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Erschienen in:
Foundations in Human Computation Kapitel lesen Erstes Kapitel lesen

2013 | OriginalPaper | Buchkapitel

The Wisdom of Crowds: Methods of Human Judgement Aggregation

verfasst von : Aidan Lyon, Eric Pacuit

Erschienen in: Handbook of Human Computation

Verlag: Springer New York

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Abstract

Although the idea is an old one, there has been a recent boom in research into the Wisdom of Crowds, and this appears to be at least partly due to the now widespread availability of the Internet, and the advent of social media and Web 2.0 applications. In this paper, we start by laying out a simple conceptual framework for thinking about the Wisdom of the Crowds. We identify six core aspects that are part of any instance of the Wisdom of the Crowds. One of these aspects, called aggregation, is the main focus of this paper. An aggregation method is the method of bringing the many contributions of a crowd together into a collective output. We discuss three different types of aggregation methods: mathematical aggregation, group deliberation and prediction markets.

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Vorheriges Kapitel Algorithms: Introduction
Nächstes Kapitel Balancing Human and Machine Contributions in Human Computation Systems
Fußnoten
1
We say “so-called”, because examples of the Wisdom of Crowds often have little to do with the notion of wisdom that philosophers care about (see Andler (2012) for further discussion), and they often involve only a group of people—even just a handful—and not a crowd in the usual sense of the word. Nevertheless, we will stick with the words that seem to have stuck.
 
2
Psychologists have found that even just single person can function as a crowd of individuals (see e.g., Vul and Pashler 2008; Herzog and Hertwig 2009; Hourihan and Benjamin 2010).
 
3
For example, it should rain on 90 % of the days that your crowd says there is a 90 % chance of rain.
 
4
This is because N and N → G entail G, so if the former two propositions are true, the latter has to be true.
 
5
As we noted in section “Thinking About the Wisdom of Crowds”, not all deliberation groups are instances of judgement aggregation. For example, the crowd could simply meet to share information and then still give different individual judgements, which could then be aggregated using one of the methods described in sections “Thinking About the Wisdom of Crowds” or “Prediction Markets”.
 
