S7E8: Human in the Middle: AI Insights feat. Jessica Ellett

We continue our series of conversations about Artificial
Intelligence and how it's changing the world around us. Today’s
episode focuses on the use of AI in the financial sector and both
it’s potential strengths and weaknesses.





Joining the show to help us start making sense of it all is
Jessica Ellett. Jessica is a senior manager and lead modeler at
Cambridge Technology, a financial services technology startup.
Jessica is also an MSBA graduate from the David Eccles School of
Business.





Jessica shares her insights on developing AI-operationalized
applications for large banks, highlighting tools like loan
processing applications, financial report generation, and
predictive trade outcome models. Frances and Jessica cover the
concept of 'human in the middle' AI and the importance of human
involvement in AI processes. Jessica also touches on concerns
around AI bias, data privacy, and the critical need for
business-led AI projects. Jessica also looks forward to what she
predicts the landscape of her industry could look like in five
years. 





Eccles Business Buzz is a production of the David Eccles School
of Business and is produced by University fm.



Show Links:

Jessica Ellett | LinkedIn

CTFSI - Cambridge Technology Financial Services Inc.

Master of Science in Business Analytics - The David Eccles
School of Business

David Eccles School of Business (@ubusiness) • Instagram

Eccles Alumni Network (@ecclesalumni) • Instagram 

Eccles Experience Magazine




Episode Quotes:




How the MSBA programme equipped Jessica to be a voice in
the AI space





[37:02]: When I first finished in 2018 with the MSBA program, I
got multiple job offers afterwards when we moved here to
Charlotte, North Carolina. And, often, it was kind of an
undefined structure. Hey, what can you help us do? What can you
help us know or ask? Help us do this in a better way, or help us
ask the right questions. And so I think it's still young enough—I
mean, the whole program, data science programs, MSBA
programs—within the last 10 years, I would consider that a really
young program. And so new talent coming out of those are going to
be the thought leaders on how AI gets adopted and how these
programs run at different companies. And think about that. So you
come out of this program and you think, "Well, I don't know much.
I just got this degree, or I don't have a lot of application."
But people are willing to listen to you because you've had
focused study on this topic more than they have, so for better or
for worse, you're going to be a voice in that space.





How AI works best with people by having the human in the
middle





[07:24]: Think of AI as the best assistant you've ever had, but
you need the right systems or processes in place to interact with
that assistant to get the most out of them, right? So, it's not
just building or designing the perfect assistant. It's when am I
going to use them? How am I going to use the output? How do I
give it the right information to get out of it? What I want—all
that interaction. That's human in the middle. You have to design
that well to get the most out of it.





Why do AI projects need to align with business
goals?





[41:18]: I'd say AI projects need to align with the business
goals, not just tech advancements. You have a shiny new tool, and
you want to use it but don't lose sight of what the business goal
is. Using a shiny new tool could be expensive. If you suddenly
have to build the whole machine that it fits with, that could get
expensive. So, I'd say that transformation has to have a
business-led approach because it has to align with the business
goals. And if none of the business goals are ready or positioned
to need AI—which is hard to believe—but it could be possible,
then it doesn't fit in the plan or the goals.