Hi all!

It seems to me that the problem with expected utility as a theory of
rational decision making is that it does not properly take into account
the variances of the outcomes for the different options, especially if
the decision is to be made in only few instances, maybe even only once.
I have not followed the discussion really closely, but it seems to me
that the only reference to this is the notion of "risk aversion" that
turned up a few times. My personal problem is that I cannot see risk
aversion as irrational, even if this means choosing the option with
the lower expected value.

In other words, expected utility theory works, as its name says, with
the expected utility of an option. However, the expected utility is the
only relevant value only if I am offered to make the decision several,
(or actually quite a lot of) times. Then the law of large numbers says
that the average utility of the outcomes in these different instances
converges in probability to the expected utility. This basically means
that I can neglect the variance, as it goes to zero with a large number
of instances. But if I can make the decision only few times, or if
I can make it even only once, the variance cannot be neglected and
information about this variance becomes relevant. In my opinion, the
paradoxes only show that human beings take this information about the
variances into account - and I see nothing irrational in this. It is
just that expected utility theory neglects this information and thus
is not sufficient as a proper model of rational decision making
(descriptive as well as normative).

To make my point clear, I would like to quote (or actually translate
from the German/Swiss original, as I do not own an English translation)
from Max Frisch's novel "Homo Faber". The setting: Elisabeth Piper,
daughter of Hanna Piper, was bitten by a snake and has been admitted
to a hospital. The narrator of the story is Walter Faber, an engineer
with a completely rationalistic world view.

   "Did you know", I ask, "that the rate of mortality from snake bites
 is only three to ten percent?"
   I was surprised.
   Hanna does not think much of statistics, that I discovered soon.
 [...]
   "You and your statistics!" she says. "If I had a hundred daughters,
 each of them bitten by a viper, then yes! Then I would loose only
 three to ten daughters. Surprisingly few! You are absolutely right."
   Her laughter with this.
   "I have only a single child!" she says.

The point is: A single decision instance is different from a (large)
set or sequence of instances of the same type. The frequentist (or
empirical) interpretation of probability explicitely acknowledges
this, for instance, by refraining from saying that there is a certain
probability that a particular smoker gets lung cancer - it only says
that he/she belongs to a "risk group", in which a certain (higher)
percentage of people gets lung cancer. By this I am not saying that
the subjective (or personalistic) interpretation of probability is
wrong or inappropriate. I just would like to point out a problem
connected with it, which should be handled with care.

It appears to me that it could be checked whether my view is correct
by considering the following settings:
a) One can choose in a single instance between the two lotteries of
   Allais' paradox.
b) One can do this 5 to 10 times, each decision independent of any
   other.
c) One can do it 100 or 1000 times, again each decision independent
   of any other.
I assume that with a higher number of times one can choose between the
lotteries, it will turn out that in a certain percentage of the cases
people will go for the sure payoff and in the rest for the higher
expected value (which, however, is connected to a higher risk), thus
achieving a certain expected value to variance (or risk) relation.
And this is what I believe people are actually optimizing - and
I think that they are acting completely rationally if they do so,
simply because the law of large number does not really apply to most
decision situations of individual real life.

Best regards,
Chris

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