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Transcript
AGAINST MORAL
CHARACTER EVALUATIONS:
The undetectability of virtue and vice
Peter B. M. Vranas
Iowa State University
Conference on Virtue Ethics and Moral Psychology, 7 October 2005
THE EPISTEMIC THESIS
Epistemic thesis: Moral character evaluations
are almost always epistemically unwarranted.
Definitions:
 Moral character evaluations: evaluations of
people as good, bad, or intermediate.
 A person is indeterminate iff the person is
neither good nor bad nor intermediate.
 A person is fragmented iff the person would
behave deplorably in an open list of situations
and admirably in another such open list.
THE ARGUMENT FOR
THE EPISTEMIC THESIS
(P1) Most people are fragmented.
(L1) The prior probability that a person is
fragmented should be high.
(P2) The posterior probability that a person is
fragmented shouldn’t differ much from the prior.
(L2) The posterior probability that a person is
fragmented should be high.
(P3) Fragmentation entails indeterminacy.
(C1) The posterior probability that a person is
indeterminate should be high.
___________________________________________________________________________________________________________________________________________________________
___________________________________________________________________________________________________________________________________________________________
___________________________________________________________________________________________________________________________________________________________
OVERVIEW
Part 1: Review of previous results
 Most people are fragmented (P1)
 Fragmentation entails indeterminacy (P3)
Part 2: Posterior probability of fragmentation
 Approximate IndependencePosterior @ Prior
 Approximate Independence holds
Part 3: Objections to the epistemic thesis
 The triviality objection
 The objection from ought-implies-can
 The objection from comparative evaluations
(P1) MOST PEOPLE ARE
FRAGMENTED
(1) There is an open list of situations in which
most people would behave deplorably:
 Obedience experiments (Milgram)
 Stanford Prison Experiment (Zimbardo)
 Seizure experiments (Latané & Darley)
(2) There is an open list of situations in which
most people would behave admirably:
 Electrocution experiments (Clark & Word)
 Theft experiments (Moriarty)
 Rape experiments (Harari et al.)
(P3) FRAGMENTATION
ENTAILS INDETERMINACY
(P0) If A behaves much better than B in an open
list of situations and much worse in another
list, then A is neither better nor worse than B.
(1) Every fragmented person is neither better nor
worse than some intermediate person (who
never behaves deplorably or admirably).
(2) Every good person is better, and every bad
person is worse, than any intermediate person.
(3) No fragmented person is good or bad.
Similarly, no fragmented person is intermediate.
__________________________________________________________________________________________________________________________________________________________
__________________________________________________________________________________________________________________________________________________________
PART 2
Part 1: Review of previous results
 Most people are fragmented (P1)
 Fragmentation entails indeterminacy (P3)
Part 2: Posterior probability of fragmentation
 Approx. IndependencePosterior@Prior
 Approx. Independence holds
Part 3: Objections to the epistemic thesis
 The triviality objection
 The objection from ought-implies-can
 The objection from comparative evaluations
THE POSTERIOR PROBABILITY
OF FRAGMENTATION
Notation:
F: person p is fragmented.
Ds: p behaves deplorably in situation s.
Approximate Independence Condition:
P(Ds|Ds) @ P(Ds)...
The argument:
(P4) If Approximate Independence holds,
then P(F|Ds) shouldn’t differ much from P(F).
(P5) Approximate Independence holds.
(P2) P(F|Ds) shouldn’t differ much from P(F).
________________________________________________________________________________________________________________________________________________________
(P4) INDEPENDENCE
POSTERIOR @ PRIOR
Theorem. Consider S independent and identically distributed random variables, each of which
can take the values -1, 1, and 0 with probabilities pD ,pA , and 1-pD-pA respectively. Let ND and
NA be the numbers of these variables which take
the values -1 and 1 respectively, and ND and NA
the corresponding numbers for (any) S-1 of the S
variables. Let F = ND > sD & NA > sA and let
Ds = the s-th variable takes the value -1. Then:
P(F|Ds)-P(F) = (1-pD)P(ND = sD & NA > sA)
-pAP(ND > sD & NA = sA).
