Speaker 1: Hello everyone, and welcome to Talk Nerdy. Today is Monday,
June eighth, twenty twenty sixth, and I'm the host of
the show, Doctor Kara Santa Maria, And as always, before
we dive into this week's episode, I want to thank
those of you who make Talk Nerdy possible. Remember, this
show is and will always be one hundred percent free
to download as long as I can keep it on
the air. We're in our six hundred fifth episode, Wow,
and many of you have been with us from the
very beginning. I want to give a shout out to
this week's top patrons. They include Chuck Blell, David J. E. Smith,
Daniel Lang, Mary Neva, Bill Sorry, Will Defrain, David Compton,
Brian Holden, Gabo, Jay Ulrica Hagman, Pus Squally, Jelati, Rika
Maharaj and Joe Wilkinson. Thank you all so so much.
All right, let's not waste any time and get into
this week's episode. I had the opportunity to speak with
doctor Chad M. Topaz. Chad is a professor of Complex
Systems at Williams College and co founder of the q
Side Institute, which uses data science to promote equity and justice.
He's received several awards from different international and national communities
all about the studies that he's written that he's published,
and of course his opinion pieces as well that sort
of exist at the intersection of data science, social justice,
and public policy. His new book is right along that vein.
It's called Unlocking Justice, The Power of Data to confront
inequity and Create Change. So, without any further ado, here
he is doctor Chad M. Topaz. Well, Chad, thank you
so much for joining me today.
Speaker 2: Thank you, Krotz. I'm honored to be here.
Speaker 1: Yeah, it's going to be a fun chat. I'm looking
forward to talking about your new book, Unlocking Justice, The
Power of Data to confront inequity and create change. So
before we get into Unlocking Justice, I want to learn
a little bit more about you. I always like to
kind of start off the episodes with a bit of background.
So you are. I love your title. You're a professor
of complex systems. Like, does every single person you talk
to go like, what does that mean when you first
tell them?
Speaker 2: Pretty much?
Speaker 1: Yes, So what department would a professor of complex systems
be working in?
Speaker 2: Well, my department is perhaps hilariously called the Department of humanities,
which makes me sound even more confusing than I already do.
But I would say care that people who work on
complex systems come from like a range of different disciplines,
and what we all have in common is wanting to
understand the ways that macroscopic behaviors and patterns and structure
and order come out of groups of things that are
interacting with each other.
Speaker 1: So are we talking everything from psychology to sociology, to
economics to even like mathematics.
Speaker 2: Absolutely, and my own background, I'm trained as a mathematician,
that's my background. But yes, I think all of those
disciplines have inroads into complex systems for sure.
Speaker 1: So you are a pattern seeking creature. I love this,
and so like, are we talking like big data here?
Are we talking the sort of intersection between all of
the pieces of information that we collect all the time,
either actively and intentionally or passively through other systems, and
how we can actually use that data for I guess
good and not evil?
Speaker 2: Yes, that's exactly that's exactly right, And I guess just
to share maybe ten seconds worth of the story, you know,
I mentioned I'm trained as a mathematician and I used
to work on complex systems in uh, physics, in chemistry
and in biology, and I found that work really rewarding.
But I also had this very like political activist side
to me, and I eventually sort of realized that the
issues out in the world that I was really passionate
about and a quantitative skill set that I had could
be brought together to work on some of these justice
issues that are you know, the things that make me
mad when I'm when I wake up every morning and
read the news.
Speaker 1: Yeah here here, I absolutely love to hear it. So
when we talk about these sort of uh, these areas
where you had already been spending your time, you know,
studying outside of academia, marching, you know, engaging in political activism,
are we really talking about all of those obvious places
and I guess not so obvious places where vulnerable people
are disadvantaged by a system. So we're talking racial issues,
gender queer issues, issues around poverty, just all the places
where we can highlight that individual people have been I
guess unfairly disadvantaged.
Speaker 2: Yes, that's exactly right. And I think you've given a
pretty great definition of what social justice is really about.
I think I am a strange melange of privilege and
lack of privilege, and that weird mix is kind of
what has brought me to this table of working on
social justice issues. So, on one hand, I am a
Cis white man who grew up in a very privileged
setting in the northern suburbs of Chicago. And on the
other hand, I am a now married gay man who
kind of came of age in the eighties and nineties
and have put up with my fair share of things
on account of that identity, and so that that is
part of what has brought me to the table. But
of course I am trying to use the places where
I have privilege and use the places where I have
voice to bring some attention to issues that maybe people
like me don't don't always pay as much attention to.
Speaker 1: You know, I think that's such an important point that
you make, and it's one that I I guess I
relate to really deeply. I mean, first and foremost the
listeners probably know this, But to kind of parallel your description,
so I guess I would be considered I'm a woman,
and I'm I present, I am white, I present white,
and I'm afforded all the privileges of whiteness, but I'm
half Puerto Rican I guess I identify as queer, and
I so I live in these but I'm also like,
I have a PhD, like and so do you, right,
So like there's there's like a huge amount of privilege
that comes from having navigated these academic I guess structures
as well, and so it does. It's an important I
guess point about intersectionality that there are those whose voices
are not elevated enough, and then there are those of
us who are in positions where we can work to
elevate those voices. And sometimes the very people doing that
work are the people with the privilege, and are the
people who whose colleagues and peers do not recognize why
this work matters.
