the cost for a crowdsourced project ranges from $2,000 to $4,000 for simple tagging projects to $10,000 to $20,000 for more complex custom applications. Stephen Mechler, managing director of the German crowdsourcing Web site Floxter, which uses its own technologies to handle the mechanics of creating and assigning tasks and compensating workers, calculates that it is 33% less expensive to crowdsource projects like data classification and tagging than to complete them with in-house employees.
Other companies focus their crowdsourcing efforts on specific types of projects. New Mexico-based Casting-Words uses Turk to transcribe audio files. Through a propriety algorithm, files are first split into three- to four-minute chunks. Next, Turkers listen to a few seconds of each clip to judge the quality of the recording, which in turn helps determine pay rates for the transcription work. Once each file has been transcribed, a full draft is assembled and sent back to Turk to be graded for consistency and precision, and retranscribed where necessary. Finally, Turkers edit and polish the transcript to be sent back to the client. Total costs range from $. 75 to $2.50 per audio minute, depending on how quickly a client needs the work completed.
Researchers like Carnegie Mellon University computer science professor Luis von Ahn are also finding ways to put crowdsourcing to work. Unlike his corporate peers, von Ahn is unable to pay for the completion of a task, so he relies on social incentives—and tries to make tasks fun. To entice people to manually label a collection of digital images, for instance, von Ahn created the ESP Game, which randomly matches each player with an anonymous partner. Players try to guess which words or phrases their partners (whom they can’t communicate with) would use to describe a certain image. Once both players type the same descriptor, a new image appears and the process begins anew. In 2006, Google licensed the idea and created its own version of the game in order to improve image search results.
Since then, von Ahn has developed other games with a purpose to harness the wisdom of crowds. In Peekaboom, for example, one player attempts to guess the word associated with a particular im-
age as the other player slowly reveals it. In fact, designing a game is much like designing an algorithm, as von Ahn has pointed out: “It must be proven correct, its efficiency can be analyzed, a more efficient version can supersede a less efficient one.” And since many people are inherently competitive, building a community around each game to recognize outstanding performers helps increase participation, as well.
ReCAPTCHA, on the other hand, is an attempt to take advantage of a task that millions of people perform in the course of their everyday online lives: solve the ubiquitous character recognition tests known as CAPTCHAs to prove they are human. “I developed reCAPTCHA because I found out that we’re wasting 500,000 collective hours each day solving these mindless tasks,” says von Ahn. To put that brainpower to use, reCAPTCHA presents users with scanned images from old books and newspapers, which computers have difficulty deciphering. By solving the reCAPTCHA they help digitize the works. Since 2007, some 400 million people have helped digitize more than five billion words, according to von Ahn.
Crowdsourcing’s critics claim it is unethical and exploitive, paying pennies or nothing for honest labor (though diligent workers often make close to minimum wage). In a struggling economy, people may grow choosier about the ways they earn extra income. On the other hand, they may also be more interested in blowing off steam on the Internet—and being rewarded with a few extra dollars.
Leah Hoffmann is a Brooklyn-based science and technology writer. Valerie nygaard, microsoft, contributed to the development of this article.
the percentage of internet
users age 55 and older who
have a profile on an online
social network has quadrupled
during the last four years, from
8% in 2005 to 35% in 2008,
according to a new survey by
the pew internet & american
life project.
although media coverage
has largely focused on how
children and young adults use
social network sites, adults still
comprise the majority of the
users of the social network sites
because adults make up a larger
portion of the U.S. population
than teens, 65% of whom use
social network sites.
overall, however, younger
adults are much more likely
than older adults to use social
networks. For instance, 75% of
online adults age 18–24 have a
profile on a social network; 57% of
online adults 25–34 have a profile;
30% of online adults 35–44 have
a profile; 19% of online adults
45–54 have a profile; 10% of adults
55–64 have a profile; and only 7%
of online adults 65 and older have
a profile.
in terms of gender, adult
women and men are equally
likely to use social networks.
the pew study also reported
that minority groups are more
prevalent on social sites than
previously expected. it found
that 48% of african-american
adults and 43% of nonwhite
hispanic adults have a social
profile, compared to 31% of
white adults.
the personal use of social
networks is more prevalent
than professional use, both in
the orientation of the networks
that adults choose to use as
well as the reasons they give
for using the applications. For
instance, 50% of adult users
have a profile on MySpace,
22% on Facebook, and 6% on
linkedin.
the applications are mostly
used to explain and maintain
personal networks, and most
older adults are using them
to connect with people they
already know, usually to keep
up with (89%), make plans with
friends (57%), or to make new
friends (49%). other uses include
organizing with others for an
event, cause or issue; flirting;
promoting one’s self or work; and
making new business contacts.
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