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A Defense of Temperate Epistemic Transparency

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A Defense of Temperate Epistemic Transparency. ELEONORA CRESTO CONICET (Argentina) University of Konstanz – July 2011. EPISTEMIC TRANSPARENCY. If S knows that p , S knows that she knows that p : KK Principle : Kp  KKp Knowledge reflexivity Positive introspection - PowerPoint PPT Presentation
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A DEFENSE OF TEMPERATE EPISTEMIC TRANSPARENCY ELEONORA CRESTO CONICET (Argentina) University of Konstanz – July 2011
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Page 1: A  Defense  of  Temperate Epistemic Transparency

A DEFENSE OF TEMPERATE EPISTEMIC TRANSPARENCY

ELEONORA CRESTOCONICET (Argentina)

University of Konstanz – July 2011

Page 2: A  Defense  of  Temperate Epistemic Transparency

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EPISTEMIC TRANSPARENCY

If S knows that p, S knows that she knows that p:

KK Principle: Kp KKp

Knowledge reflexivity Positive introspection Self-knowledge Transparency Luminosity

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GOAL

A defense of a moderate version of KK

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RISE AND FALL OF KK

1960 s: Dogma

Then….

Externalism – e.g.: Reliabilism

Williamson (2000)

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STRATEGY

(A) Why do we want transparency?

(B) Indirect argument

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WHY DO WE CARE ABOUT TRANSPARENCY?

Ideal agentsIdeally rational?

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WHY DO WE CARE ABOUT TRANSPARENCY?

Knowledge and responsibility

How?

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WHY DO WE CARE ABOUT TRANSPARENCY?

Responsibility demands us to be in an appropriate reflective state.

What reflective state?Epistemic responsibility entails

“ratifiability”.

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A MODAL FRAME

F = <W, R, Pprior>

K = {w W: x W (wRx x )}

R(w) = {x W: wRx}

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WILLIAMSON: IMPROBABLE KNOWING

Pw(): the evidential probability of in w.

Pw() = Pprior( | R(w)) = Pprior ( R(w)) / Pprior (R(w))

Pw(R(w)) = 1   [P() = r] =def. {w W: Pw() = r}

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IMPROBABLE KNOWING

“The KK principle is equivalent to the principle that if the evidential probability of p is 1, then the evidential probability that the evidential probability of p is 1 is itself 1” (Williamson, p. 8).

   We can build a model in which

Pw([P(R(w))=1]) is as low as we want.

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PROBLEMS

Why should we say that the evidential basis (in w) is always R(w)?

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PROBLEMS

Recall that:

[P() = r] = {w W: Pw() = r}

[Pw() = r] ?

 

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PROPOSAL (FIRST VERSION)

We’ll have a sequence of languages L0, L1, … Ln….with probability operators P0, …Pn…

We’ll have a sequence of functions P1w…

Pnw… on sentences i of language Li

Piw: Li-1 ℝ

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PROPOSAL (FIRST VERSION)

Expressions of the form Pprior() or Piw() do

not belong to any language of the sequence L0, L1…Ln….

“Pi()=r” is true in w iff Piw()=r.

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PROPOSAL (FIRST VERSION)

How should we conditionalize?

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PROPOSAL (FIRST VERSION)

For P1w(), the relevant evidence is R(w).

For P2w(P1()=r), the relevant evidence is

KR(w).

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CONDITIONALIZATION (FIRST VERSION)

C* rule:For i 1: Pi

w (Pi-1(…P()=r...)) =

Pprior(Pi-1(…P()=r…) | Ki-1...KR(w))

where Ki-1 is the same K-operator iterated i-1 times

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DIFFICULTIES

C* divorces probability 1 from knowledge.

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A MODEL FOR MODERATE TRANSPARENCY (SECOND VERSION)

M = <W, R1,...,Rn..., Pprior, v>

New operators K0…Kn…, in addition to P0, …Pn…

We define a sequence of relations R1…Rn which correspond to the different Ks.

The Rs are nested: Ri Ri-1 ... R1

Ri is a reflexive relation over W, for all i, and transitive for i > 1.

