June 7th, 2010
by Alek Felstiner
In the last post, I looked briefly at the roots of our existing employment and labor law, and why employment classification presents such a tricky issue in crowd work. For individual workers, being classified a statutory employee is the main hurdle. Once you’re “covered” by a particular law, you’re entitled to its protections unless the law gives employers a way out (e.g. if a business is too small to meet the size requirement).
But employment law does more than entitle individuals to particular benefits – it also protects them when they act together. The individual right to join together with others is crucial to the ability of individuals to function effectively in groups. Especially where the group is large and, perhaps by virtue of the size, or for some other reason, no individual member has sufficient power to alter his/her situation.
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May 28th, 2010
by John Le
Last week we did a quick survey of Amazon Mechanical Turk workers (colloquially known as Turkers). Next it seemed natural to do the same survey of workers on Gambit, another workforce to which we channel work. This analysis of Gambit is interesting in and of itself because it permits comparison between our two largest workforces. Our work on Gambit, however, is especially fascinating for a number of reasons. The volume and completion rates are comparable to those of Turk, but workers on Gambit are working for virtual currency in online social games like Facebook’s “SportsBets.” Virtual currency can be redeemed in games and on sites like Swag Bucks. Rarely does virtual currency translate into actual money. This phenomenon is amazing, and we are consistently struck by the innovative nature of our partnership with Gambit.
Another interesting thing about the Gambit workforce is how similar its composition is to the Turk workforce of two years ago, in which 80 percent of workers were from North America (the United States and Canada). (The exact results and methods for determining this is discussed below). This similarity points to how labor workforces are globalizing very quickly with Turk (one of the first marketplaces for online work) at the forefront of this growth. Gambit could possibly be moving in this direction as well. For now we’ll leave this discussion to a later blog post, as first we must see the results to this survey.
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May 26th, 2010
by Alek Felstiner
On May 10th I presented at the Crowdflower Distributed Distributed work Meetup, talking about employment law and regulation. As it turned out, my 15-minute presentation turned into an hour and a half of exploring the legal issues involved in crowd work. The group of clients, workers, and crowdsourcing vendors displayed a real hunger for guidance on how the courts might apply existing laws to crowd work. Our long and involved discussion illustrated how little is actually out there to help people understand these issues.
By way of a recap for those with the good fortune of not having had to endure my fleeting law professor fantasy, I’ve broken up the presentation into a few parts, which I’ll post here. This segment looks at the basic reasons why applying our current law is so difficult, and the threshold question of how to properly classify crowd workers. The next one will deal with civil liberties and group rights in virtual work, and the final one (if I get that far) will present my best case for immediate regulatory intervention. If you don’t want to wait, you can find a thorough (and probably boring) treatment of this topic here.
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May 23rd, 2010
by Lukas Biewald
This is a guest post written by my friend Dana Chandler on how the context of a task motivates the person working on it. He has a longer academic paper on the topic you can find at the bottom of this post. It once again shows how traditional economic incentives can’t fully explain workers’ behaviors on Mechanical Turk.
Imagine for a moment that you were a turker from either the US or India, looking at the above image. You are given the task of clicking on the blue circular objects with red borders. What you see is only a fraction of the full image. Each image has 90 blue objects to identify. If you’re as good as the average worker, you’ll complete your first image in a little over five minutes and you’ll earn 10 cents (for an hourly wage of $1.20).
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May 14th, 2010
by Stephanie Geerlings
Here are a few of the colors we asked about.
Lukas gave a presentation today at TEDxDU. It was a great event with more than 1,000 attendees.
At the beginning of his presentation he told the audience members if they were bored they could work on a CrowdFlower task. It turns out a lot of people were bored! The task was describing colors, but with a twist—describe the color as precisely as possible. You can see the task here.