June 18, 2024 • 44 mins
Book Nook Books:
Within Reason: https://amzn.to/45CILLB
Brooklyn: https://amzn.to/3XpVv6l
Hey, Tangled Minds! Today Harry and I are talking about “bias” in our respective fields and how Jack thinks it’s all the same. We also started a new segment we are calling “Jack’s Book Nook.” Let us know what you think of the segment, the episode, and any thoughts you might have by emailing us at ourtangledminds@gmail.com!
Email us at ourtangledminds@gmail.com
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Harry Weidner (00:04):
All right.
Welcome back to our tangledminds.
Jack Weidner (00:09):
Welcome to our tangled minds.
Harry Weidner (00:11):
I'm Harry Weidner.
Jack Weidner (00:12):
I'm Jack Bagnato season
Harry Weidner (00:14):
two, episode two, I hope you liked the brand new
launch of season one. I hopeeveryone tuned in and said, Wow,
this sounds fun again. And we'lltry to keep it rolling
throughout season two, I'mhaving fun with it. If you
haven't voted with it,
Jack Weidner (00:30):
I am I actually wanted to see if you wanted to
implement a new podcast feature,where we start by talking about
something we are reading rightnow.
Harry Weidner (00:40):
Yeah, I would love to. But before we do that,
we had a fan mail listener maillistener reaching out to us, oh,
I don't know about this. OnBuzzsprout, which is the podcast
hosting site, the Jack and Iuse, they say intellectual
humility. It's something weshould all strive for our nation
would be so much better for it.
And I just wanted to thank youfor reaching out, that really
(01:03):
meant a lot. To me.
Jack Weidner (01:06):
The engagement is a while to me right now here for
the first time. Yeah, I
Harry Weidner (01:09):
didn't tell Jack about this. The engagement is
great. I really appreciate that.
It's a, it's a fun way to hearwhat you guys are thinking about
what we're thinking about. Sokeep it coming. Keep the fan
mail rollin. You can shoot us atext. It's the first line in the
description, oftentimes onSpotify and Buzzsprout. And you
can still email us at ourtangled. minds@gmail.com.
Jack Weidner (01:33):
Yeah. Okay, cool.
Nice. Who set up? Do you know?
Harry Weidner (01:37):
I don't know. It doesn't cheer. Oh, fun. Yeah.
But fun. No, awesome. So thankyou very much, again, for
reaching out. Thank you. Tothose of you who haven't yet
reached out, please reach out ifyou have thoughts. And to
Jack Weidner (01:51):
those of you who have not just that person, but
bless for the previous episodesas well. Thank you. I read them.
And I forward them to Harry.
Harry Weidner (02:00):
We get it all. We appreciate your interactions
with us. And now on to Jack'snew segment that he wanted to
bring up
Jack Weidner (02:09):
Jack's book No book. Doesn't have to be a book
though. can be anything? I don'tknow. I just came up with that
off.
Harry Weidner (02:14):
Jack's book nook.
Jack Weidner (02:15):
Okay. What are you reading right now, Harry? Oh,
God, this is really turning intoa podcast. Yeah. Well,
Harry Weidner (02:20):
I'm honestly two white men
Jack Weidner (02:23):
who are talking about what they're reading in
there. Yeah, it's in the world.
That's what the world's missingright now.
Harry Weidner (02:27):
I still haven't finished within reason I did.
That was something that I put onpause for a long time. And I
still haven't finished the JackKerouac book on the road
restarted. I started I startedit in the airport today, next
day that you gave it to me. AndI just, unfortunately, I'm
packing up my room. So I packedit away. So it's going to wait
(02:51):
until I get to Denver for me toreopen dacha, but you should
Jack Weidner (02:56):
actually not pack it and read it on your way to
Denver, I would actually be avery,
Harry Weidner (03:03):
unfortunately, the very bottom of
Jack Weidner (03:07):
a box. That seems like a huge problem, and
Harry Weidner (03:10):
I will not be able to get it. But I am
finishing within reason bySandra glia, the Dean of the
School of Public Health. It'sabout public health. It's about
about Yes, it's aboutliberalism, and not the kind of
liberalism that's very heatedright now. But
Jack Weidner (03:30):
liberalism with a lowercase owl by definition,
liberalism.
Harry Weidner (03:36):
And coming coming from the perspective of public
100, Capitol Hill, I think itwould be business
Jack Weidner (03:44):
on freedom. It doesn't matter what it is. We're
going to look it up. Freedom,emphasis on freedom, liberalism.
Harry Weidner (03:50):
So it's about public health's failures
throughout COVID. And how wehave sort of shifted public
health to illiberalism, whereit's been more about mandates
and all of these things that arereducing public's trust in the
(04:12):
system.
Jack Weidner (04:15):
I'm already i Okay, wait, I have a question.
Answer. So we talk we spoke lastepisode about the importance of
vaccine mandates. What's yourtake? I mean, that's in direct
opposition to that mindset,right? Well,
Harry Weidner (04:32):
it is. But the whole point of the book goes
back to education, and propereducation, hopefully, proper
public health education wouldlead people to understand that
the risks of vaccination is sosmall, and the benefits of
vaccination are so great thatthey would make the proper
choice. It's
Jack Weidner (04:53):
so interesting to me that how foundational of
principle education is in anykind of liberalism. Because
liberalism requires and aneducated populace to work, which
is fascinating to me. Literallylike a pop like, oh, gosh,
(05:14):
that's
Harry Weidner (05:14):
so
Jack Weidner (05:15):
interesting. It's huge. It's so idealistic, for,
for people to say, education isthe thing that is going to get
us out of this. Because I thinklike that requires a
generational shift, nogenerations, shift I
(05:36):
generational multi generationalshift in the way we interact
with institutions. It's like,how do we get them to trust
institutions, it's to understandwhy those institutions are there
and to understand how theyfunction. And we, in this
country, at least have such aninherent distrust of
institution, we were founded onthe distrust of institutions.
(05:58):
That is literally how ourdemocracy came to be. It was a
bunch of people who didn't trustinstitutions, or didn't like
that they weren't the headinstitution. And that is part of
the fabric of our country. Andthat is so fascinating. And it's
got to be so frustrating forthose who are so charismatic,
who like your Dean, who is sosad, like he would I'm sure he
(06:21):
would advocate to just giveeveryone an education where they
can understand this and thatoutreach. And it's so yeah, be
so hard. That's so interesting.
Harry Weidner (06:29):
The another sort of key point of the book, is
that we need to fall back on thescience and fall back on the
numbers and be critical onarguments of both sides.
Jack Weidner (06:45):
And yeah, it liberalism requires that middle
ground, it
Harry Weidner (06:48):
requires a lack of polarization.
Jack Weidner (06:52):
Okay, so
Harry Weidner (06:55):
I don't want to I don't want to say it's, I don't
want to say it requires middleground. But it requires your
right to be you can still be onthe very far end of the
spectrum. Yes, requires you tounderstand the other side. And
so I don't want to call thatmiddle ground. You know what I
mean, though,
Jack Weidner (07:13):
that's an interesting point. Because I
have been really annoyed withthis idea of people saying like,
Oh, well, I'm an independent, asif that makes you better for
like, as if, and when I don'tthink that's what they're
saying. Like, there's people whosay like, I'm independent, but
that doesn't necessarily meanthat you're a in the middle B,
(07:34):
that you're truly independent.
Or see that you're actuallylike, like you could be removed
from the system, like that ideaof independent that idea of
like, being in the middle of twoissues, I think is false. And I
think that we like kind of, likeglorify that as like, not taking
aside like being intellectualsto be in the middle. But it's
not like that's your right,this. I'm glad you call back.
(07:55):
Yeah, you're
Harry Weidner (07:57):
very entitled to your opinion, but your opinion
has to be informed by ideas fromthe other side.
Jack Weidner (08:07):
Yeah.
Harry Weidner (08:08):
So that's, that's what I'm reading. What are you
reading? I'm interested, I'malways interested to hear what
you're reading.
Jack Weidner (08:13):
I'm reading Brooklyn, by I am going to
butcher his name, because it'ssuper Irish. And it would be
like me trying to say, Sure,sure, sir. Sharon. And without
like, understanding how she saysher name. It's like comb. Tobin.