(P5) APPROXIMATE
INDEPENDENCE HOLDS
Argument 1: Average correlation coefficients
low. E.g., Hartshorne & May (1928, 1930).
Objection: We can predict our friends’ actions.
Reply: Behavior may be temporally stable
(in recurring situations) but not crosssituationally consistent. In everyday life we
observe our friends in recurring situations.
Argument 2: Personality characteristics like religiosity, authoritarianism, introversion don’t
predict who obeys in Milgram’s experiments.
PART 3
Part 1: Review of previous results
 Most people are fragmented (P1)
 Fragmentation entails indeterminacy (P3)
Part 2: Posterior probability of fragmentation
 Approximate IndependencePosterior @ Prior
 Approximate Independence holds
Part 3: Objections to the epistemic thesis
 The triviality objection
 The objection from ought-implies-can
 The objection from comparative evaluations
OBJECTION 1:
TRIVIALITY
The objection: (1) We seldom make MCEs, so
(2) the epistemic thesis is uninteresting.
Reply 1: (1) is false. Empirical evidence:
Never
Almost
never
Rarely Somewhat Somewhat Frequ- Very
Almost
rarely
frequently ently frequently always
_______________________________________________________________________________________________________________________________________________
#1: 3
20 30 46 54 26 5 5
#2: 0
5 10 25 53 53 34 8
Reply 2: (2) does not follow from (1). MCEs
sometimes have important functions: they
underlie esteem and contempt, praise and
blame, explanations of behavior, and advice.
OBJECTION 2:
OUGHT-IMPLIES-CAN
The objection: (1) We cannot avoid making
MCEs (cf. Spontaneous Trait Inferences, STIs).
(2) We have no epistemic obligation to avoid
believing what we cannot avoid believing.
(3) The epistemic thesis implies that we have
an epistemic obligation to avoid making MCEs.
Reply 1: (1) is false. STIs may be controllable.
Reply 2: (2) is false. We have an epistemic
obligation to avoid believing P iff our evidence
makes P unlikely, but this can happen even if
we cannot avoid believing P.
OBJECTION 3:
COMPARATIVE EVALUATIONS
The objection: (1) If p is better than at least one
good person, then p is good. (2) P(p is better
than at least one good person|p is better than
most people) high. Thus: (3) P(p is good|p is
better than most people) should be high. So
MCEs are justified if comparative MCEs are.
Against (2): We don’t know what percentage of
people are good, so even if p is better than
(e.g.) 80% of people we can’t be confident
that p is better than at least one good person.
CONCLUSION:
THE PRAGMATIC THESIS
Local evaluations: referring to behavior in a
relatively narrow range of situations.
The pragmatic thesis: there is good pragmatic
reason to prefer local to global evaluations.
The argument:
(1) Local evaluations avoid costs of global
ones: tempting one’s luck, testing people.
(2) Local evaluations preserve benefits of
global ones: decisions about association,
regulation of emotions.
EPSTEIN AND AGGREGATION
Epstein: Not surprising that correlations low. If
you measure once, large error. You need to
average many measurements. Correlations
between aggregated measures will be high.
Reply 1: Epstein’s argument presupposes
constant true score, as when measuring length.
But this presupposes cross-situational consistency. The issue is empirical, not a priori.
Reply 2: Empirical evidence against Epstein;
e.g., Hartshorne, May, & Shuttleworth 1930.
THE VALIDITY OF THE
ARGUMENT FOR P1
Theorem 1. Consider P people, SD situations in
each of which at least pD people behave deplorably, and SA different situations in each of which
at least pA people behave admirably. Let F be the
number of people each of whom behaves deplorably in more than sD of the former SD situations
and behaves admirably in more than sA of the
latter SA situations. Then:
F p D / P  s D / SD p A / P  s A / S A


 1.
