Bayes Theorem and Respect

Regular readers of this blog will know very well that I keep talking about how everything in life is Bayesian. I may not have said it in those many words, but I keep alluding to it.

For example, when I’m hiring, I find the process to be Bayesian – the CV and the cover letter set a prior (it’s really a distribution, not a point estimate). Then each round of interview (or assignment) gives additional data that UPDATES the prior distribution. The distribution moves around with each round (when there is sufficient mass below a certain cutoff there are no more rounds), until there is enough confidence that the candidate will do well.

In hiring, Bayes theorem can also work against the candidate. Like I remember interviewing this guy with an insanely spectacular CV, so most of the prior mass was to the “right” of the distribution. And then when he got a very basic question so badly wrong, the updation in the distribution was swift and I immediately cut him.

On another note, I’ve argued here about how stereotypes are useful – purely as a Bayesian prior when you have no more information about a person. So you use the limited data you have about them (age, gender, sex, sexuality, colour of skin, colour of hair, education and all that), and the best judgment you can make at that point is by USING this information rather than ignoring it. In other words, you need to stereotype.

However, the moment you get more information, you ought to very quickly update your prior (in other words, the ‘stereotype prior’ needs to be a very wide distribution, irrespective of where it is centred). Else it will be a bad judgment on your part.

In any case, coming to the point of this post, I find that the respect I have for people is also heavily Bayesian (I might have alluded to this while talking about interviewing). Typically, in case of most people, I start with a very high degree of respect. It is actually a fairly narrowly distributed Bayesian prior.

And then as I get more and more information about them, I update this prior. The high starting position means that if they do something spectacular, it moves up only by a little. If they do something spectacularly bad, though, the distribution moves way left.

So I’ve noticed that when there is a fall, the fall is swift. This is again because of the way the maths works – you might have a very small probability of someone being “bad” (left tail). And then when they do something spectacularly bad (well into that tail), there is no option but to update the distribution such that a lot of the mass is now in this tail.

Once that has happened, unless they do several spectacular things, it can become irredeemable. Each time they do something slightly bad, it confirms your prior that they are “bad” (on whatever dimension), and the distribution narrows there. And they become more and more irredeemable.

It’s like “you cannot unsee” the event that took their probability distribution and moved it way left. Soon, the end is near.

Correlated judgment

When you judge people about something, you do not normally judge them on that thing alone. You also judge them on “correlated traits”. For example, there is this popular adage (that was popular when I was in IIT) that goes “beauty times brains equals constant”. This implies that anyone who is above average in terms of looks is likely to be below average in terms of mental capabilities. Whether such a correlation exists is not known, but by instinct if we someone beautiful, we assume that the person is not great in terms of mental ability (in my later years at IIT, we recognized this limitation of the model and proposed “beauty times brains times availability equals constant”, acknowledging that beautiful intelligent people exist, but are most likely taken).

There is no end to such correlations, which usually make rounds around college campuses. For example, there is the “he is the partying types, so is unlikely to be a good worker”. Now, while it is true that the amount of time available to most people is constant, and that heavy partying can come at the cost of working, such an adage discounts the fact that some people could simply be better time managers, or don’t care much for some axis apart from partying and working (sleeping, for example!), which allows them to be good at two things that people are normally not good at!

It is common for people to judge people. However, thanks to implicit correlations of traits that are built into people’s minds, when you get judged on one thing, that is not the only thing you are judged on – you are also judged on the things that are correlated with that!

Time for more examples. Once my parents saw a friend of mine very evidently flirting with a girl. They immediately judged him as being “a flirt” and branded him thus. While judgmental, there is no mistake in that judgment – he was indeed a flirt, and would gladly admit to it. But then my parents, using their inbuilt correlation filters, went one step ahead. “He is such a flirt”, they told me, “We don’t think he is a good person. You should not hang out with him any more”!!

Back in 2005, in IIMB, I had stood for elections to the Academic Council. At a party a week before the elections I happened to get wasted, and ended up talking to people inappropriately. The next morning, as I’m trying to get over my hangover, I heard “dude, how could you get wasted if you are standing for elections?” I have no clue how getting wasted at one party would make me a bad Academic Councillor! I must mention I lost the elections.