I don't know. Okay, it the moviecame out sorcerer running was in
(08:35):
the movie. And basically, it isa about an Irish girl after
World War Two is an immigrant toAmerica. And she settles in
Brooklyn. And it is a lovestory. But it's also an
immigrant story. It's also anAmerican story. And it's also a
story. Yeah, it's just it'sreally interesting. I'm reading
(08:58):
it now, because it's one of myfavorite movies. And I the
sequel just came out. It'scalled Long Island. And before I
read Long Island, because I'mnot going to wait for them to
make a movie of this book thatjust came out. I'm going to read
Brooklyn, and then I'm gonnaread Long Island. I'm really
excited. I love thesecharacters, eats he has a very
distinct writing style. That isapparently very Irish. And I
(09:23):
don't have a lot of experiencewith that. And what's fun for me
is I've spent a lot of timereading Italian immigrant
narratives and Italian immigrantstories and kind of trying to
understand that sense of notonly like immigrant experience,
but also just what Italian NewYork was like. And this is very
much an Irish side of that wherethey're speaking about a time
(09:44):
she falls in love with anItalian, Italian man was you she
gets into a relationship with anItalian man. Okay, and there's a
lot of cultural shock thereabout her coming into an Italian
family and the way she sees theworld Like there's, there's kind
of I, I'm very curious, she'svery alone, she's very isolated,
(10:07):
which I think is not an Italian.
That's not like a trademark ofThai and experience it to be
like Italians came in, they verymuch wanted to like recreate
Italy. And the Irish kind oflike they came Ireland, there
were a lot of Irish. But the wayshe the way he writes for her,
it's she's very much alone.
(10:30):
She's very much without thefeeling of community. And she's
very much of masking herfeelings of being sad and in
pain. And she's not talkingabout it. She's she's, she,
there's a there was a paragraphthat I read yesterday, where she
was proud about how she maskedher true intentions. And she was
(10:53):
somewhat to a priest who wascaring for her. Oh, it was so
interesting, she said. And Isaid it in a way like my mother
would, that wouldn't allow himto know if I was truly grateful
or not this level of what Ithink of as stereotypically
(11:14):
Irish where you're like, I'm notgoing to feel anything, I'm
going to be outwardly polite.
The key, there's this underlyingdialogue, and I'm excited to get
because the way she talks shespeaks about the Italians is
very different. They're they'reapproaching her, they're a
little bit more boisterous. I'mjust, I'm excited to get through
the story. And I love hiswriting. And it's, it's
(11:36):
fascinating. So
Harry Weidner (11:38):
when you're reading a book like that, what
does that teach you aboutyourself? Or does that teach you
about? Does I mean, obviouslygives you perspective, but are
you reading for enjoyment? Areyou reading it to learn
something or a little bit ofboth?
Jack Weidner (11:54):
A little bit of both. Um, this is the first book
that I picked up purely forenjoyment. And a while, I've
been reading a lot ofnonfiction, and a lot of just
kind of like, books where I wantto learn or I want to get this
viewpoint. And this is justsomething that, like, I'm so
fascinated by immigrantnarratives, and New York City
(12:17):
and Brooklyn, that this is justhappens to scratch every edge.
But I'm like reading it, and I'mthinking about, I'm thinking
about different things. So it'skind of like it's helping me to
think about different things,see different perspectives,
understand what you know, fromthis single, like, understand
this woman's experience from herperspective. And also, I'm just
(12:44):
enjoying the heck out of it.
Because it's like Brooklyn,they're cheering for the
Dodgers. She's working in anotable department store. Cool.
Yeah. She's going down AtlanticAvenue. Very fun. Nice. Yeah,
no, it's it's great. And I justI am yeah, I'm always so cute.
Because I always think about,like, our family that came over
is that you know, and howdifferent that experience was.
(13:04):
They also came over at adifferent time. Right, so yeah,
cool. What
Harry Weidner (13:13):
a fun little segment a lot more fun. Great.
What is it? What did we call it?
Book? No, no.
Jack Weidner (13:18):
Next book, Nick.
Harry Weidner (13:19):
Jack's book No duck guy, right. Welcome to the
book, Nook. Should we come tothe book? I like it. Should we
leave the book snug?
Jack Weidner (13:29):
Yeah, let's leave.
Let's get out of the book. Let'slet's go into the wider world.
Let's step out of the nuk.
Harry Weidner (13:33):
So this week, Jack called me one day. And you
were in a little bit of a rushin a panic. And I'll have you
explained I
Jack Weidner (13:43):
didn't have it wasn't a panic. I was out of
breath. I had seven minutes totalk to you before a meeting.
Okay, that's why I wasn't out ofbreath. I was trying to get
through all my thoughts before Ihad to go into this meeting that
wasn't about this that. So
Harry Weidner (14:00):
I'm going to make you explain the backstory more.
But you called me and youbrought up bias. And I thought
it was interesting because weboth have, I mean, obviously a
similar definition of bias. ButI look at bias very differently
than the way that you look atbias and right into it. But I
come in, come at it from anepidemiology perspective. And
(14:22):
you come at come at it from moreof a like, traditional and
psychological bias perspective.
And we'll we'll dissect it andgo into it and talk about the
different kinds of biases maybenot specifically but effects. I
know that bias and how itaffects our view on the world.
Jack Weidner (14:44):
Okay. Um, so I was watching a I was actually
watching. The Khan Academy has aseries on AI for educators. And
I was just interested in what itwould be so was watching it
before a meeting becauseeveryone's talking about AI and
(15:04):
the workforce. And, and I wasjust, you know, I, I don't know
if anyone be surprised when Iencounter something that I don't
understand that my firstreaction is to try to watch as
many videos and read as muchabout it as I can to understand
it. And the first section wasjust about what is AI blah,
(15:26):
blah, blah. And they're kind oflike, going into all of these
terms where they're talkingabout, like how we think, how do
we know something? How do weknow something to be correct?
How do we learn? And for a longtime, I've always thought like,
Oh, these are just, you know,these are fundamental philosophy
(15:46):
questions, like you were doing,I forgot what the actual
philosophical and I knew it, andI remembered it before this is
there is a there's a branch ofphilosophy that is about the
study of knowing and the studyof knowledge. It's like pista,
Mala G, I think, check me onthat. Look that up while I keep
talking,
Harry Weidner (16:04):
Jack did have that correct. Epistemology,
okay, back to the episode. But
Jack Weidner (16:11):
essentially, and I said, these are just basic
philosophical questions that Ithink computer science people,
and you know, engineer,whoever's working on these
massive machine learningcomplexes are thinking about,
and I was like, Oh, these arejust humanitarian caught, like
humanities concepts that they'reputting into science. And now
(16:33):
engineers are like, Oh, wait,what? Like, do we know anything?
And I want to go to a video onthe dangers of AI. And they were
talking about bias in data sets,and how it is important, when AI
gives you information to read itcritically. And a lot of the
(16:57):
people were like, you might getsomething and think that it's
right, because it came from amachine, which is a bad practice
on any ground. But I think whenyou we're especially working
with things that are, let's say,let's say they're like I think
we look at a binary system ispretty objective. Like I think
(17:19):
we view not machines, but thingswith a code, we look at them as
object, right? I think that thatis a bias and humanity. But they
were saying you have to read andscrutinize and that if the data
(17:39):
that it is fed is biased, theoutput that the machine
learning, I don't know machinelearning system will provide the
algorithm will be biased. And Icalled Harry and I said, that's
interesting to me that thatwould not be assumed from the
(18:01):
get go. Because in thehumanities, I think when we in
our intro classes, we are taughtto question what we read. If we
are given a paper written bysomeone, we ask, what is their
position? What is theirconnection to this topic? What
is their expertise? How like,what are their biases that might
influence what they're writing?
And then how do we read thatcritically by questioning or you
(18:24):
know, you get like, famous caseyou're reading JD Salinger's
Catcher in the Rye. Is HoldenCaulfield, an unreliable
narrator How do you know thatyou read and you're questioning?
Hold it has bias because to livein the world is to have bias.
And I called Harry and I said,do scientists don't think about
this? Is that not something thatyou were just taught to read
(18:46):
everything with the possibilityof bias? And Harry said no. And
I think we can kind of continuelet's, let's start a
Harry Weidner (18:55):
discussion here.
And all will start here. BecauseI said no, immediately, because
I was thinking of my like,introductory. And you said you
just you discuss this in yourintro courses.
Jack Weidner (19:08):
You have to so to read anything you have to
Harry Weidner (19:12):
in, in biochemistry, and I think a lot
of like intro hard sciences, youdon't think about bias at all.
The point of those classes is tolearn the information. I have to
learn these proteins, I have tolearn what they do and the
signaling pathway. And we'rereally not taught to question it
(19:36):
until you reach a level ofunderstanding beyond that intro
level. So it wasn't until Ijoined labs and we were actually
forming questions questionformation and research design
and how to answer the questionbest that we really started to
(19:56):
think about bias but On day one,no, you don't think about bias.
Remember how you think back tohigh school biology? You just
learn these things that aregiven to you as fact. And you
don't really have the space, thewiggle room to question them.
Because I
Jack Weidner (20:17):
asked, I asked him, like one of my fundamental
questions. I'm like, What issomething? What is living? Like?
Why I don't I still I asked thisand I asked your biology class
that I had.
