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Page 1: Can Small Crowds Be Wise? Moderate-Sized Groups Can … · 2018-07-03 · 1 Can small crowds be wise? Moderate‐sized groups can outperform large groups and individuals under some

Can Small Crowds Be Wise?Moderate-Sized Groups CanOutperform Large Groups andIndividuals Under Some TaskConditionsMirta GalesicDaniel BarkocziKonstantinos Katsikopoulos

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Cansmallcrowdsbewise?

Moderate‐sizedgroupscanoutperformlargegroupsand

individualsundersometaskconditions

MirtaGalesic12*,DanielBarkoczi2,&KonstantinosKatsikopoulos2

1SantaFeInstitute

1399HydeParkRoad

SantaFe,NM87501,USA

2CenterforAdaptiveBehaviorandCognition

MaxPlanckInstituteforHumanDevelopment

Lentzeallee94,14195,Berlin,Germany

*Correspondingauthor:[email protected]

Keywords:wisdomofcrowds;majorityrule;CondorcetJuryTheorem;group

decisionmaking

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Abstract

Decisionsaboutpolitical,economic,legal,andhealthissuesareoftenmadeby

simplemajorityvotingingroupsthatrarelyexceed30‐40membersandaretypicallymuch

smaller.Giventhatwisdomisusuallyattributedtolargecrowds,andthattechnological

advancesmakegroupmeetingseasierthaneverbefore,shouldn’tcommitteesbelarger?In

manyreal‐lifesituations,expertgroupsencounteranumberofdifferenttasks.Mostare

easy,withaverageindividualaccuracyisabovechance,butsomearesurprisinglydifficult,

withmostgroupmembersbeingwrong.Examplesofthelatterareelectionswith

unexpectedoutcomes,suddenturnsinfinancialtrends,ortrickyknowledgequestions.

Mostofthetime,groupscannotpredictinadvancewhetherthenexttaskwillbeeasyor

difficult.Weshowthatinthesecircumstancesmoderate‐sizedgroupscanachievehigher

averageaccuracyacrossalltasksthanlargergroupsorindividuals.Thishappensbecause

anincreaseingroupsizecanleadtoadecreaseingroupaccuracyfordifficulttaskswhich

islargerthanthecorrespondingincreaseinaccuracyforeasytasks.Wederivethisnon‐

monotonicrelationshipbetweengroupsizeandaccuracyfromCondorcetJuryTheorem

andusesimulationsandfurtheranalysestoshowthatitholdsunderavarietyof

assumptions,includingtwoormoretaskdifficulties,taskswithtwoandmoreoptions,

independentandcorrelatedvotes,andsamplingfromeitherinfinitepopulationsorfrom

finitepopulationswithoutreplacement.Wefurthershowthatsituationsfavoring

moderate‐sizedgroupsoccurinavarietyofreal‐lifedomainsincludingpolitical,medical,

andfinancialdecisions,andgeneralknowledgetests.Wediscussimplicationsforthe

designofdecision‐makingbodiesatalllevelsofpolicy.

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Introduction

Individualsandsocietiesoftenmakedecisionsbyfollowingthemajorityvoteof

moderatelysizedgroups.Forexample,jurysizesinmanycountriesrangefromsixto15

peoplewhomostoftendecidebysimplemajority(Leib,2008).Localtownandparish

councilssuchasthoseintheUnitedKingdomandAustraliaconsistoffivetoaround30

members(U.K.DepartmentforCommunitiesandLocalGovernment,2008;Electoral

CouncilofAustralia&NewZealand,2013),governingbodiesofmostGermanlaborunions

havefromthreeto35members(dejure.org,2013),parliamentarycommitteesinthe

UnitedStates,theEuropeanUnion,Australia,andothercountrieshaveonaverage20to40

members(EuropeanParliament,2014;Haas,2014;ParliamentofAustralia,2014),

subcommitteesintheU.S.HouseandSenateconsistofonaverage10to15people(Haas,

2014),andpolicyboardsofmostcentralbankshaveupto12members(Lyberk&Morris,

2004).Similarly,individualsconsideringavarietyofdecisionstypicallyrelyonsixorfewer

closefriends(Galesic,Olsson,&Rieskamp,2012)andreadaboutfiveandrarelymorethan

30onlinereviewsbeforedecidingwhethertotrustabusiness(Anderson,2014).Deciding

inmoderately‐sizedgroupscanalsobeobservedinotherspeciesthroughouttheanimal

kingdom(Krause&Rukton,2002).

Inmanycases,decidingingroupsratherthanrelyingonanindividualdecision

makercanboostoveralldecisionaccuracy(Surowiecki,2004).Thishasbeenshownboth

forpredictionsofcontinuousvariables,suchasinGalton’sdemonstrationsofthevalueof

voxpopuli(Galton,1907),andforcategoricalchoicesbetweendistinctcoursesofaction

undercertainconditions(Condorcet,1785).Today,technologicaladvancesmakemeeting

andcommunicationinlargergroupseasierthaneverbefore(e.g.,varioussocial

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networkingsites;LiquidFeedback,2014).Why,then,domostcommitteesremain

moderatelysized,andwhydomostpeopleconsultonlyalimitednumberofothers’

opinions?Existingexplanationsfocusontimeandcoordinationcostsoroncognitive

limitationsthatpreventstablerelationshipswithalargenumberofindividuals(Dunbar,

1993).Wecomplementtheseexplanationswithanargumentforthesuperiorityof

moderategroupsizesbasedsolelyongroupdecisionaccuracy.

Inmanyreal‐lifesituations,expertgroupsencountermostlyeasytasksonwhich

averageindividualaccuracyisabovechance,andsomesurprisinglydifficulttaskswhere

mostmembersguesswrongly(seenextsectionforexamples).Hereweshowthat,whenit

isnotknownwhetherthenexttaskwillbeeasyordifficult,averagedecisionaccuracypeaks

whenvotingisdonebymoderatelysizedgroups.Thisdoesnotoccurbecauseofselective

samplingofgroupmembersbasedonexpertise(Budescu&Chen,2014;Goldstein,McAfee,

&Suri,2014;Mannes,Soll,&Larrick,2014)butsolelybecausetheaccuracyofgroups

decidingbysimplemajorityorpluralityrulesincreaseswiththeirsizeforrelativelyeasy

tasksbutdecreasesfortasksforwhichmostindividualsmakethewrongprediction.

TaskswithSurprisingOutcomes

Taskswithunexpectedoutcomesthataredifficulttopredictcanbefoundinmany

domains,includingpoliticalandeconomicforecasts,medicaldiagnoses,andgeneral

knowledgetests.Forexample,considerelectionforecasts.Expertforecastersoftenshow

better‐than‐chancepredictionaccuracy,butafewelectionyearshavebeensurprisingly

difficulttopredict.SuchwastheU.K.2015generalelection,whereallbutonepolling

companyerroneouslypredictedthatTorieswouldnotwinamajorityofseatsinthe

Parliament(Bialik,2015).Similarly,majorityofforecastersintheU.S.2000presidential

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electionspredictedGore’svictoryoverBushinFlorida(Graefe,2014;Whitson,2001).As

illustratedinthelastsection,expertssuchaspoliticalforecasters,medicaldoctors,

financialexperts,ortriviaquizparticipants,whodonotknowwhetherthenexttaskwillbe

easyordifficult,willoftendobesttodecidebymajorityinmoderatelysizedgroupsrather

thaninlargegroupsorindividually.

