The Tech Humanist Show: Episode 12 – Sarah T. Roberts

About this episode’s guest:

Sarah T. Roberts is an Assistant Professor in the Department of Information Studies, Graduate School of Education & Information Studies, at UCLA. She holds a Ph.D. from the iSchool at the University of Illinois at Urbana-Champaign. Prior to joining UCLA in 2016, she was an Assistant Professor in the Faculty of Information and Media Studies at Western University in London, Ontario for three years. On the internet since 1993, she was previously an information technology professional for 15 years, and, as such, her research interests focus on information work and workers and on the social, economic and political impact of the widespread adoption of the internet in everyday life.

Since 2010, the main focus of her research has been to uncover the ecosystem – made up of people, practices and politics – of content moderation of major social media platforms, news media companies, and corporate brands.

She served as consultant to and is featured in the award-winning documentary The Cleaners, which debuted at Sundance 2018 and aired on PBS in the United States in November 2018.

Roberts is frequently consulted by the press and others on issues related to commercial content moderation and to social media, society and culture, in general. She has been interviewed on these topics in print, on radio and on television worldwide including: The New York Times, Associated Press, NPR, Le Monde, The Atlantic, The Economist, BBC Nightly News, the CBC, The Los Angeles Times, Rolling Stone, Wired, The Washington Post, Australian Broadcasting Corporation, SPIEGEL Online, and CNN, among many others.

She is a 2018 Carnegie Fellow and a 2018 recipient of the EFF Barlow Pioneer Award for her groundbreaking research on content moderation of social media.

She tweets as @ubiquity75.

This episode streamed live on Thursday, October 1, 2020. Here’s an archive of the show on YouTube:

About the show:

The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill.

Subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube for updates.

Transcript

01:43
all right
01:44
hey humans
01:48
how we doing out there come on in start
01:50
gathering around the uh the old digital
01:52
campfire
01:54
let me hear from those of you who are in
01:55
line uh right now tell me
01:57
tell me who’s out there and tell me
01:59
where you’re tuning in from
02:01
i hope you’re starting to get your
02:02
questions and thoughts ready
02:04
for our guest i’m sure many of you have
02:06
already seen who our guest is and i’ll
02:07
be reading her bio here in just a moment
02:09
so start thinking of your questions
02:11
about commercial content moderation and
02:13
what you want to
02:14
know about that and you know all that
02:17
kind of stuff
02:18
uh i hear sarah laughing in the
02:19
background it’s not to laugh
02:22
really good valid questions i think i
02:25
was just snorting
02:26
honestly through my uh through my sinus
02:29
trouble
02:30
so uh welcome to those of you who are
02:32
all tuned in welcome to the tech
02:34
humanist show this is a multimedia
02:36
format program
02:37
exploring how data and technology shape
02:39
the human experience
02:41
and i am your host kate o’neil so i hope
02:44
you’ll subscribe and follow wherever
02:45
you’re catching this
02:46
so that you won’t miss any new episodes
02:49
i
02:50
am going to introduce our guest here in
02:51
just a moment uh one one last shout out
02:53
if anybody’s out there wanting to say hi
02:56
feel free
02:56
you are welcome to comment and i see a
02:59
bunch of you
03:00
online so feel free to tune uh
03:03
comment in and tell me who you are and
03:05
where you’re tuning in from
03:07
but just get those you know type in
03:08
fingers warmed up because we’re gonna
03:10
want you to
03:10
to weigh in with some questions and
03:12
comments as the show goes on
03:14
but now i’ll go ahead and introduce our
03:17
esteemed guest so today we have the
03:19
very great privilege of talking with
03:21
sarah t roberts who
03:22
is an assistant professor in the
03:24
department of information studies
03:26
graduate school of education and
03:28
information studies at ucla
03:30
she holds a phd from the ischool at the
03:32
university of illinois urbana-champaign
03:34
my sister’s school i went to university
03:36
of illinois chicago
03:38
prior to joining ucla in 2016 she was an
03:40
assistant professor
03:42
in the faculty of information and media
03:44
studies at western university in london
03:46
ontario for three years
03:47
on the internet since 1993 she was
03:50
previously an information technology
03:52
professional for 15 years and as such
03:54
her research interests focus on
03:56
information work and workers and on the
03:58
social
03:59
economic and political impact of the
04:01
widespread adoption of the internet in
04:02
everyday life right totally
04:06
so since 2010 the main focus of her
04:08
research has been to uncover the
04:10
ecosystem
04:11
made up of people practices and politics
04:14
of content moderation of major social
04:16
media platforms
04:17
news media companies and corporate
04:19
brands
04:20
she served as consultant tune is
04:21
featured in the award-winning
04:22
documentary
04:23
the cleaners which debuted at sundance
04:26
2018
04:27
and aired on pbs in the united states in
04:29
november
04:30

