Causal Models: How People Think about the World and Its Alternatives

218 Pages·2005·2.22 MB·English

by  Steven Sloman

Causal Models
How People Think about the World
and Its Alternatives
Steven Sloman
1
2005
1
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LibraryofCongressCataloging-in-PublicationData
Sloman,StevenA.
Causalmodels:howpeoplethinkabouttheworldanditsalternatives/
byStevenSloman.
p. cm.
Includesbibliographicalreferencesandindex.
ISBN-13978-0-19-518311-5
ISBN0-19-518311-8
1. Psychology—Mathematicalmodels. 2. Causation. I. Title.
BF39.S562005
122—dc22 2004031000
2 4 6 8 9 7 5 3 1
PrintedintheUnitedStatesofAmerica
onacid-freepaper
Contents
1. Agency and the Role of Causation in Mental Life 3
TheHigh Church ofCognitive Science:A HereticalView 3
AgencyIsthe Ability toRepresent CausalIntervention 5
ThePurpose of ThisBook 6
Planof the Book 8
Part I. The Theory
2. The Information Is in the Invariants 11
SelectiveAttention 13
SelectiveAttentionFocuses onInvariants 14
In the Domain ofEvents, CausalRelations Arethe
Fundamental Invariants 17
3. What Is a Cause? 21
Causesand EffectsAreEvents 21
Experiments Versus Observations 22
Causal RelationsImply CertainCounterfactuals 24
Enabling, Disabling,DirectlyResponsible: Everything’s
aCause 26
Problems, Problems 27
Could ItBeOtherwise? 31
Not AllInvariance Is Causal 33
x Contents
4. Causal Models 36
TheThree Partsof aCausal Model 37
Independence 39
StructuralEquations 40
WhatDoes ItMeantoSay Causal RelationsAre
Probabilistic? 42
CausalStructure ProducesaProbabilistic World:
ScreeningOff 43
EquivalentCausal Models 45
InferringCausal StructureIs aMatterof Faith 46
TheTechnical Advantage:HowtoUse aGraphto
SimplifyProbabilities 49
5. Observation Versus Action 52
Seeing:The Representation of Observation 52
Action: TheRepresentation of Intervention 57
ActingandThinking byDoing:Graphical Surgery 59
Computing WiththeDo Operator 61
TheValue ofExperiments: AReprise 63
TheCausal Modeling FrameworkandLevels of Causality 64
Part II. Evidence and Application
6. Reasoning About Causation 69
Mathematical Reasoning About CausalSystems 70
SocialAttribution and Explanation Discounting 74
Counterfactual Reasoning:The LogicofDoing 78
Conclusion 81
7. Decision Making via Causal Consequences 83
Making Decisions 84
TheGambling Metaphor: Expected Utility Theory 85
DecidingbyCausal Explanation 88
Newcomb’s Paradox: CausalTrumpsEvidential
Expected Utility 89
TheFacts: PeopleCare AboutCausal Structure 93
WhenCausal KnowledgeIsn’t Enough 98
8. The Psychology of Judgment: Causality Is Pervasive 101
CausalModels as aPsychologicalTheory: Knowledge
IsQualitative 102
TheCausality Heuristic andMental Simulation 104
BeliefPerseveration 106
SeeingCausalityWhen It’s NotThere 107
CausalModels andLegalRelevance 110
Conclusion 114
Contents xi
9. Causality and Conceptual Structure 116
Inference OverPerception 118
TheRole ofFunction in Artifact Categorization 120
Causal Modelsof ConceptualStructure 121
SomeImplications 127
Causal Versus Other Kindsof Relations 128
Basic-level CategoriesandTypical Instances 129
Conclusion 131
10. Categorical Induction 132
Inductionand CausalModels 133
ArgumentStrength: Similarityand CausalKnowledge 134
ArgumentStrength: Causal PrinciplesAreSufficient 136
Causal Explanations 137
Causal Analysis Versus Counting Instances:TheInside
Versus the Outside 138
Conclusion 140
11. Locating Causal Structure in Language 141
Pronouns 141
Conjunctions 142
If 143
TheValue of CausalModels 152
12. Causal Learning 154
Correlation-based Theoriesof CausalStrength 156
StructureBeforeStrength 159
Insufficiency of CorrelationalData 163
CuestoCausal Structure 164
TheInterventional Advantage 167
TheBenefits ofIntervention 169
TheCostsof Intervention 170
Conclusion 171
13. Conclusion: Causation in the Mind 174
Assessing theCausal Model Framework 174
Cognition Isfor Action 177
WhatCausal ModelsCan Contribute toHuman Welfare 178
TheHuman Mechanism 179