Literatur
Amrstrong JS (2006) Should the forecasting process eliminate face-to-face meetings? Int J Appl Forecast 5:3–8
Andler D (2012) What has Collective Wisdom to do with Wisdom? In: Landemore H, Elster J (eds) Collective wisdom. Cambridge University Press, Cambridge, pp 72–84
Armstrong J (2001a) Principles of forecasting. Kluwer Academic, BostonCrossRef
Armstrong S (2001b) Combining forecasts. In: Armstrong S (ed) Principles of forecasting: a handbook for researchers and practitioners. Kluwer Academic, NorwellCrossRef
Arrow KJ, Forsythe R, Gorham M, Hahn R, Hanson R, Ledyard JO, Levmore S, Litan R, Milgrom P, Nelson FD, Neumann GR, Ottaviani M, Schelling TC, Shiller RJ, Smith VL, Snowberg E, Sunstein CR, Tetlock PC, Tetlock PE, Varian HR, Wolfers J, Zitzewitz E (2008) The promise of prediciton markets. Science 320:877–878CrossRef
Asan G, Sanver R (2002) Another characterization of majority rule. Econ Lett 75(3):409–413
Bao P, Gerber E, Gergle D, Hoffman D (2010) Momentum: getting and staying on topic during a brainstorm. In: Proceedings of the SIGCHI conference on human factors in computing systems, Atlanta, pp 1233–1236
Black D (1963) The theory of committees and elections. Springer, Norwell, MA
Brownstein JS, Freifeld CC, Madoff LC (2009) Digital disease detection—harnessing the web for public health surveillance. N Engl J Med 360(21):2153–2157CrossRef
Burgman M, McBride M, Ashton R, Speirs-Bridge A, Flander L, Wintle B, Fidler F, Rumpff L, Twardy C (2011) Expert status and performance. PLoS One 6(7):e22998CrossRef
Chen Y, Pennock D (2010) Designing markets for prediction. AI Mag 31(4):42–52MathSciNet
Chen Y, Dimitrov S, Sami R, Reeves D, Pennock D, Hanson R, Fortnow L, Gonen R (2010) Gaming prediction markets: equilibrium strategies with a market maker. Algorithmica 58(4):930–969MathSciNetCrossRefMATH
Clemen RT (2008) Comment on cooke’s classical method. Reliab Eng Syst Saf 93(5):760–765CrossRef
Collier N, Kawazoe A, Jin L, Shigematsu M, Dien D, Barrero R, Takeuchi K, Kawtrakul A (2006) A multilingual ontology for infectious disease surveillance: rationale, design and challenges. Lang Resour Eval 40(3):405–413
Condorcet M (1785) Essai sur l’application de l’analyse á la probabilité des décisions rendues á la pluralité des voix. Paris: l’Imprimerie Royale. (Reprint, 1972, Chelsea, New York)
Cooke RM (1991) Experts in uncertainty: opinion and subjective probability in science. Oxford University Press, New York
Diehl M, Stroebe W (1987) Productivity loss in brainstorming groups: toward the solution of a riddle. J Personal Soc Psychol 53(3):497–509CrossRef
Dietrich F (2012) Judgment aggregation and the discursive dilemma. In: Encyclopedia of philosophy and the social sciences. Sage
Fidler F, Wintle B, Thomason N (2013) Groups making wise judgements. Final report to IARPA (Intelligence Advanced Research Projects Activity)
Frongillo R, Della Penna N, Reid M (2012) “Interpreting prediction markets: a stochastic approach.” In: Proceedings of neural information processing systems
Galton F (1907a) Letters to the editor: the ballot-box. Nature 75:900–1
Gerber E (2009) Using improvisation to enhance the effectiveness of brainstorming. In: Proceedings of the SIGCHI conference on human factors in computing systems, Boston, pp 97–104
Gigone D, Hastie R (1993) The common knowledge effect: informaiton sharing and group judgments. J Personal Soc Psychol 65(5):959–974CrossRef
Graefe A, Armstrong JS (2011) Comparing face-to-face meetings, nominal groups, delphi and prediction markets on an estimation task. Int J Forecast 27(1):183–195CrossRef
Hanson R, Oprea R (2009) A manipulator can aid prediction market accuracy. Economica 76(302): 304–314
Hanson R, Oprea R, Porter D (2006) Information aggregation and manipulation in an experimental market. J Econ Behav Organ 60(4):449–459
Herzog SM, Hertwig R (2009) The wisdom of many in one mind improving individual judgments with dialectical bootstrapping. Psychol Sci 20(2):231–237CrossRef
Hourihan KL, Benjamin AS (2010) Smaller is better (when sampling from the crowd within): low memory-span individuals benefit more from multiple opportunities for estimation. J Exp Psychol Learn Mem Cogn 36(4):1068CrossRef
Keller M, Blench M, Tolentino H, Freifeld C, Mandl K, Mawudeku A, Eysenbach G, Brownstein J (2009) Use of unstructured event-based reports for global infectious disease surveillance. Emerg Infect Dis 15(5):689CrossRef
Klayman J, Soll J, González-Vallejo C, Barlas S (1999) Overconfidence: it depends on how, what, and whom you ask. Organ behav Hum Decis Process 79(3):216–247CrossRef