  1. so roberts is frequently consulted
    04:33
    by the press and others on issues
    04:34
    related to commercial content moderation
    04:36
    and to social media society and culture
    04:38
    in general
    04:39
    she’s been interviewed on these topics
    04:41
    in print on radio
    04:42
    on television worldwide and now on the
    04:44
    tech humanist show
    04:45
    uh including the new york times
    04:47
    associated press npr
    04:48
    le monde the atlantic i mean this list
    04:50
    is going to go on and on so
    04:52
    buckle in folks the economist bbc
    04:55
    rolling stone wired and picking and
    04:57
    choosing now it’s a really really
    04:59
    impressive list of media
    05:00
    she’s a 2018 carnegie fellow and a 2018
    05:04
    recipient of the eff barlow
    05:06
    pioneer award for her groundbreaking
    05:08
    research on content moderation
    05:10
    of social media so audience again please
    05:12
    start getting your questions ready for
    05:13
    our outstanding guest
    05:15
    please do note as a live show i well
    05:17
    i’ll do my best to vet comments and
    05:19
    questions in real time
    05:20
    we may not get to all of them but very
    05:23
    much appreciate
    05:24
    you being here tuned in and
    05:25
    participating in the show so with that
    05:27
    please welcome uh our dear guest
    05:31
    sarah t roberts and you are live on the
    05:34
    show
    05:34
    sarah thank you so much for being here
    05:37
    thank you uh
    05:38
    thanks for the invitation and thanks to
    05:40
    your audience and
    05:41
    uh all those interested folks who are
    05:44
    spending time with us today i’m really
    05:45
    grateful
    05:46
    for the opportunity we’ve already got uh
    05:48
    david polgar
    05:49
    saying excited for today’s talk hey our
    05:52
    buddy
    05:53
    dave drp
    05:54
    [Laughter]
    05:56
    all right so i wanna talk right away
    05:59
    about your um
    06:01
    your book behind the screen i i hadn’t
    06:03
    had a chance to read and until i was
    06:05
    preparing for the
    06:06
    show and it was it was wonderful to get
    06:07
    a chance to dig into your research
    06:09
    so tell us a little bit about that came
    06:11
    out last year is that right
    06:13
    um yeah it just just a little over a
    06:15
    year ago uh
    06:16
    came out on on yale university press
    06:19
    um you know the academic
    06:23
    publishing cycle is its own beast it’s
    06:25
    its own world
    06:26
    it uh as it relates to
    06:29
    um kind of like journalism and and
    06:31
    mainstream press timelines it’s much
    06:33
    slower
    06:34
    that said uh i wrote the book in about a
    06:37
    year which is about a normal
    06:39
    a normal cycle but it took about eight
    06:42
    years to put together the research that
    06:44
    went into the book
    06:46
    and this is because when i started my
    06:48
    research in 2010
    06:50
    which you know we say 2010 it seems like
    06:53
    yesterday that was a decade ago now
    06:55
    you know if we’re in terminable 2020
    06:59
    you know which is which is a million
    07:01
    years long so far but
    07:03
    back in 2010 when i started looking into
    07:05
    this topic as a
    07:07
    as a doctoral researcher at the
    07:09
    university of illinois
    07:10
    uh you know there were a lot of things
    07:12
    stacked against that endeavor
    07:14
    including the fact that i was a doctoral
    07:16
    student at the university of illinois i
    07:17
    had no cachet i had very few
    07:20
    like material resources um you know to
    07:23
    finance
    07:24
    a study that would require uh
    07:27
    at the end of the day required going
    07:29
    around the world quite literally
    07:32
    but maybe the biggest barrier at the
    07:34
    time was the fact
    07:36
    that i was still fighting an uphill
    07:38
    battle trying to tell people
    07:40
    that major mainstream social media
    07:43
    platforms
    07:44
    were engaged in a practice that is now
    07:47
    weirdly um you know a phrase that you
    07:51
    might say around the dinner table and
    07:52
    everyone would get which is content
    07:54
    moderation
    07:55
    and that further when i would um raise
    07:58
    the issue
    08:00
    and and bring up the fact that firms
    08:01
    were engaged in this practice which
    08:04
    you know has to do with the adjudication
    08:06
    of people’s
    08:08
    self-expression online and sits
    08:10
    somewhere between users
    08:13
    and the platform and then the platform’s
    08:15
    recirculation of users material
    08:18
    uh you know people would argue with me
    08:20
    at that point
    08:22
    about the fact that that practice would
    08:24
    even go on
    08:25
    and then when i would say that uh you
    08:27
    know kind of offer
    08:28
    incontrovertible proof that in fact it
    08:30
    did go on uh
    08:32
    then we would uh find ourselves in a
    08:34
    debate about whether or not
    08:36
    it was a legion of human beings
    08:40
    who was undertaking this work or uh in
    08:43
    fact it was computational
    08:45
    now in 2010 in 2020 the landscape is
    08:48
    complicated but in 2010
    08:51
    the technology and the sort of
    08:53
    widespread adoption
    08:54
    of of computational uh
    08:58
    automated let’s say algorithmic kinds of
    09:01
    content moderation or machine learning
    09:03
    and forum content moderation was not a
    09:05
    thing
    09:05
    it was humans and so i had to start the
    09:09
    conversation
    09:10
    so far below baseline
    09:14
    that it you know it took uh it took
    09:17
    quite a lot of effort just to get
    09:19
    everybody on the same page to discuss it
    09:22
    and you know when i’m talking about
    09:24
    uh engaging in these conversations i
    09:27
    mean just like trying to vet this as a
    09:29
    as an appropriate research topic at the
    09:32
    graduate school you know what i mean
    09:34
    like to get faculty members
    09:36
    many of whom were world experts in in
    09:39
    various aspects of uh of the internet or
    09:42
    of
    09:42
    media or information systems themselves
    09:46
    um it was new to them too that was did
    09:49
    you originally frame it was it it’s a
    09:51
    question of how
    09:52
    is this done or what was the original
    09:54
    framework of that question yeah
    09:56
    so i’ll tell you a little bit about the
    09:57
    origin of why i got interested
    10:00
    and it’s something that i write about in
    10:01
    the book because i think it’s so
    10:03
    important to acknowledge kind of those
    10:06
    those antecedents i had read i was
    10:08
    actually teaching down at the university
    10:10
    of illinois in the summer
    10:12
    of 2010 and i was on a break from
    10:15
    teaching and
    10:16
    you know probably drinking a latte which
    10:18
    is what i’m doing right now
    10:19
    and um and uh uh reading the paper i was
    10:23
    reading the new york times and there was
    10:24
    a very small
    10:26
    uh but compelling article in the new
    10:28
    york times about a group of workers
    10:30
    who were there there were a couple of
    10:32
    sites they mentioned but there was in
    10:33
    particular a group of workers in rural
    10:35
    iowa well here i was sitting in rural
    10:38
    central illinois thinking about this
    10:40
    group of workers in rural iowa as
    10:42
    profiled in this piece
    10:44
    who were in fact engaging in what we now
    10:46
    know as commercial content moderation
    10:48
    they were working
    10:49
    in effectively a call center uh
    10:53
    adjudicating content for unnamed kind of
    10:55
    you know
    10:56
    media sites websites and social media
    10:59
    properties
    11:00
    and i kind of circulated that article
    11:03
    around i shared it with friends i shared
    11:05
    it with my colleagues and i shared it
    11:06
    with professors and
    11:07
    the argument that i made was that it was
    11:10
    it was multifaceted first of all it
    11:12
    sounded like a miserable
    11:14
    job and guess what that has been borne
    11:16
    out it is a
    11:17
    very difficult and largely unpleasant
    11:20
    job
    11:21
    uh so i was captivated by that fact that
    11:24
    there were these you know
    11:25
    unnamed people who a generation or two
    11:28
    ago would have been on a family farm
    11:30
    who were now in the quote unquote
    11:32
    information economy but seemed to be
    11:34
    doing
    11:34
    a drag just awful work
    11:38
    uh but also there was this bigger issue
    11:41
    of
    11:42
    uh you know really having this this big
    11:44
    reveal
    11:45
    of the of the actual
    11:48
    ecosystem an unknown here for unknown
    11:51
    portion of the social media ecosystem
    11:54
    effectively letting us know how the
    11:56
    sausage was being made right
    11:58
    and yet if you were to look at any of
    12:01
    the
    12:02
    the uh the social media platforms
    12:05
    themselves or any of the discourse at
    12:06
    really high levels in
    12:08
    industry or in regulatory bodies this
    12:11
    was not
    12:12
    this was a non-starter but i was was
    12:14
    arguing at the time
    12:16
    that how content was being adjudicated
    12:18
    on the platforms
    12:20
    under what circumstances under what
    12:23
    conditions and under what policies was
    12:25
    in fact
    12:27
    maybe the only thing that mattered at
    12:29
    the end of the day
    12:30
    right now in 2010 that was a little bit
    12:32
    of a harder case to make
    12:34
    by 2016 not so much after we saw the uh
    12:38
    the ascent of donald trump in the united
    12:40
    states we saw brexit
    12:42
    we saw uh this the rise of bolsonaro and
    12:45
    in brazil largely
    12:46
    uh attributed to um
    12:49
    social media campaigns there and kind of
