June 15, 2021 • 18 mins
Afua Bruce's career in data science and technology is dotted with a bunch of impressive acronyms: IBM, the FBI (!), even working for the POTUS (Obama) as Executive Director of the National Science and Technology Council. Now, she's taken on a new challenge as Chief Program Officer for Datakind, a global non-profit that harnesses the power of data science and AI in the service of humanity. Heck, she even has her own statue as part of the #IfThenSheCan women in STEM initiative (https://ifthenshecan.org). Tune in to hear an amazing story of a truly unique life path.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:06):
This is on the Job, a podcast about finding your
life's work on the job, is brought to you by
Express Employment Professionals. This season, we're bringing you stories of
folks following their passion to carve their own career path.
In a digital age, software engineers and data scientists are
the unsung heroes that make all of our convenient technology possible,
(00:27):
and while they dedicate their careers to making all of
our lives easier, they often go unnoticed. Well, today we
talked to a standout techie whose love for science took
her from jobs and computing to government agencies to working
with nonprofits on the front lines of the pandemic today.
As someone who immediately thinks that rumbas and Siri will
(00:48):
take over the world at some point, he was pretty
reassuring to hear that our interviewee today is not un
teamed rob apocalypse. Absolutely. My goal is certainly to leverage
data science and AI in service of humanity. This is
a Fua, so Fua Bruce. I am the chief program
officer at Data Kind and I'm based just outside of
(01:09):
the DC area. A fua is a wildly talented software
engineer with a pretty fascinating work history. She's currently in
a more managerial role at data Kind, a nonprofit organization
that connects other organizations in the social sector with technology
and scientists that can help them do their jobs more efficiently.
So Data Kind has been partnering with a couple of
(01:31):
different organizations and a couple of different African countries on
frontline health systems. Frontline health systems basically, you know when
you go to the doctor and you've got to fill
out tons and tons of information every time, explaining your
medical history or past doctors you've seen, Well, that process
really bogs down frontline health workers. At least over fifty
(01:51):
percent of a frontline health workers time is spent accessing
in updating patient records instead of caring for patients. And
so if you can look how do we improve the
data integrity of these systems, you can then let frontline
health workers do the things they want to do, which
is to care for patients and the things they're most
trained for. Right So, this is why a lot of
(02:12):
Data Kainan's work has been in I mean, your job
essentially right now is to make other people's jobs easier. Yeah,
you could sum it up that way. That's the goal
right now. Her projects are in a few African countries
and in India. Basically, she's making the records that doctors
(02:34):
and nurses and volunteers need more accessible. The fact that
frontline workers spend over fifty percent of their time on
this stuff was really surprising to me. I gotta believe
that it's not what a lot of doctors are thinking
about when they make the huge commitment to go to
medical school. I would say it's probably not high on
the priority list. Really making sure you understand how to
(02:55):
fill out different technical systems, how you enter data and systems,
and how track that data. I think people often go
to medical school to be able to practice medicine. These
projects are only a couple of years old, so she's
getting to see them work in the field for the
first time right now, but already organizations that use their
data systems and software have seen it drastically shave off
(03:17):
the time workers are spending looking through those records, so
you can take people who are doing that apply them
to other things that need to be done instead. It
also means that people who are looking at that data
to make decisions about what type of care is best,
what type of care should we recommend here, What are
trends that we're seeing here, What should we be changing
(03:38):
and how should we be reacting based on accurate data
of what actually happened. So in the way that the
best technology knows what you need and provides it for you,
maybe even before you know you need it. Data kind
systems are meant to be fluid, intelligent tools that substantially
cut down on the menial tasks that frontline workers are
(03:59):
currently with. And so this means that people can go
back to providing care to the people who need care
rather than looking at the streams of data that are
that's coming in. A fool plays it cool, but her
work has massive implications that are directly aimed at how
(04:21):
our health system works all over the world. It's huge.
