title: Lessons Learned from Crowdsourcing Complex Engineering Tasks.
abstract: Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations.
  Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data.
  We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task.
  
  
  CONCLUSIONS
  With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.
authors.affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Matthew
authors.initials: M
authors.lastname: Staffelbach
authors.affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Peter
authors.initials: P
authors.lastname: Sempolinski
authors.affiliation: Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Tracy
authors.initials: T
authors.lastname: Kijewski-Correa
authors.affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Douglas
authors.initials: D
authors.lastname: Thain
authors.affiliation: Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Daniel
authors.initials: D
authors.lastname: Wei
authors.affiliation: Department of Civil & Environmental Engineering & Earth Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Ahsan
authors.initials: A
authors.lastname: Kareem
authors.affiliation: Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana, United States of America.
authors.forename: Gregory
authors.initials: G
authors.lastname: Madey
mesh_terms: D000328:Adult; D001076:Aptitude; D003198:Computer Simulation; D063045:Crowdsourcing; D004738:Engineering; D005260:Female; D006801:Humans; D008297:Male; D011340:Problem Solving; D055815:Young Adult