Considertheknowledgequestion“Whichcityisfarthernorth,NewYorkorRome?”,

whichmostpeopleanswerincorrectly.Temperature,thecuethatisvalidformostother

comparisonsofcitylatitudes,pointstothewronganswerforthispairofcities(Gigerenzer,

Hoffrage,&Kleibölting,1991).Incasessuchasthese,majorityofindividualscanbewrong,

resultinginaverageindividualaccuracybelow50%onthoseparticulartasks.Thiscan

happenbecausethesetasksarecharacterizedbythesocalledBrunswikianuncertainty

(Juslin&Olsson,1997)thatoccursbecauseofimperfectcorrelationsofenvironmentalcues

andtheactualstatesoftheworldtheyareusedtopredict.Ifmostpeoplerelyonthesame

cues(or,equivalently,opinionleaders,mediareports,etc.)tomakeinferences,caseswhere

acue(leader,report)ismisleadingcancreatesituationswhereamajorityofpeopleare

incorrect.

However,evenwhenindividualsrelyondifferentcues,thesecuescouldallfailto

predictthecorrectoutcomeforsomespecifictasks;eitherbecausetheyarenotsuitedfor

predictingsomeparticularcasesorbecausetheenvironmenthaschangedbetweenthe

momentofpredictionandthemomentwhentheoutcomewasobserved.Forinstance,most

diseasesmightbeaccuratelydiagnosedbasedontheirsymptoms,butsomelesswell‐

knownorrarediseaseshavesymptomsthatcanpointtoseveraldifferentdiagnoses;or,

forecastsofeconomicgrowthmayprovetobewronginsomeyearsbecauseof

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unobservableunderlyingcomplexitiesaffectingthefinancialmarkets.Inwhatfollows,we

willcalltaskswithsurprisingoutcomesthatmostpeoplepredictincorrectly“difficult”,and

thosethatmostpeoplepredictcorrectly“easy”.

GroupSizeandAccuracyoveraRangeofTaskDifficulties

Mostcommitteeswillfaceavarietyoftaskdifficultiesinthecourseoftheir

existence,rangingfromveryeasytoquitedifficult.However,mostpaststudiesofgroup

decisionaccuracyhaveassumedthatgroupsalwaysencountertasksofthesameand

knowndifficulty.Oncetaskdifficultyisknown,itisrelativelystraightforwardtotellwhat

thegroupsizeshouldbetomaximizeaccuracy,atleastwhengroupmembersvote

independently.Inprinciple,foreasytasks,inwhichaverageindividualaccuracyofgroup

members(averageindividualprobabilityofbeingcorrect)islargerthan0.5,majorityvote

inlargergroupswillbemoreaccuratethaninsmallergroups,andviceversafordifficult

tasks(Condorcet,1785).However,inmostreal‐lifesituationsonecannotpredictin

advancehowdifficultthenexttaskwillbe.Allonemightknowisanapproximate

distributionoftaskdifficultiesagroupmightface.Forinstance,anexpertgroupmight

encountermostlyquiteeasytasksandoccasionallysomesurprisinglydifficulttasks.A

novicegroupmightfindmosttasksverydifficultandsomequiteeasy.Inaddition,insome

domainspredictionsareinherentlyeasierthaninothers.Notknowingexactlywhattask

difficultiesagroupwillface,canwesayanythingaboutthegroupsizethatwillleadto

highestachievableaccuracy?

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WisdomofSmall,RandomlySelectedCrowds

Hereweshowthatinmanyreal‐lifesituationsmoderate‐sizedgroupswillachieve

higheraccuracythanlargergroupsorindividuals.Wefocusontasksinwhichgroupsneed

tovoteforoneoftwoormorepossiblecoursesofactionanddecidebysimplemajority,

andwhereitiseventuallypossibletodeterminewhetherthegroupdecisionwascorrector

not(seereal‐worldexamplesinthelastsection).Notethatthevotingstagemayormaynot

beprecededbyagroupdiscussionwheremembersdeterminecommongroundfor

understandingtheproblem,sharesomeoralloftheinformationtheypossessindividually,

makevariousquantitativejudgmentsrelevantfortheproblem,anddiscussconsequences

oftakingoneortheothercourseofaction.Wefocusonthefinalstageofthedecision‐

makingprocess,whereindividualvotesaretransformedintoagroupvoteforoneoftwoor

morepossiblecoursesofaction.

Forsimplicity,wefirstanalyzesituationswithtasksinvolvingtwooptionsbetween

whichgroupschoosebysimplemajorityrule,consideringonlytwotaskdifficulties,

assumingthatindividualgroupmembersvoteindependently,andassumingthattheyare

selectedfromaverylargepopulationwithreplacement.Afterwards,weaddanumberof

morerealisticassumptions,allowingformorethantwotaskdifficultiesandmorethantwo

optionsineachtask,forcorrelatedjudgmentsofgroupmembers,andforsamplingof

groupmembersfromafinitegroupwithoutreplacement.Inthelastsection,weprovide

severalreal‐worldexamplesfromdifferenttaskdomainswheresmallergroupscan

performbetterthanlargerones.

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TwoTaskDifficulties

Todeterminehowgroupaccuracydependsongroupsizewhenasingletask

involvesmakingachoicebetweentwooptionsusingasimplemajorityrule,wecanusethe

CondorcetJuryTheorem(CJT),whichcanberepresentedas

∑ 1 [1]

wherePnisgroupaccuracyatgroupsizen,missizeofsimplemajority,and isaverage

individualaccuracy.Withoutlossofgenerality,nisassumedtobealwaysodd.Individual

groupmemberscanhaveheterogeneousskills.1Othervotingrulesarepossible,suchas

requiringtwo‐thirdsmajorityorunanimousdecision,butithasbeenshownthatsimple

majorityleadstobestperformance(Sorkin,West,&Robinson,1998).

Tostudyaveragegroupaccuracyovertwoormoretasks,wefirstassumethat

groupsencountertwotaskdifficulties:Withprobabilityetheyencountereasy(denotedE)

tasks,forwhichaverageindividualaccuracy 0.5;andwithprobability1‐ethey

encountersurprisingordifficult(denotedD)tasks,forwhichaverageindividualaccuracy

0.5.Figure1showshowaveragegroupaccuracy acrossthetwotaskdifficulties

changeswithincreaseingroupsizen,assumingthattheproportionofeasytasksise=0.6.