But to back up, it all started off when she
was a young kid who just like numbers. Growing out,
my favorite subject was always math. I always really loved computers,
love playing games and computers. I love video games. Remember
my dad buying me remote control cars and figuring out
(04:42):
those were a lot of fun. She moved around a
lot as a kid. She lived in about nine states.
She was into dance and tennis, but even at a
young age, she was really into volunteering and did a
lot of social work, and now makes sense to be
on this side of it that I would find myself
in a career that let's you figure out how to
use technology to support communities. Who was a first generation American.
(05:06):
Both her parents are from Ghana, and the mentality in
her household growing up instill the importance of helping out
early on. Just I think the focus on community and
the focus on the people around you and really making
sure that you're teaming care of not just yourself, which
is important, but also you're meeting needs that you can
where possible. She went out to study computer engineering at
(05:27):
Purdue in Indiana, and while she was there, she started
working for IBM as a student. IBM hired her full
time as a software engineer right out of school, and
she loved it. I really liked being an engineer. I
really liked toting. I really liked the different the software
that we were building work on some of the IBM's
LURCH servers. I enjoyed IBM's culture. I really enjoyed the work.
(05:53):
Already having an impressive start to her career, she actually
decided to take a leave of absence from IBM going
back to school at University of Michigan for an MBA,
and she fully planned on going back to IBM with
her newly acquired business degree, but while she was on campus,
she got recruited as a special advisor for the FBI. Yeah,
(06:16):
and so I made an unexpected to everyone shift from
IBM to the FBI. And that was really the start
for myself of really seeing how my text goals could
really think more focused in the public interest, working in
government and working in the nonprofit sector. So when people
(06:37):
asked you what you did at that point and you said,
I worked for the FBI, it absolutely felt great to
say that I worked for the FBI. I really, I
really did really cool to say. It was definitely cool
to just say my name as a Foo Bruce and
I'm here representing the FBI. She worked a lot of
strategy and program management positions there the Science and Technology branch,
(07:01):
and she got to work on a lot of the
tech that the FBI uses. Really got to see how
tech support, what agents do? What do you mean like
Q James Bond kind of stuff. Yes, in facts, my
boss at the time would describe the division as Q.
That's where all the fun, toys were built and tested,
and so it's really it's really cool. Did you get to,
(07:23):
like work on stuff that you can't talk about? I
think inherently part of what the FBI does things that
you can't talk about. However, she did get to see
some of the stuff she was working on get notoriety
in upper management and even on the news, things like
her work on forensics technology, improving fingerprint tech and systems
(07:44):
for gun background checks. It was certainly easy to feel
a part of something bigger when you know that a
lot of the work that you do really matters. It
was important to keep Americans safe, it was important to
keep community safe. It was important to keep and I
say that it was important to keep children safe just
goes to show you we can be a cool government
(08:05):
crime fighter even if you don't carry a badge and
a gun. People used to ask a food if she
carried one all the time. And I always quote one
of my good colleagues in a fellow special advisor. He
used to say that our weapons will excel in PowerPoint.
So well, the job does sound very exciting. Sometimes it
really does boil down to simple tools into a simple
(08:28):
understanding and really figuring out how you can leverage your
skill set to really help move a mission forward. That's
exactly what an undercover agent would say. We'll get back
to our story in a second. Navigating the professional job
(08:50):
search is hard. You know the perfect job is out there,
you're just not sure how to find it. The good
news is you don't have to go it alone. You
need the Specialized Recruiting Group. We're here to guide you
and help you find a job that fits all without
costing a dime. We're the Specialized Recruiting Group and Express
Employment Professionals Company. Go to SRG express dot com for
(09:12):
free support and get on the right course. Now back
to on the job of who was next stop. She
got put on a two year assignment at the White
House in twenty fifteen. Under Obama, she served as the
executive director of the White House's National Science and Technology Council,
(09:34):
basically overseeing a massive think tank with tons of committees
and experts that convene and come up with plans for
how we as a country can use science and tech
to our benefit. There are a lot of experts throughout
the federal govermm who have spent a lot of time
and energy educating and being educated on and getting smart
(09:54):
on and working on both policy and technology development on
a lot of different areas, and so be able to
just create an environment where you can convene true expertise
and then produce something that can really guide future investments
in future work is is pretty awesome. At this point,
she really wanted to get back to working with on
the ground technical projects, which is how she found herself
(10:16):
at Data Kind where she is now. It really allows
me the opportunity to combine my data knowledge, my technology knowledge,
and really passion for working directly with communities and working
directly with nonprofits. So now she's back to what she
started off wanting to do, using data science to make
people's lives easier, which is something we all use every
(10:39):
day and speaking personally, take for granted, you can yell
at Siri to order you a pizza, and thirty minutes
later you get a pizza. Software engineers make that happen.
