The Design Inference: Eliminating Chance Through Small Probabilities

Dissertation, University of Illinois at Chicago (1996)
Shoot an arrow at a wall, and then paint a target around it so that the arrow sticks squarely in the bull's eye. Alternatively, paint a fixed target on a wall, and then shoot an arrow so that it sticks squarely in the bull's eye. How do these situations differ? In both instances the precise place where the arrow lands is highly improbable. Yet in the one, one can do no better than attribute the arrow's landing to chance, whereas in the other one rightly attributes the arrow's landing to the archer's skill. ;Highly improbable events occur all the time, and by themselves may legitimately be attributed to chance. Yet when an event also conforms to a pattern given independently of that event , one rightly refuses to attribute the event to chance. Patterns given independently of events are called specifications. This dissertation explicates the relation of independence between specification and event, and sets precise bounds on what may count as a probability small enough to eliminate chance. Although this dissertation connects with how statistics eliminates chance, it considerably extends and clarifies the range of application for chance-elimination arguments based on small probabilities. ;The dual notions of specification and small probability together help justify a regulative principle of probability called the Law of Small Probability, which asserts that specified events of small probability do not occur by chance. This principle engenders a form of inference called the design inference, and a mode of explanation called design. To infer design in explaining an event is to eliminate decisively explanations of that event which appeal to law-like regularities or chance
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DOI 10.1093/mind/112.447.521
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