As a Computer Scientist I am interested in two primary research questions about crowdsourcing:
- How might new systems broaden the range and increase the utility of crowdsourced work?
- What models, tools, and languages can help designers and developers create new applications that rely on crowdsourcing at their core?
I am investigating these questions together with my students at the Berkeley Institute of Design, in our Crowdsourcing Course, and through external collaborations (e.g., Soylent). At CHI, we will present works-in-progress on letting workers recursively divide and conquer complex tasks and on integrating feedback loops into work processes.
As a humanist, I believe it incumbent upon us to also think about the values our systems embody. I have a recurring uneasiness with the brave new world conjured by some of our projects for two reasons. The first one has been articulated before: many crowdsourcing research projects (including my own) rely at their core on a supply of cheap labor on microtask markets. Techniques we introduce to insure quality and responsiveness (e.g., redundancy, busy-waiting) are fundamentally inefficient ways of organizing labor that are only feasible because we exploit orders of magnitude in global income differences .
My second reservation is that the language used to describe how our systems decompose, monitor, and regulate the efforts of online workers recalls that of Taylor’s Scientific management. By observing, measuring and codifying skilled work, Taylorism moved knowledge from people into processes. This increased efficiency and made mass manufacturing possible; but it also led to the creation of entire classes of repetitive, undesirable, deskilled jobs.
I believe Stu Card had it right when he wrote that “We should be careful to design a world we actually want to live in.” As a step in this direction we might want to consider whether we ourselves would participate as workers in our own crowdsourcing systems. An exercise in my class, where students had to earn at least $1 as workers on Mechanical Turk suggests that the answer is today is a resounding “No.”
This leads me to ask a third research question – one I am less prepared to answer but where finding an answer is important if we believe that crowdsourcing will actually grow into a significant role in our future economy:
- How might we increase the utility, satisfaction and beneficience of crowdsourcing for workers?
I am looking forward to discuss these questions with you at the workshop.
1: Thanks to Volker Wulf for this thought.