CRITICAL PERSPECTIVES
Difference Work: A
Conversation with Lilly Irani
Lilly Irani
UC San Diego
lirani@ucsd.edu
Monika Sengul-Jones
UC San Diego
msengulj@ucsd.edu
Lilly Irani is a cultural theorist
and a computer scientist, a professional mix which gives her an
analytical edge in
addressing the socio-cultural politics of programming microwork
platforms in the "service economy." This conversation discusses her
ethnographic and praxis-based research on Amazon's Mechanical Turk
(AMT). AMT is an Internet-based software that facilitates the
distribution of micro-"Human Intelligence Tasks" (HITs) requested by
users registered as "requesters" to be completed by users registered as
"workers" (sometimes called "Turkers"), who may earn pennies for their
work at the discretion of the "requester." Irani researches AMT and
collaboratively designed and maintains an online tool, Turkopticon
(TO), to enable workers to report their experiences with "requesters,"
good and bad, as a form of collective, mutual aid.
~MSJ
MSJ: One of your main
field sites, Amazon’s Mechanical Turk (AMT), is
broadly described by Amazon and by industry titans as a "technology"
instead of, for instance, a contracting or outsourcing company. This
rhetorical categorization in part paved the way for the proliferation
of start-up mobile phone applications and Internet software marketplaces
in the United States such as Uber, Taskrabbit, Handy, even a
freelance marketplace like [what was formally called] oDesk [now
Upwork].
The classification of these as "technology" companies is
significant because, as you point out in your Winter 2015 article in South Atlantic Quarterly,
the work they broker is a kind of piecework (2015b). The practice of
paying
workers a fixed rate for a unit of work or an action performed is not
new. However, in
your essay, you note there's a distinct difference in the "speed,"
"scale," and "technical means through which diverse workers are
rendered into computation resources, directly feeding the algorithms of
entrepreneurs and Fortune 500 companies alike" (Irani 2015b, p. 226).
Algorithmic processes differentiate newer digitally-mediated forms of
labor from other forms of piecework, such as hiring homeworkers to sew
or even cold-call marketing leads. Why is the distinction between older
and newer forms of technological piecework significant for
understanding contemporary forms of crowdwork labor?
LI: The first difference
is one of scale and ease of deployment. Systems like AMT reduce the
cost and risk of becoming an employer of pieceworkers or outsourced
service workers. Piecework is a very old form of organizing production
within homes and families, dating at least back to European craft guild
systems. Systems like AMT, however, make pieceworkers available to
anyone with a computer and a US bank account. Potential employers don't
have to find the workers, transport materials to them, or transport the
work output to sites of sale. The AMT website builds the assembly line,
payroll, and contract structure; employers can access pieceworkers in a
few clicks and abandon them even more quickly. The pieceworkers are
already available in one place—the AMT website—and are
already
organized for the employer to access. Amazon offers cognitive
pieceworkers as a plug-and-play module, easily accessible to, and
disposable by, employers.
This is only possible because of the massive suffusion of Internet
infrastructures connecting our homes to Amazon and to
employers—Internet cable, payment infrastructures, bank
protocols, for
example. AMT's labor relations are microstructural mechanisms that rely
on global forms of connectivity and coordination. These relations are
also only possible because Amazon pushes the risk generated by these
cadres of new, inexpert employers and their ever-changing experiments
out to workers. I'm thinking with Gina Neff's work on Venture Labor
(2012) and the individualization of social risks of innovation
industries here. The site's interface also shields employers from
seeing the conditions under which workers work—are they trying to
make
ends meet? Working at home to care for children or a family member?
Anthropologist of microfinance Megan Moodie (2013) argues that
microfinance works in much the same way—by hiding the gendered
work of
making ends meet and keeping the home together in economies of
microfinance.
The second difference is how being classified a "technology" company,
as compared to a "labor" company, financially benefits companies like
Uber, Taskrabbit, and Amazon. Venture capital investors, or VCs,
estimate how much a company will be worth in the future; they routinely
value technology companies more highly than labor companies. VCs assume
technology companies need more investment to set up at first, but that
those companies will scale up their profits without scaling up their
operating costs. To act as "technology" companies, microlabor companies
must convince investors, first, that their labor force is of little
risk and of little cost, and second, that their technology confers an
advantage over other companies. Hiding the AMT-like labor is key to how
these
start-ups are valued by investors, and thus key to the speculative but
real winnings of entrepreneurs.
We can deconstruct how technology as a
social category lets companies elide labor, but we also need to
consider that we as analysts also elide the labor and social relations
mediated by technology. The category "technology" does cultural and
financial work, mobilizing subjects, citizens, value, and visions of
progress.
