how scientists helped create a digital labor union

Stingy academics inspired a new platform for those doing menial digital work, and not in a good way.

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Amazon’s Mechanical Turk lets you assign menial, yet attention-intensive tasks to actual human beings, despite the name’s ambiguity, and those humans want to be paid consistently and a fair fee for their efforts. This is why in March of last year, they launched the Dynamo platformwhich allows them to warn each other of bad clients who were stingy or unreasonable. The brainchild of Stanford PhD student Niloufar Salehi, who wanted to study digital labor rights, it came about in large part due to many of those stingy, unfair clients being academics. With small budgets for surveys and preparing complex machine learning algorithms, researchers were often paying an insultingly token sum to the workers they recruited, something Dynamo argues hurts the quality of their research by limiting their labor pool to the truly desperate and ill-qualified in its rules and guidelines for ethical academic requests for inquiring researchers looking for assistance.

It’s hard to know what’s worse, the fact that we give so little funding to researchers they have to rely on strangers willing to work for scraps, or that academics are fine with the notion of paying the equivalent of prison odd job wages to their remote assistants. Part of the problem is that the issues are interdependent. Many academics can’t afford to pay more and still meet their targets for sufficient survey responses or machine learning algorithms’ training set sizes. Turkers most qualified for the job can’t afford to accept less than 10 cents a minute, which doesn’t sound like much, until you realize that 15,000 units of work taking half an hour come out to $45,000 or so, a hefty chunk of many grad students’ budgets. Something’s gotta give and without more money from universities and states, which is highly unlikely, academics will either keep underpaying the crowds they recruit, or end up doing less ambitious research, if not less research in general…

# science // crowdsourcing / digital labor / scientific research

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