Crowdsourcing: Background and Working Definitions
Definition: Although crowdsourcing can have many meanings, we define it here to mean breaking down large tasks into small ones that can be performed asynchronously.
- The Best Practices entry for crowdwork, developed last year and reposted on Class 3, classifies crowdwork three ways:
First, a large group of workers may do microtasks to complete a whole project; the best-known platform in this arena is Amazon Mechanical Turk. Second, companies may use cloudwork platforms to connect with individual workers, or a small group of workers, who then complete larger jobs (e.g., Elance and oDesk). Finally, a company may run “contests,” where numerous workers complete a task and only the speediest or best worker is paid (e.g., InnoCentive and Worth1000). In some contests, the company commits to picking at least one winner; in others, there is no such guarantee.
- General Information on Crowdsourcing.
- For a quick overview by Jeff Howe, author of Crowdsourcing, take a look at this YouTube clip.
- Northwestern University Professor Kris Hammond also explains crowdsourcing, but argues its downsides are worker rewards and quality.
- Our very own Jonathan Zittrain discusses crowdsourcing in his talk, Minds for Sale.
- Several individuals gathered to discuss crowdsourcing in panel moderated by New York Times correspondent Brad Stone.
- In the News.
Although the idea of crowdsourcing has been around for many years, the Internet has made it much easier, cheaper, and efficient to harness the power of crowds. The power of crowds was popularized in 2005, James Surowiecki published a book entitled, The Wisdom of Crowds, which purported to show how large groups of people can, in many cases, be more effective at solving problems than specialists.. The following year, journalist Jeff Howe, coined the phrase "crowdsourcing" to refer to work that was performed by the "masses" online. Since Howe's article was published in 2006, numerous authors have written books on crowdsourcing, each choosing to focus on different aspects of the topic. Howe himself took up the topic in 2008, proclaiming crowdsourcing to be a panecea--a place were a perfect meritocracy could thrive.[ Howe examined crowdsourcing from a variety of perspectives: what benefits it can provide, what kinds of tasks it can accomplish, and the potential changes it may bring about. Howe's diagnosis of crowdsourcing was positive--in it he saw many potential solutions and few potential problems. Others have followed Howe's lead in describing the benefits of crowdsourced work. Clay Shirky has published two books--Here Comes Everybody (2008) and Cognitive Surplus (2010)--in which he describes how technology does more than enable new tools, it also enables consumers to become collaborators and producers. Although Shirky's book are not expressly about crowdsourcing per se, they mirror the optimism Howe expresses, both in terms of collaborative enterprises and the Internet's power to enable them.
While some focused on the potential consumer revolution, others examined the business-related aspects of crowdsourcing. In Groundswell (2008), Charlene Li and Josh Bernoff focus on how to most effectively use crowdsourcing to advantage businesses. The authors highlight how users bases of products can undermine a product or brand. As a result, the authors propose businesses use the "groundswell" to their advantage, fostering communities that can provide valuable feedback and economic payoffs. Marion K. Poetz and Martin Schreier also have taken a business perspective on crowdsourcing. They argue that the crowd is capable of producing valuable (but not always viable) business ideas at a low cost. They suggest future research to better understand their findings.
Other authors have pointed out some of the problems with crowdsourcing. Dr. Mathieu O'Neil has argued that, despite its benefits, crowdsourcing is inconsistent in quality, can lack the diversity, and can contain many irresponsible actors. Miram Cherry has argued that some crowdwork can be exploitative, sometimes forcing people to work for absurdly low wages. She argues that we need a legal framework for addressing low wages, proposing we apply the Fair Labor Standards Act (FLSA) to crowdsourced work like that found on Mechanical Turk. In a forthcoming article, she takes a more systematic (but still legal) approach to different kinds of virtual work. Cherry seems to be the only law professor to have written on addressing crowdsourcing from a doctrinal perspective.
Much of the other literature on the subject concerns the problem of quality. Cheat detection--the ability to filter out individual who complete tasks without actually reading them, seeking only money--has recently drawn attention. Indeed, a possible crowdsourced solution to cheaters has been proposed. Others have attempted to increase the quality of the traditionally-automated mechanism used to translate words by crowdsourcing translation tasks. In addition to simple crowdsourcing, one set of authors suggests combining human crowdwork with machine work. This process, according to the authors, the system can specific a specific "speed-cost-quality tradeoff," which is based on an allocation of tasks among computers and humans.
A Framework For Analyzing Issues in Crowdsourcing
1. How do concerns of reputation and identity play into crowdsourced work quality?
- tasks where want rep known, others not known
- phone card/coupon system
- Verification of workers is becoming a problem (can access the linked article through Harvard Library).
2. Can we ensure work quality using (semi)automated mechanisms?
- Some have attempted to use crowdsourcing to ensure quality on crowsourced tasks using cheat detection mechanisms. This can be done for both routine and complex tasks.
3. Can we enhance work quality using a targeting system
- Amazon rec, ebay sytle, MT?, differentiate tasks?