Speaker 2: I think that's exactly right, and I write a little
bit about this in the book. So I have a
chapter that maybe comes off as memoir, but it's really
meant to be about my own positionality. And I think,
you know, positionality is a tool where the point of
it isn't to so doubt on the way we think
about things because of who we are. The point of
positionality is to provide transparency and help everyone see how
our backgrounds informs our views and the ways we think
about things, and so on that note, I sort of
talk about how I actually, you know, I do care
about LGBTQUIA plus issues. I care about them deeply. But
most of the work that I do in social justice,
despite the fact that I'm on I'm my white man,
is on issues of race and gender because those are
axes of identity on which I have a ton of
privilege and people listen to me because I'm a white man.
Now there's there's a lot we can say about that
because this potentially steers dangerously into savior territory, and so
there's a lot that needs to be said about how
one tries to avoid that. But that's that's the basic
idea is. You know, I, because of my identities, I've
been given a voice, and so I think, like many
other people who care about things and share my identities,
I'm just trying to use those tools absolutely.
Speaker 1: And I mean, yeah, I hear you this idea of
like it does steer dangerously into savior territory and also
like appropriation, I think territory and at the same time,
like I'm not gonna say, but I'm gonna say, and
you know, I've had so many conversations let's say with
my partner, for example, where he will discuss because you know,
I identify as queer, my partner identifies as queer, and
yet from the outside it looks like we're in a
heteronormative relationship, and so he will discuss some of his
male colleagues and peers, especially as white male colleagues and peers,
like views and opinions, especially in this sort of post
Trumpian world where we're living. I mean, just the other day, gosh,
I hope he doesn't get mad at me for outing
him for this one. The other day, he was saying
how he was at this art thing because he's an artist,
and folks were talking about, oh, it's just like men
can't even get single solo shows anymore. They're all going
to win, and he was like, are you fucking kidding me?
And so we're always talking about how important it is
for him to speak up in those moments because they
may not listen to me. The very sensibility that underlie
somebody bitching and moaning about women getting all of the
art shows is going to make it so that my
opinion weighs less to them than a male counterpart opinion
and it's frustrating as that is that's the reality of
the world we're in.
Speaker 2: I think this is absolutely true, and you know I
experienced this. People get mad at me because of the
things I say in defense of other groups, and you know,
I can handle it because it's actually very hard to
hurt me, Carol. Like, I'm a upper middle class CIS
white man who's like tenured and promoted at a fancy college.
Like they're so little other than saying mean words. There's
so little that that people can do to me, and
in most ways, I'm really like not vulnerable. I Also,
I wanted to circle back to the thing about art
because this is so interesting to me. My book is
really about social justice as it pertains to race in
the criminal legal system. But I tell a story early
on about how part of what brought me to doing
this kind of work was another project that was specifically
about demographic diversity in art museums. And so this is
the story here, if I can share with you, is
that I live in the Northern Berkshire, so in the
northwest corner of the state of Massachusetts, and ten minutes
from my house is the Massachusetts Museum of Contemporary Art, MassMOCA,
and oftentimes people think, oh, a big art museum in
Massachusetts is in Boston, but actually no, mass Moca is
a giant museum and it's it's ten minutes away from
me out here in western mass And soon after I
moved here, in the summer of twenty seventeen, a new
wing was opening at MassMOCA, and I happened to be
friends with a bunch of artists sort of in person
and online, and they were all discussing the fact that, like, wow,
did anyone notice that all of the new artists, you know,
shown in the new wing at mass Moca are white dudes?
And I was like, I was like so naive care.
I was like, oh, I'm like typing at my computer
on Facebook because this was ten years ago. I was like, always,
is diversity in the art world a problem? Question mark?
And my friend, my friend, who's like an art scholar,
is like, Chad, yes, like, get with the program. It's
like a huge problem.
Speaker 1: And I'm like, it's the problem literally everywhere. So why
would it avoid that part of this, you know, the
social miliaure exactly?
Speaker 2: But I said, but but how big? And He's like big,
And I'm like okay, but I am a numbers nerd.
How big And he's like shrug, like no one actually knows.
And I thought, okay, I actually know how to help
figure this out. And I don't at all want to
say that counting something is the thing that makes it real.
That is not true at all. And it is a
very key important message of my book that like, numbers
are one way of understanding things, and they give us
a lens, but they do not replace humans. There are
other ways of knowing things, and ultimately it's human stories
and human experiences matter. But that said, we were able
to show numerically the extent to which major US art
museums are just absolutely dominated in their collections by white men,
and we were able to use this to open some
conversations with museum curators and kind of force them to
reckon with a truth that I think they may have
been more able to deny previously.
Speaker 1: Right without without the actual like statistics in front of them.