Harry Weidner (20:29):
You are a Why is a
Jack Weidner (20:30):
cell living? If it if the components within it, you
know, like, Okay, I'm gonna beable to pitch it. We're not
gonna go on a huge, we don'thave to. Yeah, I could ask you
this. I've asked you thisbefore. It drives me nuts. Yeah.
Okay. I do. I do, though, Iguess
Harry Weidner (20:48):
you do you Sure.
But I think for most students,point blank, you don't question
the facts that you're given whenyou're given a PowerPoint?
Because you just think that it'sall well understood. The real
world says it's not. And thenwhen I came to grad school, and
I did my epidemiology studies,that's all about bias, but it's
(21:10):
a different kind of bias thanwhat you were talking about.
Jack Weidner (21:18):
Okay. So I would like to start, I think, trying
to think like, what makes themost sense from a narrative
perspective? Let's start withthis. That what point you didn't
think about bias, or inquestioning those facts that you
were given? And you said, untilyou came to grad school?
Harry Weidner (21:37):
Until I joined labs? Okay. And I don't think
all students have thatexperience. Okay. So tell me, I
think my experience with Andrewreally was formative in my
ability to critically thinkabout information that's
presented.
Jack Weidner (21:54):
So tell me about like kind of your first
experiences with questioningsome of those things, some of
that some facts with Andrew orhow he kind of shifted your
mindset when you were given someinformation to ingest? Or how
utterly Andrew change yourperspective,
Harry Weidner (22:09):
he really just said, Don't believe anything
anyone tells you. And, and soever since I heard that from
him, I always think about everyfact that's presented, and if I
leave a class, now, it's weirdthat I'm graduated. But if I
(22:29):
leave a class, and I don't havequestions, I didn't pay
attention well enough. And Ididn't think enough about the
information. Because if youdon't have questions, then
you're not thinking about it.
That's kind of what Andrew setme up to do. So any paper that I
would read, how did they dothis? Why did they do this? And
that set me up to understandbias from a scientific
perspective. Okay,
Jack Weidner (22:51):
so can you explain to me bias from a scientific
perspective? Or what is your
Harry Weidner (22:56):
understanding about in epidemiology
specifically? Sure, yeah. So
Jack Weidner (23:00):
you got to college, and you learn about
bias and and epidemiology? Yeah.
Harry Weidner (23:03):
So I think most epidemiology textbooks would
define bias as a systematicerror in the design, or analysis
of a study that results inincorrect conclusions about
associations, or measures ofassociation like odds ratio,
(23:26):
hazard ratio, risk ratio, andsort of outcomes. So that would
be selection bias, informationbias, confounding recall bias.
And so those biases, impact thevalidity of the result that
you're given, or the result thatyou find from these studies.
(23:48):
It's systematic error in design.
And now, let's go ahead,
Jack Weidner (23:54):
go go ahead. Go ahead. Go ahead.
Harry Weidner (23:55):
No, no, you go,
Jack Weidner (23:56):
I was gonna ask them, like for because I'm not a
scientist, when you saysystematic error in design, what
does an error what is an exampleof an error in design?
Harry Weidner (24:07):
Um, so it's flaws in the study design. I know, I
just repeated what you said. ButI'll give you a selection bias.
It's when participants areincluded in the study that
aren't representative of thetarget population. And in order
to mitigate or reduce selectionbias, you need to clearly define
(24:30):
the target population.
Jack Weidner (24:32):
Right. And so now now we're at where we kind of
left off a call when we weretalking about this the other
week. Yeah.
Harry Weidner (24:39):
So it's all about properly identifying and
defining the research questionso that you can deliberately
minimize the bias to answer thatspecific question. Okay, it's
about understood Finding whatyou want, and designing your
(25:02):
study to answer that. Okay, now,I want to hear about your
Jack Weidner (25:07):
well, so I'm gonna like go back because basically,
I mean, if you are, if youaren't hip, this idea for bias,
there's a lot of examples of AIbeing, quote unquote biased,
because of the information. Andit is fed in a very, like,
mocking the same mundane, but inour low stakes, but and just
(25:31):
kind of like a lesscontroversial example,
basically, like, becausehumanity has said, so many
things, and comments and jokesand false studies and statistics
about women being bad drivers,if you ask AI, you give it four
(25:51):
names, one for three or clearlymasculine, one is more feminine
in nature, it might pick thefemale name as being worse at
drive, because of how we are aspeople in the world being
terrible, right. And they weresaying that means your data is
(26:14):
biased. And that's not good. Andyou have to think about that
beforehand. And I just thoughtthat was weird, because I would,
I would like i To me, this wasengineers being like, oh, my
gosh, not everything we have notengineers. But you know what I
mean? Like the scientificcommunity being like, oh, not
everything we have is, you know,good information, obviously,
(26:39):
right? Like you're getting intoyou feed AI histories. And in
history class, a big thing isunderstanding that history is
written by the winners. Soeverything you read has to be
read through that mindset. Youhave to find different sources,
you have to work really hard toget an accurate, like, the study
of history is not an objectivestudy. And I think like kind of
(27:03):
where I've landed, is thatnothing because of human like
humans by nothing is anobjective study. Right? So I
just did and why I called you isI'm looking the humanities are
under attack right now. In theworld of like, why are they
(27:24):
important to study. And I think,that mindset, that they that
they teach you to criticallythink, which is an overused
term, but I think it really istrue. Just the they teach you to
critically analyze theinformation which with which
were given, and I think thesciences now that we have
created something that is hyperlogical, meaning that it takes
(27:48):
everything it reads as a fact,and then makes its own
judgement, like you can gothrough a logical process and
say, like, and arrive at aconclusion. That is sounded
logic, but false. That is like aPhyllis, that is a
philosophically sound thing thatcan happen, right? You can be
(28:09):
logically sound and false. And Ithink we've created something
that's better at doing that thanwe are sometimes it's right,
sometimes it's wrong. That is
Harry Weidner (28:20):
a big problem.
Right?
Jack Weidner (28:24):
And I think studying the humanities will
become very important. And youhave people who are asking, wait
a second, not all of thisinformation out here is correct.
How do we know what's correct?
And I think we're asking like,what are humans? What are humans
good at? In this question? What?
(28:45):
How do we know what we know? Andwe're just back to these
philosophical principles, thesephilosophical questions. So to
me reading this, taking thisvery academic course by all of
these brilliant, you know,you've computer scientists, you
have engineers, CEOs, whatever,they're teaching you this
information. They're just sayingbasic human concepts that I
(29:09):
learned in my humanities classesback to me. So to me, like bias,
Harry said, I get to ask him, Isaid, What kind of like, are you
talking about? What kind of biasis where you are? What kind of
bias because I knew he was gonnasay this. Epidemiology has a
certain type of bias. Andscience has a certain type of
bias and I, I agree that it'sphrased differently, and he's
(29:32):
like, What is your definition ofbias? I said, I don't know the
Merriam Webster definition, aninclination of temperament or
Outlook, an incidence of suchprejudice, deviation of the
expected value of statisticalestimate from the quantity it
estimates. Those are threedefinitions, the top three of
(29:55):
bias, but actually, it's justthe top one because they're all
law. lumped together into asingular definition, where
they're all basically saying thesame thing. So an instance of
prejudice is thrown into thesame group definition of
deviation of the expected valueof a statistical estimate from
(30:17):
the quantity, it estimates andsystematic error introduced into
sampling or testing. Those areall within prejudice. Because
and that kind of, I didn't knowthat until just now. But that
really speaks to my argument,that no matter how specific, you
(30:37):
would like to say epidemiology,his definition of biases, it is
still just my definition ofbias.
Harry Weidner (30:52):
But I think the mitigation of these biases is
different, because the goal isdifferent. And you'll tell me
the goal is not what is the whatis the goal? What's the goal?
The goal of like, identifyingepidemiology biases? Sure. It's
(31:14):
to answer the question, orunderstand if the question that
you're asking is appropriatelyanswered. But
Jack Weidner (31:21):
that's not the goal. Because what's the goal?
The question? What's the goal ofany question and epidemiology
study? And what is the goal ofepidemiology?
Harry Weidner (31:42):
To understand environmental factors or other
factors that cause disease, and
Jack Weidner (31:46):
why do we want to do that?
Harry Weidner (31:49):
Public Health?
Jack Weidner (31:50):
Why is public health poor? I'm going to make
you say,
Harry Weidner (31:54):
I don't know what you want me to say here, but I
mean, the health of populations.
Okay.
Jack Weidner (31:59):
So we want you are studying epidemiology in order
to get the best information tocare for the most people in the
most effective way?
Harry Weidner (32:09):
Yes, okay. So what is the goal? Yes.
Jack Weidner (32:14):
What is the goal of a scientific epidemiologist
Harry Weidner (32:19):
to benefit humanity?
