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andmoreperceptive.Wejliketothinkthatbecomingaware(viaknowledgeofbehavioralscience)ofwhyandwhenpeopleareunlikelytonoticediscriminationwillincreasethelikelihoodthatmoreindividualswilPerceivetheProblemsaroundthem.SomePeoplew记alsobecourageousenoughtotrytofaxthoseProblems.Thatleadstothenextquestion:HovwcanthosedishabituationentrepreneuishelpothersdishabituateySURPRISEDBYBIASAswestressedeatjlier,thebrainisapredictivemachine.堆ItscentralmissionistoPredict,asaccuratelyaspossible,whatw刘happennextsothatitcanprepareandreactintime一tohidebeforetheenemyatfives，hoardwaterbeforethedrought，haveanumbrellahandywhenitpours，WegenerateaccuratePredictionsbywatchingandlearning，WeobserveyearafteryearthatinNovemberitrainsmorethaninJune,sowecatrryanumbrelladuringlatefallratherthanearlysummer.WeareconstantlyabsorbingdatafromtheworldandconsciouslyorUnconsciouslyUpdatingourjudgmentstoenableustomakeaccuratePredictions.AttheirbesbourneuronsareSophisticatedbiologicalcalculators，keepingtrackoffrequencies,means,associations,andmore.So让forexample，mostpilotswemeetaremen，weexpecttoSeeamalepilotwhenwegetonaPlane.WhenthoseexpectationsaremebthereisnosurprisesignalinouUrbrainalertingusthatsomethingiswrong.Fromthesestatisticalobservationswethenmakeassumptionsaboutthe

Look Again 【再看一眼】 pdf

underlyingcause.Ifmostpilotsaremales,ouUrbrainw计quicklyconcludethatmenareespeciallysuitedtofyingaPlane.开the“data”isbiasedbecauseofhistoricaldiscrimination,，ratherthanreflectingsomekindoftruthaboutthecapabilitiesofmenandwomen,OUconclusionswillbebiasedbecauseouUrbrainisdoingwhatitwasbuilttodo:deducegeneralrulesbasedonPerception.EverydaywerelyonsuchStereotypesandgeneralizationswhenmakingdecisions.Indecidingwhomtohire,employersoftenuseProxiesofmanysorts，even让thoseproxiesareoverbroadgenerajizationsandfarfromentirelyaccurate.Forexample,testScores,employmentrecords,levelofeducation,andPrestigeofcollegeattendedareallPartofwhatyoumaythinkofasrationalfactorsinemploymentdecisions，YoumightchoosesomeonewhowenttoagreatUniversityoverSomeonewhowenttoagooduniversityeventhoughplentyofPeoplewhowenttogooduniversitieswoulddobetterthanplentyofpeoplewhowenttogreatUniversities.Raceandsexoftenoperateassimilarproxies.Womenmaybemorejlikely由anmentobethePrimarycaretakersofchildrenandmorelikelytoleavetheemploymentmafrkettotakethatrole.Ifso,anemployermightdiscriminatenotbecausehedislikesordevalueswomenorisprejudicedintheordinarysense,butbecausehebelieves(onthebasiseitherofplausibleassumptionsofactualexperience)thatsomeStereotypeistrueenoughtobeabasisfore

Look Again 【再看一眼】 pdf

mploymentdecisions，Overtime，suchStatisticaldiscriminationcanbeaself-fulfillingProphecy.Itcanaggravatetheveryproblemtowhichitisaresponse.Matterscangetevenworseonceyouaddartificialintelligencesystemstothemix.AIsystemasarebuilttoimitatethehumanmind一theyuseinputsfromtheworldaroundthemtomakepredictionsandjudgments.瑟HIthedatatheyreceiveisbiased，AIsystemsw计reactlikehumanbeings:thedecisionsandrecommendationstheymakewillbebiased.ConsidertheexperienceofDavidandJamieHeinemeierHansson.eIn2019thematriedcoupleappliedforanApplecreditcard.TIhetwosharealltheirfinancialresources，includingbankaccountsandProperty.、Theywere由usastonishedtolearnthatAppleofferedDavidamuchhighercreditlimitthanitdidtohiswife,Jamie一twentytimeshigher.AfterSharingtheirstoryonsocialmedia,theydiscoveredthatothershadexperiencedthesame,includingApplecofounderSteveWozniakandhiswife.Applewasusingabiasedmachine-learningalgorithmtoassigncredit，TIodevelopcredit-cardscoring,，analgorithmisfedmillionsofexamplesofgoodchoices(forexample,dataonpeoplewhohavepaidtheirdebb)andbadchoices(forexample,dataonpeoplewhohavenot).ItthenlearnswhichfactorsPredictgoodchoices.Iffemalesarepaidlessthanmalesorfnditmorediffculttogetajobbecauseofgenderdiscrimination,thealgorithmwillconcludethatmalesare

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