Technology Vision 2018 for Pega: Citizen AI

Technology Vision 2018 for Pega: Citizen AI


David Steuer (Accenture): Don, thanks for
joining me today. Don Schuerman (Pega): Of course. Accenture: We’re going to talk a little
bit about the Accenture Tech Vision and five themes that
we have within the Tech Vision. Pega: Excited to talk about this. At Pega we spend a
lot of time thinking about how technology can impact
both how our clients and our joint clients engage their
customers and how they can drive better efficiency in
their operations. So let’s dig in. Accenture: Fantastic, fantastic. So the first trend
is what we call Citizen AI, or the idea of raising AI
to benefit the business and benefit society. And
you know, there’s a lot of positive as well as some
negative press around AI. Pega: Yep. Accenture: You hear about sometimes bots getting
out of control, you know, we’ve all seen some
examples around that, at the same time, we’ve seen
examples of how AI can help individuals and help citizens
and help organizations to do better. And what we see around
citizen AI is the way the role that the bot is going to
play within society. And I know that Pega has an AIenabled
Customer Decision Hub. Pega: Yep
Accenture: And maybe you can talk a little bit about
some of the features that will enable more responsible AI. Pega: Yeah, you know, I think one of the big
ways to think about AI and one of the ways we think
about AI is, how do you make it as a partner to the
humans that are responsible for driving your business,
responsible for engaging your customers? Whether that’s being
able to guide them to the next best action to take with
a conversation with a customer, whether that’s being
able to automate a piece of work so they can focus
on other things. And one of the first keys to be able
to do that is the AI needs to be trustable, it needs to
be transparent. So if you think about a lot of the AI
technologies, especially some of the more emerging
ones, things like deep learning. Accenture: Yeah
Pega: Right, a lot of that AI has a degree of
opaqueness to it, there’s so much data feeding into
it that the AI engine that Google’s using to do facial
recognition, for example, would have a very hard time
explaining how it recognizes faces to you. Much of
the same way that we would have a really hard time
explaining how do we recognize a face when we see it. Accenture: Sure, yeah. Pega: Which is great, if you’re trying to
identify pictures of your friends on Facebook, it’s
probably not great if you’re trying to approve somebody
for a loan. Accenture: Sure, yeah. Pega: Right? And so leveraging AI in a way that is
transparent when it needs to be, and leveraging the pieces of AI technology of which there
are lots, predictive and certain machine learning models,
that can actually be very transparent, and allow you
to do things like ensure that there’s no bias baked
into the algorithm, allow you to show the algorithm
back out the customer that it’s helping or employee
that it’s helping so they can understand and trust it. And so we’ve invested in what we call a
T-switch or a transparency switch into the product, so the
business people have a control over how transparent
they need the AI to be, based on the risk level of the
decision they’re trying to make. Accenture: Fantastic, so what it does is basically
it’ll use, based upon whether you flip that switch for
transparent or opaque, it may use different algorithms. Pega: It’ll use different algorithms and
it will allow for the, if you make it transparent, we won’t
use things like neuro-networks that aren’t really
good at explaining how they made a decision. Whereas
if you got a decision that’s lower-risk, perhaps what
advertising treatment you throw for a client, those
algorithms are perfectly fine. On the bot side, we’ve
spend a lot of time and see probably the most benefit
when bots are deployed next to humans, not away
from humans. If I deploy a bot to help a contact center
agent get signed into all their systems, or wrap up a
call, or help somebody who’s doing research on claims
pull together all the data they need to answer that
claim, our experience is one, you get better adoption,
because you’re actually demonstrating to the
employee on making your job easier and helping you
be more effective. It’s faster to deploy because they
don’t have to capture all the edge cases and exception
cases that happen when I deploy standalone bots and
the ROI is instantly visible. So these kinds of bots that
actually assist human beings, we often call it tended
robotics, is where we’ve see a still very untapped
potential value and operational improvement for the
enterprise. Accenture: Yeah, that sort of environment
creates almost a win-win-win, right. Because the employees
are happy because its helping them to do their job
better, its helping the customer, it’s helping the
organization as a whole. So it’s a human plus bot, not a
human – bot. Pega: Yeah, I’ve seen rooms of contact center
employees stand up and cheer when bots have been
introduced because it’s making their lives better, its
reducing cost from the organization, and is allowing
them to focus on the customer which improves engagement.

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