Jack Weidner (32:21):
Okay. So let's talk about bias, okay. Your
definition of bias would notcover the example and I know it,
you can change your mind. Butyou told me it wouldn't cover my
example. When I gave you this aweek ago. No, I said, Yeah.
Target. The you said a specificaudience, or what was your
(32:41):
specific wording of like, itdidn't like your set group? It
didn't like focus right on yourset group.
Harry Weidner (32:50):
Like the study by variation?
Jack Weidner (32:51):
Yeah, the study population? Was that it?
Harry Weidner (32:54):
I don't remember exactly what I said.
Jack Weidner (32:57):
You said something, because I was I kept
giving you examples. I was like,okay. So historically, science
has excluded research on whitemen or excluded research on
white women, women of all races,people of color, just across the
board, right? Those are very,very rapid, different, different
(33:18):
race, different races, differentgenders. They pretty least do a
lot of research on white men.
Yeah. And I said it's white men.
Yeah. Except if they admit thattheir target audience is just
white men. They're not theirtarget audience, but they're,
like, split like, we're just,we're testing this drug only on
(33:39):
white men. Yes, thattechnically, isn't bias. No. But
it is bias. Because what, like,if their reasoning that they are
doing that is deemed is becauseis rooted in some sort of
racism, some sort of sexism thatwould only make them care about
(34:04):
white men. That is bias in thesetup of the study. I won't
disagree with that. But I thinkit is so important for the
scientists to start admittingwhat the purpose, what the
actual purpose of the study is,and really starting to call and
I know that they that I provideda an egregious example where it
(34:28):
is so black and white cut anddry clear, but that is bias. But
to scrutinize studies, with thatkind of idea. Yeah. And
Harry Weidner (34:39):
but I think I think this goes back to our very
first episode of the podcast,where we talked about how the
entire educational system needsreform. Sure, sure. source or
source or source or sourceresource resource, for sure. I
mean, yes, I do. I think I wouldhave much benefited, very
greatly benefited But I wasgonna get to a bias education.
Jack Weidner (35:03):
As you start, like, young Truda, I wanted that
this is actually gonna get to.
Okay. Yeah, sure. I mean, yougot it in high school. You read
Catcher in the Rye, you talkedabout unreliable narrators,
Harry Weidner (35:16):
I guess. But we got to know, you what you
Jack Weidner (35:19):
weren't taught is to bring that mindset into every
single class. Yes. That is thebenefit of the humanities that I
think people are missing. It'sthat it's a mindset. Right.
Harry Weidner (35:34):
And I, I love it.
Jack Weidner (35:37):
Do you do I realize I've tried to, I just,
it's so interesting to me, youknow, like you and I talk about
learning in a vacuum and how youjust can't do it. And I just
think bias the good note in thisin the age of AI, I think the
study of the humanities is soimportant, because it is
teaching you a way ofinteracting with the world.
Harry Weidner (35:57):
Yeah, I think we'll see a rise in AI use
classes at an undergraduateinstitutions. If there's
Jack Weidner (36:08):
what I don't want, is it to be aI use classes, not
that no one gives a shit what Iwant like this, the train has
left the station, I just don'tthink it's as beneficial to have
it be aI use. Because AI is aform of as a way of interacting
(36:28):
with the world. There will beother ways of interacting with
the world. Other than AI, whathave we had before AI that
change the way we interact withthe world? A million things,
right? Like industrialrevolution, agriculture, the
agricultural revolution,industrial revolutions. We've
found, right now we're talkingabout social media. So if you
(36:51):
teach AI use classes short,you'll learn Yeah, you're gonna
learn about bots, you're gonnalearn that, you know, beat
question AI. Great. But whatabout the next thing? If we
focus so heavily on AI? Have wefailed to prepare? For what is
the what is in the future? And Ithink time and time again, my
(37:15):
argument is that you create,like, what if this is the start
of the podcast, this is the sameconversation that we just had
about
Harry Weidner (37:23):
this is learning it in English class and applying
it broadly.
Jack Weidner (37:28):
Right, but exactly, I'm building Yeah,
learning an English class ofbuying a broadly. But this is
also how important an educatedcitizen is to, like educated
populace is to a liberaldemocracy, right? How important
education is to a society. Andthen, what it means to me is
(37:52):
redefining what an education is.
I'm not saying you didn't havethis, I'm sorry, I don't want to
know, go ahead. People who arein the sciences get an education
in any sense, they get aneducation, an incredible
education, from, you know, theirfor whatever, they got a four
year degree, whether they wenton to graduate school. I just
(38:14):
think their way of interactingwith the world could be could
benefit from a humanitiesapproach to ingesting knowledge.
In the same way. I think all ofthe people in the humanities
(38:35):
could deal with being challengedit seeing how the sciences
interact with information, thereis an importance to prove you
what you are saying, yeah. Andthat kind of logical. Flow is
pivotal to the humanities, we donot get together in a circle,
(38:58):
sing Kumbaya, and talk about ourfeelings. Sometimes we do. I was
gonna say, maybe you did.
Sometimes we did. But that'sgood. Talk about your feelings.
Sorry. Yeah. So I just I'm sopassionate. No, I
Harry Weidner (39:12):
appreciate it. I think. I think you're right. So
much of my degree was focused onunderstanding epidemiological
bias. And there was way less ofan I mean, I wrote papers on
bias. And I wrote papers onunderstanding papers on bias.
(39:32):
And but it was it was veryspecific, like, systematic study
design, error that influencesmeasures of association, either
up or down toward or away fromthe null. And that's what it
was. But do I think it couldhave been more focused on the
(39:54):
broader discussion of bias thatwe just had? Yeah, and I think
that would benefit science. Andwhat's coming out of
epidemiology specifically,tremendously? Do you think
there's a benefit to bias?
Jack Weidner (40:12):
I'm gonna say yes.
Because I feel like I have to.
Because I feel like to exist ashuman beings, we must exist with
bias, right? And to exist withbias and to exist authentically.
And to admit that that bias isthere allows us to see different
(40:32):
perspectives from our. So Ithink, in the same way, men,
this really does go back to whatlike how I said, me reading
Brooklyn has introduced me toanother perspective that I have
not gotten to introduce or tointeract with that her bias is
(40:52):
the characters bias. And thewriters bias that him being an a
Thai, or an Irish immigranthimself, that his bias has shown
me a new perspective. I don't, Ithink where we fall, and where I
think, why I'm so interested inAI, is when we assume that there
(41:17):
is not biased. And we presentthings with objectivity that
don't have that. But I thinkbias is just the way that we
live and to say, is there abenefit to bias? To me that's
like saying, Is there a benefitto having multiple perspectives
in anything? Yeah, absolutely.
What about you? Do you thinkthat there's benefit to bias?
(41:37):
Yeah,
Harry Weidner (41:38):
I mean, I think, to give a little less elegant,
elegant of an answer. Humans arepattern recognition machines.
And this is a grape, most of ourlives, whether we want to admit
it or not, are spent trying tofind patterns and things to
reduce cognitive load. And soevolutionarily, bias is
(42:03):
tremendously beneficial. Eating,you know, cavemen eating
something, this thing is good,it gives me fuel. I will do that
again. What does the shake, youknow, it's, it's
Jack Weidner (42:19):
just you're such a good point. It's like to have
bias against something thatlooked like a bear. If it's not
a bear, you're still safer thatit would be that it would be if
you went to investigate it.
Like, that's a good point.
Harry Weidner (42:35):
And so I think that's, that's why bias is such
a big problem. Because it's soevolutionarily rooted in our
success as a species.
Jack Weidner (42:47):
And I think like, what's so much fun, is that you
and I can sit here and have thisconversation, acknowledge bias,
acknowledge its benefits, andstill have that curiosity to
dive further. Because I thinkcuriosity and an openness is
really the cure to bias it sir.
It serves that evolutionarypurpose. It Sir, it is just to
(43:10):
to be biased is to be human. Andthen how do you remedy that? You
must push yourself for you mustbe curious to scrutinize and to
question. Education,
Harry Weidner (43:29):
education,
Jack Weidner (43:30):
everything falls to education. That's this whole
podcast. Yeah. Awesome, dude.
Oh, my gosh, is there anythingelse we should say about bias? I
don't think so. This is I hadfun. This was a good this is
what I'm sorry. I talked somuch. I'm just really passionate
about this. I'm so curious aboutit. I'm so curious about the
future of humanity. It's likeI'm excited. And I want to see
what's going on. And likethat's, you know, like this
(43:52):
awesome. Party on man, Dadparty. All right. I'm gonna wrap
it up. Thank you so much forlistening. If you have any
thoughts on bias, if you haveany biases, don't email us the
biases, but email us yourthoughts on bias. Or you can
text us Oh, go ahead. Well,you're gonna
Harry Weidner (44:15):
say I was gonna say we'll link to the books that
we talked about. Yeah. Earlierin the description. If you buy
me support the show, that wouldbe awesome. Yes. That's huge.