It was at a discussion yesterday with Bharati and my wife Priyanka that this topic of correlated judgment came up, when we were discussing how life in a business school can be unforgiving. A few minutes later, Priyanka popped up “that baby was so cute, I expected him to be dumb!”

Budget Analysis

So I finally finished going through today’s Mint and noticed that most of it was filled with analysis of the budget. I tried reading most of them, and didn’t manage to finish any of them (save Anil Padmanabhan’s I think). Most of them were full of globe, each had an idea that could have been expressed in a few tweets, rather than a full column.

Thinking about it, I guess I was expecting too much. After all, if you are calling captains of the industry and sundry bankers and consultants to write about the budget, I don’t think you can expect them to come out with much honest analysis. Think about their incentives.

As for corporate guys, you will expect them to make the usual noises and perhaps be partisan in their judgment. You can expect them to crib about those parts of the budget that shortchanged their company or industry or sector or whatever. But you don’t need them in an op-ed to tell you that – it is obvious to you if you read the highlights, or some rudimentary analysis that the paper anyway provides.

However, these guys won’t want to rub the ruling party the wrong way, so they fill up the rest of their essays with some globe about how it is a “progressive” budget or a “pro-poor” budget or some such shyte. So far so good.

The think tank guys are probably better. At least they don’t have any constituency to pander to, and they can give a good critical analysis. However, as academics (and most likely, not being bloggers) what they write is usually not very easy to read, and so what they say (which might actually contain something useful) can be lost to the reader.

The worst of all are the fat-cat consultants and bankers. The reason they write is primarily to gain visibility for themselves and for their firm, and given how lucrative government business is for these guys (look at the ridiculously low fees these guys charge for government IPOs, and you’ll know) they have absolutely no incentive to tell something useful, or honest. Again these guys aren’t used to writing for a general audience. So you can expect more globe.

All that I needed to learn about the budget I learnt by way of a brief unopinionated summary sent in an internal email at work yesterday (it took me 2 mins to read it on my blackberry). And also Anil Padmanabhan’s cover page article in today’s Mint.

update:

I must mention I wrote this post after I’d read the main segment of today’s Mint. Starting to read the “opinion” supplement now, and it looks more promising

A Balance Sheet View of Life

The basic idea of this post is that interpersonal relationships (not necessarily romantic) need to be treated as balance sheets and not as P&L statements, i.e. one should always judge based on the overall all-time aggregate rather than the last incremental change in situation.

Just to give you a quick overview of accounting, the annual statement typically has two major components – the P&L statement which reflects what happened between the last release of the statement and the currrent point, and the balance sheet which reflects the position of the company at the point of time of release of the statement.

I think Bryan Caplan had made this point in one of his posts, but I’m not able to find it and hence not able to link it. The point is that you should look at relationships on a wholesome basis, and not just judge it based on the last action. The whole point is that there is volatility (what we refer to in my office as “the dW term”) and so there are obviously going to be time periods during which you record a loss. And if on each of these occasions you were to take your next course of action based on this loss alone, you are likely to be the loser.

I’m not saying that you should ignore the loss-making periods and just move on. You do need to introspect and figure out what you need to do in the next accounting period in order to prevent this kind of a loss from repeating. You will need to “work the loss”, not make a judgment to break the relationship based on it. I think a large part of the problems in this world (yeah, here goes another grand plan) stems from people using one-period losses in order to take judgments on relationships.

Another thing is not to generate the accounting statements on a shorter time period. This is similar to one funda I’d put long ago about how you shouldn’t review your investments at extremely short intervals since that will lead to a domination of the volatility term (dW) and thus cause unnecessary headache. You might notice that corporates rarely release their accounts statements more frequently than once a quarter – this has more to do with volatility than with the difficulty in generating these statements.It is similar in the case of interpersonal relationships. Don’t judge too often – the noise term will end up dominating.

One caveat though – very occasionally the last loss may be so bad that it more than wipes out the balance sheet and takes to zero (or even less) the value of the firm. In that kind of a situation, there is no option but to shut down the firm (or break the relationship) and move on. Once again, however, the clincher in the decision to break up has to be the balance sheet which has gone to zero (or negative) and not just simply the magnitude of the last loss.

Life based on a balance sheet view is a balanced life.