    12:52
    discontinued sustained
    12:54
    support through those channels uh and
    12:57
    here we are in 2020 where uh
    13:00
    we might argue or we might claim that
    13:02
    misinformation and disinformation online
    13:04
    is one of the primary
    13:06
    concerns of civil society today
    13:09
    and i would put front and center
    13:13
    in those all of those discussions
    13:16
    the fact that social media companies
    13:18
    have this incredible immense power
    13:20
    to decide what stays up and what doesn’t
    13:24
    and how they do it and who they engage
    13:27
    to do it
    13:28
    should actually be part of the
    13:30
    conversation if not
    13:31
    i would argue that it’s a very
    13:33
    incomplete conversation so when i talk
    13:35
    about like the
    13:36
    scholarly publishing cycle it took a
    13:39
    year to put the book out right but it
    13:40
    took eight years to amass the evidence
    13:44
    to um to do the to the interviews and
    13:47
    media that you mentioned
    13:48
    to converse with industry people at the
    13:51
    top levels eventually but
    13:52
    you know starting at the bottom with the
    13:54
    workers themselves to find workers who
    13:56
    are willing
    13:56
    to talk to me and break those
    13:58
    non-disclosure agreements that they were
    14:00
    under um and to kind of create also
    14:04
    a a locus of activity for other
    14:07
    researchers and scholars and activists
    14:09
    who are also interested in in uncovering
    14:12
    uh this area and really sort of create
    14:14
    co-create a field of study so that’s
    14:17
    what took eight years it took a year to
    14:18
    get the book out
    14:19
    um but all that legwork of proving in a
    14:22
    way
    14:23
    that this mattered took a lot longer i
    14:25
    don’t have to make that same case
    14:27
    anymore
    14:27
    as i’m sure you you can imagine um
    14:30
    people people are interested they’re
    14:33
    concerned
    14:34
    and um they want to know more they’re
    14:36
    demanding a lot more
    14:38
    um from firms as users
    14:41
    you know as people who are now engaged
    14:43
    in social media in some aspect
    14:45
    of their lives every day need i say more
    14:48
    about zooming
    14:49
    constantly which is now our you know our
    14:52
    primary
    14:53
    medium of connection for so many of us
    14:55
    in our work lives even
    14:57
    yeah hey we already have a question from
    15:00
    our buddy drp david ryden-polgar let me
    15:04
    uh
    15:04
    put this against the background we can
    15:06
    actually see it here uh
    15:08
    he says sarah would love to hear your
    15:10
    thoughts on section 23
    15:12
    230 and how any potential changes would
    15:15
    impact content moderation
    15:16
    so we’re going right in right deep yeah
    15:19
    really
    15:20
    so um let me try to flush that out a
    15:22
    little bit
    15:24
    for others who aren’t um you know inside
    15:26
    quite as as deep
    15:28
    um section 230 is
    15:31
    a part of the uh communications decency
    15:34
    act which goes back to 1996 but
    15:36
    effectively what what anyone needs to
    15:38
    know about section 230 is that
    15:40
    it’s the it it’s sort of the legal
    15:42
    framework
    15:43
    that informs social media companies
    15:48
    rights and responsibilities around
    15:51
    content
    15:52
    when we think about legacy media um
    15:55
    so-called uh broadcast television for
    15:58
    example or other other forms of of media
    16:01
    that we consume
    16:02
    you know i always bring up the the
    16:04
    example of george carlin who
    16:06
    famously um uh
    16:10
    you know made a career out of the seven
    16:12
    dirty words that you couldn’t say
    16:13
    on radio right so there are all kinds
    16:16
    of governing uh
    16:19
    legal and other kinds of norms about
    16:22
    what is allowed and disallowed in some
    16:24
    of these legacy media
    16:26
    when it comes to social media however
    16:30
    there is a pretty
    16:35
    drastically contrasted permissiveness
    16:38
    that is in place uh that
    16:41
    seeds the power of the decision-making
    16:44
    around
    16:45
    what is allowable and what is not
    16:46
    allowable to the platforms themselves so
    16:49
    this is a really different kind of
    16:50
    paradigm right
    16:52
    and it’s section 230 that allows that
    16:54
    that’s the
    16:55
    that’s the precedent that’s the that’s
    16:57
    the guidance uh
    16:58
    legally that uh that provides that kind
    17:01
    of
    17:02
    uh both responsibility and discretion
    17:05
    and what it does is it allows the
    17:07
    companies
    17:08
    um to make their own decisions
    17:12
    effectively
    17:13
    about what policies they will follow
    17:15
    internally now this doesn’t go for
    17:17
    every single piece of content you know
    17:18
    one of the the biggest examples that
    17:21
    uh that this does not cover is child
    17:24
    sexual exploitation material which is
    17:25
    just illegal full stop it doesn’t matter
    17:28
    if platforms wanted to traffic in that
    17:30
    material or not it’s illegal
    17:32
    but beyond that just to certain to a
    17:35
    certain extent what section 230 allows
    17:38
    is for platforms to redistribute
    17:42
    effectively material that other people
    17:44
    submit
    17:45
    uh without being held liable for that
    17:47
    material
    17:48
    and so if we think about that that’s
    17:50
    actually the business model of social
    17:51
    media
    17:52
    the business model of social media is to
    17:54
    get other people to create content
    17:56
    upload it circulate it and engage with
    17:59
    it download it
    18:00
    and effectively the platforms have um
    18:03
    you know argued and claimed that they
    18:04
    are really
    18:05
    you know don’t kill the messenger right
    18:07
    like they’re just like the
    18:08
    the the apparatus by which this material
    18:10
    gets shared
    18:12
    i think that um
    18:15
    you know at one time that really made
    18:16
    sense particularly when the
    18:18
    when this uh when the communications
    18:20
    decency act was passed and this goes
    18:22
    back in
    18:23
    into the mid 90s when what was
    18:26
    kind of imagined as needing this this
    18:29
    uh reprieve from liability was an isp an
    18:33
    internet service provider
    18:35
    which at that time uh i guess the most
    18:38
    imaginative version of that you could
    18:40
    think of would be america online for
    18:41
    those of you who
    18:42
    remember that on the program shout out
    18:45
    to the aol days yeah
    18:47
    right aol like all the you know the
    18:49
    discs and cd-roms you got and used as
    18:51
    coasters
    18:52
    um but you know back in that time but an
    18:55
    internet service provider really was a
    18:57
    pass-through in some cases you know i
    18:58
    knew a guy who ran an isp locally
    19:01
    he really just had a room with a with a
    19:03
    huge internet pipe coming in
    19:06
    and a wall of modems and you would dial
    19:08
    up through your modem and connect
    19:10
    through and then be on the internet to
    19:11
    some other service
    19:12
    so that was the model then but the model
    19:15
    now
    19:15
    uh is you know multi-billion dollar
    19:19
    transnational corporations
    19:21
    uh who have immense power in decision
    19:24
    making around content
    19:26
    and yet are are uh
    19:29
    in the american context at least largely
    19:32
    not liable for those decisions
    19:34
    uh legally or or otherwise um
    19:38
    making incredibly powerful
    19:42
    decisions about what kind of material we
    19:45
    all see and engage in
    19:47
    and what is permissible and what is not
    19:49
    online and they do that at their
    19:50
    discretion well if they’re doing that at
    19:52
    their discretion
    19:54
    do you think that they’re largely going
    19:56
    to um
    19:58
    fall into a mode of altruism and like
    20:01
    what’s best
    20:01
    for civil society are they going to look
    20:03
    at their bottom line
    20:05
    and their shareholder demands and
    20:07
    respond to that i mean
    20:09
    the audience yeah i mean frankly
    20:12
    publicly traded companies
    20:13
    have a legal mandate to respond to their
    20:15
    shareholders and to generate revenue for
    20:17
    them so
    20:18
    um when those things are at odds when
    20:20
    when those things are aligned with
    20:22
    what’s good for you know
    20:23
    america is good for uh facebook’s
    20:26
    internal policies around content
    20:28
    moderation that works out great
    20:29
    but if there’s you know if ever those
    20:32
    two pathways should diverge
    20:34
    we know which one they’re going to fall
    20:35
    under and there’s just there’s very
    20:37
    little
    20:37
    um legal consequence or legal uh
    20:41
    expectation for uh reporting out on how
    20:46
    uh these decisions get made the way that
    20:48
    that
    20:49
    we have seen more decisions getting uh
    20:52
    publicly
    20:53
    unveiled through things like um
    20:56
    the publication of of what had been
    21:00
    previously kind of closely held secret
    21:03
    policies internally is through public
    21:06
    pressure
    21:06
    through the pressure of civil society
    21:08
    groups and advocacy groups through the
    21:10
    pressure
    21:11
    of the public through the pressure and
    21:13
    the constant threat of
    21:15
    you know things like reform to section
    21:17
    230 or other kinds of
    21:19
    regulation so it’s a very interesting
    21:23
    moment and it’s interesting to bring up
    21:24
    section 230 because
    21:26
    again a couple of years ago i had
    21:28
    colleagues um
