estimation-biases
Systematic tendencies in human prediction and estimation that cause deviations from accuracy, which can be mitigated through metaknowledge and corrective second-order predictions.
1 chapter across 1 book
Epistemology: An Introduction to the Theory of Knowledge (2003)Nicholas Rescher
Chapter 2 explores the concept of fallibilism in epistemology, emphasizing the inherent liability of human knowledge to error and the necessity of metaknowledge—knowledge about our knowledge. It discusses the practical acceptance of putative knowledge despite its imperfections, the epistemic challenges such as the Preface Paradox, and the importance of viewing scientific knowledge as best current estimates rather than absolute truths. The chapter also highlights systematic biases in prediction and estimation, advocating for a fallibilist approach that balances costs and benefits in our understanding of truth.