P
1 s D / SD
1 s A / S A
THREE CONCEPTIONS OF
CHARACTER EVALUATIONS
Q6 true
(consistency
of bad people)
Q5 true (con- Consistency
sistency of
conceptions
good people) (middle line)
Q5 false (no
______
consistency of
good people)
Q6 false (no
consistency
of bad people)
Impurity
conceptions
(hard line)
Averaging
conceptions
(soft line)
(P3) FRAGMENTATION
ENTAILS INDETERMINACY
(Q5) A person who often behaves deplorably is
not good.
(Q6) A person who often behaves admirably is
not bad.
(Q7) A person who often behaves deplorably
and often behaves admirably is not
intermediate (between good and bad).
(P3) A person who often behaves deplorably
and often behaves admirably is neither good
nor bad nor intermediate.
___________________________________________________________________________________________________________________________________________________________
(Q7) FRAGMENTATION PRECLUDES “INTERMEDIACY”
(Q10) Every good person is better than any
intermediate person.
(Q11) For any fragmented person f there is a
good person g who is not better than f.
(Q7) No fragmented person is intermediate.
In support of Q11: Take f and g who behaves
(a) admirably when f behaves deplorably, and
(b) neutrally when f behaves admirably or
neutrally. Then g is good but, by the Incommensurability Argument, g is not better than f.
____________________________________________________________________________________________________________________________________________________________
OBJECTIONS 1-2 TO Q5
Objection 1: Goodness of character depends on
motives, regardless of whether acts deplorable.
Reply: (a) I’m not denying that motives matter.
(b) If the claim is that only motives matter, I
disagree: weakness of will no adequate excuse.
Objection 2: Counterfactual behavior is irrelevant to character because of “moral luck”.
Reply: Counterfactual behavior is irrelevant to
responsibility but can be relevant to character.
OBJECTIONS 3-4 TO Q5
Objection 3: Certain counterfactuals irrelevant.
You would have committed atrocities had you
been raised in Nazi Germany.
Reply: Only actual dispositions relevant to Q5.
Objection 4: Even some actual dispositions irrelevant to character. You would kill if tortured.
Reply: Irrelevant only if torture excuses killing;
if it does, then killing after being tortured is not
deplorable, so counterfactual irrelevant to Q5.
OBJECTIONS 5-6 TO P5
Objection 5: Only extremely deplorable behavior
precludes compensation. Crushing ants?
Reply: Disagreement about antecedent of P5.
Objection 6: People choose their situations.
Reply: Take p1 and p2, who (know they) would
kill if drunk. p1 drinks, p2 does not. Then p1 cp
worse than p2, but both cp worse than p3, who
would not kill if drunk. Disposition to choose
situations does matter, but counterfactual behavior even in unchosen situations also matters.
OBJECTION 7 TO P5
Objection 7: There is no fact of the matter about
how you would behave in various situations.
Reply: Only counterfactuals about whose truth
there is a fact of the matter are relevant to P5.
Rejoinder: What if all dispositions probabilistic?
Reply: Two extreme cases. (1) For most people
high probabilities. Then most people still fragmented. (2) For most people low probabilities.
Then most people not fragmented but still
indeterminate.
AN OBJECTION TO Q6:
WHAT ABOUT HITLER?
Maybe Hitler was bad; consider Ted Bundy.
Being nice to your mother is not admirable.
A few isolated instances are no open list.
 Bundy was not better than an intermediate
person who never behaves admirably.
 I’m not saying Bundy was good; only not bad.
So badness cannot be fully compensated.
 Anchoring bias: good or bad news first?
 Symmetry argument: why give greater weight
to deplorable than to admirable behavior?


THE INCREDIBILITY
OBJECTION
First form: It’s incredible to deny that a brutal
serial killer is bad just because in a psychological experiment he would (e.g.) stop a thief.
Reply: (a) I’m not saying he’s good (or not bad).
(b) I’m not relying just on experiments.
(c) Anchoring bias: bad or good news first?
Second form: I know my wife is good. It doesn’t
matter that she would behave sadistically in an
experiment; I don’t even believe she would.
Reply: -You can’t predict. -Experiments matter.