    21:30
    who are in uh legal studies and who are
    21:34
    you know law professors essentially tell
    21:36
    me that 230 would soon be rendered
    21:38
    moot anyway because it’s just it’s it’s
    21:41
    you know based on um on
    21:45
    well it should be solely relevant in the
    21:47
    united states right in the jurisdiction
    21:49
    of the united states
    21:50
    and so because these platforms were
    21:52
    going worldwide
    21:54
    uh you know there
    21:57
    it would be rendered mood well i would
    21:59
    say it’s actually been the opposite
    22:00
    that’s right that what is happening is
    22:02
    that section 230 is getting bundled up
    22:04
    as the norm
    22:06
    and is now being promulgated either just
    22:09
    through uh through the process of these
    22:13
    platforms going global but kind of
    22:14
    keeping their americanness and
    22:16
    keeping their um their response their
    22:20
    you know business practices largely
    22:22
    responsible to american laws first and
    22:24
    foremost
    22:25
    but also even to the point that uh you
    22:28
    know it recently
    22:29
    has become known i think more and more
    22:32
    to people like me who aren’t legal
    22:34
    scholars but who have a great interest
    22:36
    in how this stuff goes down that section
    22:39
    230 like language
    22:41
    is being bundled up and put into trade
    22:44
    agreements
    22:45
    uh at the nation state level or
    22:48
    you know region level with the united
    22:50
    states and trading partners and we know
    22:52
    that
    22:53
    you know these these trade agreements
    22:56
    which have been you know huge hugely
    22:57
    politically
    22:59
    uh problematic and were a major issue in
    23:03
    fact of the 2016 election
    23:05
    uh you know they’re they’re they’re
    23:07
    anti-democratic i mean how do you even
    23:09
    know what’s in a trade agreement they’re
    23:10
    totally secret
    23:12
    uh but i i learned while watching a uh
    23:15
    uh house uh subcommittee
    23:19
    uh convening about section 230 from
    23:22
    a highly placed google executive
    23:26
    that in fact their their lobbyists are
    23:28
    pushing for this kind of language in
    23:31
    in these trade agreements so we see that
    23:33
    instead of 230 becoming less relevant
    23:35
    because of the globalization
    23:37
    of american social media platforms it’s
    23:39
    actually becoming a norm that is now
    23:42
    being
    23:43
    first of all it was sort of like softly
    23:45
    reproduced just because of the spread of
    23:47
    these american platforms and
    23:49
    how they were doing business but now
    23:50
    it’s actually becoming codified
    23:52
    through other means means like like
    23:55
    trade agreements that the public has
    23:57
    really no
    23:58
    mechanism to intervene upon and i think
    24:00
    that’s really worrisome
    24:02
    what about those mechanisms where the
    24:04
    sorry what were you gonna say
    24:06
    no okay i was just gonna say that’s one
    24:07
    of my short and concise professorial
    24:09
    answers
    24:11
    let me drink a coffee well david
    24:14
    uh thanks you for that uh great
    24:17
    historical overview and i’m sure
    24:18
    the rest of our viewers and listeners do
    24:20
    too i i wonder about the ones
    24:22
    the the examples that don’t have that
    24:25
    kind of
    24:26
    uh consumer involvement so i’m wondering
    24:28
    about for example
    24:29
    you know youtube and it’s kids content
    24:32
    and
    24:33
    and so there have been a lot of changes
    24:35
    it seems like
    24:36
    with regard to that that platform and
    24:38
    that subject over the
    24:40
    over the last few years so can you maybe
    24:42
    give us an overview of
    24:43
    how that has gone down um
    24:46
    well i think that you know youtube is
    24:49
    such an interesting example
    24:51
    to talk about for for many reasons uh
    24:53
    for its reach and pervasiveness you know
    24:56
    it’s a
    24:56
    market leader for sure it’s globality i
    24:59
    would also say that youtube is
    25:01
    particularly interesting because when we
    25:04
    think about
    25:05
    uh social media content as being
    25:10
    monetized there is no greater
    25:13
    and more direct example than youtube
    25:15
    where it actually pays people who are
    25:17
    really highly successful on the platform
    25:19
    for content right
    25:20
    so like when there’s no kind of like a
    25:23
    metaphor there about monetization it is
    25:25
    literally monetized right
    25:27
    um and this you know just to kind of tie
    25:30
    this back to the section 230
    25:31
    conversation
    25:32
    when we imagined isps as just path
    25:35
    pass-throughs you know that was one
    25:37
    thing but here we have
    25:39
    these huge companies like youtube and
    25:40
    others involved actively
    25:43
    in production so that kind of like
    25:46
    firewall between just being an
    25:48
    intermediary and actually being actively
    25:50
    engaged in producing media
    25:51
    has gone but the there’s like a legacy
    25:54
    legal environment that it still
    25:56
    informs it so youtube you know they pay
    25:58
    producers they have these like
    26:01
    uh pretty extraordinary studios in
    26:05
    in major uh in major
    26:08
    cities around the world including la
    26:10
    where i live
    26:12
    uh they you know they are kind of the
    26:15
    go-to outlet and people
    26:18
    want to participate in youtube for all
    26:20
    sorts of reasons but there’s certainly
    26:21
    you know a dollar sign reason that
    26:24
    people get involved
    26:25
    and you bring up this issue of kids
    26:27
    content
    26:28
    um again here’s where we see sort of
    26:31
    like the softening and the eroding of
    26:33
    regulation too it
    26:35
    started it’s it’s not just youtube i
    26:36
    have to confess it’s not just
    26:38
    social media companies that have eroded
    26:40
    uh you know child protections around
    26:42
    um media that that goes back to the you
    26:45
    know 40 years ago in the reagan
    26:47
    administration when there used to be
    26:48
    very stringent rules around
    26:50
    uh saturday morning cartoons for example
    26:52
    and advertising to children that could
    26:54
    go on
    26:55
    during that time uh shout out to my
    26:58
    colleague molly neeson who has worked
    27:00
    extensively on that
    27:01
    on that particular topic and that
    27:02
    erosion so
    27:05
    i see uh on on youtube again
    27:08
    a lot of the pressure to kind of reform
    27:11
    and
    27:11
    i think when you’re talking about kids
    27:13
    content you’re talking about
    27:15
    some of like some like really disturbing
    27:17
    and weird content that was showing up
    27:20
    um you know kind of like cheaply made
    27:22
    unknown
    27:23
    weird creepy sometimes not really
    27:25
    clearly
    27:27
    necessarily uh
    27:30
    benevolently made like you know
    27:33
    sometimes creepy sexual undertones
    27:36
    uh other kinds of stuff going on you
    27:38
    know really and really no way to know
    27:40
    that’s part of the problem no way to
    27:42
    know right um
    27:43
    and then uh the massive problem of
    27:46
    trying to
    27:48
    moderate that material right um you know
    27:51
    i think of it
    27:52
    as like the the classic story of the the
    27:55
    whole
    27:56
    springing through the the dyke holding
    27:58
    the water back you know
    27:59
    you plug one hole another one springs
    28:02
    open
    28:02
    so it’s a little bit falls down so the
    28:05
    whole wall
    28:06
    and then your inundated that’s right
    28:07
    that’s right and so
    28:09
    you know that is a good metaphor to
    28:10
    think about the problem of these like
    28:12
    kind of isolated
    28:14
    uh hot spots that explode on platforms
    28:17
    as a new social issue or maybe a new
    28:21
    uh a geopolitical conflict erupts
    28:25
    somewhere in the world it’s you know
    28:26
    gets meted out and replicated on social
    28:28
    media and attention gets drawn to it
    28:31
    and so i think this issue of child
    28:34
    content and its kind of exploitive
    28:35
    nature and
    28:36
    strange nature in some cases was
    28:38
    something that advocacy groups and
    28:40
    others brought attention to
    28:41
    and the platform had to reconfigure and
    28:44
    focus on it
    28:45
    now i mentioned earlier that you know
    28:47
    back in 2010 it really was humans who
    28:49
    were doing this work almost exclusively
    28:50
    but by 2020
    28:52
    we are using computational tools
    28:55
    to try to deal with content as well
    28:57
    although i
    28:58
    i’ll repeat the quote that i once heard
    29:00
    from a reporter
    29:02
    who who heard it from a an engineer at a
    29:05
    company that shall not be named but it
    29:06
    might sound like
    29:08
    um you know boo-boob let’s say might
    29:10
    rhyme with that
    29:11
    uh and the quote was uh whatever the
    29:14
    algorithm is doing it’s
    29:15
    not watching the video so you know
    29:17
    they’re using these computational
    29:19
    mechanisms to do all kinds of other
    29:21
    stuff but it’s not like
    29:22
    an algorithm can watch and sense make
    29:25
    out of a video it has to look at other
    29:26
    stuff
    29:28
    so that’s an interesting point though
    29:30
    too and i want to follow up on that with
    29:31
    a question about
    29:32
    you know do you do you personally
    29:34
    advocate for more
    29:35
    ai in the mix of con of content
    29:38
    moderation such as you know facebook
    29:39
    recently made an announcement that they
    29:40
    were using
    29:41
    ai to simulate bad actors so that they
    29:44
