Human Computation

Human Computation

Edith Law, Luis von Ahn,
ISBN: 9781608455164 | PDF ISBN: 9781608455171
Copyright © 2011 | 121 Pages | Publication Date: 01/01/2011

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Human computation is a new and evolving research area that centers around harnessing human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms. With the growth of the Web, human computation systems can now leverage the abilities of an unprecedented number of people via the Web to perform complex computation. There are various genres of human computation applications that exist today. Games with a purpose (e.g., the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while playing an enjoyable game. Crowdsourcing marketplaces (e.g., Amazon Mechanical Turk) are human computation systems that coordinate workers to perform tasks in exchange for monetary rewards. In identity verification tasks, users perform computation in order to gain access to some online content; an example is reCAPTCHA, which leverages millions of users who solve CAPTCHAs every day to correct words in books that optical character recognition (OCR) programs fail to recognize with certainty.

This book is aimed at achieving four goals: (1) defining human computation as a research area; (2) providing a comprehensive review of existing work; (3) drawing connections to a wide variety of disciplines, including AI, Machine Learning, HCI, Mechanism/Market Design and Psychology, and capturing their unique perspectives on the core research questions in human computation; and (4) suggesting promising research directions for the future.

Table of Contents

Introduction
Human Computation Algorithms
Aggregating Outputs
Task Routing
Understanding Workers and Requesters
The Art of Asking Questions
The Future of Human Computation

About the Author(s)

Edith Law, Carnegie Mellon University
Edith Law is a Ph.D. candidate at Carnegie Mellon University, who is doing research on human computation systems that harness the joint efforts of machines and humans, with a focus on games with a purpose and citizen science. She is the co-organizers of the 1st and 3rd human computation workshops (HCOMP 2009 and HCOMP 2011), and the recipient of Microsoft Graduate Research Fellowship 2009-2011. Her work on TagATune has received a best paper nomination at CHI 2009.

Luis von Ahn, Carnegie Mellon University
Luis von Ahn is the A. Nico Habermann Associate Professor in the Computer Science Department at Carnegie Mellon University. His current research interests include building systems that combine the intelligence of humans and computers to solve large-scale problems that neither can solve alone. An example of his work is reCAPTCHA, in which over 750 million people (more than 10% of humanity) have helped digitize books and newspapers. He is the recipient of a MacArthur Fellowship, a Packard Fellowship, a Microsoft New Faculty Fellowship, and a Sloan Research Fellowship. He has been named one of the 50 Best Minds in Science by Discover Magazine, one of the 100 Most Creative People in Business of 2010 by Fast Company Magazine, and one of the "Brilliant 10" scientists of 2006 by Popular Science Magazine.

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Related Series

Human Language Technologies

Reviews

Today, it may be difficult to find anybody browsing the Web who has never seen a CAPTCHA (completely automated public Turing test to tell computers and humans apart), a simple mechanism that many Web sites use to ensure that the visitors to the site are indeed human. In a typical CAPTCHA, the user is asked to identify and type in a word or some other sequence of letters and/or numbers based on a distorted image presented to the user. Today, users are more likely to encounter a reCAPTCHA, a modification of the same technique, in which two words are presented, one of which is generated from a scanned text that an optical character recognition system failed to recognize. By presenting the same unrecognized word to a large number of humans and asking them to type in the word that they see, a consensus emerges, thus solving a recognition problem that a computer system could not solve.

Law and von Ahn introduce the field of human computation, which leverages the collective force of human minds to solve simple tasks in order to solve computationally complex problems. reCAPTCHA is just one example of a human computation system that solves the problem of identity verification. Amazon’s Mechanical Turk is an example of a crowdsourcing marketplace, a human computation system where workers perform small tasks in exchange for monetary rewards. Other types of human computation systems include games that help tag audiovisual information, and distributed data collection for scientific purposes.

This book has several objectives. It surveys the nascent field of research and development in the area of human computation; offers a comprehensive review of many existing projects in this area; shows that a number of connections exist between the field of human computation and a broad variety of other disciplines, including machine learning, human-computer interaction, and psychology; and identifies emerging directions for further research in the field.

This book concludes with a comprehensive bibliography, to which the authors refer throughout the text. Given that human computation is a very young and rapidly developing research area, many sources in this bibliography may quickly become outdated. The authors should be commended for achieving two seemingly mutually exclusive tasks: presenting the material in a way that is accessible to a well-rounded generalist while not sacrificing the depth of coverage.
Stan Kurkovsky - ACM Computing Reviews

Reviews (1)

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