before_revision: Relation to traditional epistemology Traditional epistemology and Bayesian epistemology are both forms of epistemology, but they differ in various respects, for example, concerning their methodology, their interpretation of belief , the role justification or confirmation plays in them and some of their research interests. Traditional epistemology focuses on topics such as the analysis of the nature of knowledge, usually in terms of justified true beliefs , the sources of knowledge , like perception or testimony, the structure of a body of knowledge, for example in the form of foundationalismor coherentism, and the problem of philosophical skepticism or the question of whether knowledge is possible at all . These inquiries are usually based on epistemic intuitions and regard beliefs as either present or absent . Bayesian epistemology, on the other hand, works by formalizing concepts and problems, which are often vague in the traditional approach. It thereby focuses more on mathematical intuitions and promises a higher degree of precision. It sees belief as a continuous phenomenon that comes in various degrees, so-called credences. Some Bayesians have even suggested that the regular notion of belief should be abandoned. But there are also proposals to connect the two, for example, the Lockean thesis, which defines belief as credence above a certain threshold. Justification plays a central role in traditional epistemology while Bayesians have focused on the related notions of confirmation and disconfirmation through evidence. The notion of evidence is important for both approaches but only the traditional approach has been interested in studying the sources of evidence, like perception and memory. Bayesianism, on the other hand, has focused on the role of evidence for rationality: how someone's credence should be adjusted upon receiving new evidence. There is an analogy between the Bayesian norms of rationality in terms of probabilistic laws and the traditional norms of rationality in terms of deductive consistency. Certain traditional problems, like the topic of skepticism about our knowledge of the external world, are difficult to express in Bayesian terms.
after_revision: Relation to traditional epistemology Traditional epistemology and Bayesian epistemology are both forms of epistemology, but they differ in various respects, for example, concerning their methodology, the propositional attitudes they study , the role justification or confirmation plays in them and some of their research interests. Bayesian epistemology focuses on degrees of belief, also often called credences. On the other hand, Traditional epistemology focuses on knowledge, analyzed by Plato as being justified true beliefs . They then seek to understand what counts as knowledge and how to evaluate one's beliefs (see foundationalism, coherentism, and the problem of philosophical skepticism or the question of whether knowledge is possible at all ) . Bayesian epistemology, on the other hand, works by formalizing concepts and problems, which are often vague in the traditional approach. It thereby focuses more on mathematical intuitions and promises a higher degree of precision. It sees belief as a continuous phenomenon that comes in various degrees, so-called credences. Some Bayesians have even suggested that the regular notion of belief should be abandoned. But there are also proposals to connect the two, for example, the Lockean thesis, which defines belief as credence above a certain threshold. Justification plays a central role in traditional epistemology while Bayesians have focused on the related notions of confirmation and disconfirmation through evidence. The notion of evidence is important for both approaches but only the traditional approach has been interested in studying the sources of evidence, like perception and memory. Bayesianism, on the other hand, has focused on the role of evidence for rationality: how someone's credence should be adjusted upon receiving new evidence. There is an analogy between the Bayesian norms of rationality in terms of probabilistic laws and the traditional norms of rationality in terms of deductive consistency. Certain traditional problems, like the topic of skepticism about our knowledge of the external world, are difficult to express in Bayesian terms.
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