    could train their moderation
    29:45
    systems automated moderation systems to
    29:47
    more effectively recognize it do you
    29:49
    think that that ultimately
    29:50
    will work and will benefit the humans
    29:52
    who are part of this ecosystem or
    29:54
    is it likely to produce unintended ill
    29:56
    effects so i mean that’s a really great
    29:59
    question because that’s sort of like the
    30:01
    64 000 question about my work if
    30:04
    you know one would one would think if my
    30:05
    concern is the welfare of workers
    30:08
    which has always kind of been my cut in
    30:10
    on this topic and where i start and
    30:11
    where i come back to an end
    30:13
    um then hey wouldn’t it be great if
    30:15
    tomorrow we could just flip that switch
    30:16
    and go
    30:17
    to those uh purely computational means i
    30:20
    think that
    30:21
    in theory right in theory but i think
    30:24
    there are a lot of red flags there
    30:26
    you know one red flag is that if it’s
    30:29
    been this difficult
    30:30
    as and i kind of laid the groundwork for
    30:32
    that at the at the front end of the show
    30:34
    to unpack and uncover uh
    30:37
    the ecosystem involving humans and i
    30:39
    have to say
    30:40
    the majority of my work has been
    30:43
    reliant upon the willingness of human
    30:46
    beings involved in the system
    30:48
    to leak essentially to break
    30:51
    their non-disclosure agreements and to
    30:54
    you know essentially snitch on what they
    30:56
    felt was
    30:58
    problematic also sometimes what they
    31:00
    felt was good about the work they did
    31:02
    how do you get uh an algorithm or a
    31:04
    machine learning based tool
    31:06
    to call a journalist or
    31:09
    uh you know do an interview with a
    31:11
    researcher
    31:13
    i don’t know how to do that you know the
    31:14
    closest thing we could come to is
    31:16
    getting access to it and looking
    31:18
    at code but that’s not easy to do and
    31:20
    it’s much harder to do
    31:22
    than finding uh and i cannot stress the
    31:25
    difficulty of what it was like
    31:27
    in the early days to find people willing
    31:29
    to talk to me so
    31:30
    you know you can’t do that with ai how
    31:32
    do we how do we audit those tools how do
    31:34
    we
    31:35
    how do we you know what’s the check on
    31:37
    power that the firms have with those
    31:39
    tools
    31:40
    in terms of how they’re set up and what
    31:42
    they keep in and what they keep
    31:43
    out it also sounds like a potentially
    31:46
    even greater violation
    31:47
    of uh that non-disclosure if someone
    31:50
    leaks a bit of code
    31:51
    rather than just tell their own personal
    31:53
    story oh for sure i mean and and
    31:56
    you know the the other thing too that
    31:58
    that comes to mind for me is
    32:00
    the nature of how these tools work
    32:03
    and you know a great worry and i think a
    32:05
    legitimate worry of many people in the
    32:07
    space
    32:07
    is that uh they
    32:11
    the tendency to use those tools would be
    32:13
    to
    32:14
    uh calibrate them
    32:17
    to be even uh less permissive let’s say
    32:21
    or to you know because of their nature
    32:23
    they would have less of an
    32:24
    ability to look at a given piece of
    32:27
    content
    32:28
    and you know see that it violates abc
    32:31
    policy but understand it in the context
    32:34
    of you know again
    32:35
    a cultural expression or um
    32:38
    you know an advocacy piece around a
    32:41
    conflict zone
    32:42
    and then make an exception so what we
    32:44
    would see
    32:45
    is uh more conservative and greater
    32:49
    false positives around material that
    32:52
    quote unquote is disallowed right
    32:55
    again all of this adjudicating to the
    32:58
    logic that the firms themselves create
    33:00
    which for um for many years itself was
    33:03
    opaque
    33:05
    uh so this is you know it’s not as easy
    33:08
    to say unfortunately if we could just
    33:10
    get those darn algorithms right if we
    33:11
    could just get
    33:12
    you know machine learning to get
    33:13
    sophisticated enough we could
    33:16
    take out the human element and and
    33:18
    basically
    33:19
    you know save people from having to do
    33:21
    this work
    33:23
    unfortunately i think it’s more
    33:24
    complicated than that and i would say
    33:26
    that
    33:26
    you know bringing up the idea of
    33:29
    training machine learning tools as you
    33:30
    did
    33:31
    one of the gross ironies of this whole
    33:33
    thing that i’ve been
    33:34
    monitoring is that uh
    33:38
    content moderation commercial content
    33:40
    moderation for these major platforms
    33:42
    is its own kind of self-fulfilling uh
    33:46
    industry that begets uh sub industries
    33:49
    in and of itself
    33:49
    so that when machine learning tools have
    33:52
    come on what needs to happen
    33:54
    is that people need to sort data sets to
    33:56
    create data sets for the machine
    33:58
    learning tools to train on
    33:59
    and they need to be themselves trainers
    34:02
    and classifiers for the machine learning
    34:04
    tools so now we have a whole new stratum
    34:06
    of people
    34:07
    working to train machine learning
    34:09
    algorithms which has them essentially
    34:11
    doing a certain kind of content
    34:12
    moderation
    34:13
    it’s a lot easier that cottage industry
    34:14
    of evil ai
    34:16
    spawn it’s like anything like
    34:19
    how are we gonna make the ai bad enough
    34:21
    to train our ai
    34:23
    uh automation systems to recognize that
    34:25
    so that we can keep a good environment
    34:27
    but then you’ve got this whole cottage
    34:29
    industry around the bad
    34:30
    ai seems like a very awkward way of
    34:32
    going
    34:33
    so you know as someone who monitors like
    34:36
    like hiring trends and things like that
    34:37
    too
    34:38
    i was i was watching companies looking
    34:41
    for people to to come be
    34:42
    classifiers on data sets which is just
    34:44
    moderation before the fact right
    34:46
    yeah you know you talked about that in
    34:48
    the book too you have
    34:50
    you presented a taxonomy of sorts of
    34:52
    labor arrangements from
    34:53
    in-house moderators to what you call
    34:56
    micro labor you know looking at
    34:58
    mechanical turk and things like that can
    34:59
    you walk us through that a little bit so
    35:01
    that we can become familiar with what
    35:02
    the
    35:02
    the human issues relative to each level
    35:06
    yeah one of the one of the early
    35:07
    insights i had when i was trying to
    35:09
    figure out the contours of this industry
    35:11
    from
    35:11
    you know the outside and it reminds me
    35:13
    of that parable of you know
    35:15
    people feeling different parts of the
    35:16
    elephant without really being
    35:18
    being able to see it and they don’t
    35:19
    really they don’t really get the big
    35:21
    picture
    35:22
    um was that you know what i was
    35:24
    considering as being kind of like a
    35:26
    monolithic
    35:27
    practice really wasn’t it was happening
    35:28
    in all kinds of different places and in
    35:30
    different guises
    35:32
    including using different names like
    35:33
    there was no kind of cohesive name to
    35:35
    call
    35:36
    this this work practice so i started out
    35:38
    kind of knowing about these workers
    35:40
    in in iowa that i reference in the book
    35:42
    and i referenced today
    35:44
    who were working in a call center and it
    35:46
    turned out that call centers were really
    35:48
    a prevalent way
    35:50
    that this work was going that it was um
    35:53
    you know kind of at somewhat of a remove
    35:55
    geographically and organizationally so
    35:57
    it’d be kind of like a third party
    35:59
    contracted out group of workers
    36:00
    somewhere in the world
    36:02
    when i started out i knew about the
    36:03
    workers in places like iowa florida etc
    36:06
    but i soon came to know about workers in
    36:08
    places like india
    36:09
    or in malaysia or of course key to the
    36:12
    book in the philippines
    36:13
    so that um that that call center
    36:16
    environment for content moderation work
    36:18
    is really prevalent
    36:20
    and it’s global but there are also
    36:23
    workers who
    36:24
    uh prior to covid we’re going every day
    36:26
    for example in the bay area down from
    36:28
    san francisco on the
    36:30
    company buses um and going on site to
    36:33
    companies
    36:34
    that i describe in the book one that has
    36:36
    the you know
    36:37
    pseudonym of megatech and is a stand-in
    36:40
    for
    36:40
    any number of companies in fact i’ll
    36:42
    just tell you a little anecdote that
    36:44
    i’ve met a lot of people from industry
    36:46
    who like over cocktails after meetings
    36:48
    will come up to me
    36:49
    all from different companies and say
    36:52
    we’re mega tech aren’t we and it’s like
    36:54
    you know like at least six different
    36:56
    corporations think they’re making
    36:57
    answers
    36:58
    yes yes sounds right yeah that tells you
    37:01
    something
    37:02
    so um you know these people were on site
    37:05
    workers they were
    37:06
    in you know the belly of the beast
    37:07
    essentially they were working
    37:09
    in places where there was also uh
    37:11
    engineering product development
    37:13
    marketing
    37:14
    uh communications you know soup to nuts
    37:16
    uh
    37:17
    although interestingly enough they were
    37:20
    also contractors in the case of the
    37:21
    books so
    37:22
