We propose that selection favors nonveridical perceptions that are tuned to fitness. Current textbooks assert, to the contrary, that perception is useful because, in the normal case, it is veridical. Intuition, both lay and expert, clearly sides with the textbooks. We thus expected that some commentators would reject our proposal and provide counterarguments that could stimulate a productive debate. We are pleased that several commentators did indeed rise to the occasion and have argued against our proposal. We are also pleased that several others found our proposal worth exploring and have offered ways to test it, develop it, and link it more deeply to the history of ideas in the science and philosophy of perception. To both groups of commentators: thank you. Point and counterpoint, backed by data and theory, is the essence of science. We hope that the exchange recorded here will advance the scientific understanding of perception and its evolution. In what follows, we respond to the commentaries in alphabetical order.
Keywords: Bayesian inference; Categorization; Parameter estimation; Perceptual categorization and identification; Visual perception.