And I think, you know, I had, in a micro
version of that, a similar experience when I was getting
all like huffy when we were texting about this. He
was overseas at the time, and I was like, what
do they mean, what is their argument. He was like, oh,
just that it's so hard for like a dude, or
especially like a white dude to get a solo art
show because of like the the you know culture, the
dei kind of culture we're living in. And I just
like literally googled for two minutes and I was like,
eighty seven percent of exhibited artists in major US museums
are men, seventy percent of artists exhibited in major galleries
are men. And how about this one ninety six percent
of art sold at auction is my male artists?
Speaker 2: M Yeah, I was like.
Speaker 1: Oh no, those ninety six percent of men are having
a hard time right now.
Speaker 2: I know I could as a white man, I can
make this joke. It's like white dudes will like lose
one percent of what they have and complain about it
before they go to therapy, right, Yes, yes.
Speaker 1: They will do anything before therapy. Right, Like my favorite
meme online is like dudes doing MMA or like all
sorts of really aggressive do anything before therapy. No, it's
it's such it's such a major concern. And again, like
part of our privilege is being able to laugh about
this right now, because I can imagine that there is
a you know, a queer black female artist who's listening
to this episode and who's like, there's like smoke coming
out of her ears, or this is you know, causing
like a triggering of some real trauma. And that's I
think part of you know, I'm so glad we're having
this conversation today because this is just a small thing
by comparison. But I literally just sent this morning a
message to somebody at the hospital where I work. I'm
a psychologist in a large hospital about the fact that
and I wasn't saying this is institutionwide, because it's absolutely not,
but that there are certain pockets of individuals where consistently
they refer to me as Kara when they refer to
male physicians as doctor so and so, And I think
part of it is the intersectionality of being a woman
versus man. But then I was like, you know, they
refer to the site some of the other psychiatrists as
doctor so. And then I was like, oh, is it
because I'm a psychologist and not a psychiatrist because my
doctor is a PhD and not an MD. And I
think that's another area, Like it's a weird nuanced area
in hospitals where there is some amount of like inequity
around titling, and I hate having to talk about it
because it makes me sound petulant. And at this same time,
it's not a good precedent because it's steeped in so
much sort of gendered nonsense, just a lot of history
around women having to work ten times as hard to
get the exact same outcome as a man.
Speaker 2: Completely agree. This is also a thing in my experience
in academia. Right, So, I teach at a small liberal
arts college where part of what we prize is like
just really sort of like close knit relationships with our
students where we work one on one with them and
are very accessible to them. And it's that kind of experience.
And in my teaching career, I've always gone by my
first name, you know, college Chad. And at some point
in my career a colleague of mine, who I respect
greatly and who is a woman, said to me, like,
you know, it's great that you can do that with
your students, but like I don't actually have quite the
same privilege of being able to do that, because my
students already like have a hard time believing that I'm
a professor or that I'm a doctor, or that I
am someone who they should like pay some modicum of
respect to. And it was really important for me to
hear that and really important for me to think about that.
And so now this is like something that I discussed
with colleagues, like how are you comfortable like with me
titling myself? And I also discuss it with my own students,
like if you're going to call me by my first name,
we can have that agreement, but you need to understand,
like here are some of the structures at play. You
can't do this with your other faculty. You need to
follow like how they want to be addressed and realize
the positions that they're in.
Speaker 1: Yeah, that's when it's nuanced, right. And I remember, like
I was grappling with my wording, and I think I
said something like among colleagues and in the right context,
I'm perfectly happy being called Kara, Like I don't mind
that you call me kara, and that so and so
calls me kara. But what I don't like is when
in rich and correspondence in the same context you call
me kara, and then you call so and so doctor
so and so like that that's a horrific precedent, yep,
because then people don't even know what my title is
or what you know, it kind of what's appropriate within
a business Meeta, It's like, oh my god. And I
think that that's just one example of like so many
under the radar areas of kind of unequal treatment that
then translate to you know, disparities in the social or
in the criminal justice system, disparities with global poverty. You know.
It's like these little things are directly related to really
really big things, aren't they.
Speaker 2: Yes, I mean I think that many times. Uh, And
I'm always I'm always a little bit careful with this
word because when we say the word in microaggression, it
makes it sound like the thing is unimportant, And I
think that's not the meaning of the word microaggression, right.
Speaker 1: It's more that like people don't realize they're doing it, right,
not that it doesn't have like huge psychological impact.
Speaker 2: Right, and that it's happening on a very localized scale
around you, right, it's your personal experience. But I do
think that the source of these microaggressions and the source
of you know, the big structural disparities that we that
we see out in the world. Those things are really
tied together, undeniably.
Speaker 1: Absolutely, And so I'm curious, you know, in your career
thus far, whether we're talking about your uh, I guess,
your doctoral dissertation back whenever that was all the way
up through the the active research that you're engaged in now,
or the work that your students do, or even your teaching,
how has you know, big data taken I guess, how
has that been positioned in some of these important questions
that you've been asking. What are you kind of been
focusing on throughout your career?