And, yeah, reach out. We lovethe feedback and we love
interacting with people. So
Jack Weidner (44:32):
thanks. Thank you so much for seeing how this mess
unravels and we'll see you intwo weeks with a special guest
Harry Weidner (44:40):
right on this morning.
All right.
Welcome back to our tangledminds.
Jack Weidner (00:09):
Welcome to our tangled minds.
Harry Weidner (00:11):
I'm Harry Weidner.
Jack Weidner (00:12):
I'm Jack Bagnato season
Harry Weidner (00:14):
two, episode two, I hope you liked the brand new
launch of season one. I hopeeveryone tuned in and said, Wow,
this sounds fun again. And we'lltry to keep it rolling
throughout season two, I'mhaving fun with it. If you
haven't voted with it,
Jack Weidner (00:30):
I am I actually wanted to see if you wanted to
implement a new podcast feature,where we start by talking about
something we are reading rightnow.
Harry Weidner (00:40):
Yeah, I would love to. But before we do that,
we had a fan mail listener maillistener reaching out to us, oh,
I don't know about this. OnBuzzsprout, which is the podcast
hosting site, the Jack and Iuse, they say intellectual
humility. It's something weshould all strive for our nation
would be so much better for it.
And I just wanted to thank youfor reaching out, that really
(01:03):
meant a lot. To me.
Jack Weidner (01:06):
The engagement is a while to me right now here for
the first time. Yeah, I
Harry Weidner (01:09):
didn't tell Jack about this. The engagement is
great. I really appreciate that.
It's a, it's a fun way to hearwhat you guys are thinking about
what we're thinking about. Sokeep it coming. Keep the fan
mail rollin. You can shoot us atext. It's the first line in the
description, oftentimes onSpotify and Buzzsprout. And you
can still email us at ourtangled. minds@gmail.com.
Jack Weidner (01:33):
Yeah. Okay, cool.
Nice. Who set up? Do you know?
Harry Weidner (01:37):
I don't know. It doesn't cheer. Oh, fun. Yeah.
But fun. No, awesome. So thankyou very much, again, for
reaching out. Thank you. Tothose of you who haven't yet
reached out, please reach out ifyou have thoughts. And to
Jack Weidner (01:51):
those of you who have not just that person, but
bless for the previous episodesas well. Thank you. I read them.
And I forward them to Harry.
Harry Weidner (02:00):
We get it all. We appreciate your interactions
with us. And now on to Jack'snew segment that he wanted to
bring up
Jack Weidner (02:09):
Jack's book No book. Doesn't have to be a book
though. can be anything? I don'tknow. I just came up with that
off.
Harry Weidner (02:14):
Jack's book nook.
Jack Weidner (02:15):
Okay. What are you reading right now, Harry? Oh,
God, this is really turning intoa podcast. Yeah. Well,
Harry Weidner (02:20):
I'm honestly two white men
Jack Weidner (02:23):
who are talking about what they're reading in
there. Yeah, it's in the world.
That's what the world's missingright now.
Harry Weidner (02:27):
I still haven't finished within reason I did.
That was something that I put onpause for a long time. And I
still haven't finished the JackKerouac book on the road
restarted. I started I startedit in the airport today, next
day that you gave it to me. AndI just, unfortunately, I'm
packing up my room. So I packedit away. So it's going to wait
(02:51):
until I get to Denver for me toreopen dacha, but you should
Jack Weidner (02:56):
actually not pack it and read it on your way to
Denver, I would actually be avery,
Harry Weidner (03:03):
unfortunately, the very bottom of
Jack Weidner (03:07):
a box. That seems like a huge problem, and
Harry Weidner (03:10):
I will not be able to get it. But I am
finishing within reason bySandra glia, the Dean of the
School of Public Health. It'sabout public health. It's about
about Yes, it's aboutliberalism, and not the kind of
liberalism that's very heatedright now. But
Jack Weidner (03:30):
liberalism with a lowercase owl by definition,
liberalism.
Harry Weidner (03:36):
And coming coming from the perspective of public
100, Capitol Hill, I think itwould be business
Jack Weidner (03:44):
on freedom. It doesn't matter what it is. We're
going to look it up. Freedom,emphasis on freedom, liberalism.
Harry Weidner (03:50):
So it's about public health's failures
throughout COVID. And how wehave sort of shifted public
health to illiberalism, whereit's been more about mandates
and all of these things that arereducing public's trust in the
(04:12):
system.
Jack Weidner (04:15):
I'm already i Okay, wait, I have a question.
Answer. So we talk we spoke lastepisode about the importance of
vaccine mandates. What's yourtake? I mean, that's in direct
opposition to that mindset,right? Well,
Harry Weidner (04:32):
it is. But the whole point of the book goes
back to education, and propereducation, hopefully, proper
public health education wouldlead people to understand that
the risks of vaccination is sosmall, and the benefits of
vaccination are so great thatthey would make the proper
choice. It's
Jack Weidner (04:53):
so interesting to me that how foundational of
principle education is in anykind of liberalism. Because
liberalism requires and aneducated populace to work, which
is fascinating to me. Literallylike a pop like, oh, gosh,
(05:14):
that's
Harry Weidner (05:14):
so
Jack Weidner (05:15):
interesting. It's huge. It's so idealistic, for,
for people to say, education isthe thing that is going to get
us out of this. Because I thinklike that requires a
generational shift, nogenerations, shift I
(05:36):
generational multi generationalshift in the way we interact
with institutions. It's like,how do we get them to trust
institutions, it's to understandwhy those institutions are there
and to understand how theyfunction. And we, in this
country, at least have such aninherent distrust of
institution, we were founded onthe distrust of institutions.
(05:58):
That is literally how ourdemocracy came to be. It was a
bunch of people who didn't trustinstitutions, or didn't like
that they weren't the headinstitution. And that is part of
the fabric of our country. Andthat is so fascinating. And it's
got to be so frustrating forthose who are so charismatic,
who like your Dean, who is sosad, like he would I'm sure he
(06:21):
would advocate to just giveeveryone an education where they
can understand this and thatoutreach. And it's so yeah, be
so hard. That's so interesting.
Harry Weidner (06:29):
The another sort of key point of the book, is
that we need to fall back on thescience and fall back on the
numbers and be critical onarguments of both sides.
Jack Weidner (06:45):
And yeah, it liberalism requires that middle
ground, it
Harry Weidner (06:48):
requires a lack of polarization.
Jack Weidner (06:52):
Okay, so
Harry Weidner (06:55):
I don't want to I don't want to say it's, I don't
want to say it requires middleground. But it requires your
right to be you can still be onthe very far end of the
spectrum. Yes, requires you tounderstand the other side. And
so I don't want to call thatmiddle ground. You know what I
mean, though,
Jack Weidner (07:13):
that's an interesting point. Because I
have been really annoyed withthis idea of people saying like,
Oh, well, I'm an independent, asif that makes you better for
like, as if, and when I don'tthink that's what they're
saying. Like, there's people whosay like, I'm independent, but
that doesn't necessarily meanthat you're a in the middle B,
(07:34):
that you're truly independent.
Or see that you're actuallylike, like you could be removed
from the system, like that ideaof independent that idea of
like, being in the middle of twoissues, I think is false. And I
think that we like kind of, likeglorify that as like, not taking
aside like being intellectualsto be in the middle. But it's
not like that's your right,this. I'm glad you call back.
(07:55):
Yeah, you're
Harry Weidner (07:57):
very entitled to your opinion, but your opinion
has to be informed by ideas fromthe other side.
Jack Weidner (08:07):
Yeah.
Harry Weidner (08:08):
So that's, that's what I'm reading. What are you
reading? I'm interested, I'malways interested to hear what
you're reading.
Jack Weidner (08:13):
I'm reading Brooklyn, by I am going to
butcher his name, because it'ssuper Irish. And it would be
like me trying to say, Sure,sure, sir. Sharon. And without
like, understanding how she saysher name. It's like comb. Tobin.
I don't know. Okay, it the moviecame out sorcerer running was in
(08:35):
the movie. And basically, it isa about an Irish girl after
World War Two is an immigrant toAmerica. And she settles in
Brooklyn. And it is a lovestory. But it's also an
immigrant story. It's also anAmerican story. And it's also a
story. Yeah, it's just it'sreally interesting. I'm reading
(08:58):
it now, because it's one of myfavorite movies. And I the
sequel just came out. It'scalled Long Island. And before I
read Long Island, because I'mnot going to wait for them to
make a movie of this book thatjust came out. I'm going to read
Brooklyn, and then I'm gonnaread Long Island. I'm really
excited. I love thesecharacters, eats he has a very
distinct writing style. That isapparently very Irish. And I
(09:23):
don't have a lot of experiencewith that. And what's fun for me
is I've spent a lot of timereading Italian immigrant
narratives and Italian immigrantstories and kind of trying to
understand that sense of notonly like immigrant experience,
but also just what Italian NewYork was like. And this is very
much an Irish side of that wherethey're speaking about a time
(09:44):
she falls in love with anItalian, Italian man was you she
gets into a relationship with anItalian man. Okay, and there's a
lot of cultural shock thereabout her coming into an Italian
family and the way she sees theworld Like there's, there's kind
of I, I'm very curious, she'svery alone, she's very isolated,
(10:07):
which I think is not an Italian.
