Philosophers have long grappled with the nature of knowledge, looking to distinguish it from mere opinion or belief. In ancient Greece, Plato proposed a definition that would shape the foundation of epistemology: knowledge is justified true belief. For a person to "know" something, three conditions had to be met—it must be true, the individual must believe it, and there must be justification for the belief. However, in the 20th century, an American philosopher would rock that concept to its core.
In 1963, Edmund Gettier published a short yet revolutionary paper that introduced scenarios where a belief was true, justified, and yet intuitively did not qualify as knowledge. For instance, imagine someone has strong evidence to believe their friend owns a Ford and concludes, “Either my friend owns a Ford, or they are in Barcelona.” Unknown to them, their friend no longer owns the Ford but happens to be in Barcelona by sheer coincidence. While the belief is true and justified, it seems to lack the essence of what we call "knowledge."
Such examples, now known as "Gettier cases," exposed the cracks in the traditional framework. The Gettier problem remains unresolved, leaving philosophers searching for a more robust definition of knowledge. It highlights the need to go beyond justification, truth, and belief to account for situations where truth occurs accidentally or coincidentally. This challenge has deep implications for fields like science, law, and artificial intelligence, where precise definitions of knowledge are essential.
It might seem easy to define knowledge or recognize it, but it’s not that simple. In daily life, we often think our beliefs are correct and well-supported. However, examples like Gettier’s show how we can confuse luck or coincidence with real understanding. This reminds us to think critically and examine evidence carefully. Just as the Gettier problem challenges philosophers, it also pushes us to question what we think we know and avoid being too confident in our beliefs.
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