Speaker 2: Yeah? Absolutely, So When I started out in my academic career,
like as a graduate student, I worked in physics, I
worked in fluent physics, Like I was so far from
this stuff you can't even believe, and it was not
very data driven. But you know, the past couple of
decades have seen what we like to describe very commonly
as the deluge of data or the proliferation of data.
We have access to more data than we've ever had before.
We also have access to more computing power than we've
ever had before. And these things make new inquiries possible, right,
like new routes of investigation that we could not do previously,
and so really like the work that I described in
my book is centered around using data relevant to the
criminal legal system to expose and hopefully remedy injustice, specifically
around race and specifically around issues such as policing and
bail and criminal sentencing. Those are things that I've been
really putting a lot of attention on. And I think
there's two stories there. One is just like the story
of the disparities and the discrimination and how data can
help us. The other is sort of a meta story
about data itself and why it is that even in
this era of data, sometimes getting information about the way
our criminal legal system is operating is way harder than
it should be given what our rights are in this country.
And so that's a whole other level to the book
is like what are the forces that shape our access
to data? What are the forces that shape biases inherent
in the data? All of these sorts of things. And
I mean, I'll pause here because I don't want to
filibuster you with my speech, but I I have some
absolutely bunkers stories about the way data has been made
inaccessible to hide injustice and the ways that data itself
has encoded racist things over the years.
Speaker 1: Okay, I am like, I'm fascinated and excited to get
into that because I have a feeling that's going to
be what we spend the majority of this hour on.
I wanted to flag beforehand. It's so funny you're talking
about these different kind of layers and this sort of
like meta kind of I guess, yeah, layer component to
the book, and it's I was about to. I was
like biting my tongue. I was like, I want to
talk about process and content. And I got some feedback
from a listener recently that was like that one episode
where you were going on about process and I could
not fall that was so boring and I was like,
okay to but it's definitely something I think about a
lot as a psychologist, and I often talk about with
my students the trainees that I supervise. Is even like
when we're in a therapy session, there is a difference
between process and content, Like the content is the stuff,
and sometimes in therapy people will get in the weeds
talking about all the minutia and the details of the stuff,
and that can be really important. That can be necessary
to get something off your chest and to feel validated
or to really do the work. And then the process
is you know, from a psychological perspective, it's the how
would I put this? It's the sort of top down
umbrella gestalt of what that stuff represents. Oh okay, here's
a pattern. I'm seeing that over and over. You're struggling
with boundaries, Like we could talk about all the little
thing and then she said this, and he said this,
and she said but really, like I'm hearing over and
over that, like you're trying to set boundaries for other
people instead of setting boundaries for yourself. Let's like unpack that.
And so a book like this, I was curious, how
much did you struggle with Okay, do I talk about
individual specific stories and examples, because that's the stuff that
I think really gets people interested. That's the content, but
in service to helping us understand these processes, because it's
not just I guess, a conglomeration. It's not just like
a laundry list of insults. It's not a laundry okay,
And then here's this story, and then here's this story,
and then like really, after a while, we have to
recognize that a pattern is emerging from this data, and
that there are systems at play, and I feel like that,
for some reason is much harder for the citizenry to understand.
They love saying that guy is racist, and they really
struggle with the idea that a system could be racist.
Speaker 2: Yes, I completely agree, and so that is a major
mission of the book and the way that you're talking
about content and process, I would say the sort of
analogy I've made in the book is to think about,
like when you watch a movie, and there's the movie,
and then there's the director's track, which is like, what
was the story going on behind the movie that informs
why it is the way it is secretly, And that's
the way I look at the book. And so there's
these stories of injustice in the criminal legal system and
us using data to address it, and then the director's
track is the part that talks about why was getting
the data so hard? Why are these the racial categories
in the data? Wow, that's a really messed upset of categories,
Like Wow, why is it that we have you genesists
who were using data this way? Right? And so that
the book is really an attempt to give those things
more or less equal weight.
Speaker 1: Yeah, speaking of you, I love that you use that example.
I'd love to dig into that. I always like to
tell the story of Like I was watching a talk
once as an undergraduate when I was you know, had
my little naive baby brain, and I was still learning
so much. I mean, I'm still learning so much. But
man was I learning so much back then. And there
was a visiting scholar who told a story about the
kind of the foundations of uh psychological statistic You know,
a lot of our statistics was was first developed by psychologists,
and a lot of it was developed with the express
uh kind of intention of proving the superiority of white people.
Speaker 2: Like this was, Yeah, it.
