A topic in the Open Knowledge Graph — a free, open map of 15,290 topics and the order to learn them in.

Responses to the Gettier Problem

College Depth 100 in the knowledge graph I know this Set as goal
44topics build on this
538prerequisites beneath it
See this on the map →
Gettier ProblemsEpistemic LuckDefeasibility Conditions and KnowledgeProcess Reliabilism+1 more
Gettier no-false-lemmas causal-theory defeasibility knowledge-analysis

Core Idea

Responses to Gettier fall into several families. The no-false-lemmas condition adds that knowledge may not depend essentially on any false intermediate belief, but this fails for direct Gettier cases that use no false lemmas. The causal theory (Goldman 1967) requires that the fact that p causally produce the belief that p, handling perceptual cases but struggling with knowledge of mathematical or future truths. Defeasibility theories require that no true proposition, if added to the evidence, would defeat the justification. Each response captures something right while facing its own counterexamples, motivating a shift away from the analysis project entirely toward reliabilism or virtue epistemology.

How It's Best Learned

For each proposed fourth condition, construct a case that satisfies JTB plus that condition but still intuitively lacks knowledge. This systematic pressure helps explain why many epistemologists abandoned the analysis project.

Common Misconceptions

Explainer

From your study of Gettier problems, you know that justified true belief is not sufficient for knowledge. Gettier's 1963 counterexamples showed that a belief can be justified and true and yet fail to be knowledge because the justification and the truth are connected only accidentally — through luck. The immediate philosophical reaction was to look for a fourth condition to add to the JTB analysis that would rule out Gettier cases while preserving all genuine cases of knowledge. The history of these responses is a case study in philosophical dialectic: each proposed fix is plausible, but each is either too weak (it still admits some Gettier-like cases) or too strong (it excludes cases that do seem like knowledge). Understanding why each response fails is as important as understanding the response itself.

The no-false-lemmas condition (sometimes called the "no-false-grounds" condition, associated with Gilbert Harman) adds that knowledge requires that the belief not be inferred from any essentially false intermediate premise. This handles Gettier's original cases directly: in those cases, the agent infers a true conclusion from a false belief (e.g., infers "someone in this office owns a Ford" from the false belief "Jones owns a Ford"). Ruling out false lemmas excludes those cases. The problem is direct Gettier cases that use no false lemmas at all. The classic example: Henry is driving through the countryside and sees what looks exactly like a barn. It is a barn, and his perception is functioning normally — he has no false beliefs in his reasoning chain. But unbeknownst to Henry, he is in "Fake Barn County," where nearly all the barn-shaped structures are elaborate facades. By luck, this particular one is a real barn. Henry has a justified true belief with no false lemma, but intuitively he does not know there is a barn. The no-false-lemmas condition cannot exclude this case.

Alvin Goldman's causal theory of knowledge (1967) takes a different approach: it requires that the fact that p *causally produce* the belief that p through an appropriate causal chain. This handles perceptual cases elegantly — your belief that there is a barn is caused by the barn itself (through light, retina, neural processing), so that is knowledge. In Gettier's original cases, the causal connection between the truth (someone in the office does own a Ford) and the belief is broken or accidental. The causal theory excludes those cases. But the theory struggles with knowledge of abstract or non-causal truths: how can you have knowledge that 7 is prime if there is no causal process linking the mathematical fact to your belief? Abstract mathematical and logical truths do not cause anything, yet we clearly know them. The causal theory would either deny we know these truths (implausible) or require a strained notion of "appropriate causal chain" that threatens to swallow the original insight.

Defeasibility theories (Lehrer and Paxson, Chisholm) require that there be no true proposition which, if the subject were to learn it, would undermine the justification. In the Fake Barn case, the true proposition "most barn-like structures here are facades" would defeat Henry's justification if he learned it, so defeasibility rightly says he lacks knowledge. The problem is misleading defeaters: in some cases, there exists a true proposition that would defeat the justification if believed, but only because that proposition is itself misleading. Suppose Tom sees his friend Grabit steal a book, and Tom justifiably believes Grabit stole it. Unknown to Tom, Grabit's mother — a notorious liar — has told police that Grabit has a twin who committed the theft. The proposition "Grabit's mother said he has a twin" would, if believed by Tom, defeat his justification. Yet intuitively Tom does know Grabit stole the book. A simple defeasibility condition cannot distinguish genuine defeaters from misleading ones.

The significance of this catalog of failures is not merely negative. Each failed response isolates something real about Gettier cases — the role of false reasoning, the need for appropriate causal connection, the requirement that no defeating information lurks in the environment — without fully capturing it. Many epistemologists concluded that the analysis project itself was misconceived: the attempt to give necessary and sufficient conditions for "S knows that p" in terms of simpler notions may be an instance of what Wittgenstein called the demand for definitions where there is only family resemblance. The responses to Gettier set the stage for reliabilism (Goldman's later view: knowledge is belief produced by a reliable cognitive process) and virtue epistemology (Sosa, Zagzebski: knowledge is belief produced through the exercise of intellectual virtues), which shift the question from conditions to processes and character — and explicitly abandon the hope of a short-form analysis.

What did you take from this?

Topics in reflective domains aren't scored by quiz answers. Read, reflect, and mark when you've thought it through.

Quiz me anyway →

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication 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 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicIntroduction to Predicate Logic (First-Order Logic)First-Order Logic SyntaxTerms and Atomic Formulas in FOLVariable Binding and ScopeOpen and Closed Formulas in First-Order LogicVariable Substitution and Capture-Avoidance in First-Order LogicQuantifier Instantiation Rules in First-Order Proof SystemsUniversal Quantification: Meaning and ScopeFree Variables and Bound VariablesSubstitution and Instantiation in Predicate LogicTerms and Atomic FormulasFormulas and Well-Formed ExpressionsStructures and InterpretationsModel Interpretation and SatisfactionInterpretation, Truth, and Satisfaction of FormulasLogical Consequence and EntailmentSoundness Theorem and Validity of Proof SystemsDeductive Reasoning and Formal Proof SystemsFirst-Order ResolutionPropositional ResolutionSemantic Tableaux (Propositional)Semantic Tableaux (First-Order)Decidable Fragments of First-Order LogicGödel's Completeness Theorem for First-Order LogicGödel's Incompleteness TheoremsIntroduction to Intuitionistic LogicIntroduction to Modal LogicThe Sensitivity Condition and Tracking TruthAnti-Luck Conditions and SensitivityEpistemic LuckResponses to the Gettier Problem

Longest path: 101 steps · 538 total prerequisite topics

Prerequisites (2)

Leads To (3)