evolution, empiricism and purposeness (1)

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    EVOLUTION,

    EMPIRICISM AND

    PURPOSENESS (1)

    Jess Zamora Bonilla

    November, 2009

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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

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    DEMBSKIS

    EXPLANATORY

    FILTER

    To explain a phenomenon P,

    try first through necessity,

    then by chance,and, if these dont work,

    infer that P comes out ofdesign

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    WHAT DOES EXPLANATION MEAN IN

    THE EXPLANATORY FILTER

    In empirical science, to explain is to provide a

    theoretical modelthat allows to...

    logically or statistically derive the explanandum

    from assumptions about regularities andprevious contingentconditions

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    In this sense, in order to be part of a REAL scientific

    explanation, design must be included in a MODEL

    indicating how the explanandum FOLLOWSfrom the

    models assumptions

    Design (as, by the way, natural selection) has tobe seen more as a promiseof explanation than as

    an actualexplanation

    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: Necessityrefers 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 whatID defenders take as the main reason to reject it; but they dont

    demand the same to ID)

    Empirically given purposeful causes are just aparticular case ofnatural mechanisms of that kind

    Design is a mere subclass of necessity (i.e., of the

    notion of causal mechanism).

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    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 kindof natural

    mechanisms

    This does not entail thatall existing purposeful

    agents are natural,

    only that the inference to design-instead-of-necesity

    is not granted

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    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 isexplained through chance, what we really mean is

    that it is NOT explained at all

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    So, the right explanatory filter would look

    something like this:

    Phenomenon PExplained by someproposedmechanism

    M1, M2, ..., Mn, ...?

    (Mi = specific laws + specific random noise)

    (some Mis being purposeful agents)

    Yes?: OKNo? Then: P unexplained

    (Nota bene: Dembskis filter would not leaveANYTHING

    unexplained, what is unrealistic as a scientific method)