For people committed to social justice, the financial stakes of such
classifications of technology and labor suggest a new way that the
politics of representation matters. Representations are not only a
question of epistemology, but also part of the production of financial
value. Our tactical media practices can work in the speculative
terrains of financial futures. I was once on a panel where a
crowdsourcing CEO scribbled to himself in his notebook: "NO
CONTROVERSY." I realized then that possibility of a controversy could
weaken his pitch for investment funds. Digital labor start-ups do
better when they look like technology companies with a low-risk,
infinite labor supply. By
helping workers become visible, by showing how they organize, and by
creating friction we can contest anticipatory knowledge in order to
affect companies’ bottom lines today.
MSJ: Tell us about the
hidden workers—the "Turkers," as they call themselves. You
describe
their skills in an article on Turkopticon (Irani and Silberman, 2013)
based on four years of participant observation of MT. I was struck by
your description of the range of skills they have as professionals. How
did getting to know Turkers affect your understanding of crowdwork?
LI: Getting to know
Turkers has really expanded my sense of how much of what these workers
accomplish goes unrecognized and uncompensated. It's one thing to say
that Turkers doing data-processing work should share more broadly in
the value employers get from their labor—through profit-sharing,
for
example.
It's a whole other thing to recognize how AMT sets up this labor market
platform to make workers available, but at the same time workers
themselves are organizing their own forums, teaching new workers,
educating employers, and doing free task design consulting for
employers to sustain AMT so they don't lose the opportunity to work
from their homes. This is free labor in the sense that the digital
labor scholar Tiziana Terranova (2000) has written about it. But,
unlike the AOL moderators Terranova describes, the AMT workers who step
up as leaders don't always do it for the satisfaction. Many also rely
on
AMT as a form of work they can do at home while caregiving for family
members or to make ends meet; they worry that employers will disappear
if they don't get good work on AMT. The social factory depends not only
on getting us to have fun and fulfillment as companies tap our
communication and relations for profit, but also conditions of
precarity that make us fear that we'll lose work if we don't fill in
the gaps to keep employers and platforms working well.
MSJ: I want to return to
the work of the AMT software, which as you've helped us to understand,
has been described as a "technology" that solves a problem, a
classification that makes invisible the embodied labor
involved. In your article in New
Media & Society
(Irani, 2015a) you ask how a software management system such as AMT,
which Amazon describes as "artificial artificial intelligence," plays a
crucial and under-recognized role in facilitating these labor
relations. You propose that "the sociotechnical configuration of AMT
does cultural work; this cultural work happens not only through talk or
co-present social interaction, but also through the relational politics
of interface and systems design" (Irani, 2015a, p. 721). You are
arguing
that the software is a vortex mediating these cultural meaning of
work! Can you elaborate how you've developed this analytic of software
as conduit of culture?
LI: Well, honestly, I
think the analytic emerges more out of the mud and mess of practice
than from a prism drawn gleaming from the heavens.
MSJ: An appropriate
metaphor, indeed, for demystifying "the cloud."
LI: Amazon launched
Mechanical Turk in 2005 not as a labor service, but as a computational
service of "artificial artificial intelligence" alongside its cloud storage
and computing services, S3 and Elastic Cloud. My question became: What
is at stake when a company pretends that many, many workers are simply
software or an algorithm?
I backed into this analytic of the software doing cultural work
from my
experiences with computers as a kid, traversing the Internet to connect
to worlds through the screen, and then as a software designer when I
worked at Google. I was doing design at Google in California when the
company was opening offices in India. I witnessed a swirling vortex of
screen-mediated contact and the anxieties that came out of it: US
software workers worrying about their jobs getting outsourced to India,
US designers drawing on stereotypes to make sense of Indian job
candidates
they interviewed on the phone, Google using software to farm out data
processing work of various sorts to temporary workers without access to
the central campus. Google's engineers and managers could believe in
the company
mission "don't be evil" only because architectures of
invisibility—screen-mediated Indian workers, temps quarantined
elsewhere on campus—allowed a bunch of engineers to believe that
they
were making the world a better place, as they often say. These
architectures include spaces, infrastructures, extractive
relationships, and ideologies about race, gender, and work that shape
the production of value and difference.
MSJ: How so?
LI: For example, Google
would check all the advertisements to appear on its search results to
make sure the ads did not link to pornography or alcohol purchases.