    they still had this differential and
    37:24
    lesser status even though they were
    37:26
    going on site
    37:27
    to the corporate hq you know it still
    37:31
    wasn’t quite the right badge caller as
    37:33
    they described it to me although they
    37:35
    thought about the people who were
    37:36
    working as contractors and call centers
    37:38
    as another kind of worker
    37:40
    even though they were essentially very
    37:43
    very similar
    37:44
    then we had people that i encountered
    37:47
    who were
    37:48
    you know very entrepreneurial and
    37:50
    especially in in sort of the early days
    37:52
    were
    37:52
    developing a model that looks almost
    37:56
    like an ad agency they were
    37:58
    independent companies that were starting
    38:00
    to specialize in providing content
    38:02
    moderation services
    38:03
    to other companies and it was a boutique
    38:05
    kind of service
    38:06
    a specialty service and they would often
    38:09
    offer
    38:10
    social media management across the board
    38:13
    so not only were they offering
    38:14
    the removal of content in some cases but
    38:16
    they would even
    38:18
    offer again in that advertising model
    38:20
    the generation of content
    38:22
    because believe it or not sometimes you
    38:24
    know your auto parts company’s facebook
    38:26
    page just doesn’t
    38:27
    generate a lot of organic interest and
    38:29
    so you hire a company to come post about
    38:31
    how awesome your auto parts company is
    38:34
    um likewise if there’s a you know as
    38:37
    somebody once
    38:38
    told me and it’s in the book too if you
    38:40
    open a hole on the internet it gets
    38:41
    filled with
    38:43
    bleep with uh you know if you have
    38:46
    a web page or you have a facebook page
    38:48
    and there’s no activity
    38:49
    that’s like organic or really about what
    38:51
    it’s supposed to be about i guarantee
    38:52
    you that somebody will be posting
    38:54
    invective racist comments and so on
    38:56
    these boutique firms said
    38:58
    to usually to smaller companies hey
    39:00
    we’ll manage the whole thing we’ll
    39:01
    delete that stuff
    39:02
    we’ll generate new stuff for you it’ll
    39:04
    look organic nobody will really know
    39:06
    that that’s what we’re doing
    39:07
    and they were having great success when
    39:09
    i talked to them was that generally
    39:11
    filed under this sort of banner of user
    39:12
    generated content
    39:14
    or was it called other things generally
    39:16
    um
    39:17
    you know it was kind of like a social
    39:19
    media management is how they would call
    39:21
    couch that and how they would pitch it
    39:25
    and uh you know it was like uh hey
    39:28
    company x you your business has nothing
    39:31
    really to do with social media that’s
    39:33
    not
    39:33
    you know your primary business let us
    39:35
    handle it for you
    39:36
    and a lot of companies jumped at the
    39:38
    chance to kind of outsource that and not
    39:40
    deal with it
    39:41
    an interesting thing in that kind of
    39:43
    bucket of
    39:44
    of the taxonomy that you mentioned is
    39:46
    that those companies
    39:48
    uh in some cases got bought up by
    39:52
    ad firms or ad firms have started doing
    39:54
    this service as well
    39:56
    or they become really really big and
    39:58
    successful so there’s like a few that
    40:00
    kind of
    40:01
    uh uh rose to the top and have survived
    40:05
    and then you already mentioned this
    40:07
    really interesting and and kind of
    40:09
    worry some arena where this work goes on
    40:12
    which is in the micro labor realm
    40:14
    the amazon mechanical turk model
    40:17
    uh which is effectively you know digital
    40:19
    piece work it’s people
    40:21
    adjudicating a bit of content here
    40:23
    they’re often
    40:25
    paid a per view or per decision
    40:28
    uh and then they try to aggregate enough
    40:30
    to make that make sense for them
    40:31
    financially
    40:33
    and it it turns out although that’s
    40:36
    supposed to be an anonymous relationship
    40:38
    you know savvy mechanical turkers they
    40:40
    can figure out who they’re working for
    40:42
    because a lot of times
    40:43
    you know they’d receive a set of of
    40:46
    images or other content to adjudicate
    40:48
    and like you know the interface was
    40:50
    obvious
    41:00
    [Music]
    41:02
    before and you get those guidelines
    41:04
    again then you know yeah
    41:06
    that’s right so you know i i came to
    41:09
    know some folks who were
    41:10
    uh you know who themselves sort of began
    41:13
    to specialize within
    41:14
    mechanical turk and other platforms on
    41:17
    this kind of thing and they would seek
    41:18
    out this work because they got good at
    41:20
    it like you said
    41:21
    and they got good at knowing the
    41:22
    internal policies and juggling them for
    41:24
    all these different firms and
    41:26
    began to specialize in this work on that
    41:28
    platform
    41:29
    i was wondering you know when thinking
    41:31
    about this as you mentioned earlier
    41:33
    about the
    41:34
    the consequences of misinformation
    41:36
    especially as we
    41:37
    are deep in the process of the us
    41:40
    presidential election cycle and
    41:42
    i say the u.s because i want to be
    41:43
    sensitive to the fact that there are
    41:44
    global viewers but i feel like everyone
    41:46
    in the world is kind of
    41:48
    you know hooked into the u.s
    41:49
    presidential election right now
    41:51
    and we’re all like yeah aren’t they
    41:53
    right and we’re all being subject to
    41:55
    you know all of this uh well the the
    41:58
    dumpster fire of it all but also the
    42:00
    misinformation that accompanies it
    42:02
    and so i wonder how should people think
    42:04
    and understand the difference between
    42:07
    content on social media and content in
    42:09
    news media
    42:10
    and what are some of the differences in
    42:12
    approaches to moderating
    42:14
    harmful content and you know kind of
    42:16
    just thinking about
    42:18
    the access to you know free access to
    42:21
    information you know this is kind of a
    42:23
    big
    42:24
    muddy question i’m not sure i’m
    42:26
    articulating very well but
    42:27
    hopefully you see the direction of of
    42:29
    the um
    42:30
    the question that i’m asking her yeah i
    42:34
    i’ll i’ll do my best to respond and we
    42:36
    can
    42:36
    you know we can you can offer guidance
    42:40
    yeah as i go i mean i i think your
    42:43
    question in essence is what the hell
    42:45
    right yeah
    42:48
    information misinformation
    42:50
    disinformation the election
    42:52
    what the hell and so i think you speak
    42:54
    for a global audience when you pose that
    42:56
    question and
    42:58
    you’re right about the u.s election i
    43:00
    know uh friends and colleagues who were
    43:02
    up early in australia watching it and
    43:04
    you know as mortified as we were by the
    43:06
    the behavior on display
    43:08
    and the other night yes the debate and
    43:11
    the kind of the nadir
    43:12
    of uh you know american politics in my
    43:15
    lifetime is how i described it
    43:17
    um you know i i often
    43:20
    bring up the the rise of social media
    43:24
    as a force in again in american civic
    43:27
    life
    43:29
    that it’s important to not think about
    43:31
    it having happened in a vacuum or having
    43:33
    happened
    43:34
    uh without without
    43:37
    um other forces at play and in the other
    43:40
    part of my life i
    43:42
    am a professor in a program that trains
    43:44
    and prepares
    43:45
    people for careers and information
    43:47
    professions primarily in librarianship
    43:50
    and so i know something about the way
    43:53
    in which we’ve seen a gross
    43:57
    erosion of the american
    44:00
    public sphere and opportunities for
    44:03
    people to become informed
    44:06
    in places that traditionally have been
    44:10
    more transparent more committed to the
    44:13
    public good
    44:13
    not-for-profit i’m thinking about
    44:16
    institutions like public schools
    44:18
    and institutions like public libraries
    44:21
    so if we were to take
    44:24
    you know uh funding a funding graph or
    44:28
    something like that and put them
    44:29
    together about expenditures or
    44:31
    where where money goes in our society we
    44:34
    would see
    44:35
    you know that off the cliff kind of
    44:37
    defunding
    44:38
    of of these uh institutions that i just
    44:41
    mentioned
    44:42
    while we see a rise in social media
    44:46
    and what i think that suggests at least
    44:49
    to me is that
    44:50
    it’s not that the american public
    44:51
    doesn’t have a desire to be informed
    44:54
    or to have information sources and i
    44:56
    would add to that by the way
    44:57
    it’s not necessarily in the public
    44:59
    sphere in the same way
    45:00
    but we have seen total erosion in
    45:04
    regional and local journalism too right
    45:06
    during the same time right
    45:08
    into mega media that’s right mega media
    45:11
    which
    45:12
    you know came about by the shuttering of
    45:14
    local news
    45:15
    and it there was a time when you know
    45:17
    cities like mine i come from madison
    45:19
    wisconsin 250
    45:21
    000 people yeah they yeah they might
    45:24
    have had a a
    45:25
    a reporter in dc you know what i mean
    45:28
    for our local paper the capitol times
    45:30
    which went the way of the dodo some
    45:33
    some years ago and that that local paper
    45:35
    no longer exists in a print form
    45:38