That's not like a trademark ofThai and experience it to be
like Italians came in, they verymuch wanted to like recreate
Italy. And the Irish kind oflike they came Ireland, there
were a lot of Irish. But the wayshe the way he writes for her,
it's she's very much alone.
(10:30):
She's very much without thefeeling of community. And she's
very much of masking herfeelings of being sad and in
pain. And she's not talkingabout it. She's she's, she,
there's a there was a paragraphthat I read yesterday, where she
was proud about how she maskedher true intentions. And she was
(10:53):
somewhat to a priest who wascaring for her. Oh, it was so
interesting, she said. And Isaid it in a way like my mother
would, that wouldn't allow himto know if I was truly grateful
or not this level of what Ithink of as stereotypically
(11:14):
Irish where you're like, I'm notgoing to feel anything, I'm
going to be outwardly polite.
The key, there's this underlyingdialogue, and I'm excited to get
because the way she talks shespeaks about the Italians is
very different. They're they'reapproaching her, they're a
little bit more boisterous. I'mjust, I'm excited to get through
the story. And I love hiswriting. And it's, it's
(11:36):
fascinating. So
Harry Weidner (11:38):
when you're reading a book like that, what
does that teach you aboutyourself? Or does that teach you
about? Does I mean, obviouslygives you perspective, but are
you reading for enjoyment? Areyou reading it to learn
something or a little bit ofboth?
Jack Weidner (11:54):
A little bit of both. Um, this is the first book
that I picked up purely forenjoyment. And a while, I've
been reading a lot ofnonfiction, and a lot of just
kind of like, books where I wantto learn or I want to get this
viewpoint. And this is justsomething that, like, I'm so
fascinated by immigrantnarratives, and New York City
(12:17):
and Brooklyn, that this is justhappens to scratch every edge.
But I'm like reading it, and I'mthinking about, I'm thinking
about different things. So it'skind of like it's helping me to
think about different things,see different perspectives,
understand what you know, fromthis single, like, understand
this woman's experience from herperspective. And also, I'm just
(12:44):
enjoying the heck out of it.
Because it's like Brooklyn,they're cheering for the
Dodgers. She's working in anotable department store. Cool.
Yeah. She's going down AtlanticAvenue. Very fun. Nice. Yeah,
no, it's it's great. And I justI am yeah, I'm always so cute.
Because I always think about,like, our family that came over
is that you know, and howdifferent that experience was.
(13:04):
They also came over at adifferent time. Right, so yeah,
cool. What
Harry Weidner (13:13):
a fun little segment a lot more fun. Great.
What is it? What did we call it?
Book? No, no.
Jack Weidner (13:18):
Next book, Nick.
Harry Weidner (13:19):
Jack's book No duck guy, right. Welcome to the
book, Nook. Should we come tothe book? I like it. Should we
leave the book snug?
Jack Weidner (13:29):
Yeah, let's leave.
Let's get out of the book. Let'slet's go into the wider world.
Let's step out of the nuk.
Harry Weidner (13:33):
So this week, Jack called me one day. And you
were in a little bit of a rushin a panic. And I'll have you
explained I
Jack Weidner (13:43):
didn't have it wasn't a panic. I was out of
breath. I had seven minutes totalk to you before a meeting.
Okay, that's why I wasn't out ofbreath. I was trying to get
through all my thoughts before Ihad to go into this meeting that
wasn't about this that. So
Harry Weidner (14:00):
I'm going to make you explain the backstory more.
But you called me and youbrought up bias. And I thought
it was interesting because weboth have, I mean, obviously a
similar definition of bias. ButI look at bias very differently
than the way that you look atbias and right into it. But I
come in, come at it from anepidemiology perspective. And
(14:22):
you come at come at it from moreof a like, traditional and
psychological bias perspective.
And we'll we'll dissect it andgo into it and talk about the
different kinds of biases maybenot specifically but effects. I
know that bias and how itaffects our view on the world.
Jack Weidner (14:44):
Okay. Um, so I was watching a I was actually
watching. The Khan Academy has aseries on AI for educators. And
I was just interested in what itwould be so was watching it
before a meeting becauseeveryone's talking about AI and
(15:04):
the workforce. And, and I wasjust, you know, I, I don't know
if anyone be surprised when Iencounter something that I don't
understand that my firstreaction is to try to watch as
many videos and read as muchabout it as I can to understand
it. And the first section wasjust about what is AI blah,
(15:26):
blah, blah. And they're kind oflike, going into all of these
terms where they're talkingabout, like how we think, how do
we know something? How do weknow something to be correct?
How do we learn? And for a longtime, I've always thought like,
Oh, these are just, you know,these are fundamental philosophy
(15:46):
questions, like you were doing,I forgot what the actual
philosophical and I knew it, andI remembered it before this is
there is a there's a branch ofphilosophy that is about the
study of knowing and the studyof knowledge. It's like pista,
Mala G, I think, check me onthat. Look that up while I keep
talking,
Harry Weidner (16:04):
Jack did have that correct. Epistemology,
okay, back to the episode. But
Jack Weidner (16:11):
essentially, and I said, these are just basic
philosophical questions that Ithink computer science people,
and you know, engineer,whoever's working on these
massive machine learningcomplexes are thinking about,
and I was like, Oh, these arejust humanitarian caught, like
humanities concepts that they'reputting into science. And now
(16:33):
engineers are like, Oh, wait,what? Like, do we know anything?
And I want to go to a video onthe dangers of AI. And they were
talking about bias in data sets,and how it is important, when AI
gives you information to read itcritically. And a lot of the
(16:57):
people were like, you might getsomething and think that it's
right, because it came from amachine, which is a bad practice
on any ground. But I think whenyou we're especially working
with things that are, let's say,let's say they're like I think
we look at a binary system ispretty objective. Like I think
(17:19):
we view not machines, but thingswith a code, we look at them as
object, right? I think that thatis a bias and humanity. But they
were saying you have to read andscrutinize and that if the data
(17:39):
that it is fed is biased, theoutput that the machine
learning, I don't know machinelearning system will provide the
algorithm will be biased. And Icalled Harry and I said, that's
interesting to me that thatwould not be assumed from the
(18:01):
get go. Because in thehumanities, I think when we in
our intro classes, we are taughtto question what we read. If we
are given a paper written bysomeone, we ask, what is their
position? What is theirconnection to this topic? What
is their expertise? How like,what are their biases that might
influence what they're writing?
And then how do we read thatcritically by questioning or you
(18:24):
know, you get like, famous caseyou're reading JD Salinger's
Catcher in the Rye. Is HoldenCaulfield, an unreliable
narrator How do you know thatyou read and you're questioning?
Hold it has bias because to livein the world is to have bias.
And I called Harry and I said,do scientists don't think about
this? Is that not something thatyou were just taught to read
(18:46):
everything with the possibilityof bias? And Harry said no. And
I think we can kind of continuelet's, let's start a
Harry Weidner (18:55):
discussion here.
And all will start here. BecauseI said no, immediately, because
I was thinking of my like,introductory. And you said you
just you discuss this in yourintro courses.
Jack Weidner (19:08):
You have to so to read anything you have to
Harry Weidner (19:12):
in, in biochemistry, and I think a lot
of like intro hard sciences, youdon't think about bias at all.
The point of those classes is tolearn the information. I have to
learn these proteins, I have tolearn what they do and the
signaling pathway. And we'rereally not taught to question it
(19:36):
until you reach a level ofunderstanding beyond that intro
level. So it wasn't until Ijoined labs and we were actually
forming questions questionformation and research design
and how to answer the questionbest that we really started to
(19:56):
think about bias but On day one,no, you don't think about bias.
Remember how you think back tohigh school biology? You just
learn these things that aregiven to you as fact. And you
don't really have the space, thewiggle room to question them.
Because I
Jack Weidner (20:17):
asked, I asked him, like one of my fundamental
questions. I'm like, What issomething? What is living? Like?
Why I don't I still I asked thisand I asked your biology class
that I had.
Harry Weidner (20:29):
You are a Why is a
Jack Weidner (20:30):
cell living? If it if the components within it, you
know, like, Okay, I'm gonna beable to pitch it. We're not
gonna go on a huge, we don'thave to. Yeah, I could ask you
this. I've asked you thisbefore. It drives me nuts. Yeah.
Okay. I do. I do, though, Iguess
Harry Weidner (20:48):
you do you Sure.