FollowingCJT(Eq.1),foreasytasksgroupaccuracy islargerthan andincreases

monotonicallyto1asgroupsgetlarger(reddashedlinesinallpanelsofFigure1).For

difficulttasks, anddecreasesmonotonicallyto0withincreaseingroupsize(blue

1 Aslongasthedistributionofindividualskillsissymmetrical,CJTpredictionsremainessentiallythesameasifallindividualshadthesameskilllevel(Grofmanetal,1983).Deviationsoccuronlyinexceptionalcases,forinstancewhensomeindividualsconsistentlyhaveaccuracy0or1orwhenaverageaccuracyiscloseto0.5andgroupsareverysmall.Withincreaseinn,groupaccuracyPmonotonicallyincreasesto1fortaskswithaverageindividualaccuracies 0.5andmonotonicallydecreasesto0fortaskswith 0.5.Whenaverageofindividualaccuracies 0.5,Pwillconvergetoavaluebetween0.39and0.61(Owen,Grofman,&Feld,1989).Inotherwords,CJTpredictionsgeneralizetoalargerangeofasymmetricaldistributionsofindividualskills(Grofmanetal.,1983).

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dottedlines).Theaveragegroupaccuracy (fullblacklines)isequaltotheaverageof

groupaccuraciesoneasyanddifficultytasks,weightedbytheproportionoftasksofeach

difficultythatthegroupencounters:

, 1 , [2]

where istheaverageaccuracyofagroupofsizen,eistheproportionofeasytasks,and

, ( , )istheaccuracyofagroupofsizenoneasy(difficult)tasksderivedbytheCJT.

AsFigure1illustrates,changesin withchangesinndependonthetypeoftask

environment.Ina“friendly”taskenvironment,easytasksarequiteeasyanddifficulttasks

arenottoodifficult.Suchataskenvironmentmightbeencounteredbyagroupofexperts

whoareskilledinsolvingparticulartasksand,evenwhensurprised,don’tdotoobadly.In

contrast,an“unfriendly”taskenvironmentmightmoreoftenbeencounteredbyagroupof

novices:here,difficulttasksareverydifficultandeveneasytasksarenottooeasy,as

specifiedbelow.

Moreformally,wedefinea“friendly”environmentasoneinwhich 1,a

“neutral”environmentasoneinwhich 1,andan“unfriendly”environmentas

oneinwhich 1.Thesedefinitionsexpresswhetheritistheaccuracyineasytasks

ortheaccuracyindifficulttasksthatisfurtherawayfromchance.Forexample,

1isequivalentto 0.5 0.5 ,whichmeansthatinfriendly

environments,theaccuracyineasytasksisabovechancemorethantheaccuracyin

difficulttasksisbelowchance.

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Figure1.Averagegroupaccuracycanpeakatmoderategroupsizes.Illustrationofchangesingroupaccuracyasafunctionofgroupsizenanddifferentcombinationsoftaskdifficulties,assumingproportionofeasytaskse=0.6.Notethatasnincreases,averagegroupaccuracy convergestoe.(A)Ina“friendly”taskenvironment( 1), increasesuntiln=7,thendecreasestowarde.(B)Ina“neutral”taskenvironment( 1), increasesmonotonicallywithnuntilitreachese.(C)Inan“unfriendly”

taskenvironment( 1), decreasesuntiln=3,thenincreasestowarde=0.6even

though 0.5.

Inallenvironments, willstartfrom 1 ,whichistheaverage

individualaccuracyacrosseasyanddifficulttasks,andwithincreaseinnwilleventually

convergetotheproportionofeasytaskse.Convergencetoeratherthanto0or1aswould

bepredictedbythesimpleCJThappensbecauseforlargeenoughn,PEreaches1andPD

reaches0,so convergesto 1 1 0 .

Inbetweenthesetwoextremes, ande, canbeamonotonicallyincreasing,

monotonicallydecreasing,U‐shaped,orinverted‐U‐shapedfunctionofn.Whichofthese

shapesobtainsiscompletelydeterminedbytwofactorsdefinedpreciselyabove:thetype

ofenvironment(friendly,neutral,orunfriendly)andthevalueofthestartingpoint .

15 9 19 29 39 49 59 69 79 89 990

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Gro

up

acc

ura

cy

159 19 29 39 49 59 69 79 89 990

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size nG

rou

p a

ccu

racy

159 19 29 39 49 59 69 79 89 990

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Gro

up

acc

ura

cy

Group accuracy PE for easy tasks ( ) Group accuracy PD for difficult tasks ( ) Average group accuracy , assuming e = 0.6

A. “Friendly” task environment ( 0.8, 0.4)

B. “Neutral” task environment( 0.7, 0.3)

C. “Unfriendly” task environment( 0.6, 0.2)

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Notethatbecause 1 ,thecondition >0.5canbeequivalently

expressedas 0.5 / .

Moreprecisely,thefollowingholdsasnincreaseston+2(thenextoddgroupsize):

0if∆ , ∆ ,

0if∆ , ∆ ,

0if∆ , ∆ ,

[3]

where∆ ischangeinaveragegroupaccuracyacrossalltasks,and

∆ , , and∆ , , representchangeinaveragegroupaccuracy

acrosseasyanddifficulttasks,respectively.Inwords,averagegroupaccuracy will

increasewithgroupsizeiftherateofchangeinaccuracyoneasytasks∆ , ishigherthan

therateofchangeinaccuracyondifficulttasks∆ , ,weightedbytherelativeprevalence

ofdifficulttasks .Putmoresimply,ifanincreasefromnton+2leadstoagainin that

islargerthantheweightedlossitproducesin , willincreaseandotherwisedecrease.It

willreachitspeakwhenthegainsandweightedlossescanceleachother.

ToillustrateEq.3,considerafriendlyenvironment,inwhich 0.5 0.5 .

Here,therateofchangeinaccuracyoneasytasksisinitiallyhigherthantherateofchange

ondifficulttasks,asfollowsfromEq.1when iscloserto1than isto0.Whenin

additioneasytasksareencounteredmoreoften,thatiswhene>0.5andthus 1,the

differenceinratesofchangeisfurthermagnifiedand willdefinitelyincreasewithgroup

size.Ontheotherhand,wheneasytasksareencounteredlessoften,thatiswhene<0.5

andthus 1, maynotincreasewithgroupsizeeveniftheenvironmentisfriendly.

Importantly,evenwithe>0.5,theinitiallyincreasingtrendin maybereversedasn

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continuestoincreasebecause willreachitslimitingvalue,1,while willstillbe

decreasingtowardszero,driving down.ThisiswhathappensinFigure1A.Inthis

friendlytaskenvironment,anincreaseinninitiallyleadstoanincreasein ,herepeaking

at0.7forn=7beforedecreasingtoe.

Similaranalysiscanbeappliedtootherenvironments.Thecomponentof , or

1 ,whicheverinitiallychangesfaster,willbethefirsttoconvergetoitslimiting

valueandthentheothercomponentwillstartchangingfaster.Figure1Bshowsacaseofa

neutralenvironment,where increasesmonotonicallywithnuntilitreachese.Finally,

Figure1Cshowsaparticularlyinterestingcasethatoccursinunfriendlyenvironments.

