Gettier-type counterexamples challenge the traditional idea that a “justified true belief” necessarily qualifies as knowledge. Imagine an agent developing a mental model supported by strong empirical evidence. The model makes correct predictions within scope. However, unknown to the agent, the prediction succeeded by luck! It worked only because two hidden errors canceled each other out. The prediction was correct, but the internal reasoning was flawed.
First of all, TST does not treat Gettier cases as fatal paradoxes, nor does it require eliminating every possibility of luck before accepting a justified belief. To the contrary, Gettier cases demonstrate why justified “true belief” alone is insufficient to establish knowledge. They reinforce that our perception of reality is never exhaustive. For most models, and perhaps all complex models, we have no way of conclusively ruling out undiscovered errors. Yet another reason why we must never mistake our representations of reality for reality itself (the Split).
In other words, correct predictions do not “automatically” validate justification. Reliable belief develops through a process that includes continuous error correction. This is true for worldview belief and public belief. A model can achieve accidental empirical alignment with reality even when its justrication fails to achieve structural alignment with the processes it attempts to describe. When any errors are discovered, we fix them, revise the model if needed, and recalibrate.
Clarifying and revising ideas, justification, and credence are all part of building reliable belief. The possibility of undiscovered errors does not invalidate that process. It is the very reason the process must remain fallible, disciplined, and open to correction.