But I think for most students,point blank, you don't question
the facts that you're given whenyou're given a PowerPoint?
Because you just think that it'sall well understood. The real
world says it's not. And thenwhen I came to grad school, and
I did my epidemiology studies,that's all about bias, but it's
(21:10):
a different kind of bias thanwhat you were talking about.
Jack Weidner (21:18):
Okay. So I would like to start, I think, trying
to think like, what makes themost sense from a narrative
perspective? Let's start withthis. That what point you didn't
think about bias, or inquestioning those facts that you
were given? And you said, untilyou came to grad school?
Harry Weidner (21:37):
Until I joined labs? Okay. And I don't think
all students have thatexperience. Okay. So tell me, I
think my experience with Andrewreally was formative in my
ability to critically thinkabout information that's
presented.
Jack Weidner (21:54):
So tell me about like kind of your first
experiences with questioningsome of those things, some of
that some facts with Andrew orhow he kind of shifted your
mindset when you were given someinformation to ingest? Or how
utterly Andrew change yourperspective,
Harry Weidner (22:09):
he really just said, Don't believe anything
anyone tells you. And, and soever since I heard that from
him, I always think about everyfact that's presented, and if I
leave a class, now, it's weirdthat I'm graduated. But if I
(22:29):
leave a class, and I don't havequestions, I didn't pay
attention well enough. And Ididn't think enough about the
information. Because if youdon't have questions, then
you're not thinking about it.
That's kind of what Andrew setme up to do. So any paper that I
would read, how did they dothis? Why did they do this? And
that set me up to understandbias from a scientific
perspective. Okay,
Jack Weidner (22:51):
so can you explain to me bias from a scientific
perspective? Or what is your
Harry Weidner (22:56):
understanding about in epidemiology
specifically? Sure, yeah. So
Jack Weidner (23:00):
you got to college, and you learn about
bias and and epidemiology? Yeah.
Harry Weidner (23:03):
So I think most epidemiology textbooks would
define bias as a systematicerror in the design, or analysis
of a study that results inincorrect conclusions about
associations, or measures ofassociation like odds ratio,
(23:26):
hazard ratio, risk ratio, andsort of outcomes. So that would
be selection bias, informationbias, confounding recall bias.
And so those biases, impact thevalidity of the result that
you're given, or the result thatyou find from these studies.
(23:48):
It's systematic error in design.
And now, let's go ahead,
Jack Weidner (23:54):
go go ahead. Go ahead. Go ahead.
Harry Weidner (23:55):
No, no, you go,
Jack Weidner (23:56):
I was gonna ask them, like for because I'm not a
scientist, when you saysystematic error in design, what
does an error what is an exampleof an error in design?
Harry Weidner (24:07):
Um, so it's flaws in the study design. I know, I
just repeated what you said. ButI'll give you a selection bias.
It's when participants areincluded in the study that
aren't representative of thetarget population. And in order
to mitigate or reduce selectionbias, you need to clearly define
(24:30):
the target population.
Jack Weidner (24:32):
Right. And so now now we're at where we kind of
left off a call when we weretalking about this the other
week. Yeah.
Harry Weidner (24:39):
So it's all about properly identifying and
defining the research questionso that you can deliberately
minimize the bias to answer thatspecific question. Okay, it's
about understood Finding whatyou want, and designing your
(25:02):
study to answer that. Okay, now,I want to hear about your
Jack Weidner (25:07):
well, so I'm gonna like go back because basically,
I mean, if you are, if youaren't hip, this idea for bias,
there's a lot of examples of AIbeing, quote unquote biased,
because of the information. Andit is fed in a very, like,
mocking the same mundane, but inour low stakes, but and just
(25:31):
kind of like a lesscontroversial example,
basically, like, becausehumanity has said, so many
things, and comments and jokesand false studies and statistics
about women being bad drivers,if you ask AI, you give it four
(25:51):
names, one for three or clearlymasculine, one is more feminine
in nature, it might pick thefemale name as being worse at
drive, because of how we are aspeople in the world being
terrible, right. And they weresaying that means your data is
(26:14):
biased. And that's not good. Andyou have to think about that
beforehand. And I just thoughtthat was weird, because I would,
I would like i To me, this wasengineers being like, oh, my
gosh, not everything we have notengineers. But you know what I
mean? Like the scientificcommunity being like, oh, not
everything we have is, you know,good information, obviously,
(26:39):
right? Like you're getting intoyou feed AI histories. And in
history class, a big thing isunderstanding that history is
written by the winners. Soeverything you read has to be
read through that mindset. Youhave to find different sources,
you have to work really hard toget an accurate, like, the study
of history is not an objectivestudy. And I think like kind of
(27:03):
where I've landed, is thatnothing because of human like
humans by nothing is anobjective study. Right? So I
just did and why I called you isI'm looking the humanities are
under attack right now. In theworld of like, why are they
(27:24):
important to study. And I think,that mindset, that they that
they teach you to criticallythink, which is an overused
term, but I think it really istrue. Just the they teach you to
critically analyze theinformation which with which
were given, and I think thesciences now that we have
created something that is hyperlogical, meaning that it takes
(27:48):
everything it reads as a fact,and then makes its own
judgement, like you can gothrough a logical process and
say, like, and arrive at aconclusion. That is sounded
logic, but false. That is like aPhyllis, that is a
philosophically sound thing thatcan happen, right? You can be
(28:09):
logically sound and false. And Ithink we've created something
that's better at doing that thanwe are sometimes it's right,
sometimes it's wrong. That is
Harry Weidner (28:20):
a big problem.
Right?
Jack Weidner (28:24):
And I think studying the humanities will
become very important. And youhave people who are asking, wait
a second, not all of thisinformation out here is correct.
How do we know what's correct?
And I think we're asking like,what are humans? What are humans
good at? In this question? What?
(28:45):
How do we know what we know? Andwe're just back to these
philosophical principles, thesephilosophical questions. So to
me reading this, taking thisvery academic course by all of
these brilliant, you know,you've computer scientists, you
have engineers, CEOs, whatever,they're teaching you this
information. They're just sayingbasic human concepts that I
(29:09):
learned in my humanities classesback to me. So to me, like bias,
Harry said, I get to ask him, Isaid, What kind of like, are you
talking about? What kind of biasis where you are? What kind of
bias because I knew he was gonnasay this. Epidemiology has a
certain type of bias. Andscience has a certain type of
bias and I, I agree that it'sphrased differently, and he's
(29:32):
like, What is your definition ofbias? I said, I don't know the
Merriam Webster definition, aninclination of temperament or
Outlook, an incidence of suchprejudice, deviation of the
expected value of statisticalestimate from the quantity it
estimates. Those are threedefinitions, the top three of
(29:55):
bias, but actually, it's justthe top one because they're all
law. lumped together into asingular definition, where
they're all basically saying thesame thing. So an instance of
prejudice is thrown into thesame group definition of
deviation of the expected valueof a statistical estimate from
(30:17):
the quantity, it estimates andsystematic error introduced into
sampling or testing. Those areall within prejudice. Because
and that kind of, I didn't knowthat until just now. But that
really speaks to my argument,that no matter how specific, you
(30:37):
would like to say epidemiology,his definition of biases, it is
still just my definition ofbias.
Harry Weidner (30:52):
But I think the mitigation of these biases is
different, because the goal isdifferent. And you'll tell me
the goal is not what is the whatis the goal? What's the goal?
The goal of like, identifyingepidemiology biases? Sure. It's
(31:14):
to answer the question, orunderstand if the question that
you're asking is appropriatelyanswered. But
Jack Weidner (31:21):
that's not the goal. Because what's the goal?
The question? What's the goal ofany question and epidemiology
study? And what is the goal ofepidemiology?
Harry Weidner (31:42):
To understand environmental factors or other
factors that cause disease, and
Jack Weidner (31:46):
why do we want to do that?
Harry Weidner (31:49):
Public Health?
Jack Weidner (31:50):
Why is public health poor? I'm going to make
you say,
Harry Weidner (31:54):
I don't know what you want me to say here, but I
mean, the health of populations.
Okay.
Jack Weidner (31:59):
So we want you are studying epidemiology in order
to get the best information tocare for the most people in the
most effective way?
Harry Weidner (32:09):
Yes, okay. So what is the goal? Yes.
Jack Weidner (32:14):
What is the goal of a scientific epidemiologist
Harry Weidner (32:19):
to benefit humanity?
Jack Weidner (32:21):
Okay. So let's talk about bias, okay. Your
definition of bias would notcover the example and I know it,
you can change your mind. Butyou told me it wouldn't cover my
example. When I gave you this aweek ago. No, I said, Yeah.
Target. The you said a specificaudience, or what was your
(32:41):
specific wording of like, itdidn't like your set group? It
didn't like focus right on yourset group.
