Human computation

By Luis von Ahn. 2009 46th ACM/IEEE Design Automation Conference, 2009

701 citations recorded by the source corpus.

Subfields: Information Systems, Molecular Biology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/f537128e57f798c2345c162830a45200a22861e4

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Citations in the corpus

Cloud-based robot grasping with the google object recognition engine (2013, background): “Users upload millions of digital photos every day and there are several image labeling projects using humans and machine learning [33] [36] [38].”
Studying Gamification: The Effect of Rewards and Incentives on Motivation (2015, methodology): “Von Ahn and Dabbish ( 2008 ) state that using points increases motivation by providing a clear connection between effort in the game, performance and outcomes.”
Image Object Label 3 D CAD Model Candidate Grasps Google Object Recognition Engine Google Cloud Storage Select Feasible Grasp with Highest Success Probability Pose EstimationCamera Robots Cloud 3 D Sensor (2014, background): “systems with computation performed by humans [129], [154].”
A Survey of Research on Cloud Robotics and Automation (2015, background): “11). research and many in industry, with the ROS Industrial project created to support these users [17].”
Autotagging Facebook: Social network context improves photo annotation (2008, result): “(A small number of faces have been withheld by request from the results above, none of which were correct matches.) this way, from only 53 community members, we compiled a labeled database of face samples that is signiﬁcantly larger than most manually-collected databases reported in the literature…”
Information and Computation (2013, background): “Before delving into the role of information theory as a descriptive tool for human computation (von Ahn, 2009), we have to agree on at least two things: what is human, and what is computation, as human computation is at its most general level computation performed by humans.”
Evaluation in artificial intelligence: from task-oriented to ability-oriented measurement (2017, background): “Notions such as ‘animat’ (Williams and Beer, 2010), machine-enhanced humans (Cohen, 2013), human-enhanced machines (von Ahn, 2009), other kind of hybrids and, most especially, collectives (Quinn and Bederson, 2011) of any of the former, suggest that the distinction between animals, humans and…”
Disentangling the Effects of Social Signals (2014, background): “For instance, studies of news aggregators (Hogg and Lerman, 2012; Stoddard, 2015) and product recommendation (Wang et al., 2014) used such models to identify contributions of position bias, social signals and the appeal of the content to popularity.”
Designing Contestability: Interaction Design, Machine Learning, and Mental Health (2017, background): “For example, reCAPTCHA [18] is a popular authentication service in which users provide semantic labels for images before they are allowed to access a desired website.”
Crowdsourced Data Management: Industry and Academic Perspectives (2015, background): “Thesis [182]: “Crowdsourcing (or Human Computation) is a paradigm that utilizes human processing power to solve problems that computers cannot yet solve.”
Social Cues, Social Biases: Stereotypes in Annotations on People Images (2018, background): “A key challenge is that the inter-dependencies and tensions between these design decisions are “intricate and little understood” (Law and von Ahn 2011) (p. 58).”