Koriat A (2012) When are two heads better than one and why? Science 336:360–2CrossRef
Ladha KK (1992) The condorcet Jury theorem, free speech, and correlated votes. Am J Political Sci 36(3):617–634
Landemore H, Elster J (2012) Collective wisdom: principes and mechanisms. Cambridge University Press, New YorkCrossRef
Lehrer K, Wagner C (1981) Rational consensus in science and society: a philosophical and mathematical study, Vol 24. D Reidel, DordrechtCrossRefMATH
Linstone HA, Turoff M (1975) The Delphi method: techniques and applications. Addison-Wesley, ReadingMATH
List C, Goodin RE (2002) Epistemic democracy: generalizing the condorcet Jury theorem. J Political Philos 9(3):277–306CrossRef
List C, Pettit P (2002) Aggregating sets of judgments: an impossibility result. Econ Philos 18(01):89–110
Lo, A (2007) Efficient market hypothesis, in The New Palgrave: A Dictionary of Economics, L. Blume, S. Durlauf (eds), Palgrave Macmillan
Loewer B, Laddaga R (1985) Destroying the consensus. Synthese 62(1):79–95CrossRef
Lyon A, Fidler F, Burgman M (2012a) Judgement swapping and aggregation. In: 2012 AAAI fall symposium series
Lyon A, Nunn M, Grossel G, Burgman M (2012b) Comparison of web-based biosecurity intelligence systems: biocaster, epispider and healthmap. Transboundary Emerg Dis 59(3):223–232CrossRef
Lyon A, Grossel G, Nunn M, Burgman M (2013) Using internet intelligence to manage biosecurity risks: a case study for aquatic animal health. Divers Distrib 19(5–6):640–650CrossRef
Manski C (2006) Interpreting the predictions of prediction markets. Econ Lett 91(3):425–429CrossRef
Maskin E (1995) Majority rule, social welfare functions and game forms. In: Choice, welfare and development: a festschrift in honour of Amartya K. Sen. Oxford University Press, Oxford, pp 100–109
May K (1952) A set of independent necessary and sufficient conditions for simply majority decision. Econometrica 20(4):680–684CrossRefMATH
Nielsen M (2011) Reinventing discovery: the new era of networked science. Princeton University Press, Princeton
Nuwer R (2013) Software could make rare diseases easier to spot. New Sci 218(2913):21CrossRef
Othman A, Sandholm T (2010) When do markets with simple agents fail? In: Proceedings of the 9th international conference on autonomous agents and multiagent systems, AAMAS ’10, Toronto, vol 1, pp 865–872
Pacuit E (2012) Voting methods. In: Zalta EN (ed) The stanford encyclopedia of philosophy. (Winter 2012 edn)
Page S (2008) The difference: how the power of diversity creates better groups, firms, schools, and societies (new edn). Princeton University Press, Princeton
Pennock DM, Sami R (2007) Computational aspects of prediction markets. In: Nisan N, Roughgarden T, Tardos E, Vazirani V (eds) Algorithmic game theory. Cambridge University Press, Cambridge/New York
Plummer B (2012) How to swing the prediction markets and boost Mitt Romney’s fortunes, The Washington Post Wonkblog, October 23
Regan HM, Colyvan M, Markovchick-Nicholls L (2006) A formal model for consensus and negotiation in environmental management. J Environ Manag 80(2):167–176CrossRef
Rothschild D (2009) Forecasting elections: comparing prediction markets, polls and their biases. Public Opin Q 73(5):895–916CrossRef
Sunstein C (2011) Deliberating groups versus prediction markets or Hayek’s challenge to habermas. In: Social epistemology: essential readings. Oxford University Press, Oxford/New York, pp 314–337
Surowiecki J (2005) The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. Doubleday, New York
Thaler R, Ziemba W (1988) Anomalies: parimutuel betting markets: racetracks and lotteries. J Econ Perspect 2(2):161–174CrossRef
Von Ahn L, Maurer B, McMillen C, Abraham D, Blum M (2008) Recaptcha: human-based character recognition via web security measures. Science 321(5895):1465–1468MathSciNetCrossRefMATH
Vul E, Pashler H (2008) Measuring the crowd within probabilistic representations within individuals. Psychol Sci 19(7):645–647CrossRef
Wolfers J, Zitzewitz E (2004) Prediction markets. Journal of Economic Perspectives, 18(2):107–126
Metadaten
Titel
The Wisdom of Crowds: Methods of Human Judgement Aggregation
verfasst von
Aidan Lyon
Eric Pacuit
Copyright-Jahr
2013
Verlag
Springer New York
Buch
Handbook of Human Computation

Print ISBN: 978-1-4614-8805-7

Electronic ISBN: 978-1-4614-8806-4

Copyright-Jahr: 2013

DOI
https://doi.org/10.1007/978-1-4614-8806-4_47

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