I appreciate data science sometimes for being able to log
in to whatever shopping platform I'm using at the time
and being suggested items that just happened to be what
(11:02):
I want to see and what I want to Where
customizis options presented to me and my life made easier
by data science that's run in the background. Yeah, I
mean I love that too, and yeah, yeah, the technology
is I don't even I don't get how it works.
It's it's like magic. It's crazy how advanced it is.
And then for that kind of tech to exist and
(11:26):
for you to be working on a project at Data Kind,
like making record systems more accessible for frontline workers, yeah,
like that's kind of crazy, right, Yeah. Yeah. One of
the Data Kind co founders used to say, I'm actually
not sure if it's his quote up to I forgot
it from someone else, but he used to say, the
future is here, it's just not evenly distributed, which is
(11:51):
something that really resonates for me, because you know, so
many times we have these technology systems to your point,
just we don't even question them anymore, we don't even
think about them. But in some sectors it just hasn't
been adopted yet. Technology often mirrors what our priorities are
(12:14):
as a society. They can be inspiring and also pretty
upsetting at the same time, Like back in the nineteen
sixty nine we put humans on the Moon and at
the same time back on Earth, cities all over the
country didn't have clean water systems or roads that work
and still don't today. I can yell at Syria to
get me a pizza in thirty minutes, and a frontline
(12:35):
worker during COVID might have to spend hours and hours
on the phone tracking down a patient's medical history so
that they know what they can or can't safely treat
them with. You know, I joined data kind because social
sector organizations who are out there saving lives, trying to
give people access to healthcare, give people access to housing,
give people access to food, don't always have the time
(12:57):
to invest in data systems or technology systems, and so
ways that data kind can really partner with those organizations
to help them do your mission more effectively incredibly important work.
A fool joined data kind right before the pandemic hit,
and she was hearing from organizations that were using data
kind systems about how much they helped with the crisis.
(13:19):
Organizations like Plentiful, an app that makes it easier for
individuals and families to get food from food pantries, and
so hearing that kind of feedback from an organization like
Plentiful or other organizations you know that will say the
work you did helps us save you know, the time
our drivers are out by fifteen percent or something like that,
and really refocus their efforts on again actually huting on
(13:42):
their mission, which is why people who joined nonprofits join
on profits. Is just really that's just really great to
hear again a foo is demeanor. I feel like it
doesn't match the gravity of the work that she's done,
but that's because she's really humble. From IBM to the FBI,
(14:04):
to the White House to her work with data kind
that could have massive implications around the world. The work
that she's doing and has done is monumental and it's
not flying under the radar. In twenty nineteen, she was
asked to be an ambassador for the if then Initiative,
the tagline being if we support a woman in STEM,
then she can change the world. About one hundred and
(14:27):
twenty women were selected from all different science, technology, engineering,
math professions and the goal of the if then initiative
is to highlight women in STEM so that girls get
excited about pursuing STEM career someday. One of the things
that the if then initiative did was take three D
(14:47):
scans of all the ambassadors and a week before our interview,
a FUA flew down to Dallas, Texas to see an exhibit.
They put up a grassy field filled with bright orange statues.
