Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships
Complex Tasks and Learning in Crowdsourcing
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Suzuki, Ryo
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Salehi, Niloufar
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Lam, Michelle S.
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Marroquin, Juan C.
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Bernstein, Michael S.
Proceedings of the ACM CHI'16 Conference on Human Factors in Computing
Systems
2016-05-07
v.1
p.2645-2656
© Copyright 2016 ACM
Summary: Expert crowdsourcing marketplaces have untapped potential to empower
workers' career and skill development. Currently, many workers cannot afford to
invest the time and sacrifice the earnings required to learn a new skill, and a
lack of experience makes it difficult to get job offers even if they do. In
this paper, we seek to lower the threshold to skill development by repurposing
existing tasks on the marketplace as mentored, paid, real-world work
experiences, which we refer to as micro-internships. We instantiate this idea
in Atelier, a micro-internship platform that connects crowd interns with crowd
mentors. Atelier guides mentor-intern pairs to break down expert crowdsourcing
tasks into milestones, review intermediate output, and problem-solve together.
We conducted a field experiment comparing Atelier's mentorship model to a
non-mentored alternative on a real-world programming crowdsourcing task,
finding that Atelier helped interns maintain forward progress and absorb best
practices.
We Are Dynamo: Overcoming Stalling and Friction in Collective Action for
Crowd Workers
The Impact of Crowd Work on Workers
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Salehi, Niloufar
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Irani, Lilly C.
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Bernstein, Michael S.
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Alkhatib, Ali
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Ogbe, Eva
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Milland, Kristy
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Clickhappier
Proceedings of the ACM CHI'15 Conference on Human Factors in Computing
Systems
2015-04-18
v.1
p.1621-1630
© Copyright 2015 ACM
Summary: By lowering the costs of communication, the web promises to enable
distributed collectives to act around shared issues. However, many collective
action efforts never succeed: while the web's affordances make it easy to
gather, these same decentralizing characteristics impede any focus towards
action. In this paper, we study challenges to collective action efforts through
the lens of online labor by engaging with Amazon Mechanical Turk workers.
Through a year of ethnographic fieldwork, we sought to understand online
workers' unique barriers to collective action. We then created Dynamo, a
platform to support the Mechanical Turk community in forming publics around
issues and then mobilizing. We found that collective action publics tread a
precariously narrow path between the twin perils of stalling and friction,
balancing with each step between losing momentum and flaring into acrimony.
However, specially structured labor to maintain efforts' forward motion can
help such publics take action.
The many faces of Facebook: experiencing social media as performance,
exhibition, and personal archive
Papers: managing social media
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Zhao, Xuan
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Salehi, Niloufar
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Naranjit, Sasha
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Alwaalan, Sara
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Voida, Stephen
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Cosley, Dan
Proceedings of ACM CHI 2013 Conference on Human Factors in Computing Systems
2013-04-27
v.1
p.1-10
© Copyright 2013 ACM
Summary: The growing use of social media means that an increasing amount of people's
lives are visible online. We draw from Goffman's theatrical metaphor and
Hogan's exhibition approach to explore how people manage their personal
collection of social media data over time. We conducted a qualitative study of
13 participants to reveal their day-to-day decision-making about producing and
curating digital traces on Facebook. Their goals and strategies showed that
people experience the Facebook platform as consisting of three different
functional regions: a performance region for managing recent data and
impression management, an exhibition region for longer term presentation of
self-image, and a personal region for archiving meaningful facets of life.
Further, users' need for presenting and archiving data in these three regions
is mediated by temporality. These findings trigger a discussion of how to
design social media that support these dynamic and sometimes conflicting needs.