Here,adownwardpeakoccurs,with initiallydecreasingandthenslowlyincreasing

towarde.Notethatinthiscase willultimatelybecomelargerthan0.5(becausee=0.6)

eventhoughtheaverageindividualaccuracyacrossdifferenttaskdifficultieswaslower

than0.5( 0.44).

SolvingEq.3analyticallyinvolvestakingderivativesofthebinomialcumulative

distributionfunctions and withrespectton.Thisproducescumbersomesolutionsso

approximationshavebeendevelopedforlargen(Grofmanetal.,1983).Toexaminehow

changesinsmallnrelatetogroupaccuracyfordifferentcombinationsoftaskdifficulties,

wecalculated usingEq.2acrossarangeofgroupsizes,forallcombinationsofeasy(0.6≤

≤0.9)anddifficult(0.1≤ ≤0.4)tasks,separatelyfordifferentproportionsofeasy

tasks0.1≤e≤0.9,inincrementsof0.1.ResultspresentedinFigures2andS1showthat

non‐monotonicchangesin ,suchasthoseshowninFigure1,occurinmorethanhalfofall

possiblecombinationsoftaskdifficulties.

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Figure2.Averagegroupaccuracydependsoncombinationoftaskdifficultyandproportionofeasytasks.Eachpanelshowschangesinaveragegroupaccuracy asafunctionofgroupsizen,differentcombinationsofeasy(0.6≤ ≤0.9)anddifficult(0.1≤≤0.4)tasks,anddifferentproportionsofeasytasks(0.1≤e≤0.9).Redlinesrepresent

casesinwhichaverageindividualaccuracyacrosstasks 0.5,bluelinesarefor0.5,andblacklinesfor 0.5,where 1 .Circlesshow

maximumvalueof foreachcase.Dashedlinesdenotecaseswhere changesmonotonicallywithnuntilitreachese,whilesolidlinesdenotecaseswhere changesnonmonotonically,thatis,reachesanupwardoradownwardpeakatmoderategroupsizenbeforereachinge.Ineachpanel,upperlinesrepresenthigherproportionsofeasytaskse(seelegendtotherightofeachrow).Panelsabovethediagonalrepresentfriendlytaskenvironments,thoseinthediagonalneutral,andthosebelowthediagonalunfriendlytaskenvironments(seemaintextfordetails).Graydottedlinesdenoteregioninwhich0.6≤

≤0.8,asiscommonlyobservedinreal‐worldpolicytasks.

1 59 15 25 35 45 55 65

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1

pE=0.9 p

D=0.4

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1

pE=0.9 p

D=0.3

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1

pE=0.9 p

D=0.2

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1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

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pE=0.8 p

D=0.4

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pE=0.8 p

D=0.3

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pE=0.8 p

D=0.2

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pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

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pE=0.7 p

D=0.4

A

vera

ge g

roup

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pE=0.7 p

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pE=0.7 p

D=0.2

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pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

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pE=0.6 p

D=0.4

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pE=0.6 p

D=0.3

Group size n1 59 15 25 35 45 55 65

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pE=0.6 p

D=0.2

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pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

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Moderategroupsizeshaveadvantageoverlargergroupsorsingleindividualsinall

friendlyenvironments( 1,subplotsabovethediagonal)wheneverproportionof

easytasksis 0.5 / ,thatis,whenaverageindividualaccuracyacross

tasksislargerthanchance( 0.5).Inaddition,moderategroupsizesareasgoodas

largergroupsizesinneutral( 1,subplotsonthediagonal)andunfriendly

environments( 1,subplotsbelowthediagonal)whenevereasytasksarevery

easy( >=0.8)andareencounteredmorethanhalfofthetime(e>0.5).Inthesecasesthe

groupaccuracyquicklyconvergestoeandafurtherincreaseinndoesnotprovide

additionalimprovement.

Figure2furthershowshowaveragegroupaccuracyPchangeswithincreasein

groupsizenwithfriendlinessofthetaskenvironment(asreflectedinthesumofaverage

individualaccuracyoneasyanddifficulttasks ),andaverageindividualaccuracy

acrosstasks( ).Specifically,(i)when 1and 0.5, willreachan

upwardpeakatmoderaten;(ii)when 1and 0.5, willdecrease

monotonicallywithntowardse;(iii)when 1and 0.5, willincrease

monotonicallywithntowardse;and(iv)when 1and 0.5, willreacha

downwardpeakatmoderaten.

Insum,theanalysispresentedsofarshowsthatsmallgroupscanbemoreaccurate

thanlargergroupswhenexpertgroups,whosemembersaremoreaccuratethanchanceon

anaveragetask,encountermostlyquiteeasytasksbutaresometimesconfrontedwith

moderatelydifficulttaskswithsurprisingoutcomes.Inthefollowingsections,weadd

furtherrealisticassumptionsandexaminereal‐worldsituations.

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Beforeproceeding,notethatinthispaperweformallytesttheverbalconjecture

madebyGrofmanetal.(1984)thatnonmonotonicityinaverageproportioncorrectacross

differentsamplesizescanbeexpectedinmulti‐itemtaskswithhardandeasyitems.We

provideseveralnovelresultsthatwerenotanticipatedordescribedbyGrofmanetal.First,

wedefineexactconditionswhenaverageaccuracyoverseveraltaskswillincreasewith

groupsize,whenitwilldecrease,andwhenitwillachieveapeak,ratherthanstatingonly

verballythatthesechangesareexpectedtobenon‐monotonicinsomecircumstances(Eq.

3aboveandrelateddiscussion).Second,weshowthatmoderately‐sizedgroupscanbe

preferabletolargergroupsevenwithouttakingintoaccounttheabsolutevalueofcorrect

decisionandthecostofutilizingadditionalgroupmembers;ratheritisenoughtoassume

thatacorrectdecisionismorevaluablethananincorrectone.Third,wedisprovethe

assumptionofGrofmanetal.(p.355)that,whenevertheproportionofhardtasksislarger

thantheproportionofeasytasks,groupperformancewilldecreasewithincreasinggroup

size(Figure2).Fourth,wedelineateconditionsfornon‐monotonictrendsingroup

accuracywithdownwardpeaks,thatiswhenmoderategroupsizesarelessaccuratethan

bothsingleindividualsandlargegroups(seeabove).Fifth,inwhatfollows,wetestour

findingsunderavarietyofassumptions,includingtwoormoretaskdifficulties,taskswith

twoandmoreoptions,independentandcorrelatedvotes,andsamplingfromeitherinfinite

populationsorfromsmallerpopulationswithoutreplacement.Finally,weshowthat

situationsfavoringmoderate‐sizedgroupsoccurinavarietyofreal‐lifedomainsincluding

political,medical,andfinancialdecisions,andgeneralknowledgetests.