There are about one hundred and twenty to life size
statues of women in stem, one of them being me.
You have a statue. I do have a statue. Really
(15:10):
flattering and really humbling and really exciting. How did that
feel seeing a statue of yourself? Yeah, it was. It
was surreal walking around the statue exhibit looking for myself
and then just you know, seeing a life size me
(15:31):
holding my laptop by my side was pretty incredible. I
had the opportunity to see it for the first time
with my family, you know, watching my sisters take us
selfie with my statue also really surreal. Talking with the FUA,
(15:54):
you probably wouldn't guess this is a person who has
a statue made of her, not because she shouldn't, but
because we often dedicate statues to people who are the
face of a cause or at the front of a
historic event. And when we make statues of people, it's
because we want them to be idolized. They are figures
we choose to literally look up to. It makes me
(16:18):
pretty happy that as a society, we're choosing more and
more to look up to people like Afua, Smart, humble
people working intelligently and diligently every day to make all
of our lives easier. People whose weapons are Excel and PowerPoint.
It must have felt so cool to be recognized in
that way with a bunch of other people who are
(16:40):
behind the scenes, in a way that most people would
never know about them if they weren't orange statues in Dallas, Texas. Right.
I can't honestly say that I never imagine saying myself
as a statue. Having an opportunity to be recognized certain
selfishly makes me feel great. But again, I'm really hoping that,
(17:04):
you know, someone will read the description of what I do.
I'm a little plaque that's there next to my statue
and think, oh, I could also think of ways to
use science and technology to strengthen communities. That's great for
this person who's a statue, but it's something I could
do too. For On the Job, I'm Otis Gray. Thanks
(17:40):
for listening to On the Job, brought to you by
Express Employment Professionals. This season of On the Job is
produced by Audiation. The episodes were written and produced by
me Otis Gray. Our executive producer is Sandy Smallens. The
show is mixed by Matt Noble for Audiation studios at
The Loft and Bronxville, New York. Music by Blue Dot Sessions.
(18:01):
Find us on iHeartRadio and Apple Podcasts. If you liked
what you heard, please consider rating and reviewing the show
on Apple Podcasts or wherever you listen. We'll see you
next time. For more inspiring stories about discovering your life's work,
Audiation
This is on the Job, a podcast about finding your
life's work on the job, is brought to you by
Express Employment Professionals. This season, we're bringing you stories of
folks following their passion to carve their own career path.
In a digital age, software engineers and data scientists are
the unsung heroes that make all of our convenient technology possible,
(00:27):
and while they dedicate their careers to making all of
our lives easier, they often go unnoticed. Well, today we
talked to a standout techie whose love for science took
her from jobs and computing to government agencies to working
with nonprofits on the front lines of the pandemic today.
As someone who immediately thinks that rumbas and Siri will
(00:48):
take over the world at some point, he was pretty
reassuring to hear that our interviewee today is not un
teamed rob apocalypse. Absolutely. My goal is certainly to leverage
data science and AI in service of humanity. This is
a Fua, so Fua Bruce. I am the chief program
officer at Data Kind and I'm based just outside of
(01:09):
the DC area. A fua is a wildly talented software
engineer with a pretty fascinating work history. She's currently in
a more managerial role at data Kind, a nonprofit organization
that connects other organizations in the social sector with technology
and scientists that can help them do their jobs more efficiently.