They could not fully automate this work—artificial intelligence
couldn't decide with confidence in certain cases—so they hired
workers
in India to check. While the advertiser was waiting for their ad
to get approved, I had to design the interface that explained to
customers that Google was checking the link without letting them know
that humans were doing it. The customer probably thought that Google
engineered some magical algorithms; this perception is good for
business and good for the stock price. This perception also sustains
America's confidence that engineers are the source of so much value
that we need to boost STEM majors. Similarly, AMT allows
employer-programmers to appear as technological wizards even as the
cognitive and physical labors of Turk workers power that magic.
In this way, AMT mediates the production of difference between these
innovators and the workers they rely on but know little about and often
stereotype as unskilled—it does difference work.
MSJ: This reminds me of
an argument in your essay for South
Atlantic Quarterly
(2015b) about fragility—how "fragile" the boundary is for
maintaining
the subjectivity of the entrepreneur, who is "dependent on the Turker
as mediated through AMT's interfaces" (p. 233). Fragility suggests that
things could be otherwise.
Which brings us back to Turkopticon, which you describe as "an activist
system that allows [AMT] workers to publicize and evaluate their
relationships with employers" (Irani and Silberman 2013, p. 611). How
did you come to develop Turkopticon as a scholarly activist project?
LI: Turkopticon was an
attempt to interrupt the invisibility of workers powering these
algorithmic systems. Turkopticon grew out of a course project called
Tactical Media taught by the late Beatriz da Costa, an artist trained
in computer science and feminist theory and who worked collaboratively
with scientists and engineers in a range of fields on projects about
public and political aspects of science and technology. The course was
part of a strange and wonderful
intersection of feminist science studies, critical communication
studies, mechanical art, and computation design that flourished at UC
Irvine between ACE, the Arts, Computation, Engineering program, and the
Graduate Feminist Emphasis.
At that time, da Costa and the historian of science Kavita Philip were
also co-editing the book Tactical
Biopolitics
(Da Costa and Philip, 2010) and teaching in that interdisciplinary,
tactical, and political mode. The ACE program was run out of a trailer.
It admitted its last student a few years ago, undone by funding cuts
exacted in the name of a budget crisis.
Meanwhile, the tech press was celebrating crowdsourcing as a tool of
mass collaboration. I was disturbed by how these celebrations erased
the labor and masked precarity. But I wanted to know how Turkers
understood their conditions and situation. I built on two lines of
thinking: Haraway's situated knowledges (2003)—the idea that we
need
knowledge for social justice but can't claim membership in a category
that gives us a standpoint for the whole category, and Patricia Hill
Collins' (2009) writing on self-definition and self-valuation in black
feminist thought.
MSJ: So this was an
opportunity to question difference work by making. How were you able to
animate these lines of thinking with a live platform?
LI: I put out a survey on
AMT itself, asking workers what they did and did not like about the
work, and asking them to write a bill of Turk rights. I took off from
the points of overlap among diverse workers—the platform offered
workers no protection against irresponsible or abusive employers. I
presented a sketch of employer rating software in class and da Costa
said, "you should make that." That was in 2008. Six Silberman, a
programmer and mathematician interested in open source, stepped up to
help build it. We built it. To our surprise, one Silicon Valley
crowdsourcing CEO thought it was a great idea to "level the playing
field" and helped us advertise it to their workers. That company,
liberal in every sense, turned out to pay pretty poorly and would later
get sued by its workers in a class action lawsuit. Truth is stranger
than fiction. Over the years, the user base grew and workers stepped up
to moderate comments and flag fraudulent reviews.
Turkopticon worked in the sense that many workers found it
useful—20,000 workers use it each month. But it also provoked
public
debates about the politics of digital labor—much more so than if
I
wrote a paper and went around giving talks. Six finished his PhD and
now works for the German union IG Metall. Turkopticon remains active,
sitting there on servers 24/7 as living testimony to the fact that
mutual aid is possible and our current digital labor forms produce
gross inequalities.
MSJ: What has
collaboratively making Turkopticon helped you to understand differently
about work and the digital realm?
LI: The project has
forced me to take seriously the simultaneously extractive and ethical
dimensions of high tech. We have the crowdwork start-ups that
won't pay minimum wage but are excited to have their workers have
a third-party
reputation system—these circumstances tuned me in to the
ideologies of
fairness and perfect markets that animate many engineers.
I've also learned that we need to account for the fact that our work
can be read in ways that work against our political objectives. Workers
pointed out how we, as Turkopticon's designers, could be complicit in
devaluing their skills when journalists cast AMT as a "digital
sweatshop" and Turkopticon as "union 2.0" (Brandom, 2013; Cushing,
2012).