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MorethanTwoTaskDifficulties

Sofarwehaveassumed,forsimplicity,thatagroupfacesonlytwotaskdifficulties:

thesameaverageindividualaccuracies and foralleasyanddifficulttasks,

respectively(althoughoneachtaskindividualscouldhaveheterogeneousskills).Inreal

life,groupswillfacetasksofawiderangeofdifficulties.Averagegroupaccuracyacross

manydifferenttaskscanbecalculatedbyanextensionofEq.2:

∑ , [4]

whereTisthenumberoftasks,andPt,nisgroupaccuracyonagiventasktatgroupsizen,

calculatedusingEq.1.

Moregenerally,insteadofassumingthattaskdifficulties and arethesamefor

alleasyanddifficulttasksthatagroupencounters,wecanmodelthemasrandomdraws

frombetadistributionswithparameters and 1 foreasytasks,and

parameters and 1 fordifficulttasks,wherek is a constant that

determines the size of the variance of task difficulties. Then, easy tasks have mean difficulty

/ and variance / 1 1 / 1 .

Similarly, difficult tasks can be modeled as having a mean / and variance

/ 1 1 / 1 . As k increases, the variance

decreases.

Tocheckhowassumingarangeoftwotaskdifficultiesaffectsaveragegroup

accuracy,wereplicatedthesimulationsabovefordifferentaveragetaskdifficultiesas

before,assumingdifferentlevelsofvarianceoftaskdifficulties:small(k=100),moderate

(k=50),andlarge(k=10).FiguresS2A‐S4Bshowthattheresultsdescribedaboveholdeven

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17

whendistributionsoftaskdifficultieshavelargevariances,thoughtheresultsbecome

morenoisy.

TaskswithMorethanTwoOptions

Whatiftasksinvolvepluralitychoicesbetweenmorethantwooptions?CJTcanbe

extendedtothesesituations:Groupaccuracywillincreasewithnaslongastheaverage

individualismorelikelytochoosethecorrectoptionoveranyotheroption(List&Goodin,

2001).Theprobabilitythatagroupchoosesthecorrectoneofkoptionscanbecalculated

asamultinomialprobabilityofallk‐tuplesofindividualvotesforthekoptionsforwhich

thecorrectoptionisthepluralitywinner,givenprobabilitiesp1,p2,...,pkthatanaverage

individualchooseseachofthekoptions.OncegroupaccuraciesPt,narecalculatedinthis

wayfordifferenttaskstandgroupsizesn,Eq.4canbeusedtocalculateaveragegroup

accuracy.Itistheneasytoshowthatnonmonotonicchangesinaveragegroupaccuracy

canoccurinthesesituations,aswell.

EffectofCorrelatedVotes

Sofarwehaveassumedthatgroupmembersareindependentinasensethatthey

relyondiverse(oruncorrelated)cuestomaketheirjudgments.Surprisingoutcomescan

driveamajorityofpeopleinthewrongdirectionevenwhenindividualsvote

independently.Thiscanhappeniftheenvironmentchangesinawaythatmakesallcues

incorrectorifbychanceuncorrelatedcueshappentobewrongonthesametask.However,

theassumptionofperfectindependenceisunrealistic(seee.g.,Bromell&Budescu,2009).

Inreallifepeopleareofteninfluencedbythesamecues,suchasthesamepiecesof

information,mediareports,oropinionleaders.Ithasbeenshownthatthepresenceof

opinionleadersorcommoninformationthatintroducescorrelationsbetweenindividuals’

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decisionscanreduceorevenreversethepositiveeffectsoflargergroupsizeongroup

accuracy(Kao&Couzin,2014;Boland,Proschan,&Tong,1989;Spiekermann&Goodin,

2012).

Theseeffectsofcorrelatedvotescanbeparsimoniouslyexplainedwithinthe

presentframework.Whenevertheleaderorthecommoninformationiscorrect,average

individualaccuracyimprovesandthetaskineffectbecomeseasier.Conversely,whenever

theleaderorthecommoncueiswrong,theaverageindividualbecomeslessaccurateand

thetaskbecomesmoredifficult.Hence,givenstochasticaccuracyoftheleaderorthe

commoncue,theoverallgroupaccuracycanberepresentedasanaverageofits

performanceoneasyanddifficulttasks.Accordingly,singlepeakfunctionsofthekind

presentedabovehavebeenobservedforgroupswithcorrelatedvotes(seereferences

above)buttoourknowledgethesimpleexplanationintermsofamixtureofeasyand

difficulttaskshasnotbeenproposedbefore.

Moreformally,followinganopinionleader(whodoesnotvotebutinfluencessome

groupmemberstodecideinacertainway)orvotingbasedonacommoncuecanbe

studiedasacombinationofeasytasks(whentheleaderorcueiscorrect)anddifficult

tasks(whentheleaderorcueisnotcorrect).Moreprecisely,

1 1 1 [5]

where isaverageaccuracyofagroupofsizen,lisprobabilitythatanopinionleaderis

accurateonacertaintask,Pnisgroupaccuracyatgroupsizengivenindividualaccuracy

specifiedwithinthesquarebrackets,pisinitialindividualaccuracyofgroupmembers,and

ristheproportionofgroupmemberswhoarefollowingtheopinionleader.Thehigherr,

thehigherthecorrelationamonggroupmembers,andinsomecasesthetwovaluesare

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19

identical(Spiekermann&Goodin,2012).Itiseasytoseethatwhentheleaderisaccurate

thetaskswilloverallbeeasier(i.e.,groupaccuracywillbehigher)thanwhentheleaderis

notaccurate.AconditionsimilartoEq.3mustbesatisfiedfor ¯ toincreasewithgroupsize

n:

1 1 1 1 [6]

Asimilarcasecanbemadeforsituationsinwhichcorrelationsoccurbecauseindividuals

usethesamesourcesofinformation.

Tofurtherexploreeffectsofcorrelatedvotesontheresultspresentedabove,we

introducecorrelationsbetweenvotersoneachtask,beforeaveragingacrosstasks.

FollowingBolandetal.(1989),weassumethatoneachtaskaproportionofrvotersare

followingaleaderorsomeothercuethatisstochasticallycorrectwithprobabilityl,andas

aresulttheirvotesbecomecorrelated.Whenevertheleaderorcueiscorrect,allrvoters

arecorrect,andaccuracyoftheremainingvotersdependsontheirindividualskill.More

precisely,Eqs.2and5canbecombinedtoaccountforbothcorrelatedvotesandtask

difficulty:

, 1 1 , 1

1 , 1 1 , 1 [7]

wheremeaningsofthesymbolsarelikeinEqs.5and6.

Werepeattheanalysesabove(presentedinFigures2andS1B)whileincreasingthe

assumedproportionofvotersrwhofollowtheleaderfrom0to1instepsof0.1.2With

2 Inthesesimulations,weassumedthattheleaderhasthesameskillastheaveragegroupmember( and ).Theresultsstillholdifweassumethattheleaderis10percentagepointsmoreorlesslikelytobeaccuratethantheaveragemember.Resultsforallcombinationsofrandlareavailablefromtheauthors.

