A human-based computation game or game with a purpose (GWAP) is a human-based computation technique of outsourcing steps within a computational process to humans in an entertaining way (gamification).

Luis von Ahn first proposed the idea of "human algorithm games", or games with a purpose (GWAPs), in order to harness human time and energy for addressing problems that computers cannot yet tackle on their own. He believes that human intellect is an important resource and contribution to the enhancement of computer processing and human computer interaction. He argues that games constitute a general mechanism for using brainpower to solve open computational problems. In this technique, human brains are compared to processors in a distributed system, each performing a small task of a massive computation. However, humans require an incentive to become part of a collective computation. Online games are used as a means to encourage participation in the process.

The tasks presented in these games are usually trivial for humans, but difficult for computers. These tasks include labeling images, transcribing ancient texts, common sense or human experience based activities, and more. Human-based computation games motivate people through entertainment rather than an interest in solving computation problems. This makes GWAPs more appealing to a larger audience. GWAPs can be used to help build the semantic web, annotate and classify collected data, crowdsource general knowledge, and improving other general computer processes. GWAPs have a vast range of applications in variety of areas such as security, computer vision, Internet accessibility, adult content filtering, and Internet search. In applications such as these, games with a purpose have lowered the cost of annotating data and increased the level of human participation.

History

The first human-based computation game or games with a purpose was created in 2004 by Luis von Ahn. The idea was that ESP would use human power to help label images. The game is a two player agreement game and relied on players to come up with labels for images and attempt to guess what labels a partner was coming up with. ESP used microtasks, simple tasks that can be solved quickly without the need of any credentials.Von Ahn, L., & Dabbish, L. (2004, April). Labeling images with a computer game. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 319-326). ACM.

Game design principles Output agreement game

Games with a purpose categorized as output agreement games are microtask games where players are matched into pairs and randomly assigned partners attempt to match output with each other given a shared visible input. ESP is an example of an output agreement game.

Inversion problem games

Given an image, the ESP Game can be used to determine what objects are in the image, but cannot be used to determine the location of the object in the image. Location information is necessary for training and testing computer vision algorithms, so the data collected by the ESP Game is not sufficient. Thus, to deal with this problem, a new type of microtask game known as inversion problem games were introduced by creator of ESP, von Ahn in 2006. Peekaboom extended upon ESP and had players associate labels with a specific region of an image. In inversion problem games, two players are randomly paired together. One is assigned as the describer and the other is the guesser. The describer is given an input, which the guesser must reproduce given hints from the describer. In Peekaboom, for example, the describer slowly reveals small sections of an image until the guesser correctly guesses the label provided to the describer.Von Ahn, L., Liu, R., & Blum, M. (2006, April). Peekaboom: a game for locating objects in images. In Proceedings of the SIGCHI conference on Human Factors in computing systems (pp. 55-64). ACM.

Input agreement games

In input-agreement games two randomly paired players are each given an input that is hidden from the other player. Player inputs will either match or be different. The goal of these games is for players to tag their input such that the other player can determine whether or not the two inputs match. In 2008, Edith L. M. Law created the input-agreement game called TagATune. In this game, players label sound clips. In TagATune, players describe sound clips and guess if their partner's sound clip is the same as their own given their partner's tags.Law, E. L., Von Ahn, L., Dannenberg, R. B., & Crawford, M. (2007, September). TagATune: A Game for Music and Sound Annotation. In ISMIR (Vol. 3, p. 2).

Macrotask games

Macrotask games, unlike microtask games, contain complex problems that are usually left to experts to solve. In 2008, a macrotask game called Foldit was created by Seth Cooper. The idea was that players would attempt to fold a three-dimensional representation of a protein. This task was a hard problem for computers to automate completely. Locating the biologically relevant native conformation of a protein is a difficult computational challenge given the very large size of the search space. By gamification and implementation of user friendly versions of algorithms, players are able to perform this complex task without much knowledge of biology.Khatib, F., Cooper, S., Tyka, M. D., Xu, K., Makedon, I., Popović, Z., ... & Players, F. (2011). Algorithm discovery by protein folding game players. Proceedings of the National Academy of Sciences, 108(47), 18949-18953.Lafourcade, M., Joubert, A., & Le Brun, N. (2015). Games with a Purpose (GWAPS). John Wiley & Sons.Von Ahn, L., & Dabbish, L. (2008). Designing games with a purpose. Communications of the ACM, 51(8), 58-67.

Examples Apetopia The Apetopia game helps determining perceived color differences. Players' choices are used to model better color metrics. The Apetopia game, which was launched by University of Berlin, is designed to help scientists understand perceived color differences. This game is intended to provide data on how the shades of color are perceived by people in order to model the best color parameters.

