Niloufar Salehi, Lilly C. Irani, Michael S. Bernstein, Ali Alkhatib, Eva Ogbe, Kristy Milland, and Clickhappier. 2015. We Are Dynamo: Overcoming Stalling and Friction in Collective Action for Crowd Workers. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI ’15). ACM, New York, NY, USA, 1621-1630. DOI=10.1145/2702123.2702508 http://doi.acm.org/10.1145/2702123.2702508
Discussion leader: Nai-Ching Wang
Summary
This paper proposes structured labor to overcome two obstacles impeding collective action through a year-long ethnographic field study. By participating deeply in the ecology of human computation instead of being outside observers, the authors find out although there were already forums to help better work condition, there are still several challenges preventing further collective action such as trust, privacy, risk of loss of jobs, diverse purposes of working. To support collective action in the Amazon Mechanical Turk community, Dynamo is designed to provide three affordances including trust and privacy, assembling a public, and mobilizing. With several cases on Dynamo platform, the authors identify two intertwined threats, stalling and friction, for collective action. To overcome the two threats, this paper proposes structured labor including “Debates with deadlines”, “Act and undo”, “Produce Hope”, and “Reflect and Propose” and demonstrates how the structured labor can be used in real cases.
Reflection
I see several connections from this paper to our previous topics and in-class discussions. Based on definitions from Quinn and Bederson’s paper, this paper falls into the categories of social computing and crowdsourcing and thus collective intelligence in the sense that the crowd workers on Amazon Mechanical Turk form an online community and (ideas of) social movements are crowdsourced to the community instead of some designated leaders or consultants. In the discussion of the question “Can we foresee a future crowd workplace in which we would want our children to participate?”, this paper might have provided some possibility for the crowd workers to take collective action to strive for a fair labor marketplace. This paper seems to be a good example of human-computer collaboration, too. Interestingly, Dynamo (the computer) is designed with the concept of affordances naturally in-line with the affordance-based framework discussed previously. Turkers along with admins provide human affordances such as sociocultural awareness, creativity and domain knowledge. Examples in this paper also demonstrate that crowd workers can complete not only micro-tasks as seen from last week’s discussion but also brainstorming ideas and quality writing. In addition, from this paper, it also seems that traditional management is better than algorithmic management for such topic at least for now.
Questions
- Do you think campaigns in the paper successful? Why or Why not? What else do you think important for success of collective action?
- For the labor of action (debates with deadlines, act and undo, the production of hope, reflect and propose),
- Which (part) do you think that might be addressed automatically by computer algorithms? In other words, which parts are the ones that really need human computation (at least for now)?
- Can these tasks be further divided into smaller tasks?
- How can that possibly be done?
- How do we find a trustworthy person to be the “moderator”? Or say, how do we decide if a person is trustworthy enough to be the “moderator”?
- Can we delegate some moderation to computer? Which part? And how?