So Data Kind has been partnering with a couple of
(01:31):
different organizations and a couple of different African countries on
frontline health systems. Frontline health systems basically, you know when
you go to the doctor and you've got to fill
out tons and tons of information every time, explaining your
medical history or past doctors you've seen, Well, that process
really bogs down frontline health workers. At least over fifty
(01:51):
percent of a frontline health workers time is spent accessing
in updating patient records instead of caring for patients. And
so if you can look how do we improve the
data integrity of these systems, you can then let frontline
health workers do the things they want to do, which
is to care for patients and the things they're most
trained for. Right So, this is why a lot of
(02:12):
Data Kainan's work has been in I mean, your job
essentially right now is to make other people's jobs easier. Yeah,
you could sum it up that way. That's the goal
right now. Her projects are in a few African countries
and in India. Basically, she's making the records that doctors
(02:34):
and nurses and volunteers need more accessible. The fact that
frontline workers spend over fifty percent of their time on
this stuff was really surprising to me. I gotta believe
that it's not what a lot of doctors are thinking
about when they make the huge commitment to go to
medical school. I would say it's probably not high on
the priority list. Really making sure you understand how to
(02:55):
fill out different technical systems, how you enter data and systems,
and how track that data. I think people often go
to medical school to be able to practice medicine. These
projects are only a couple of years old, so she's
getting to see them work in the field for the
first time right now, but already organizations that use their
data systems and software have seen it drastically shave off
(03:17):
the time workers are spending looking through those records, so
you can take people who are doing that apply them
to other things that need to be done instead. It
also means that people who are looking at that data
to make decisions about what type of care is best,
what type of care should we recommend here, What are
trends that we're seeing here, What should we be changing
(03:38):
and how should we be reacting based on accurate data
of what actually happened. So in the way that the
best technology knows what you need and provides it for you,
maybe even before you know you need it. Data kind
systems are meant to be fluid, intelligent tools that substantially
cut down on the menial tasks that frontline workers are
(03:59):
currently with. And so this means that people can go
back to providing care to the people who need care
rather than looking at the streams of data that are
that's coming in. A fool plays it cool, but her
work has massive implications that are directly aimed at how
(04:21):
our health system works all over the world. It's huge.
But to back up, it all started off when she
was a young kid who just like numbers. Growing out,
my favorite subject was always math. I always really loved computers,
love playing games and computers. I love video games. Remember
my dad buying me remote control cars and figuring out
(04:42):
those were a lot of fun. She moved around a
lot as a kid. She lived in about nine states.
She was into dance and tennis, but even at a
young age, she was really into volunteering and did a
lot of social work, and now makes sense to be
on this side of it that I would find myself
in a career that let's you figure out how to
use technology to support communities. Who was a first generation American.
(05:06):
Both her parents are from Ghana, and the mentality in
her household growing up instill the importance of helping out
early on. Just I think the focus on community and
the focus on the people around you and really making
sure that you're teaming care of not just yourself, which
is important, but also you're meeting needs that you can
where possible. She went out to study computer engineering at
(05:27):
Purdue in Indiana, and while she was there, she started
working for IBM as a student. IBM hired her full
time as a software engineer right out of school, and
she loved it. I really liked being an engineer. I
really liked toting. I really liked the different the software
that we were building work on some of the IBM's
LURCH servers. I enjoyed IBM's culture. I really enjoyed the work.
(05:53):
Already having an impressive start to her career, she actually
decided to take a leave of absence from IBM going
back to school at University of Michigan for an MBA,
and she fully planned on going back to IBM with
her newly acquired business degree, but while she was on campus,
she got recruited as a special advisor for the FBI. Yeah,
(06:16):
and so I made an unexpected to everyone shift from
IBM to the FBI. And that was really the start
for myself of really seeing how my text goals could
really think more focused in the public interest, working in
government and working in the nonprofit sector. So when people
(06:37):
asked you what you did at that point and you said,
I worked for the FBI, it absolutely felt great to
say that I worked for the FBI. I really, I
really did really cool to say. It was definitely cool
to just say my name as a Foo Bruce and
I'm here representing the FBI. She worked a lot of
strategy and program management positions there the Science and Technology branch,
(07:01):
and she got to work on a lot of the
tech that the FBI uses. Really got to see how
tech support, what agents do? What do you mean like
Q James Bond kind of stuff. Yes, in facts, my
boss at the time would describe the division as Q.