Speaker 1: Was like an overt decision that was, Man, I'm going
to develop an IQ test and I'm going to do
it in such a way that it shows that white
people are superior. And then I'm going to analyze the
data using you know, these regression models and all these
different tools see see white people better. Like this was
a like eugenesis were all over early psychology. I mean,
it's still in there, right and so, but they were
also talking about genetics, and you know, genetics as founded
in eugenics, and they showed this it's still to my
days like burned in my memory. This image of I
don't know many people who are listening to the show
if you spent much time in academia. But you know,
if you've ever visited a university library where all the
periodicals are, they get bound up in books every however
many years, right, so you don't just have the individual
journals you have like this, You know, these years of
journals in this hardcover and they all look the same
and very fancy like law books almost. And it literally
showed the changeover from this one journal going from being
called the Annals of Eugenics to the Annals of Genetics
the next year. And I was like whoa, And it
was just so like telling you know, and yeah, I
always love to tell that story. And I still I
haven't been able to find the image since. So if
anybody has that image, send it my way, because I
want to put it in every talk ever. Okay, go ahead,
tell me a little more about these eugenesis that you mentioned.
Speaker 2: Oh well, I must I okay. I'm always going to
say about the eugenicists is you know, we have this
phrase like lies, damn lies and statistics, and I think,
as you said, eugenics is infamous as like a really
effective and extremely harmful way of misusing statistics, so that
the eugenicists did a lot of conflating correlation with causation
in ways to claim things like a criminality is an
inherited trait, right, like not not caused by structural things
like poverty, but like, oh, some families just be crime.
And you know, eugenicists relied on biased data, so they
would do things like collect data from prisons and asylums
and then analyze the data and say like, oh, like,
you know, there's these racial groups in these prisons and
asylums and they're they're they have all of these you know,
weaknesses shown in their statistics. But of course what this
ignores is that these people have been plucked out of
life and placed in circumstances to limit their education and opportunity.
So they I mean, those are just two examples, but
they yes, they did a lot of thing. Yeah, And
I really want to be careful also that I shouldn't
only use the past tense, because we think of eugenics
as like being a thing that was like you know,
back in the day and used as sort of justification
for Nazi Germany. But we have plenty of eugenic ideologies
that are rearing their heads to this day.
Speaker 1: Absolutely, and it bears repeating, and I've said it a
million times on the show, so this should not be
new to you listener. We exported that ideology from the
United States to Germany. Like these were not ideas that
were somehow fundamentally German ideas. There was a massive eugenics
movement in the United States, and many of those ideas
which were seen at the time as positive, like it
was all about like living better through good genes and
healthy families. Like it was definitely positioned that way here
in the US prior to the nineteen thirties, which I
think is an important point to make. But you know,
there's a modern example I think of, and I wonder
if you've come across this. There's a there's a test
in the in psychology called the MMPI and it's probably
one of the most studied. It's Minnesota Multi Phasic Personality
Industry industry not industry, God, why am I blanking on
my words? The Minnesota Multi Phasic Personality Inventory. And it's
this really intense test with a million different kind of
scales inside of it, and it spits out now there's
like computer ways to score it, but it can say, oh,
this person has you know, a little hit over here
on psychopathy, and over here it looks like there's some
difficulty with social interaction, and over here there may be
some you know, gendered self questioning, and over it's it's
it's a fascinating test. It's one of the most well
researched tests, and it does have a lot of good
things going for it. But you know who consistently scores
high on scales of paranoia Black people? And literally, now
when we teach this test, we have to be like,
this test is biased. See here, it's written from a
white perspective where they ask questions like the police are
out to get me, and if people say yes, they
flag that as psychosis. Whoa yeah. So it's like all
of this stuff has to be seen in a social
context that understands inequity. But when it's written with an
assumption that everyone's on a level footing, everything downstream gets
really off.
Speaker 2: Absolutely. Well, Kara, it's funny you had mentioned the police. Yeah,
it's actually it's not funny. But one of the chapters
of my book is about my own small town of Williamstown,
Massachusetts town to meet thousand people out here in western
mass in the Berkshires, where I learned a couple of
years after arriving here that there had been a picture
of Hitler posted in the police station for about twenty years,
and this allow yes, and this led us on a
journey to try to obtain data about what the police
department was doing. And one of the things we learned
from studying this data is that the rate at which
different racial groups in town are accessing police services is vastly,
vastly different, and for anyone paying attention, this should not
come as a surprise, right, Like, if you are someone
like me, who's a white man, who's not in groups
that are targeted by the police, who's really not threatening
interactions with the police, if I have a public safety concern,
I might not hesitate too much to pick up the
phone and report my concern. But if you are someone
from a demographic group who's targeted by the police, right
who experiences violence, including murder by the police, you might
hesitate to pick up that phone and report a safety concern.
You might worry that if you call, you will find
yourself actually being the target of the police, and not
whatever is the concern you called about, and this is
something that we see showing up in our data that
we obtained in this small town where we indeed had
a Hitler picture in the police station.
Speaker 1: Oh my goodness.
Speaker 2: Yeah.
Speaker 1: And I think, like until you actually look at those
numbers again you mentioned before, and it's such an important point.
