lucidian comments on Train Philosophers with Pearl and Kahneman, not Plato and Kant - Less Wrong

65 Post author: lukeprog 06 December 2012 12:42AM

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Comment author: Plasmon 04 December 2012 01:19:25PM 3 points [-]

It's not going to happen because it would disqualify too many candidates and make courses unpopular. Maths is a huge turn off for a lot of people.

Indeed. This is a bug, not a feature, and alas, it holds these fields back.

Also, one could argue that history is releant to just about everything. Etc.

It is certainly true that history-of-(field) is useful for people doing work in (field). History in general, while useful in general, is less directly useful for a specific field. And indeed, most fields do spend reasonable (or more than reasonable!) amounts of time discussing their own history. Art does this, philosophy does this, even mathematics and physics do this to some extent.

It is true that the argument "one could argue that (some field) is relevant to just about everything and that therefore more of (this field) should be taught" can be made convincingly for many fields, but the fact that it can be made for many fields is not an argument against it, it just means that some field must be prioritized, hopefully on utilitarian grounds.

Comment author: lucidian 04 December 2012 01:31:56PM -1 points [-]

It's not going to happen because it would disqualify too many candidates and make courses unpopular. Maths is a huge turn off for a lot of people.

Indeed. This is a bug, not a feature, and alas, it holds these fields back.

I disagree that this is a bug, not a feature. I think it's useful for fields to contain people with different styles of thinking. The people who are competent at math are probably N types on the MBTI, people who are good at abstract reasoning, but who might be less competent at focusing on empirical data and specific concrete situations. The sciences, especially the social sciences, need people who are good at observing/collecting data, and I would hate to disqualify these people with a math requirement, or relegate them to lower-status because their minds operate in a different (but also useful) way.

(This comment informed by having read this essay earlier this morning.)

Comment author: somervta 04 December 2012 06:35:06PM 3 points [-]

It's not going to happen because it would disqualify too many candidates and make courses unpopular. Maths is a huge turn off for a lot of people.

Indeed. This is a bug, not a feature, and alas, it holds these fields back.

I disagree that this is a bug, not a feature. I think it's useful for fields to contain people with different styles of thinking

I suspect that the negative attitude towards math has less to do with personality type and more to do with the execrable state of mathematics education.

Comment author: Plasmon 04 December 2012 05:57:17PM 2 points [-]

That is an exceedingly optimistic hypothesis.

The people who are competent at math are probably N types on the MBTI, people who are good at abstract reasoning, but who might be less competent at focusing on empirical data and specific concrete situations.

Might be, indeed. This hasn't stopped physics, chemistry, engineering, biology, astronomy, etc. all of which have empirical data and concrete situations, and are chock-a-block with maths.

The sciences, especially the social sciences, need people who are good at observing/collecting data

Indeed they need such people. If you have evidence that the present selection procedures prevalent in the social sciences select for such people, I would be delighted to hear it.

Observing and collecting data is stereotypically something that maths types are good at. Consider google, data science and data mining.

Let me refer to Why is machine learning not used in medical diagnosis?

The top voted answer in the Quora discussion is from a medical student (...) describing the complexity of a diagnostic decision, and claims “the human body is incapable of being defined by any algorithm, no matter how bloody brilliant it is.”

The expert systems in question supposedly outperform human doctors!

The problem with machine learning in medicine is not the machine learning. Machine learning and AI have come a long way since the 80′s, and even then automated systems outperformed doctors in experimental settings.

I hypothesise as follows : the non-mathy fields maintain a group dynamic that causes a certain hostility towards mathematical ideas, even when such ideas are objectively superior. To an extent, this also prevents objective judgement of people's abilities within the field, and steers these fields away from a desirable meritocratic state. We end up with fields that select against mathematical ability (those with mathematical ability flee as soon as they realise that the entire history curriculum does not contain a single course on radiometric dating - I wish I were kidding), and that may not select for other desirable qualities instead.

Comment author: NancyLebovitz 05 December 2012 04:06:29AM 1 point [-]

From the essay:

Or to put it more provocatively: The Aspier someone is, the more likely it is that he’ll be an eager utilitarian. (You probably know people like this. Anyone who self-identifies as a ‘utilitarian’ probably has Aspie tendencies — very fluent with abstract concepts, and very eager to apply them to all aspects of life.)

It might be possible to get some information about this from the survey.

Comment author: gwern 05 December 2012 08:41:27PM *  3 points [-]

The utilitarian/autism-spectrum correlation may be true in the general population, but there doesn't seem to be any correlation between self-reported AQ and consequentialism endorsement in the LW population (perhaps because the LW population is already self-selected for either being a consequentialist or coming up with good justifications for non-consequentialism):

R> lw <- read.csv("2012.csv")
R> lwa <- subset(lw, !is.na(AutismScore))
R> levels(lwa$MoralViews)
[1] " " "Accept / lean toward consequentialism"
[3] "Accept / lean toward deontology" "Accept / lean toward virtue ethics"
[5] "Other / no answer"
R> lwa <- subset(lwa, as.character(MoralViews) != " " & as.character(MoralViews) != "Other / no answer")
R> cor.test(lwa$AutismScore, as.integer(lwa$MoralViews))
Pearson's product-moment correlation
data: lwa$AutismScore and as.integer(lwa$MoralViews)
t = 0.1663, df = 289, p-value = 0.868
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.1053 0.1246
sample estimates:
cor
0.009783

(A positive correlation suggests that higher autism scorers were a tad more likely to endorse a higher category, that is, deontology or virtue ethics.)

Comment author: NancyLebovitz 05 December 2012 09:20:26PM 1 point [-]

Thank you for checking.

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