    so there’s a whole i mean we could do a
    45:40
    whole show on this and you probably
    45:42
    shouldn’t have me on for the show so
    45:44
    apologies to to the users that this
    45:46
    isn’t my total area of expertise but i’m
    45:48
    just trying to connect some dots here
    45:50
    for people to make sense of it right
    45:52
    right and you know when we think about
    45:53
    the differences between social media
    45:55
    information circulation and something
    45:58
    like journalism
    46:00
    agree or disagree with what you read in
    46:02
    in in the newspaper or you hear on the
    46:05
    news
    46:06
    of your choice but there are things
    46:09
    there that are not present
    46:10
    in the same way in the social media
    46:12
    ecosystem uh
    46:13
    you know an author name a set of
    46:16
    principles by which
    46:18
    uh the journalists
    46:21
    at least pay lip service to but most of
    46:24
    them
    46:25
    live by you know that they have been
    46:27
    educated
    46:28
    to uh to serve and then do so
    46:31
    in their work there’s editorial control
    46:34
    that before stories go to print they
    46:37
    have to go through a number of eyes
    46:38
    there’s fact checking if you’ve ever you
    46:41
    know i’ve been on the
    46:42
    the the side of having been interviewed
    46:44
    for journalistic pieces and i get phone
    46:46
    calls from fact checkers to make sure
    46:48
    that the journalists got
    46:49
    right what i think yeah right
    46:52
    you think that did you really say xyz
    46:55
    yes i did that doesn’t exist and you
    46:57
    know
    46:58
    your your your racist uncle
    47:00
    recirculating
    47:01
    um god knows what from whatever outlet
    47:04
    that is just go those those
    47:08
    what we might think of barriers to entry
    47:10
    but we also might think of as safeguards
    47:11
    are just gone
    47:13
    and with all of the other institutions
    47:16
    eroded that i mentioned
    47:17
    you know public schooling library public
    47:20
    libraries and so on the mechanisms that
    47:22
    people might use to
    47:24
    vet material to understand what it means
    47:27
    when they look at a paper of record
    47:29
    versus
    47:32
    a dubious outlet let’s say a dubious
    47:34
    internet based outlet
    47:36
    and how those uh sources differ those
    47:39
    mechanisms to to learn about those
    47:41
    things have been eroded as well
    47:43
    um is there even a civics class anymore
    47:45
    in public school
    47:46
    i see that uh at least it looks like
    47:49
    donald trump missed it when
    47:51
    when he was coming up based on what i
    47:54
    saw in the debate the other night
    47:55
    i had one growing up i think that when
    47:57
    it might have already been spotty by the
    47:59
    time
    47:59
    i was in yeah you know i mean yeah i i
    48:02
    have that and
    48:03
    i i won’t mention my age but it’s it’s
    48:06
    probably a writer it’s not 29.
    48:11
    so you know i i’m trying to i guess what
    48:13
    i’m trying to do
    48:14
    uh in a roundabout way here is draw some
    48:17
    connections
    48:18
    around phenomena that seem often um
    48:23
    like they have come from nowhere to say
    48:25
    that actually
    48:26
    it would behoove us to to connect those
    48:29
    dots both in this moment but also draw
    48:32
    back
    48:33
    a little bit on history uh at least the
    48:36
    the last 40 years of sort of like
    48:37
    neoliberal
    48:39
    uh policies that have eroded the public
    48:41
    sphere
    48:42
    in favor of private industry and it what
    48:45
    it didn’t do was erode the public’s
    48:47
    desire to
    48:48
    know but what has popped up and cropped
    48:50
    up in that
    48:51
    vacuum left are these uh
    48:54
    you know really questionable uh
    48:57
    information sources that
    48:59
    really don’t respond to any greater
    49:02
    norms other than partisanship
    49:06
    uh advertising dollars etc
    49:09
    and and that’s on a good day i mean
    49:11
    those are the ones that aren’t totally
    49:13
    nefarious like state and extra state
    49:15
    right uh you know psyops generated stuff
    49:19
    right
    49:20
    it’s so interesting because when you
    49:21
    were talking about youtube you mentioned
    49:22
    about how
    49:23
    the quote about how the ai’s not
    49:25
    watching the video
    49:26
    and and the comment you made was about
    49:28
    you know the the idea of sense making
    49:30
    from the video and
    49:32
    what i’m hearing and what you’re
    49:33
    describing there is you know one of the
    49:35
    kind of underlying themes of my work is
    49:37
    that humans crave meaning
    49:39
    and that a lot of one of the most sort
    49:41
    of human qualities that we have or two
    49:44
    of the most human qualities are
    49:45
    meaning making and meaning uh finding so
    49:48
    it means
    49:48
    yeah so it strikes me that what you’re
    49:50
    describing is this kind of
    49:52
    systemic change you know many systemic
    49:56
    changes happening at once
    49:57
    in what information is available what
    49:59
    information is provided and yet
    50:01
    our impulse to connect dots and create
    50:05
    meaning is still there but we’re giving
    50:07
    we’re given increasingly unreliable
    50:10
    potentially
    50:10
    a sources of information and we’re
    50:14
    we’re still trying to connect those dots
    50:16
    but the the dots that connect
    50:17
    inevitably become simpler more
    50:20
    rudimentary more
    50:21
    uh fit more conspiracy theory kind of
    50:24
    narrative in many cases is that a fair
    50:26
    characterization do you think i mean
    50:28
    i that’s absolutely the conclusion i
    50:30
    come to and i actually have a
    50:32
    a doctoral candidate whom i supervise
    50:35
    right now
    50:35
    who works on this notion of conspiracy
    50:38
    theory
    50:39
    and we have talked her name’s yvonne
    50:41
    eden and i want to shout it out just
    50:42
    because i want folks to look out for her
    50:44
    coming up
    50:45
    um but i i have talked with her and
    50:49
    others about this topic
    50:51
    significantly because i have quite
    50:54
    this may surprise people but i have
    50:56
    quite a sympathetic
    50:58
    uh orientation towards people who
    51:01
    who fall prey to what we might consider
    51:04
    broadly speaking conspiracy theories
    51:06
    and it’s the reason you just laid out so
    51:08
    eloquently that
    51:09
    that human impulse as you described it
    51:11
    right and that’s the that’s really at
    51:12
    the root of the show anyway right yeah
    51:14
    we’re
    51:15
    all tech is human and it’s it’s about
    51:17
    humanity it’s about digital humanity
    51:19
    um and i think when i think about people
    51:22
    who fall victim
    51:23
    to to conspiracy theories
    51:26
    what i see underlying that is an is a
    51:30
    human impulse to want to make sense of a
    51:33
    world that increasingly doesn’t
    51:34
    and they’re doing it in the absence of
    51:37
    information
    51:38
    that is way more complex and hard to
    51:40
    parse out and actually might
    51:42
    um point criticism at places that are
    51:44
    very uncomfortable
    51:45
    right so you know a flat earth or a q
    51:47
    anon
    51:48
    uh adherent etc uh whatever else is go
    51:52
    you know lizard people who live under
    51:55
    the crust of the earth i mean i’ve heard
    51:56
    all of these things
    51:58
    um you know it’s like
    52:01
    it’s like this process of finding black
    52:04
    holes
    52:05
    that uh astrophysicists engage in
    52:08
    it’s not that they’re seeing the black
    52:10
    hole it’s that they’re seeing
    52:12
    the way the energy behaves around it
    52:14
    right um
    52:15
    for example that you know things might
    52:17
    be congregating towards a point
    52:19
    in space or uh you know there’s
    52:21
    disruptions
    52:23
    and i think about that metaphor a lot
    52:25
    when i think about people who fall
    52:26
    victim to
    52:27
    essentially bad information that they
    52:29
    sense
    52:30
    you know a disruption in the force right
    52:33
    they sense a disruption they sense
    52:36
    a wrongness about the world but they
    52:38
    don’t have
    52:39
    the right information um presented to
    52:42
    them
    52:42
    or access to it or even the ability to
    52:45
    parse it because
    52:46
    we’ve destroyed public schools and now
    52:48
    we we might suggest in my own bout of
    52:50
    conspiracy making
    52:52
    that this kind of again debasement and
    52:55
    destruction of these public institutions
    52:57
    that help people
    52:58
    uh identify good information and be good
    53:01
    citizens
    53:02
    and understand the world around them in
    53:05
    a
    53:05
    in a way that you know lasts longer than
    53:08
    a blip on the screen is political
    53:12
    and that it leaves them chasing their
    53:14
    own tail through conspiracy theories
    53:15
    instead of unpacking things like
    53:17
    you know the consequences of um of
    53:20
    western imperialism
    53:22
    or understanding human migration as
    53:25
    economic and environmental injustice
    53:27
    issues or
    53:28
    the destruction of political systems
    53:30
    that have long lasting consequences in
    53:33
    their countries of origin
    53:34
    that the u.s may have been involved in
    53:36
    you know like all of these kinds of
    53:37
    things that you learn from studying
    53:39
    history
    53:40
    or social sciences or having a
    53:42
    humanistic approach
    53:43
    uh to various topics that you know all
    53:45
    of these spaces that are getting eroded
    53:47
    from
    53:47
    from kindergarten all the way through
    53:49
    higher education um
    53:51