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A MODEL FOR MODERATE TRANSPARENCY

Our conditionalization rule now incorporates operators K1,… Kn… defined on the basis of relations R1,… Rn…

C** rule: For i 1: Pi

w (Pi-1(…P()=r...)) =

Pprior(Pi-1(…P()=r | Ki-1...KR(w))

where “Ki-1…KR(w)” includes i-1 higher-order K-operators

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A MODEL FOR MODERATE TRANSPARENCY Intended interpretation of the formalism:

“K2p” does not make sense!

A second-order evidential probability claim is the evidential probability of a probability statement.

Mutatis mutandis for higher-order levels and for conditional evidential probabilities.

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SOME CONSEQUENCES

Why should we demand such requirements for the Rs? They are not ad hoc!

Higher-order probability requires increasingly complex probabilistic claims.

For second-order evidential probability in w: We conditinalize over KR(w) Thus the second-order probability of P1(R(w)) is 1 Thus the agent knows that KR(w) K2KR(w) should be true in w

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SOME CONSEQUENCES

K K2K KK2 Principle (if [K2KR(w)] is not empty, for any w)

(K K2K) KK Principle (if [K2KR(w)] is not empty, for some w)

K2K K3K2K KK+ Principle

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SOME CONSEQUENCES

A restricted version of possitive introspection holds:

Quasi-transparency principles

KK+, KK and KK2 result from conditionalizing over higher-order levels of evidence and from the attempt to adjust probability language and knowledge attribution in a progressively coherent way.

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SOME CONSEQUENCES

Links between lower- and higher-order probabilities:

If P1w() = r = 1 or 0, then P2

w(P1()=r) = 1.

If R1 is an equivalence relation, P2

w(P1()=r) is either 1 or 0.

Suppose P2w(P()=r) = s. If 0 r 1 and

R1 is not transitive, then s need not be either 1 or 0.

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ON THE PROBABILISTIC REFLECTION PRINCIPLE (PRP)

PRP: P2

w ( | P1()=r) = r (for w W)

Iterated PRP:Pi

w ( | Pi-1( | Pi-2(|…)….)=r) = r

Is PRP a theoretical truth of M ?

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ON PROBABILISTIC REFLECTION

Necessary and sufficient condition for Iterated PRP

Ri is an equivalence relation and Ri = Ri-1

iff

for all w W and any L0: if Pi+1

w(-|-) exists, then Pi+1

w( | Pi( | Pi-1(|…)….) = r) = r

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RELATION TO OTHER WORK

Paul Egré/ Jérôme Dokic  Principal motivation: to deactivate Williamson’s

soritic argument on inexact knowledge

Perceptual vs. reflective knowledge

(KK’) K KK

Transparency failures do not generalize

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RELATION TO OTHER WORK

Differences

1. Egré/ Dokic do not offer a probabilistic framework.

2. They focus on reflection over perceptual knowledge, exclusively.

3. KK’ Principle is imposed “from the outside”.

The present model for quasi-transparency can be seen as a refinement and extension of some aspects of the system suggested by Egré - Dokic.

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CONCLUSIONS

Once we clarify some conceptual aspects of higher-order probabilities…

…we obtain the vindication of a number of introspective principles, or principles of quasi-transparency.

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CONCLUSIONS

Quasi-transparency principles were not just assumed to hold, but they have been obtained as a result of implementing a number of natural constraints on the structure of the system.

Formally speaking, they behave quite differently from presuppositions of

consistency or deductive closure.

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CONCLUSIONS

The framework vindicates the intuition that first- and second-order knowledge differ substantially:

Different attitudes about ignorance

Different attitudes toward “margin of error” principles

Second-order knowledge is concerned with the “ratification” of first-order attitudes.

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CONCLUSIONS

Quasi-transparency fully vindicates the normative link between self-knowledge and responsibility.

K+Kp: “responsible knowledge” of p.

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CONCLUSIONS

Second-order knowledge, as a state of epistemic responsibility, is a

desideratum we have qua agents.

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Thank you!


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