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Figure3.GroupaccuracyafterrepeatingtheanalysisinFigure2forcorrelationlevelsrrangingfrom0to1instepsof0.1andaveragingoverthem.Leaderaccuracylisassumedtobeequaltotheaverageindividualaccuracy (seetextformoredetails).

increaseinr,changesingroupaccuracywithitssizebecomelessandlessprominent,and

forhighrthereisalmostnochangeingroupaccuracywithincreaseinitssize(Hogarth,

1978).Becauseintherealworlditisdifficultorimpossibletoknowwhatproportionof

peoplewillfollowaleaderinaparticulartask,weaveragetheresultsoverthewholerange

ofvaluesofr.Theresults,showninFigures3andS5,demonstratethatinmostsituations

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

Ave

rage

gro

up a

ccur

acy

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

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21

thesuperiorityofmoderategroupsizesstillholdsundertheassumptionofcorrelated

votes.Moregenerally,asFigure3shows,theincreaseingroupaccuracywithnismuch

smallerwhenvotesofgroupmembersarecorrelatedthanwhentheyareindependent.

SamplingofGroupMemberswithoutReplacementfromaFinitelySizedPopulation

ModelinggroupaccuracyusingCondorcetJuryTheoremassumesthatgroup

membersaresampledwithreplacementfromaverylargepopulation.However,inreallife

groupmembersofasmallercommitteewilltypicallybeselectedwithoutreplacementfrom

alarger,butfinitelysizedcommittee.Forsuchsituations,thehypergeometricdistribution

isamoreappropriatemodel(Tideman&Plassmann,2013).Specifically,Eq.1couldbe

rewrittenusingcumulativehypergeometricratherthancumulativebinomialdistribution:

∑ [8]

wherePnisgroupaccuracyatgroupsizen,missizeofsimplemajorityofgroupofsizen,N

ispopulationsize(orsizeofthelargercommitteefromwhichthesmallergroupofexperts

israndomlyselected),I=N*i/n,andI/Nequals ,averageindividualaccuracyinthe

population.

ThebinomialdistributionusedinCJTissimplerandanalyticallymoretractable,and

isthereforetypicallyusedtoanalyzevotingmodels(Grofmanetal,1984;List&Goodin,

2001).Weadopteditabovetoenablecomparisonofourresultswithpreviousstudies,but

tocheckwhetheranyconclusionspresentedinthepaperwouldbedifferentwhenusing

hypergeometricdistribution,were‐runalltheanalysesusingthatstatisticalmodel.Figures

S6andS7showtheresultsassumingthatmembersofsmallergroupswererandomly

selectedfromfinitepopulationswithoutreplacement:FigureS6assumesapopulationof

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N=71,andFigureS7assumesN=31.Bothanalysessuggestthatthefindingthatgroup

accuracywasoftenmaximizedformoderate‐sizedgroupsis,ifanything,morepronounced

withthesemorerealisticassumptions.

Real‐WorldIllustrations

Whatisthebestcommitteesizeinreal‐worldenvironments?Toanswerthis

question,weneedtohavearoughideaofthedistributionoftaskdifficultiesatypical

committeemightencounterintherealworld.Giventhatcommitteesareusuallycomposed

ofpeoplewhoareexpertsintherelevantarea,wecouldexpectthattheyareonaverage

moreaccuratethanchance.Inaddition,wecouldexpectthattheiraccuracyineasytasksis

abovechancemorethantheiraccuracyindifficulttasksisbelowchance.Inotherwords,a

typicaltaskenvironmentinwhichcommitteesneedtomakedecisionsmightmoreoftenbe

friendlythanunfriendly.

Studiesdocumentingexpertaccuraciesacrossarangeoftasksinthefieldsof

politics,health,andeconomicssupporttheseexpectations.Toillustrate,inalongitudinal

studyofexpertforecastersoffiveU.S.presidentialelections,Graefe(2014)foundthattheir

averageindividualaccuracyacrossallyearswasabovechance( 0.66).Ineasyyears,

averageindividualaccuracy was0.88,andintwodifficultyears(Bushvs.Gore,2000;

andBushvs.Kerry,2004),averageindividualaccuracy was0.34(seegraydotsinFigure

4A).Similarly,areviewofaccuracyofmedicaldiagnosesfor11diseasesshowedthatthe

averageindividualdoctor’saccuracywasabovechance 0.70 .Fordiseasesthat

wereeasytodiagnoseaverageindividualaccuracy was0.81,andfordifficultones,

includingLymedisease,pyrogenicspinalinfections,andabdominalaorticaneurysm,

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was0.41(Schiffetal.,2009;graydotsinFigure4B).Furthermore,areviewofaccuracyof

predictionsgivenbythetopofficialsoftheU.S.FederalReserveBankaboutfuture

economictrendsshowedthattheiraverageindividualaccuracywhenpredictingwhether

unemployment,economicgrowth,andinflationwouldincreaseordecreasewasrather

high( 0.71).Twoofthedomainswererelativelyeasytopredict( =0.86),while

economicgrowthwassomewhatdifficult( =0.43;Hilsenrath&Peterson,2013;gray

dotsinFigure4C).Finally,inastudyincluding120generalknowledgetaskssuchaswhich

oftworandomlyselectedcitiesisfarthernorth,orwhichoftworandomlyselected

countriesislargerormorepopulated,Juslin(1994)foundthatonaverageparticipants

werequiteaccurate( 0.76),buttendedtobeincorrectonasubsetoftasksinwhich

otherwiseusefulcuespointedtothewronganswers(seeinsetinFigure4D).Oneasytasks,

averageindividualaccuracy was0.86,andonthedifficulttasks was0.38.Insum,in

alloftheseexamplestaskenvironmentswerefriendly( 1),andeachexperthad

abovechanceaccuracyonanaveragetask( 0.5).Theseconditionssatisfythe

conditionsoutlinedaboveforthesituationswhengroupsofmoderatesizesarelikelyto

reachthehighestaccuracy.

Ifweassumethatapolicymakeroranindividualneedstodecideonthebestgroup

sizetosolvetasksillustratedinFigure4,whatgroupsizewouldreachthehighest

accuracy?Giventhesetaskenvironments,howmanypoliticalexpertsshouldajournalist

consulttoimproveelectionforecasts,howmanydoctorsshouldapatientconsultto

improvetheaccuracyofhermedicaldiagnosis,howmanyeconomistsshouldagovernment

consulttomakeagoodguessaboutthefuturecourseoftheeconomy,andhowmany

individualsshouldoneconsulttomaximizeone’schancesofgivingacorrectanswertoa

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generalknowledgequestion?Toinvestigatethis,weuseEq.4tocombinegroupaccuracies

fordifferenttasks(graylinesinFigure4)andgetaveragegroupaccuracyineachofthe

fourdomainsillustratedabove(thickblacklineinFigure4).Thisanalysisshowsthatthe

bestgroupsizeforimprovingelectionforecastsbypoliticalexpertsinthisparticular

illustrationisn=5.Fordiagnosingavarietyofhealthproblems,thebestsizeofapanelof

medicalexpertsinthisexamplewouldben=11.Foreconomictaskssuchasthosefacedby

FederalReserveofficials,thebestgroupsizeseemstoben=7.Perhapscoincidentally,this

isthedesignatednumberofseatsontheFederalReserve’sBoardofGovernors,althoughat

themomentofwritingthispapertwoofthosesevenseatsareempty(FederalReserve,

December2015).Finally,foransweringgeneralknowledgeitemscorrectly,thebestgroup

sizeforparticipantsofJuslin’s(1994)studyisn=15.

