The Relevant Alternatives Theory

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relevant-alternatives knowledge skepticism contextualism

Core Idea

Lewis's relevant alternatives theory proposes that to know something, one must be able to rule out relevant alternatives, but not all metaphysically possible alternatives. Relevance is context-dependent: what counts as a relevant alternative shifts with conversational context, explaining how everyday knowledge claims can be true while extreme skeptical hypotheses technically remain possibilities.

How It's Best Learned

Distinguish relevant from irrelevant alternatives in concrete cases. Understand how context determines which alternatives are relevant—in a context where only physical differences matter, mental simulation hypotheses aren't relevant. Apply this to explain why we typically say we know things despite skeptical possibilities.

Common Misconceptions

Explainer

You know the structure of Cartesian skepticism from your study of external-world skepticism: a skeptic challenges everyday knowledge by pointing to possibilities you cannot rule out — you could be a brain in a vat, an evil demon could be deceiving you, your experiences might be a perfect simulation. The argument has two premises: first, you cannot distinguish the normal situation from the skeptical one; second, knowing p requires being able to rule out alternatives to p. Together these imply that you don't know ordinary things. The relevant alternatives theory attacks the second premise rather than the first.

Fred Dretske and David Lewis independently proposed that knowing p requires ruling out only *relevant* alternatives — not every metaphysically possible alternative. What counts as relevant is not fixed by logic but determined by context. In an ordinary conversation about whether there's a barn in the field, fake barns hidden in surrounding fields are not a relevant alternative (unless you happen to be in a county famous for fake barns). You know there's a barn because you can rule out everything that's relevantly in play. The brain-in-a-vat scenario is not relevantly in play in that context — it is too remote, too disconnected from any practical or conversational purpose, to count as an alternative you need to exclude in order to know.

The significant philosophical payoff is that this dissolves the apparent contradiction between ordinary knowledge and skeptical puzzles. When a philosopher explicitly raises the skeptical hypothesis in conversation, the context shifts — that once-irrelevant alternative becomes salient and thus relevant within the new conversational context. Suddenly "I know there's a barn" becomes harder to assert, not because your epistemic position changed, but because the standard for what counts as "ruling out enough" has shifted. This insight drives epistemic contextualism: the sentence "S knows that p" can be true in one conversational context and false in another without any change in S's evidence or cognitive situation. The standards encoded in "knows" are context-sensitive, much as the standards for "tall" vary with context. The relevant alternatives theory is thus both a theory of what knowledge requires and a framework for why we can speak truly about everyday knowledge while remaining technically vulnerable to philosophical skepticism — the skeptic changes the rules by raising the stakes, not by discovering that we were always deceived.

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Prerequisite Chain

Counting to 10Counting to 20Understanding ZeroThe Number ZeroCounting to FiveOne-to-One CorrespondenceCombining Small Groups Within 5Addition Within 10Addition Within 20Two-Digit Addition Without RegroupingTwo-Digit Addition with RegroupingAddition Within 100Repeated Addition as MultiplicationMultiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Two-Digit by One-Digit DivisionDivision with RemaindersRemainders and Quotients in DivisionDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueReading and Writing DecimalsComparing and Ordering DecimalsAdding and Subtracting DecimalsMultiplying DecimalsDividing DecimalsDividing FractionsMixed Number ArithmeticOrder of OperationsInteger Order of OperationsVariable ExpressionsCombining Like TermsOne-Step EquationsTwo-Step EquationsSolving Multi-Step EquationsEquations with Variables on Both SidesLiteral EquationsSlope-Intercept FormPoint-Slope FormWriting Linear EquationsParallel and Perpendicular Line SlopesGraphing Linear EquationsPiecewise FunctionsStep FunctionsComposition of FunctionsInverse FunctionsRadical Functions and GraphsRational ExponentsExponential Functions and GraphsLogarithms IntroductionBig-O Notation and Asymptotic AnalysisBreadth-First Search (BFS)Shortest Paths in Unweighted GraphsDijkstra's Shortest Path AlgorithmAlgorithm Analysis and Big-O NotationTuring MachinesThe Church-Turing ThesisEquivalence of Computational ModelsFunctionalismThe Hard Problem of ConsciousnessThe Knowledge Argument (Mary's Room)The Relevant Alternatives Theory

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