That's where all the fun, toys were built and tested,
and so it's really it's really cool. Did you get to,
(07:23):
like work on stuff that you can't talk about? I
think inherently part of what the FBI does things that
you can't talk about. However, she did get to see
some of the stuff she was working on get notoriety
in upper management and even on the news, things like
her work on forensics technology, improving fingerprint tech and systems
(07:44):
for gun background checks. It was certainly easy to feel
a part of something bigger when you know that a
lot of the work that you do really matters. It
was important to keep Americans safe, it was important to
keep community safe. It was important to keep and I
say that it was important to keep children safe just
goes to show you we can be a cool government
(08:05):
crime fighter even if you don't carry a badge and
a gun. People used to ask a food if she
carried one all the time. And I always quote one
of my good colleagues in a fellow special advisor. He
used to say that our weapons will excel in PowerPoint.
So well, the job does sound very exciting. Sometimes it
really does boil down to simple tools into a simple
(08:28):
understanding and really figuring out how you can leverage your
skill set to really help move a mission forward. That's
exactly what an undercover agent would say. We'll get back
to our story in a second. Navigating the professional job
(08:50):
search is hard. You know the perfect job is out there,
you're just not sure how to find it. The good
news is you don't have to go it alone. You
need the Specialized Recruiting Group. We're here to guide you
and help you find a job that fits all without
costing a dime. We're the Specialized Recruiting Group and Express
Employment Professionals Company. Go to SRG express dot com for
(09:12):
free support and get on the right course. Now back
to on the job of who was next stop. She
got put on a two year assignment at the White
House in twenty fifteen. Under Obama, she served as the
executive director of the White House's National Science and Technology Council,
(09:34):
basically overseeing a massive think tank with tons of committees
and experts that convene and come up with plans for
how we as a country can use science and tech
to our benefit. There are a lot of experts throughout
the federal govermm who have spent a lot of time
and energy educating and being educated on and getting smart
(09:54):
on and working on both policy and technology development on
a lot of different areas, and so be able to
just create an environment where you can convene true expertise
and then produce something that can really guide future investments
in future work is is pretty awesome. At this point,
she really wanted to get back to working with on
the ground technical projects, which is how she found herself
(10:16):
at Data Kind where she is now. It really allows
me the opportunity to combine my data knowledge, my technology knowledge,
and really passion for working directly with communities and working
directly with nonprofits. So now she's back to what she
started off wanting to do, using data science to make
people's lives easier, which is something we all use every
(10:39):
day and speaking personally, take for granted, you can yell
at Siri to order you a pizza, and thirty minutes
later you get a pizza. Software engineers make that happen.
I appreciate data science sometimes for being able to log
in to whatever shopping platform I'm using at the time
and being suggested items that just happened to be what
(11:02):
I want to see and what I want to Where
customizis options presented to me and my life made easier
by data science that's run in the background. Yeah, I
mean I love that too, and yeah, yeah, the technology
is I don't even I don't get how it works.
It's it's like magic. It's crazy how advanced it is.
And then for that kind of tech to exist and
(11:26):
for you to be working on a project at Data Kind,
like making record systems more accessible for frontline workers, yeah,
like that's kind of crazy, right, Yeah. Yeah. One of
the Data Kind co founders used to say, I'm actually
not sure if it's his quote up to I forgot
it from someone else, but he used to say, the
future is here, it's just not evenly distributed, which is
(11:51):
something that really resonates for me, because you know, so
many times we have these technology systems to your point,
just we don't even question them anymore, we don't even
think about them. But in some sectors it just hasn't
been adopted yet. Technology often mirrors what our priorities are
(12:14):
as a society. They can be inspiring and also pretty
upsetting at the same time, Like back in the nineteen
sixty nine we put humans on the Moon and at
the same time back on Earth, cities all over the
country didn't have clean water systems or roads that work
and still don't today. I can yell at Syria to
get me a pizza in thirty minutes, and a frontline
(12:35):
worker during COVID might have to spend hours and hours
on the phone tracking down a patient's medical history so
that they know what they can or can't safely treat
them with. You know, I joined data kind because social
sector organizations who are out there saving lives, trying to
give people access to healthcare, give people access to housing,
give people access to food, don't always have the time
(12:57):
to invest in data systems or technology systems, and so
ways that data kind can really partner with those organizations
to help them do your mission more effectively incredibly important work.
