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The Gettier Problem: Why True Belief Is Not Enough
A Short History of Knowledge's Most Famous Counterexample

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About this book:

The Gettier Problem: Why True Belief Is Not Enough For over two millennia, the definition of knowledge seemed settled: a justified true belief. It was the bedrock of Western thought, unshaken from Plato’s Academy to the modern university—until a three-page paper in 1963 shattered the consensus overnight. In *The Gettier Problem*, you’ll witness the intellectual earthquake triggered by Edmund Gettier’s devastatingly simple thought experiments, proving that you can be right for all the right reasons and still fail to know. From the coins in a job applicant’s pocket to the fake barns dotting a countryside drive, this book unpacks the paradox that turned epistemology upside down and sparked a fifty-year obsession with the nature of epistemic luck.

Journey through the frantic, brilliant scramble to repair the definition of knowledge. Watch giants like Goldman, Nozick, Sosa, and Williamson propose, defend, and abandon theories ranging from causal chains and reliability tracking to virtue epistemology and the radical "knowledge-first" revolution. You’ll explore why every attempted patch—ruling out false premises, demanding sensitivity, requiring safety—seems to spring a new leak, and why the elusive "fourth condition" remains philosophy’s most wanted quarry.

But this isn't just history; it’s a survival guide for the information age. As algorithms curate our reality, deepfakes blur truth, and AI systems "hallucinate" facts with confident fluency, the Gettier problem has migrated from the seminar room to the server farm. The final chapters bridge the gap to cognitive science and machine learning, asking the urgent modern question: Can an algorithm suffer from Gettier problems? If you want to understand the fragile boundary between genuine understanding and a lucky guess—in human minds or artificial ones—this is the essential map.

Table of Contents:
  • Introduction
  • Chapter 1 The Tripartite Theory: Plato and the Justified True Belief Model
  • Chapter 2 Two Millennia of Consensus: From Antiquity to the Twentieth Century
  • Chapter 3 The Three-Page Earthquake: Edmund Gettier’s 1963 Paper
  • Chapter 4 Coins and Jobs: Analysis of Gettier’s First Case
  • Chapter 5 The Ford in the Driveway: Analysis of Gettier’s Second Case
  • Chapter 6 Epistemic Luck: Why Getting it Right by Accident Isn't Knowledge
  • Chapter 7 Immediate Reactions: The Initial Philosophical Shockwave
  • Chapter 8 The No False Premise Fix: Patching the Tripartite Model
  • Chapter 9 Fallibility and Infallibility: The Search for Epistemic Certainty
  • Chapter 10 Causal Theories of Knowledge: Goldman’s Contribution
  • Chapter 11 Reliability and Trust: The Rise of Epistemic Reliabilism
  • Chapter 12 Counterfactuals and Tracking: Nozick’s Sensitivity Condition
  • Chapter 13 The Safety Condition: Sosa and Pritchard’s Modern Alternative
  • Chapter 14 Fake Barns and Epistemic Environments: Alvin Goldman's Challenge
  • Chapter 15 Virtue Epistemology: Focusing on the Agent, Not Just the Belief
  • Chapter 16 Defeasibility Theories: Undermining Evidence and Justification
  • Chapter 17 Pragmatic Encroachment: Does What Is at Stake Change What We Know?
  • Chapter 18 Knowledge-First Epistemology: Williamson’s Radical Reversal
  • Chapter 19 Linguistic Approaches: Contextualism and the Semantics of "Know"
  • Chapter 20 Experimental Epistemology: Do Intuitions About Gettier Cross Cultures?
  • Chapter 21 The Inescapability of Luck: Is the Gettier Problem Solvable?
  • Chapter 22 Cognitive Science and Epistemic Intuition: How the Brain Models Knowledge
  • Chapter 23 Artificial Intelligence and Machine Belief: Can Algorithms Suffer Gettier Problems?
  • Chapter 24 The Legacy of a Three-Page Paper: How Gettier Reshaped Modern Thought
  • Chapter 25 What It Means to Know: Epistemology Beyond the Counterexample
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Author:

Aaron Q. Romero

Published By:

MixCache.com Extended Catalog

Type:

Nonfiction

Date Published:

September 13, 2026

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