Anonymity

Crowdsourcing & Work Quality

• 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 for crowdwork, developed last year and reposted on Class 3, classify 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.

• For a quick overview by Jeff Howe, author of Crowdsourcing,[1] take a look at this YouTube clip.[2]

We are focusing on the quality of crowdsourced work.

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).[3]

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.[4] 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?