I think it bears highlighting and repeating something is not true,
only because we have statistics to back it up, but
it definitely makes it harder to reject and deny and
hide from once we have, you know, the numbers that
back it up. I remember having a conversation with two
very dear friends. We were all in like a very
deep and I think sensitive conversation at the time. I
mean this would have been like about a year ago,
so so contextually it would make sense about sort of
the issues the the anti semitism facing you know, Jewish
folks in the world today and also the abject racism
facing black folks in the world today. And it was,
you know, a black not Jewish friend and then a
white Jewish friend and all kind of having a conversation
about this, and my Jewish friend made a point, and
this was in the context of saying, we are not
talking about the oppression Olympics here. Nobody is trying to out,
you know, inequity each other. Right, But she said, you know,
when I call the cops, they still come, and they
come fast. And to me, that is a an indicator
of how society is treating these two different groups like
we yes, we have our massive issues, and yes I
feel unsafe in this, in this sort of zeitgeist, but
I am not as afraid. And I think that was
a turning point in Trump's America. Is when you know,
a white woman protester was shot point blank by ice.
Everybody said, oh shit, the privilege that we thought was
there isn't there. And then a white man you know,
and so, uh, it's it's and and I think that
brings it. That is such a perfect example of privilege
becoming crystal clear and bringing the issues home for everybody.
Is when somebody who who was like, well, but I
you know you like you said before, like it's hard
to hurt me, and then it's like all of a sudden,
oh no. That is a real obvious indicator that we
are all on the same team, fighting for the same thing,
and yes, we are still afforded significantly more privileged. But
when it comes down to it, it's like every punk
rock lyric. You know, first they came for the then
they came for they. Now who's left to defend us?
Speaker 2: Indeed?
Speaker 1: Yeah, whoof so so on? That?
Speaker 2: Really?
Speaker 1: Like you know, bone chilling, no, yes, lighthearted, this show is.
Let's talk a little bit about some of those you know,
as you said, like these kind of bonkers bananas stories
that you came across, how you chose what you wanted
to talk about in the book, and maybe you can
highlight a few of them for us.
Speaker 2: Sure. Well, my students ask me this too, They say, like, chat,
how do you decide what like projects to work on?
And honestly, like, I wake up early early every day
and I drink coffee and I like am busy feeling
I rate about things. And the answer is like, what
I feel irate about is what I try to work on.
Although I think it's I want to say that I
want my iratenus to be inclusive, right right, I don't
want to pick and choose the things that matter because
of what you just said, and like we're not we're
not free until we're all free, right in any case,
I'll tell you a story so you may remember and
the listeners may remember. A man called Paul Manifort. Paul
Manifort was Donald Trump's like first campaign chair in Donald
Trump's like a campaign for his twenty sixteen election. And
Paul Manifort was incredibly accused of doing a whole bunch
of illegal stuff and he was prosecuted and he was convicted.
And one day I was reading the news and there
was a headline that was, like, you know, the public
and legal experts gasp when Manifort given forty seven months,
like despite recommended seventeen to twenty four years sent And
I was like, what's going on? I didn't and I
have been like so shielded from the criminal legal system
that I like didn't even know how criminal sentencing works
because it's not a thing I've ever had to contend with.
But I just thought, wow, this sounds like, this sounds
bonkers that then there could be like guidelines that recommend
decades worth of prison for this convicted man, and actually
what he got was under four years, and in the
end he ended up serving substantially less than that.
Speaker 1: Even oh right, that doesn't surprise me either.
Speaker 2: Yeah, So this sent me on a very long journey
to educate myself about what we know about criminal sentencing
in this country. And because Paul Manifort was prosecuted and
convicted for federal crimes, I'm thinking in this story primarily
of our federal court system. And I learned that it
is very well known that there are inaggregate, gross racial
disparities in criminal sentencing. So you sort of do apples
to apples comparisons of black men to white men and
or Hispanic Latin men to white men, that those minoritized
racial groups receive much longer criminal sentences for the exact
same crimes and even having the same criminal histories essentially
just for the crime of not being white, right like,
they are getting longer sentences. And it was like, wow,
how can this be? And so then I had to
learn about how criminal sentencing works, and I learned how
much discretion judges actually have in choosing our criminal sentence.
We have guidelines that recommend to sentences based on many,
many factors. The US Criminal Sentencing Handbook is like six
hundred plus pages long, so it's a very complicated set
of rules for recommending criminal sentences. But in the vast
majority of cases. With very few exceptions, judges have latitude
to just choose the sentence.
Speaker 1: Which is why it's important when judges are installed with
a political agenda.
Speaker 2: Heck, yes it is and so but but care. This
is where I started losing my mind. So I thought, like, well,
we know that there's these gross racial disparities, and we
know judges are these people with vast discretion and very
secure like lifetime appointment jobs. So like, who are the
judges who are giving these bias sentences? I was like,
we must know, surely we know. And it turns out
we don't know. And it turns out that the reason
we didn't know is because the data that is put
out by the federal Judiciary about federal criminal sentences does
not include the name of the judge who gives the sentence.
