Topic:  Dretske’s Explaining Behavior, Chapter 3

[See Lisa and Shannon's notes for Chapters 1 and 2.]

*Dretske introduces this chapter by returning to the main question of the book (see the Preface for a nice statement of this question):  How can reasons (like beliefs and desires) explain behavior, given neurophysiology?  Dretske marks two steps on the road to an
answer:

    --First, differentiate between behavior and the movements that are the products of behavior.  (The distinction between
    behavior and its output.)  This step has been worked out in the first two chapters.  Dretske contends that neurophysiology
    explains the movements (the products of behavior), whereas reasons explain the behavior itself.  So, Dretske sees
    neurophysiology and reasons explanations as parts of “different explanatory games” that do NOT compete (and hence avoid
    exclusion principles!). (pp. 51-52)

    --Second, we need to ask ourselves how reasons explain.  To do this, Dretske says that we must examine the idea of
    representation, the focus of this chapter.  Beliefs are kinds of representations:

    “Beliefs are those representations whose causal role in the production of output is determined by their meaning or
    content—by the way they represent what they represent.” (p. 52)

*Representational System (RS):  “any system whose function is to indicate how things stand with respect to some other object, condition, or magnitude.” (p. 52)

    --Natural vs. Conventional representations.  With conventional representations there is no intrinsic relationship between the
    elements of the representation and the thing represented.  This representative function is imposed by, and dependent on,
    us—e.g., in the examples of popcorn, coins, and basketball players. (pp. 52-53)
 

*Conventional Systems, Type I:

    --Type I representations “have no intrinsic powers of representation”—like in the basketball/coins example given above.
    Both their function and their ability to perform that function are imposed from outside, e.g. by a human agent.  Type I
    examples include:  maps, musical notation, and natural language. (p. 53)

    --The elements of Type I systems are called symbols.  Symbols are assigned indicator functions. (pp. 53-54)

*Conventional Systems, Type II:

    --Type II systems use natural signs.  Contrast the Type I symbols with natural signs.  Natural signs intrinsically represent
    and include things like tracks in the mud, fingerprints, and cloud formations.  Type II systems:

    “…natural signs are used in a way that exploits their natural meaning, their unconventional powers of indication, for
    representational, and partly conventional, purposes.  This makes systems of Type II a curious blend of the conventional and
    the natural.” (p. 54)

    --Dretske makes the following important point:  an indicator does not require a person to whom the information is indicated.
    E.g., properly functioning boiler-pressure gauges indicate boiler pressure, whether anyone recognizes this or not.
    (Conversely, our taking X to indicate P does not make it so.)  Dretske sees the opposing position as a species of
    anti-realism about truth—that nothing is true unless someone believes it or knows it. (p. 55)

    --Senses of ‘mean’:

    Natural sense:  ‘mean’ as a synonym for ‘indicate’ (Grice is cited here).  If X means that P in this sense, then P must be the
    case—there can be no misindication.  24 rings cannot mean (in this sense) that the tree is 24 years old unless it is in fact 24
    years old.

    Non-natural sense:  the kind of meaning associated with language.  We can mean something in this sense, without it being the
    case.  (pp. 55-56)

    --Additionally, something doesn’t indicate that P unless the right dependency holds.  Example of broken fuel gauge stuck at
    half full—even when the tank is half full the gauge doesn’t indicate this.  There is generally a law-like connection between
    natural signs and what they represent. (p. 56)

    --‘Information’ will also sometimes be used to convey what is meant by ‘natural meaning’ and ‘indication’. (pp. 58-59)

    --Type II systems use natural signs, but we determine what these signs represent (i.e., have the function of indicating).  (And
    such systems can misrepresent only what they have the function of representing.)  For example, we determine that a fuel
    gauge represents fuel level of the tank instead of the additional weight (of the gasoline).  The fuel gauge does indicate things
    that we don’t take it to represent (and, hence, what it doesn’t represent). (pp. 59-60)  For these reasons, Type II
    representations are partly conventional and partly natural (partly natural because these natural signs “indicate” what they
    represent all on their own).

    --Type II systems differ from Type I systems, in that in Type I systems we assign the function and completely control the
    ability of Type I systems to fulfill that function.  In Type II systems, we do only the former.

*Natural Systems, Type III:

    --Type I and II systems are conventional systems of representation.  Natural systems of representation, Type III, are ones
    in which even the representative function is not assigned from outside the system.  Such examples include the functions of
    bodily organs like the heart, kidneys, and sensory systems.  Biologists discover the functions of such organs and systems.
    (pp. 62-64)

*Misrepresentation is an aspect of intentionality (itself, a mark of the mental).  The above-described representational systems are susceptible of misrepresentation.  Misrepresentation for Type I and II systems is only derivative on a failure in some person who assigns the representative function to the given elements.  Only Type III representational systems are capable of intrinsic misrepresentation.  The ability to misrepresent is essential for the elements of a system to have meaning. (pp. 64-67)

    --Certain indicators can function well in one environment (and for that reason have been selected naturally through the
    evolution of the species), but misrepresent in an artificial environment.  For example, a frog’s “bug detection system” would
    think that artificially crafted shadows of a certain size are bugs. (p. 68)

    --Misrepresentation is always relative to a function—e.g., perhaps the function of the so-called bug detection system is
    merely to detect certain types of shadows.  Then, there would be no misrepresentation in that false environment.
    Misrepresentation is relative to the assigned function (see Dennett “Evolution, Error and Intentionality”). (p. 69)

*The content of a representational system—what it has the function of indicating (i.e., represents). (p. 70)

    --Two aspects of these contents.  First, What is it of (reference)?  Second, How is this referent represented (sense)?  These
    two aspects capture two additional features of intentionality:  aboutness and intensionality (respectively). (p. 70)

    --There are pictorial representations in which the representations resemble what they represent, but representations certainly
    needn’t resemble what they represent.

    --There can be a representation of x without it being represented as x.  The former (‘of’ locution) is a de re content.  The
    fact that a de re belief is of x rather than y is not given in the representation itself, but by non-representational facts (e.g., a
    causal theory of reference). (p. 73)

    --De dicto beliefs (contents):  reference is determined by how it is represented. (pp. 73-74)

    --All RSs are property specific:  they can represent something as F without representing it as G, even though everything that
    is F is G.  That is, the content is intensional rather than extensional. (p. 75)