Arkansas. In each episode, you will hear from guests that will inspire you to be epic. As experts in their field, they will emphasize strategy, leadership, and entrepreneurship. This programming will highlight innovation and cutting-edge information that will leave you wanting more. Be sure to connect with Brent Williams on LinkedIn to join the conversation, access show notes and discover fantastic bonus content.