This was strange to me because there is a Supreme
Court case called Richmond Newspapers versus Virginia. I think this
is from the year nineteen eighty and one of the
outcomes of this case is that criminal courtrooms in the
United States are open. We actually have a constitutional right
to walk into criminal courtrooms and observe what's happening and
what this means is that if you and I had
all the time and money in the world, and if
we were really well organized, we could get all of
our friends together to go sit in all the courtrooms
and record data, like here's the case that I saw,
and here's what the crime was, and the person was convicted,
and these are some demographics about the individual, and this
is what the sentencing guidelines recommended as their punishment when
they were found guilty, and here's the punishment that the
judge actually gave them, and here's who the judge was.
And theoretically we're allowed to know all of these things,
and we could analyze all that data and figure out,
like what courtrooms specifically are these harsh sentences for racial
minoritize groups coming from. But the government isn't giving us
that information. So I think it's a really poignant example
of the difference between having a rite on paper and
being able to exercise or operationalize that right. And so
the quest that my collaborators and I had to go
on was like figuring out how to reidentify the missing
judge names in all of these hundreds of thousands of
federal sentencing records, and that itself is a bit of
a story. But that's that's one example of a story
that really drew me in.
Speaker 1: Yeah, I mean, oh gosh, there's so much to unpack there.
I mean, do you obviously you wrote about that in
the book. Do you bring these the awareness of these
kind of like deep systemic issues into your curriculum? For example?
Is this something that has really shifted the way that
you speak in public but also teach your students.
Speaker 2: Absolutely so. At my institution, I'm teaching two classes I created,
and one is called Data for Justice, And I'm really
all about like broadening the pathways into doing this kind
of work. You know, math and statistics and computation are
fields that have really systematically excluded racial and gender minorities,
not to mention other groups, and I am about trying
to broaden that pathway. So I teach this Data for
Justice class that's designed for anyone who's never programmed a
computer before and never done statistics before. And I'm really
trying to teach students some fundamental justice sorry, some fundamental
data science skills in a social justice context. And that
includes both technical skills and those sort of like director's track,
like thinking critically about data skills so yes, I bring
these kinds of issues and stories in there, and then
I teach a more advanced course that's Data for Justice
Research Practicum, and all that course is is a semester
long of students doing research projects, original project on various
uh justice issues that they are passionate about. So it's
it's really rewarding to get. I mean, I'm very very
fortunate to work with the amazing students that I that
I get to work with. They're great.
Speaker 1: I love that. So so tell me, you know a
little more about like the book itself. We talked about
the positionality chapter, which uh you know, I discovered when
I was working on my dissertation because I did like
a qualitative like an existential hermeneutic, a sort of phenomena
phenomenological dissertation, and I, i you know, was steeped in
the like philosophy literature of how to write phenomenologically, and
I remember working really hard on a similar chapter that
was sort of like this is where I am coming
from as I am doing this research, and these are
the biases that I'm aware of. You know, I can
only explicate what I can can see, but but I
continue to dig deeper and make those things apparent so
that you, dear reader and other researcher kind of can
understand how I am positioned or situated within all of
this context. So we discussed the positionality chapter, which of
course is right there at the beginning. We talked a
little bit about policing, of course Hitler's shadow, but how
about some of these other aspects of criminal justice, bail, jail, sentencing,
risk scores. You know, did you sort of collect a
whole bunch of interesting stories and then say, how can
I sort of lay these out end to end in
a somewhat followable narrative or did you already have a
structure in play? And then it like, wasn't that hard
to just go, well, there's an example over there. There's
an example over there, because it's literally everywhere.
Speaker 2: Yeah, I didn't have a master plan for the set
of projects that appears in this book. It's a set
of criminal legal topics, and you just name those policing, bail, jail, sentencing,
risk scores, and it's a set of things I worked on.
But as I worked through them over the course of
a number of years, I really saw these same common
themes just merging over and over again, the racial disparities,
the difficulty of getting data, the biases that are built
into the data that we do have, all these kinds
of things, and I just thought, like, there's a story
here that needs to be told. And part of the
way I've tried to weave these things and tell this
story is this is a story of hope. So I
think that these days, if if people in the US
public like know about anything at the intersection of technical
fields and social justice, it's like very likely to be
something related to like the harms that algorithms can cause, right,
like those ways that were surveiled, or like the ways
that generative AI is biased and causing us problems, like
these sorts of things, and these things are all true
and extremely serious. What I wanted to show with these
stories is the uh, the optimistic flip side of this,
which is that when used carefully and in the right way,
data science can be a powerful tool for justice. And
this is really I have to give credit in the
spirit of my hero, who's like the civil rights icon
ID B. Wells, who said that the way to right
wrongs is to shine the light of truth upon them.
And so that's really what I'm after, is like data
as a form of that light. So yeah, I had
no master plan. It was like things I worked on
and the common themes emerged as I did it.
Speaker 1: Oh I love that. Yeah, And so how did you
sort of approach the audience? You know, as as an
individual who has been in academia for quite some time,
you know, I often will talk to folks about that
difference between writing in academic publication. I mean, other than
the obvious difference, which is that one makes no money
and the other one sometimes it makes money if it
doesn't a way, but the difference are doing an academic
publication and a trade publication. Writing for a more general audience. Obviously,
I think all of our best professors already do that
when they focus and put effort into their teaching, because
undergraduates are a more general audience. And then of course
as they get more and more specialized, you can become
more specialized and specific in your language. So what was
that process like for you? Taking these concepts and writing
them in a way that is digestible.