These news stories reiterated a trope about creative, entrepreneurial
designers saving poor, exploited workers. The trope obscured broader
forms of worker skill, community, and collective action. Some workers
even noted that these awareness-raising articles attracted new
employers who wanted to hire workers at low wages.
Turkopticon has also been good to think with over the years as I read
other writers working on digital labor and related issues. As a
practice, TO forces me to confront the strange entanglements of
software, IRBs, work, and labor policy—and it helps me ask
different
questions about what I read. As I read Haraway on response-ability
(2008), I could experiment with thinking about TO as a technology that
grafts some response-ability onto AMT. As I read Jenny Reardon's work
"On the Emergence of Science and Justice" (2013), I consider her
critique that IRBs de-politicize and legitimize biotech; AMT offers a
different side. IRBs are actually the one institutional modality for
holding employers (when they are academic researchers) accountable for
low or unpaid wages. Practice constantly spills over our
categories of analysis.
MSJ: What's been the
biggest challenge?
LI: Maintenance and
repair. A problem with research and development, hackathons, and
innovation models, as far as I can tell, is that they are built on the
seminal model of change—researchers come up with an idea,
demonstrate
it, and then move on, leaving the rest of the world to sustain it,
adopt it, nurture it, or pick up the pieces (see Cohn, 2013). Regimes
that reward the
constant production of prototypes, patents, and papers can squeeze out
the energy to sustain lasting projects. Especially since I've started
as a professor, TO would be dead if not for the efforts of code
maintainer Six SIlberman, the moderators who daily debate how to keep
mutual aid going, and the server administrators at UCSD who upgrade the
operating systems and deal with power outages, etc. as a part of their
jobs. Mutual aid takes infrastructure, and infrastructure is always
labor. Progress is never just an "idea that matters," despite TED's tag
line. There's a larger discussion starting to happen in this direction,
and it is centered around the question of what feminist computing
practices look like. We need theories that emerge out of specific
struggles and experiments, but that take technology seriously once
again, understanding technology not just as that which subjects us, but
as configurable media, as a seductive object of hope, and as an object
of collective labor.
MSJ: Where do you think
this positions interventions through/in feminist STS?
LI: There's a danger of
high-tech industries co-opting feminism as a way of generating more
diverse experiments in value production—innovation par
excellence—without addressing how the jobs with the most women
and
people of color, from building maintenance to human resources to
technical writing, are devalued.
Companies and venture capitalists want diverse coders and
CEOs—more
diverse masters of technology—to the extent that it helps them
develop
new product lines and sources of value. We've seen, however, that being
a master of technology really is also being a master of other people's
labor. We need to resist the co-opting of feminism into the production
of value. Leigh Star and Lucy Suchman decades ago instead turned
feminist attention to the distribution of value and labor (Star &
Strauss, 1999; Suchman et al., 1999). We need to turn our attention to
how the categories "creativity" and "innovation"—categories
Kavita Philip analyzes as "the technological author"
(2005)—smuggle in and
valorize kinds of exploitation.
As we do this, we might take seriously the labors of sustaining
required for making otherwise. When we talk about making worlds in
feminist STS, we often go to the joys of art, prototypes, and fiction.
I'm thinking of Lisa Nakamura's interview with Donna Haraway,
"Prospects for a Materialist Informatics" (Nakamura, 2003), for
example—a discussion that features practice-based work. One way
that
Turkopticon is a bit different from a lot of the practice-based work
discussed in that conversation is that people actually use TO as a
practical tool and rely on it as infrastructure. Much practice-based
work has focused on questions of epistemology and relations, but for me
TO opens up questions of the labors and infrastructures that sustain
worlding in long duration. It needs different kinds of collective labor
and infrastructure to endure than a film, a painting, or a performance.
There are many kinds of labors of worlding. We need to theorize its
distribution and also the struggle for resources and time to do this
work.
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legacies: Temporalities of
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Bios
Lilly Irani is Assistant
Professor of Communication & Science Studies at University of
California, San Diego. She is a co-founder and maintainer of digital
labor activism tool Turkopticon. She is currently writing a book on the
cultural politics of entrepreneurialism in transnational India. Her
work has appeared at ACM SIGCHI, New
Media & Society, Science,
Technology & Human Values,
South Atlantic Quarterly, and
other venues. She earned her Ph.D. in informatics from the University
of California, Irvine.
Monika Sengul-Jones is a
Doctoral Candidate in Communication and Science Studies at the
University of California, San Diego, where her dissertation research
focuses on socio-technical interfaces of and gendered cultural
narratives about paid writing work in English. She received an M.A. in
Gender Studies at Central European University. She has received funding
from the Rotary Foundation and Wikimedia Foundation for her research.