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Figure4.Real‐worldenvironmentsareoftenfriendlyandgroupaccuracypeaksatmoderategroupsizes.Graydotsin(A‐C):Averageindividualaccuraciesforparticulartasks(fiveelectionforecastsinA,diagnosesfor11diseasesinB,forecastsforthreeeconomictrendsinC).Insetin(D):Histogramofaverageindividualaccuraciesfor120knowledgetasks.Graylines:Groupaccuracyfordifferentgroupsizes,foreachofthedifferenttasksfacedby(A)expertspredictingU.S.politicalelectionsinyears1992,2000,2004,2008,and2012(Graefe,2014),(B)doctorsgivingmedicaldiagnosesforarangeofdiseases(AC=acutecardiacischemia,BC=breastcancer,S=subarachnoidhemorrhage,D=diabetes,G=glaucoma,St=Softtissuepathology,C=cerebralaneurysm,Bi=brainandspinalcordbiopsies,L=Lymedisease,P=pyrogenicspinalinfections,AA=abdominalaorticaneurysm;Schiffetal.,2009),(C)U.S.FederalReserveBankofficialsgivingeconomicforecastsaboutfutureeconomictrendsinunemployment(unempl),inflation,andeconomicgrowth(Hilsenrath&Peterson,2013),and(D)individualsanswering120generalknowledgeitemsaboutsizes,latitudes,andpopulationsofcitiesandcountries(Juslin,1994).Inpanels(A‐C)eachgraylinerepresentsonetask;in(D)eachgraylinedepictsseveraltasksandfrequencyofdifferenttasksateachleveloftaskdifficulty( )isshownintheinset.Notethatinalldomainseasytasksprevail,accompaniedwithafewsurprisingtasksthatweredifficultformostparticipants.Thickblacklines:averagegroupaccuracyacrossdifferenttasks.Inallfourexamples,averagegroupaccuracypeaksatmoderategroupsizes(asindicatedbycircles):inAatn=5;inBatn=11;inCatn=7;andinDatn=15.

1 5 9 15 21 27 33 39 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Ave

rage

gro

up a

ccu

racy

A. Election forecasts

y2012y1992

y2008

y2000

y2004

1 5 9 15 21 27 33 39 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Ave

rage

gro

up a

ccu

racy

B. Medical diagnoses

AA P

L

Bi

CStG

DS BC

AC

1 5 9 15 21 27 33 39 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Ave

rag

e g

rou

p a

ccu

racy

C. Economic forecasts

grow th

inflation

unemployment

1 5 9 15 21 27 33 39 450

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Group size n

Ave

rag

e g

rou

p a

ccu

racy

D. General knowledge tasks

0 0.25 0.5 0.75 10

20

40

Task difficultyN

um

be

r o

f ta

sks

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26

Discussion

Ourresultssuggestthatthehighestaccuracyacrossadiversesetoftasksinvolving

choicebetweentwoormorecoursesofactionmaybeachievedbymoderatelysizedrather

thanlargegroups.Weprovidenovelresultsregardingthepreciseconditionsunderwhich

thisphenomenonoccursandshowthatitholdsevenifweassumethatindividualshave

diverseskills,thattheirvotesarecorrelated,thattaskshavemorethantwooptions,orthat

groupsencountermorethantwotaskdifficulties.

Whilegroupsizethatachieveshighestaccuracydependsontheindividualaccuracy

oneasyanddifficulttasksandtheproportionofeasytasks,weshowthatconditions

favoringrelativelysmallcommitteesmayholdinmanyreal‐worldsituations.Inthese

situations,groupsofexpertshavetodecideaboutavarietyofissuesovertime,among

whichmostarerelativelyeasytosolvebutsomeproducesurprisingoutcomes.Whilereal‐

worldgroupsizesareinfluencedbymanyfactorsotherthanaccuracy,ourresultsshow

thatgroupsthataresmallerbecauseoforganizationalorcommunicationconstrainsdonot

necessarilyhavetobelessaccuratethanlargergroups.

Eventhoughthedifferencesinaccuracybetweengroupsofmoderateandlarger

sizesmightsometimesbesmall,theyarestillrelevant.Unlessitissomehowcheaperto

supportlargerratherthansmallergroupsofotherwisecomparableindividuals,itwill

alwaysbemoreefficienttohaveamoderate‐sizedratherthanalargercommittee.

Notethatwemodeledtasksinwhichgroupsusesimplemajorityorpluralityrules

tochoosebetweendiscreteoptions,ratherthanusingaveragingtopredictaquantitative

property.Wisdom‐of‐crowdseffectsaretypicallystudiedinthelattertypeoftask(Galton,

1907;Surowiecki,2004),althoughithasbeenshowntheoreticallythattheperformanceof

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27

majorityandpluralityrulesoftencomparestothatofacomputationallymoredemanding

averagingrule(Hastie&Kameda,2005).Infurtherwork,taskswhichinvolvechoice

betweenacceptingorrejectingagivenoptioncanbemodeledusingsignaldetection

theory,followinge.g.Sorkinetal(1998).However,asdiscussedabove,theeffectsof

averagingoverdifferenttaskdifficultiesarelikelytoremainevenafteraccountingfor

individualdifferencesindetectionsensitivitiesofgroupmembersonaparticulartask.

Finally,notethatwedonotassumeanyselectivesamplingofgroupmembers,for

example,basedonexpertise(Budescu&Chen,2014;Goldstein,McAfee,&Suri,2014;

Mannesetal.,2014).Asmallergroupthatwouldproducemoreaccuratedecisionsinour

modelcansimplybeselectedrandomlyoutofalargergroupofexperts.Moregenerally,

ourresultssuggestthateventhoughmoderntechnologiesenableeasiercommunicationin

largegroups,theresultingdecisionsmaybe(sometimesdrastically)lessaccuratethan

thosethatwouldhavebeenmadeinmoderately‐sizedgroupswiththesameaverage

individualaccuracy.Institutionaldesignersingovernmentandindustrycanconsiderthese

resultswhendeterminingthebestcommitteesizefortherangeoftaskstheirexpertswill

havetoface.

Acknowledgments

Matlabscriptsforallcalculationsareavailablefromtheauthors.WethanktheMax

PlanckInstituteforHumanDevelopmentandtheSantaFeInstitutefortheirsupport;David

Budescu,ReidHastie,JohnMiller,ShenghuaLuan,HenrikOlsson,andScottPagefor

helpfulcommentsonanearlierversion;andAnitaToddforeditingthemanuscript.