Harry Weidner (32:50):
Like the study by variation?
Jack Weidner (32:51):
Yeah, the study population? Was that it?
Harry Weidner (32:54):
I don't remember exactly what I said.
Jack Weidner (32:57):
You said something, because I was I kept
giving you examples. I was like,okay. So historically, science
has excluded research on whitemen or excluded research on
white women, women of all races,people of color, just across the
board, right? Those are very,very rapid, different, different
(33:18):
race, different races, differentgenders. They pretty least do a
lot of research on white men.
Yeah. And I said it's white men.
Yeah. Except if they admit thattheir target audience is just
white men. They're not theirtarget audience, but they're,
like, split like, we're just,we're testing this drug only on
(33:39):
white men. Yes, thattechnically, isn't bias. No. But
it is bias. Because what, like,if their reasoning that they are
doing that is deemed is becauseis rooted in some sort of
racism, some sort of sexism thatwould only make them care about
(34:04):
white men. That is bias in thesetup of the study. I won't
disagree with that. But I thinkit is so important for the
scientists to start admittingwhat the purpose, what the
actual purpose of the study is,and really starting to call and
I know that they that I provideda an egregious example where it
(34:28):
is so black and white cut anddry clear, but that is bias. But
to scrutinize studies, with thatkind of idea. Yeah. And
Harry Weidner (34:39):
but I think I think this goes back to our very
first episode of the podcast,where we talked about how the
entire educational system needsreform. Sure, sure. source or
source or source or sourceresource resource, for sure. I
mean, yes, I do. I think I wouldhave much benefited, very
greatly benefited But I wasgonna get to a bias education.
Jack Weidner (35:03):
As you start, like, young Truda, I wanted that
this is actually gonna get to.
Okay. Yeah, sure. I mean, yougot it in high school. You read
Catcher in the Rye, you talkedabout unreliable narrators,
Harry Weidner (35:16):
I guess. But we got to know, you what you
Jack Weidner (35:19):
weren't taught is to bring that mindset into every
single class. Yes. That is thebenefit of the humanities that I
think people are missing. It'sthat it's a mindset. Right.
Harry Weidner (35:34):
And I, I love it.
Jack Weidner (35:37):
Do you do I realize I've tried to, I just,
it's so interesting to me, youknow, like you and I talk about
learning in a vacuum and how youjust can't do it. And I just
think bias the good note in thisin the age of AI, I think the
study of the humanities is soimportant, because it is
teaching you a way ofinteracting with the world.
Harry Weidner (35:57):
Yeah, I think we'll see a rise in AI use
classes at an undergraduateinstitutions. If there's
Jack Weidner (36:08):
what I don't want, is it to be aI use classes, not
that no one gives a shit what Iwant like this, the train has
left the station, I just don'tthink it's as beneficial to have
it be aI use. Because AI is aform of as a way of interacting
(36:28):
with the world. There will beother ways of interacting with
the world. Other than AI, whathave we had before AI that
change the way we interact withthe world? A million things,
right? Like industrialrevolution, agriculture, the
agricultural revolution,industrial revolutions. We've
found, right now we're talkingabout social media. So if you
(36:51):
teach AI use classes short,you'll learn Yeah, you're gonna
learn about bots, you're gonnalearn that, you know, beat
question AI. Great. But whatabout the next thing? If we
focus so heavily on AI? Have wefailed to prepare? For what is
the what is in the future? And Ithink time and time again, my
(37:15):
argument is that you create,like, what if this is the start
of the podcast, this is the sameconversation that we just had
about
Harry Weidner (37:23):
this is learning it in English class and applying
it broadly.
Jack Weidner (37:28):
Right, but exactly, I'm building Yeah,
learning an English class ofbuying a broadly. But this is
also how important an educatedcitizen is to, like educated
populace is to a liberaldemocracy, right? How important
education is to a society. Andthen, what it means to me is
(37:52):
redefining what an education is.
I'm not saying you didn't havethis, I'm sorry, I don't want to
know, go ahead. People who arein the sciences get an education
in any sense, they get aneducation, an incredible
education, from, you know, theirfor whatever, they got a four
year degree, whether they wenton to graduate school. I just
(38:14):
think their way of interactingwith the world could be could
benefit from a humanitiesapproach to ingesting knowledge.
In the same way. I think all ofthe people in the humanities
(38:35):
could deal with being challengedit seeing how the sciences
interact with information, thereis an importance to prove you
what you are saying, yeah. Andthat kind of logical. Flow is
pivotal to the humanities, we donot get together in a circle,
(38:58):
sing Kumbaya, and talk about ourfeelings. Sometimes we do. I was
gonna say, maybe you did.
Sometimes we did. But that'sgood. Talk about your feelings.
Sorry. Yeah. So I just I'm sopassionate. No, I
Harry Weidner (39:12):
appreciate it. I think. I think you're right. So
much of my degree was focused onunderstanding epidemiological
bias. And there was way less ofan I mean, I wrote papers on
bias. And I wrote papers onunderstanding papers on bias.
(39:32):
And but it was it was veryspecific, like, systematic study
design, error that influencesmeasures of association, either
up or down toward or away fromthe null. And that's what it
was. But do I think it couldhave been more focused on the
(39:54):
broader discussion of bias thatwe just had? Yeah, and I think
that would benefit science. Andwhat's coming out of
epidemiology specifically,tremendously? Do you think
there's a benefit to bias?
Jack Weidner (40:12):
I'm gonna say yes.
Because I feel like I have to.
Because I feel like to exist ashuman beings, we must exist with
bias, right? And to exist withbias and to exist authentically.
And to admit that that bias isthere allows us to see different
(40:32):
perspectives from our. So Ithink, in the same way, men,
this really does go back to whatlike how I said, me reading
Brooklyn has introduced me toanother perspective that I have
not gotten to introduce or tointeract with that her bias is
(40:52):
the characters bias. And thewriters bias that him being an a
Thai, or an Irish immigranthimself, that his bias has shown
me a new perspective. I don't, Ithink where we fall, and where I
think, why I'm so interested inAI, is when we assume that there
(41:17):
is not biased. And we presentthings with objectivity that
don't have that. But I thinkbias is just the way that we
live and to say, is there abenefit to bias? To me that's
like saying, Is there a benefitto having multiple perspectives
in anything? Yeah, absolutely.
What about you? Do you thinkthat there's benefit to bias?
(41:37):
Yeah,
Harry Weidner (41:38):
I mean, I think, to give a little less elegant,
elegant of an answer. Humans arepattern recognition machines.
And this is a grape, most of ourlives, whether we want to admit
it or not, are spent trying tofind patterns and things to
reduce cognitive load. And soevolutionarily, bias is
(42:03):
tremendously beneficial. Eating,you know, cavemen eating
something, this thing is good,it gives me fuel. I will do that
again. What does the shake, youknow, it's, it's
Jack Weidner (42:19):
just you're such a good point. It's like to have
bias against something thatlooked like a bear. If it's not
a bear, you're still safer thatit would be that it would be if
you went to investigate it.
Like, that's a good point.
Harry Weidner (42:35):
And so I think that's, that's why bias is such
a big problem. Because it's soevolutionarily rooted in our
success as a species.
Jack Weidner (42:47):
And I think like, what's so much fun, is that you
and I can sit here and have thisconversation, acknowledge bias,
acknowledge its benefits, andstill have that curiosity to
dive further. Because I thinkcuriosity and an openness is
really the cure to bias it sir.
It serves that evolutionarypurpose. It Sir, it is just to
(43:10):
to be biased is to be human. Andthen how do you remedy that? You
must push yourself for you mustbe curious to scrutinize and to
question. Education,
Harry Weidner (43:29):
education,
Jack Weidner (43:30):
everything falls to education. That's this whole
podcast. Yeah. Awesome, dude.
Oh, my gosh, is there anythingelse we should say about bias? I
don't think so. This is I hadfun. This was a good this is
what I'm sorry. I talked somuch. I'm just really passionate
about this. I'm so curious aboutit. I'm so curious about the
future of humanity. It's likeI'm excited. And I want to see
what's going on. And likethat's, you know, like this
(43:52):
awesome. Party on man, Dadparty. All right. I'm gonna wrap
it up. Thank you so much forlistening. If you have any
thoughts on bias, if you haveany biases, don't email us the
biases, but email us yourthoughts on bias. Or you can
text us Oh, go ahead. Well,you're gonna
Harry Weidner (44:15):
say I was gonna say we'll link to the books that
we talked about. Yeah. Earlierin the description. If you buy
me support the show, that wouldbe awesome. Yes. That's huge.
And, yeah, reach out. We lovethe feedback and we love
interacting with people. So
Jack Weidner (44:32):
thanks. Thank you so much for seeing how this mess
unravels and we'll see you intwo weeks with a special guest
Harry Weidner (44:40):
right on this morning.
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