Speaker 2: It was a challenging and extremely fulfilling experience. So look,
I am, as we have said, at a first and
foremost teaching focused institution, I'm at a small Loberal Arts college.
I love teaching. I love helping people understand new concepts,
understand complicated cons and so this book is in that spirit.
It's it's an effort to do that. I have always
enjoyed public speaking, right, telling the public stories in ways
that they can understand. I have enjoyed writing op eds,
which is a different form of public writing. But again,
it can't be technical, right, you want to get a
message to people, like you can be nerdy, and I
love being nerdy, but you can be nerdy in an
accessible way. And that that's what I've been after, and
it was the same thing with this book. Now that
is not to say that I did it perfectly from
the start. I most assurably did not. And this is
the magic of wonderful editors, right right, So I'm drafted
this book thinking like perhaps a little bit with a
little bit of hubris, like, Okay, I've like told these
stories in such plain language, this is going to be
so understandable. And I hired this wonderful like presubmission freelance
editor Nancy Rollinson, who's just brilliant, and she was like, Chad, like,
I think perhaps this is not as accessible as you
think it is. And so so Nancy, to her credit,
like gave me pushed on me really hard in places
where like, yes, I realize you think that you are
teaching this concept clearly, but like you need to do
better here. And then I have an editor at my
publisher at Christian University Press. My editor, Diana Galuley, did
an equally amazing job pushing on me in those places.
So I think if I were to sit down and
write this book again from scratch, I would understand better
and I would be able to do it better from scratch.
And so I'm always grateful when anything is a learning
experience for me as well. Right, Like, I hope the
book teaches the public something, but it taught me something.
Speaker 1: To absolutely do you think that it's something you will
endeavor to do again. It's you know, I talk to
a lot of writers who and I think I'm sort
of in that boat, like I've written a lot academically,
but I am I just like I'm not rich. I
keep telling my editor I'm not ready, Like sitting down
to write a whole book is like the most daunting
thing in the world. But then when I when I
talk to folks who are like, I did it. I
did the book. Then they're like, oh, I'm gonna do
another one. Oh that's crazy. Do you do you feel
like you've gotten bit by the bug? Or are you like, yeah,
we're gonna put that on the shelf for a while.
I need a break.
Speaker 2: Okay, this is not a promise to you or to
anyone listening, but I am probably I am probably in
the bit by the bug camp. I love it, and
it is part of this is because I am someone
who could never decide what they wanted to be when
they grew up. And apparently I'm still not grown up
and I still don't know. And like, yes, I love
doing math and I love doing data science, but I
love communicating and I love writing just as much, and
I love twenty other things just as much so. And
there was a point in my wife where I thought
I wanted to be a journalist as sort of my
my profession. So I really, I really do enjoy the
process of writing. I have some idea is for what
a next book might look like, but I haven't settled
on any of them viata and it's not developed yet,
but I think I would like to do more.
Speaker 1: Yes, oh, well, I won't hold you to it, but
I am looking forward. So on that note, Chad, let
me know, you know, we're kind of coming up to
the close of the hour. Is there anything that you
can think of that I mean, obviously there's so much
we didn't touch on, but if there's any is there
anything you can think of where you're like, I can't
believe we got to talk about this one thing, like
anything that you feel remiss in not bringing up before
we end the hour?
Speaker 2: Thank you for asking. I will say yes, and I'll
make it brief. I really, as I said, wanted this
book to be a book of hope. And one thing
I tried to do at the end of each chapter
is for any reader, even people who think they do
not love numbers and do not love data, this book
is still for them, and I try to give ways
to help anyone highlight the importance of how data can
be used for justice. And in the last chapter of
the book, I talk about I don't know if you know,
Rebecca Solm, that's book Hope in the Dark, which is
like a wonderful treatise or meditation on like how we
might think about hope and how part of Hope, Openness
to the Unknown.
Speaker 1: I need to read that because I've only read Men
Explain Things to Me by So yeah, I've definitely read
her Man Explaining book, but I should read.
Speaker 2: This also an important book. And I guess look, we
are we are. We have always had problems in this country,
but we have a lot of problems right now. It
is a very trying time. I think people wake up
and more than ever feel the weight of reality on them,
and so I have one of the one of the
most important reasons I wrote this book was to try
to give people a little bit more of a sense
of agency in ways that they may not have felt before,
and to provide them with a little bit of help.
Speaker 1: Yeah. Oh, I love that so much. Everybody. The book
is unlike Talking Justice. The Power of Data to confront
inequity and create change by doctor Chad M. Topaz. Chad,
thank you so much for being here with us today.
Speaker 2: Thank you for having me. It's really been an honor
to meet you and talk with you and your listeners.
Speaker 1: And everybody listening. Thank you for coming back week after week.
I'm really looking forward to the next time we all
get together to talk. Ridy, thank you