A fool joined data kind right before the pandemic hit,
and she was hearing from organizations that were using data
kind systems about how much they helped with the crisis.
(13:19):
Organizations like Plentiful, an app that makes it easier for
individuals and families to get food from food pantries, and
so hearing that kind of feedback from an organization like
Plentiful or other organizations you know that will say the
work you did helps us save you know, the time
our drivers are out by fifteen percent or something like that,
and really refocus their efforts on again actually huting on
(13:42):
their mission, which is why people who joined nonprofits join
on profits. Is just really that's just really great to
hear again a foo is demeanor. I feel like it
doesn't match the gravity of the work that she's done,
but that's because she's really humble. From IBM to the FBI,
(14:04):
to the White House to her work with data kind
that could have massive implications around the world. The work
that she's doing and has done is monumental and it's
not flying under the radar. In twenty nineteen, she was
asked to be an ambassador for the if then Initiative,
the tagline being if we support a woman in STEM,
then she can change the world. About one hundred and
(14:27):
twenty women were selected from all different science, technology, engineering,
math professions and the goal of the if then initiative
is to highlight women in STEM so that girls get
excited about pursuing STEM career someday. One of the things
that the if then initiative did was take three D
(14:47):
scans of all the ambassadors and a week before our interview,
a FUA flew down to Dallas, Texas to see an exhibit.
They put up a grassy field filled with bright orange statues.
There are about one hundred and twenty to life size
statues of women in stem, one of them being me.
You have a statue. I do have a statue. Really
(15:10):
flattering and really humbling and really exciting. How did that
feel seeing a statue of yourself? Yeah, it was. It
was surreal walking around the statue exhibit looking for myself
and then just you know, seeing a life size me
(15:31):
holding my laptop by my side was pretty incredible. I
had the opportunity to see it for the first time
with my family, you know, watching my sisters take us
selfie with my statue also really surreal. Talking with the FUA,
(15:54):
you probably wouldn't guess this is a person who has
a statue made of her, not because she shouldn't, but
because we often dedicate statues to people who are the
face of a cause or at the front of a
historic event. And when we make statues of people, it's
because we want them to be idolized. They are figures
we choose to literally look up to. It makes me
(16:18):
pretty happy that as a society, we're choosing more and
more to look up to people like Afua, Smart, humble
people working intelligently and diligently every day to make all
of our lives easier. People whose weapons are Excel and PowerPoint.
It must have felt so cool to be recognized in
that way with a bunch of other people who are
(16:40):
behind the scenes, in a way that most people would
never know about them if they weren't orange statues in Dallas, Texas. Right.
I can't honestly say that I never imagine saying myself
as a statue. Having an opportunity to be recognized certain
selfishly makes me feel great. But again, I'm really hoping that,
(17:04):
you know, someone will read the description of what I do.
I'm a little plaque that's there next to my statue
and think, oh, I could also think of ways to
use science and technology to strengthen communities. That's great for
this person who's a statue, but it's something I could
do too. For On the Job, I'm Otis Gray. Thanks
(17:40):
for listening to On the Job, brought to you by
Express Employment Professionals. This season of On the Job is
produced by Audiation. The episodes were written and produced by
me Otis Gray. Our executive producer is Sandy Smallens. The
show is mixed by Matt Noble for Audiation studios at
The Loft and Bronxville, New York. Music by Blue Dot Sessions.
(18:01):
Find us on iHeartRadio and Apple Podcasts. If you liked
what you heard, please consider rating and reviewing the show
on Apple Podcasts or wherever you listen. We'll see you
next time. For more inspiring stories about discovering your life's work,
Audiation
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