Artigo Artigo is a Web platform currently offering six artwork annotation games as well as an artwork search engine in English, French, and German. Three of Artigo's games, the ARTigo game, ARTigo Taboo, and TagATag, are variationsFrançois Bry and Christoph Wieser. Squaring and Scripting the ESP Game: Trimming a GWAP to Deep Semantics. Proc. of the International Conference on Serious Games Development and Applications (SGDA), Bremen, Germany, 26–29 September 2012 of Luis von Ahn's ESP game (later Google Image Labeler). Three other games of the Artigo platform, Karido, (Best Paper Award) Artigo-Quiz, and Combino, have been conceived so as to complement the data collected by the three aforementioned ESP game variations.Christoph Wieser, François Bry, Alexandre Bérard, and Richard Lagrange. ARTigo: Building an Artwork Search Engine With Games and Higher-Order Latent Semantic Analysis. Proc. of Disco 2013, Workshop on Human Computation and Machine Learning in Games at the International Conference on Human Computation (HComp), Palm Springs, California, USA, 6th - 9th November, 2013.Christoph Wieser. Building a Semantic Search Engine with Games and Crowdsourcing. Doctoral Thesis, Institute for Informatics, Ludwig-Maximilians-Universität München, 2014 Artigo's search engine relies on an original tensor latent semantic analysis.Philipp Shah, Christoph Wieser, and François Bry Parallel Higher-Order SVD for Tag-Recommendations. Proc. of the International Conference WWW/Internet 2012, Madrid, Spain, 18th-21st October, 2012

As of September 2013, Artigo had over 30,000 (pictures of) artworks mostly of Europe and of the "long 19th century", from the Promotheus Image Archive, the Rijksmuseum, Amsterdam, the Netherlands, the Staatliche Kunsthalle Karlsruhe, Karlsruhe, Germany, the University Museum of Contemporary Art, campus of the University of Massachusetts Amherst, USA. From 2008 through 2013, Artigo has collected over 7 million tags (mostly in German), 180,000 players (about a tenth of whom are registered), and in average 150 players per day.

Artigo is a joint research endeavor of art historians and computer scientists aiming at both developing an art work search engine and data analysis in art history.

ESP game

The first example was the ESP game, an effort in human computation originally conceived by Luis von Ahn of Carnegie Mellon University, which labels images. To make it an entertaining effort for humans, two players attempt to assign the same labels to an image. The game records the results of matches as image labels and the players enjoy the encounter because of the competitive and timed nature of it. To ensure that people do their best to accurately label the images, the game requires two people (chosen at random and unknown to each other), who have only the image in common, to choose the same word as an image label. This discourages vandalism because it would be self-defeating as a strategy. The ESP game is a human-based computation game developed to address the problem of creating difficult metadata. The idea behind the game is to use the computational power of humans to perform a task that computers cannot (originally, image recognition) by packaging the task as a game. Google bought a licence to create its own version of the game (Google Image Labeler) in 2006 in order to return better search results for its online images."Solving the web's image problem". bbc. 2008-05-14. Retrieved 2008-12-14. The license of the data acquired by Ahn's ESP Game, or the Google version, is not clear. Google's version was shut down on 16 September 2011 as part of the Google Labs closure in September 2011.

PeekaBoom PeekaBoom is a web-based game that helps computers locate objects in images by using human gameplay to collect valuable metadata. Humans understand and are able to analyze everyday images with minimal effort (what objects are in the image, their location, as well as background and foreground information), while computers have trouble with these basic visual tasks.. Barnard, K., and Forsyth, D. A. Learning the Semantics of Words and Pictures. International Conference of Computer Vision, 2001 Peekaboom has two main components: "Peek" and "Boom". Two random players from the Web participate by taking different roles in the game. When one player is Peek, the other is Boom. Peek starts out with a blank screen, while Boom starts with an image and a word related to it. The goal of the game is for Boom to reveal parts of the image to Peek. In the meantime, Peek can guess associated words with the revealed parts of the image. When Peek guesses words that are closer to the image, Boom can indicate whether Peek's guesses are hot or cold. When Peek correctly, the players gets points and then switch roles.

EteRNA

EteRNA is a game in which players attempt to design RNA sequences that fold into a given configuration. The widely varied solutions from players, often non-biologists, are evaluated to improve computer models predicting RNA folding. Some designs are actually synthesized to evaluate the actual folding dynamics and directly compare with the computer models.

Eyewire Eyewire is a game for finding the connectome of the retina.

Foldit

Crowdsourcing has been gamified in games like Foldit, a game designed by the University of Washington, in which players compete to manipulate proteins into more efficient structures. A 2010 paper in science journal Nature credited Foldit's 57,000 players with providing useful results that matched or outperformed algorithmically computed solutions.