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SupplementalMaterialsAvailableOnline

FigureS1.Groupsizesforwhichgroupaccuracyreachesmaximum(circles)andminimum(triangles),fordifferentcombinationsoftaskdifficultiesandproportionsofeasytasks.Circles(triangles)ineachpanelshowgroupsizenatwhichgroupachievesmaximum(minimum)accuracy,forsizes1≤n≤55.Fullredcircles(fullbluetriangles)denotecaseswheregroupreachesmaximum(minimum)accuracyatgroupsizesthatarelargerthan1butsmallerthan55.Panelsshowresultsfordifferentcombinationsofeasy(0.6≤ ≤0.9)anddifficult(0.1≤ ≤0.4)tasks.Eachpanelshowsresultsfordifferent

proportionsofeasytasks(x‐axes,0.1≤e≤0.9).Panelsabovethediagonalrepresentfriendlytaskenvironments,thoseinthediagonalneutral,andthosebelowthediagonalunfriendlytaskenvironments.

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.9 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.9 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.9 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.9 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.8 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.8 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.8 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.8 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.7 p

D=0.4

G

roup

siz

e n

for

whi

ch a

ccur

acy

reac

hes

max

imum

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.7 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.7 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.7 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.6 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.6 p

D=0.3

Proportion of easy tasks e0.1 0.3 0.5 0.7 0.9

159

15

25

35

45

55

pE=0.6 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

pE=0.6 p

D=0.1

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32

FigureS2A.Modelingmorethantwotaskdifficulties.Easytasksaredrawnfromdistributionoftaskdifficultieswithmean andvariance 1 / 1 .Difficulttasksaredrawnfromabetadistributionwithmean andvariance 1 / 1 .Here,varianceisassumedtobesmall(k=100).Therearetotalof100tasks.Eachpanelshowstheresultingdistributionoftaskdifficulties.

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.4

F

requ

ency

of t

asks

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.3

Average individual accuracy0 0.5 1

0

100

200

300

400

500

pE=0.6 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.1

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33

FigureS2B.AveragegroupaccuracyontaskswithdifficultiesdisplayedintheequivalentpanelsofFigureS2A.Varianceisassumedtobesmall(k=100).Eachpanelshowschangesinaveragegroupaccuracy asafunctionofgroupsizen,differentcombinationsofeasy(0.6≤ ≤0.9)anddifficult(0.1≤ ≤0.4)tasks,anddifferentproportionsofeasytasks(0.1≤e≤0.9).Redlinesrepresentcasesinwhichaverageindividualaccuracyacrosstasks 0.5,bluelinesarefor 0.5,andblacklinesfor 0.5,where 1 .Circlesshowmaximumvalueof foreachcase.Dashedlinesdenotecaseswhere changesmonotonicallywithnuntilitreachese,whilesolidlinesdenotecaseswhere changesnonmonotonically,thatis,reachesanupwardoradownwardpeakatmoderategroupsizenbeforereachinge.Ineachpanel,upperlinesrepresenthigherproportionsofeasytaskse(seelegendtotherightofeachrow).Panelsabovethediagonalrepresentfriendlytaskenvironments,thoseinthediagonalneutral,andthosebelowthediagonalunfriendlytaskenvironments(seemaintextfordetails).

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

A

vera

ge g

roup

acc

urac

y

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

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34

FigureS3A.LikeFigureS2A,butvarianceoftaskdifficultiesisassumedtobemoderate(k=50).

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.4

F

requ

ency

of t

asks

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.3

Average individual accuracy0 0.5 1

0

100

200

300

400

500

pE=0.6 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.1

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35

FigureS3B.LikeFigureS2B,butvarianceoftaskdifficultiesisassumedtobemoderate(k=50).

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

A

vera

ge g

roup

acc

urac

y

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

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36

FigureS4A.LikeFigureS2A,butvarianceoftaskdifficultiesisassumedtobelarge(k=10).

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.9 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.8 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.4

F

requ

ency

of t

asks

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.3

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.7 p

D=0.1

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.4

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.3

Average individual accuracy0 0.5 1

0

100

200

300

400

500

pE=0.6 p

D=0.2

0 0.5 10

100

200

300

400

500

pE=0.6 p

D=0.1

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37

FigureS4B.LikeFigureS2B,butvarianceoftaskdifficultiesisassumedtobelarge(k=10).

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

A

vera

ge g

roup

acc

urac

y

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

159 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

15915 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

Page 39: Can Small Crowds Be Wise? Moderate-Sized Groups Can … · 2018-07-03 · 1 Can small crowds be wise? Moderate‐sized groups can outperform large groups and individuals under some

38

FigureS5.Resultsaveragedacrosssituationswithdifferentlevelsofcorrelationsofindividualjudgments,for0≤r≤1:Groupsizesforwhichgroupaccuracyreachesmaximum(circles)andminimum(triangles),fordifferentcombinationsoftaskdifficultiesandproportionsofeasytasks.MeaningsofsymbolsareasinFigureS1.SeeFigure3formoredetailedresults.

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.9 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.9 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.9 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.9 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.8 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.8 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.8 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.8 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.7 p

D=0.4

G

roup

siz

e n

for

whi

ch a

ccur

acy

reac

hes

max

imum

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.7 p

D=0.3

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.7 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.7 p

D=0.1

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.6 p

D=0.4

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.6 p

D=0.3

Proportion of easy tasks e0.1 0.3 0.5 0.7 0.9

159

15

25

35

45

55

65

pE=0.6 p

D=0.2

0.1 0.3 0.5 0.7 0.9159

15

25

35

45

55

65

pE=0.6 p

D=0.1

Page 40: Can Small Crowds Be Wise? Moderate-Sized Groups Can … · 2018-07-03 · 1 Can small crowds be wise? Moderate‐sized groups can outperform large groups and individuals under some

39

Figure S6. Sampling from finite populations without replacement accentuates previous results. Similar to Figure 2 in the main text, but group members are selected from a finite population of only N=71 members, without replacement. Instead of binomial, hypergeometric distribution is used to calculate accuracies of differently sized groups.

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

e=.9

e=.5

e=.1

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

e=.9

e=.5

e=.1

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

A

vera

ge g

roup

acc

urac

y

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

e=.9

e=.5

e=.1

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

1 59 15 25 35 45 55 65

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1

e=.9

e=.5

e=.1

Page 41: Can Small Crowds Be Wise? Moderate-Sized Groups Can … · 2018-07-03 · 1 Can small crowds be wise? Moderate‐sized groups can outperform large groups and individuals under some

40

Figure S7. Sampling from finite populations without replacement accentuates previous results. Similar to Figure 2 in the main text, but group members are selected from a finite population of only N=31 members, without replacement. Instead of binomial, hypergeometric distribution is used to calculate accuracies of differently sized groups.

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.4

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.3

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.2

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.9 p

D=0.1

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.4

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.3

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.2

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.8 p

D=0.1

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.4

A

vera

ge g

roup

acc

urac

y

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.3

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.2

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.7 p

D=0.1

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.4

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.3

Group size n1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.2

1 5 9 15 25

00.10.20.30.40.50.60.70.80.9

1

pE=0.6 p

D=0.1


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