Mind projection fallacy
The mind projection fallacy is an informal fallacy first described by physicist and Bayesian philosopher E.T. Jaynes. It occurs when someone thinks that the way they see the world reflects the way the world really is, going as far as assuming the real existence of imagined objects. That is, someone's subjective judgments are "projected" to be inherent properties of an object, rather than being related to personal perception. One consequence is that others may be assumed to share the same perception, or that they are irrational or misinformed if they do not.
A second form of the fallacy, as described by Jaynes, occurs when someone assumes that their own lack of knowledge about a phenomenon (a fact about their state of mind) means that the phenomenon is not or cannot be understood (a fact about reality). (See also Map and territory.)
[I]n studying probability theory, it was vaguely troubling to see reference to "gaussian random variables", or "stochastic processes", or "stationary time series", or "disorder", as if the property of being gaussian, random, stochastic, stationary, or disorderly is a real property, like the property of possessing mass or length, existing in Nature. Indeed, some seek to develop statistical tests to determine the presence of these properties in their data...
Once one has grasped the idea, one sees the Mind Projection Fallacy everywhere; what we have been taught as deep wisdom, is stripped of its pretensions and seen to be instead a foolish non sequitur. The error occurs in two complementary forms, which we might indicate thus: (A) (My own imagination) → (Real property of Nature), [or] (B) (My own ignorance) → (Nature is indeterminate)
An 18th century example was David Hume's theory of causation, which he thought did not really exist. He thought that the apparent connection between cause and effect, e.g. throwing a brick and a breaking window, was merely psychological phenomenon, mistakenly projected onto the world and assumed to be real.
- E. T. JAYNES (1989). PROBABILITY THEORY AS LOGIC (PDF). Ninth Annual Workshop on Maximum Entropy and Bayesian Methods. pp. 1–16. CiteSeerX 10.1.1.63.5075. doi:10.1007/978-94-009-0683-9_1. ISBN 978-94-010-6792-8. Retrieved 2011-05-19.
- Jaynes, E. T. (1989). Clearing up Mysteries--The Original Goal (PDF). Maximum Entropy and Bayesian Methods. pp. 1–27. CiteSeerX 10.1.1.46.1264. doi:10.1007/978-94-015-7860-8_1. ISBN 978-90-481-4044-2.
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