Evolution, Empiricism & Purpose 1. A Criticism Of Intelligent Design

EVOLUTION, EMPIRICISM

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PURPOSENESS (1) Jesús Zamora Bonilla Presented at the symposium ‘Evolutionism and Religion’ Firenze, Italy, november, 2009 [email protected]

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MAIN MOTIVATION Analysis of the use of some concepts from philosophy of science in the arguments of defenders of “Intelligent Design” (ID). E.g. -Scientific explanation and inference -Information -Structure and dynamics of theories, and relation to empirical data 2

DEMBSKI’S “EXPLANATORY FILTER” To explain a phenomenon P, try first through ‘necessity’, then by ‘chance’, and, if these don’t work, infer that P comes out of design 3

WHAT DOES ‘EXPLANATION’ MEAN IN THE ‘EXPLANATORY FILTER’ In empirical science, to ‘explain’ is to provide a theoretical model that allows to... logically or statistically derive the explanandum from assumptions about regularities and previous contingent conditions 4

In this sense, in order to be part of a REAL scientific explanation, ‘design’ must be included in a MODEL indicating how the explanandum FOLLOWS from the model’s assumptions ‘Design’ (as, by the way, ‘natural selection’) has to be seen more as a ‘promise’ of explanation than as an ‘actual’ explanation The scientific value of these promises depends on their success in helping us make new empirical discoveries

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More importantly, ‘necessity’, ‘chance’ and ‘design’ are by no means alternative ‘types’ of explanation. 1: ‘Necessity’ refers to the existence of a regularity that describes the way (i.e., the ‘mechanism’ through which) the phenomenon arises (by the way, the theory of natural selection not doing so, is what ID defenders take as the main reason to reject it; but they don’t demand the same to ID)

Empirically given ‘purposeful causes’ are just a particular case of natural mechanisms of that kind ‘Design’ is a mere subclass of ‘necessity’ (i.e., of the 6 notion of ‘causal mechanism’).

Corollary: There is no reason to infer that there are no ‘natural mechanisms’ (besides the natural mechanisms purposeful agents consist in) that can produce outcomes with ‘specified complexity’, since (known) purposeful agents are just a kind of natural mechanisms This does not entail that all existing purposeful agents are natural, only that the inference to ‘design-instead-of-necesity’ 7 is not granted

2: ‘Chance’ enters in an explanation always as a the indeterminate element (i.e., the stochastic part) of the regularities employed (or of the initial conditions measurement) Any explanatory model produces a particular statistical distribution of outcomes (i.e., it is a ‘data generation mechanism’) When, in other cases, we say that something is explained ‘through chance’, what we really mean is that it is NOT explained at all 8

So, the ‘right’ ‘explanatory filter’ would look something like this: Phenomenon P  Explained by some proposed mechanism M1, M2, ..., Mn, ...? (Mi = specific laws + specific random noise) (some Mi’s being purposeful agents) Yes?: OK No? Then: P unexplained (Nota bene: Dembski’s filter would not leave ANYTHING unexplained, what is unrealistic as a scientific method) 9