Notes 183
References 191
Index 201
Causal Models
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1
Agency and the Role
of Causation in
Mental Life
The High Church of Cognitive Science:
A Heretical View
How do people think? The effort to answer this question is the do-
main of cognitive science, a field of study that includes cognitive
psychologyandpartsofcomputerscience,linguistics,anthropology,
and philosophy. The field emerged in lock-step with the devel-
opment of the computer. After all, the computer is at heart an in-
formation-processing device, and it would seem that people are
information-processing devices extraordinaire. Computers have in-
putdevices(e.g.,keyboards,mouses,microphones),andpeoplehave
inputdevices(e.g.,eyes,ears,skin).Computersstoreinformationin
memories; peoplestore informationin memories.Computers com-
pute; they do calculations by transforming symbols in languages
they understand (like Java and binary code); people compute by
transformingsymbolsinlanguagesthatweunderstand(likeEnglish
and arithmetic). Computers have output devices (e.g., screens,
speakers,diskdrives),andpeoplehaveoutputdevices(e.g.,mouths,
hands, feet). Indeed, it would seem, and it did seem for many years
(it still does to some), that cognitive science would answer the
question ‘‘how do people think?’’ by programming a computer to
behave like a person. The program would be the answer. This was
essentiallytheconclusionofferedbyAlanTuringinafamousessay
called ‘‘Computing Machinery and Intelligence.’’1 He carefully
3
4 Causal Models
developedacleverwayknownastheTuringTesttodecideifacom-
putercouldthinkbyfoolingajudgeintobelievingthatitwasaman
andnotawoman.
NowtherearecontestsmodeledontheTuringTest.TheLoebner
Prizeoffersagoldmedaland$100,000forthefirstcomputerwhose
responses are indistinguishable from a human’s. Each year an an-
nual prize of $2000 and a bronze medal is awarded to the most
human computer.Some machineshave proven very clever, but no-
bodyhasbuilt amachinethatcancomeclosetopassingthetestas
Turingenvisionedit.Nobodyhasyetwongold.Onereasonmaybe
the complexity of thought or the huge amount of knowledge re-
quired to mimic even a young child. Think about how much
knowledgeisrequiredtounderstandsomethingassimpleasachair.
You need to understand sitting (and that requires knowledge about
the human form). You need to understand something about mate-
rials(chairscannotbemadeoutofpowderedsugar).Youcan’teven
reallyunderstandwhatachairiswithoutunderstandingsomething
about fatigue, the benefits of rest, and perhaps the importance and
ritualofbreakfast,lunch,anddinner.Knowledgeisinterrelatedand
thereforeacriticalmassisrequiredeventounderstandthesimplest
things.
Disillusionment with the view that the computer is the best
metaphor of mind, sometimes called the High Church Doctrine of
Cognitive Science, has been widespread and has deep roots. People
differ from computers in critical ways. For one, we compute differ-
ently. Traditionally, computers perform one operation at a time;
they compute sequentially. People are able to perform many oper-
ations at a time; certain functions (like memory) involve the si-
multaneousoperationofbillionsofsimpleunits,resonatingtogether
toretrievememories,inthewaytheentirebody‘‘remembers’’how
to ride a bike. Some recent computer designs involve a limited
amountofparallelprocessing,butnothingliketheparallelismthat
operatesinthemind.
Aseconddifferenceisthat,unlikecomputers,peoplehaveemo-
tionallivesdirectlytiedtothechemicalcompositionandphysiological
processes of our bodies. We may be machines, but we’re machines
madeoutofmeat,andthatchangeseverything.
Athirddifference,andtheonethatI’mgoingtofocuson,isthat
we’re not passive consumers of information, blindly transforming
symbolsasrequested.We’reagents.Weactivelypursuegoals,bethey
the need for food, oxygen, or love or the desire for entertainment,
education,orliberty.Whetherpeoplehavefreewillisaquestionfar