When it comes to "the utility function is not up for grabs", we should jetison hyperbolic discounting far before we reject the idea that I'm the same agent now as in one second's time.

Only one out of 21 obstetricians could estimate the probability that an unborn child had Down syndrome given a positive test

Say the doctor knows false positive/negative rates of the test, and also the overall probability of Down syndrome, but doesn't know how to combine these into the probability of Down syndrome given a positive test result.

Okay, so to the extent that it's possible, why doesn't someone just tell them the results of the Bayesian updating in advance? I assume a doctor is told the false positive and negative rates of a test. But what matters to the doctor is the probability that the patient has the disorder. So instead of telling a doctor, "Here is the probability that a patient with Down syndrome will have a negative test result," why not just directly say, "When the test is positive, here is the probability of the patient actually having Down syndrome. When the test is negative, here is the probability that the patient has Down syndrome."

Bayes theorem is a general tool that would let doctors manipulate the information they're given into the probabilities that they care about. But am I crazy to think that we could circumvent much of their need for Bayes theorem by simply giving them different (not necessarily much more) information?

There are counterpoints to consider. But it seems to me that many examples of Bayesian failure in medicine are analogously simple to the above, and could be as simply fixed. The statistical illiteracy of doctors can be offset so long as there are statistically literate people upstream.

If I understand the following Wikipedia page correctly:

http://en.wikipedia.org/wiki/Positive_predictive_value

The term you are requesting is Positive predictive value and Negative predictive value is the term for not having a disorder given a negative test result.

It also points out that these are not solely dependent on the test, and also require a prevalence percentage.

But that being said, you could require each test to be reported with multiple different prevalence percentages:

For instance, using the above example of Downs Syndrome, you could report the results by using the prevalence of Downs Syndrome at several different given maternal ages. (Since prevalence of Down's Syndrome is significantly related to maternal age.)

This stops working in the case where some of the people upstream can't be trusted. Consider the following statement:

"The previous test, if you have a positive result, means that the baby has a 25% chance of having Down syndrome, according to the manufacturer. But my patented test will return a positive result in 99% of cases in which the baby has Down syndrome."

Only one out of 21 obstetricians could estimate the probability that an unborn child had Down syndrome given a positive test

Say the doctor knows false positive/negative rates of the test, and also the overall probability of Down syndrome, but doesn't know how to combine these into the probability of Down syndrome given a positive test result.

Okay, so to the extent that it's possible, why doesn't someone just tell them the results of the Bayesian updating in advance? I assume a doctor is told the false positive and negative rates of a test. But what matters to the doctor is the probability that the patient has the disorder. So instead of telling a doctor, "Here is the probability that a patient with Down syndrome will have a negative test result," why not just directly say, "When the test is positive, here is the probability of the patient actually having Down syndrome. When the test is negative, here is the probability that the patient has Down syndrome."

Bayes theorem is a general tool that would let doctors manipulate the information they're given into the probabilities that they care about. But am I crazy to think that we could circumvent much of their need for Bayes theorem by simply giving them different (not necessarily much more) information?

There are counterpoints to consider. But it seems to me that many examples of Bayesian failure in medicine are analogously simple to the above, and could be as simply fixed. The statistical illiteracy of doctors can be offset so long as there are statistically literate people upstream.

Closeness in the experiment was reasonably literal but may also be interpreted in terms of identification with the torturer. If the church is doing the torturing then the especially religious may be more likely to think the tortured are guilty. If the state is doing the torturing then the especially patriotic (close to their country) may be more likely to think that the tortured/killed/jailed/abused are guilty. That part is fairly obvious but note the second less obvious implication–the worse the victim is treated the more the religious/patriotic will believe the victim is guilty. ... Research in moral reasoning is important because understanding why good people do evil things is more important than understanding why evil people do evil things.

-Alex Tabarrok

We run the risk of going extinct, and the irony is, we did it to ourselves. The ‘smarty pants’ brain that created advanced weapons, complex global economics [and more] is routinely bossed around by the brain that shoots from the hip, makes often terrible decisions, and reacts more to fear and greed than to reason....

No one in their right mind would deliberately create the means of their own extinction, but that’s what we seem to be doing. The only conclusion is that we’re not in our right minds...

K.C. Cole

This post, by its contents and tone, seems to really emphasize the downside of signaling. So let me play the other side.

Enabling signaling can add or subtract a huge amount of value from what would happen without signaling. You can tweak your initial example to get a "rat race" outcome where everyone, including the stupid people, sends a costly signal that ends up being completely uninformative (since everyone sends it). But you can also make it prohibitively mentally painful for stupid people to go to college, versus neutral or even enjoyable for smart people (instead of there being an actual economic cost of engaging in signaling), with a huge gain to employers for being able to tell them apart.

one can look at Nikolai Roussanov's study on how the dynamics of signaling games in US minority communities encourage conspicuous consumption and prevent members of those communities from investing in education and other important goods.

As a counterpoint to this, in other cases the signaling value of education may induce people to get more education than is individually optimal, which is actually a good thing socially if you think education has large positive externalities. And if you work hard and discover a cure for cancer, you will be paid largely through other people's opinions of you, now that you've signaled to them that you are such an intelligent and hard-working and socially-conscious person. (You were just as intelligent before you cured it, but now they know). Since you cannot possibly hope to recoup even a modest fraction of the social value you will have created, that's unambiguously good for incentives.

On any other site, I would probably get away with saying: Since invention is basically the reason for our high modern standards of living, if signaling seriously encourages it, then in the long run the positive value of signaling would seem to dwarf any losses discussed above (even the "poverty" of some minority communities is nothing compared to the poverty in all of our shared historical past). But here...well, here we are pretty worried about where our invention spree might be leading us.

This sounds awesome. It would be really cool if you could configure it so that identifying biases actually helps you to win by some tangible measure. For example, if figuring out a bias just meant that person stopped playing with bias (instead of drawing a new bias), figuring out biases would be instrumental in winning. The parameters could be tweaked of course (if people typically figure out the biases quickly, you could make it so they redraw biases several times). Or you could link drawing additional biases with the drawing of epidemic cards?

I have this terrifying vision of a version where it is biases -- not diseases -- which spread throughout the world, and whenever a player's piece is in a city infected with a certain bias, they have to play with it...

Now that I'm Executive Director I don't have much time to bang my head on hard (research) problems, though I did start doing that a while back.

This is a "merely" inspirational post, but I think there's room for that on LW. There isn't much new insight in A sense that more is possible, either, but I found it valuable.