    have consequences and then the the
    53:52
    auxiliary institutions that help people
    53:55
    such as libraries and that that is
    53:58
    happening not just in the in the public
    54:00
    library sphere but there’s been gross
    54:01
    consolidation in academic libraries over
    54:03
    the years
    54:04
    uh the price of information access to
    54:06
    journals has skyrocketed for
    54:08
    virtually no reason etc you know you
    54:10
    combine all that and
    54:12
    we have created essentially an
    54:13
    information
    54:15
    access problem and an information
    54:19
    an ability to parse information a
    54:22
    problem
    54:23
    for people what do they do they reach
    54:25
    for the pablum of social media which is
    54:27
    instantaneous
    54:28
    always on constantly circulating speedy
    54:31
    easy to digest uh and
    54:34
    worth about as much as you know those
    54:37
    things might be worth
    54:38
    yeah well before we run out of time i
    54:40
    want to make sure we touch on the
    54:42
    speaking of intersecting dimensional
    54:45
    systems
    54:45
    uh the work that you are doing with uh
    54:48
    with the
    54:49
    ucla center for critical internet
    54:51
    inquiry which of course
    54:52
    you do with our previous delightful
    54:53
    guest satya noble
    54:55
    yeah we all love zapier noble uh the
    54:58
    website
    54:59
    describes it as an interdisciplinary
    55:01
    research center committed to holding
    55:02
    those who create
    55:03
    unjust technologies and systems
    55:05
    accountable for the erosion of equity
    55:07
    trust and participation i won’t read the
    55:08
    whole statement but that immediately to
    55:10
    me
    55:11
    ties back into some of what you were
    55:12
    just saying so can you tell us a little
    55:14
    bit about
    55:15
    what your initiatives and programs are
    55:17
    or are planned to be
    55:19
    well uh absolutely first of all um
    55:22
    yeah this is sort of a this is sort of
    55:26
    the
    55:26
    uh the the long lasting goal that sofia
    55:31
    and i have had and
    55:32
    just so your v your viewers and
    55:34
    listeners have a little contact sophie
    55:36
    and i
    55:36
    uh met essentially on our first day of
    55:38
    our phd program and so that’s we that’s
    55:41
    how far we go back
    55:42
    and we were both really involved in each
    55:44
    of the origin stories of each other’s
    55:46
    research and
    55:47
    if you look at the work that i do on on
    55:49
    humans in content moderation you look at
    55:51
    the work that she does on algorithmic
    55:53
    bias you can see you know the the
    55:56
    the dna is swirling around each other
    55:58
    born of so many conversations that she
    56:00
    and i have had over the years
    56:02
    and so one of our long-term goals was to
    56:05
    create a center
    56:06
    uh at what well first of all our
    56:08
    long-term goal was to get to the same
    56:10
    academic institution which for those of
    56:11
    you in academia
    56:13
    out there know that is not an easy task
    56:16
    but we managed
    56:17
    over the years to do that through
    56:19
    circuitous means and we ended up at ucla
    56:21
    together
    56:22
    then the second task that we had in mind
    56:25
    was to create a center that would
    56:27
    take the sum of the work that we do
    56:30
    put it together and allow it to be
    56:32
    bigger than it would be
    56:34
    on its own because we would be able to
    56:36
    invite others in under the umbrella and
    56:38
    under the
    56:39
    you know the big ten approach of having
    56:40
    a center
    56:42
    and so it’s really uh taking
    56:46
    uh this opportunity of having some
    56:48
    funding sources bringing on other
    56:50
    researchers
    56:51
    um holding convenings uh hopefully
    56:54
    sponsoring research studies
    56:56
    etc uh that will allow us to amplify
    57:01
    the strands of the research that i
    57:02
    talked about today and that
    57:04
    uh previous viewers and listeners will
    57:06
    know about through sophia’s work
    57:08
    and then amplifying that and making it
    57:10
    bigger than we could on our own
    57:12
    so of course in this particular moment
    57:15
    we’re absolutely interested in in
    57:18
    focusing on things like
    57:19
    uh the political situation in the us and
    57:22
    in the election
    57:23
    uh we’re absolutely committed to and
    57:26
    following the black lives matter
    57:27
    movement and how
    57:28
    uh that is that is playing out um and
    57:31
    and issues of of racial and social
    57:34
    injustice and inequity
    57:36
    that not only i would argue are
    57:38
    perpetuated in social media but are
    57:40
    exacerbated
    57:41
    in social media and um you know thinking
    57:44
    about ways in which
    57:45
    interventions should take place so that
    57:48
    that doesn’t happen
    57:49
    and i’ll leave just one anecdote you
    57:50
    know we were in a room once
    57:52
    at a megatech one of the many mega techs
    57:55
    with
    57:55
    with an engineer who was working on a
    57:58
    tool
    58:00
    his particular platform had you know had
    58:02
    it
    58:03
    had a mechanism for people to post um
    58:06
    uh job advertisements and they were
    58:08
    finding that you know people were doing
    58:10
    a lot of
    58:10
    uh racist and and other kinds of you
    58:13
    know gender discriminatory things in
    58:14
    their
    58:15
    job ads go figure and he was
    58:18
    you know he was working more on the
    58:20
    experimental side thinking about how to
    58:22
    make algorithms understand what might be
    58:24
    fair and you know he started ruminating
    58:26
    really what is
    58:27
    fairness you know and sophia and i
    58:29
    looked at each other we’re just about
    58:30
    dying we’re sitting there together we
    58:32
    say to the guy you know
    58:34
    um you could sit there and reinvent the
    58:36
    many thousands of years of philosophical
    58:38
    rumination on fairness
    58:40
    or you could look to guidance from the
    58:41
    federal government
    58:43
    that has laws about what constitutes
    58:46
    fairness and hiring practices
    58:48
    and in fact we would argue that’s what
    58:49
    you should do uh and that
    58:51
    that’s what you’re compelled to do so so
    58:53
    you see what i mean
    58:54
    they’re always doing that i’m telling
    58:57
    you a mega tug man
    58:58
    they’re on my nerves so you know this is
    59:00
    the kind of this is the kind of
    59:03
    the thing that that we want to do in a
    59:05
    bigger way
    59:06
    through the center which is to inform um
    59:09
    make these connections like we’ve talked
    59:12
    about on the on the
    59:13
    uh on the program today uh talk to
    59:16
    policymakers
    59:17
    many of whom desperately want to be
    59:20
    better informed themselves right
    59:22
    regulators uh politicians they’re going
    59:24
    to be the first to say
    59:26
    it’s a series of tubes may have been
    59:28
    more correct than than not in retrospect
    59:30
    right but they
    59:30
    they need help too to unpack and
    59:32
    understand
    59:34
    and many of the firms themselves want to
    59:36
    get better as well and we’re we’re here
    59:38
    to do all of those things and more
    59:40
    oh i i want to give you a chance to um
    59:42
    point people to
    59:43
    where they can find your work i know
    59:45
    that on on the promo for this
    59:47
    uh show we had ubiquity75 as your
    59:50
    twitter handle are there other places
    59:51
    people can find you online
    59:53
    well i think a great thing for folks to
    59:56
    do would be to follow the c2i2 the ucla
    59:59
    c2i2
    60:00
    twitter account we also have a mailing
    60:03
    list
    60:04
    that will become more active as we go
    60:07
    forward you can visit our website again
    60:11
    c2i2ucla.edu
    60:12
    and um you know follow the initiatives
    60:15
    there i i have to give people a
    60:17
    you know a content warning that the the
    60:19
    tweets from the last few days have a lot
    60:21
    of naughty words in them because i was
    60:22
    watching
    60:23
    the presidential debate and just losing
    60:25
    my mind
    60:26
    um but i’m not the only one no you’re
    60:29
    not the only one you know
    60:32
    caveat lector on my on my twitter
    60:35
    account just you know i’m a human too
    60:37
    folks i’m a technological human too
    60:42
    that’s fair enough we i think that’s a
    60:44
    great way to finish off this thought
    60:46
    thank you so much thank you to our
    60:48
    audience for tuning in
    60:49
    and uh to david ryan polgar for our only
    60:52
    question that was asked live today but i
    60:54
    know there must have been another ones
    60:55
    so
    60:55
    feel free folks to follow up with sarah
    60:58
    on
    60:59
    twitter or on her channels and engage
    61:02
    with her work
    61:03
    thank you sarah for the work you’re
    61:04
    doing it’s so appreciated and it’s so
    61:06
    important
    61:08
    thank you very much uh i guess i should
    61:10
    say the book is called
    61:11
    behind the screen content moderation in
    61:13
    the shadows of social media i didn’t
    61:15
    mention that
    61:16
    that’s the cover uh right there it’s on
    61:18
    yale university press
    61:20
    it’s coming out in a french edition on
    61:22
    october 8th
    61:23
    on la de cuvert uh uh press and so for
    61:26
    any
    61:27
    french speakers or french readers who
    61:30
    may be watching or if you have friends
    61:32
    uh they can now read it in in french
    61:39
    thank you very much all right thanks
    61:41
    everyone bye bye now
    61:43
    all right thank you

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