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.


Taking the easy way out

Taking the easy way out is a concept that is much frowned upon, especially in India (though I must confess I don’t have enough exposure to other cultures to have noticed this). When you take the easy way out on something, people assume that you’re cheating – like you’re using a cheat code in a computer game.

For example, purists believe that if one were to get the good karma that one deserves by going to Tirupati, it will accrue if and only if you were to walk up the hill on foot. People who take the easy way out by taking a cab or bus uphill apparently don’t get as much good karma.

During festivals such as Sankranti, people who buy the sugar candies and the eLL (sesame) mixture from a shop are again frowned upon, given they are taking the easy way out rather than preparing them at home. Employing a cook is similarly frowned upon, as is taking an auto rickshaw or a cab rather than a bus.

And to take an example that long-time readers of this blog might appreciate, fighters tend to view studs with derision since the latter seemingly get things done without putting in the same amount of effort as the former.

Ok I might have claimed in the past that my pieces are usually long on analysis and short on rhetoric, but as you can see, this is not one of those pieces. All I’ve done so far is to give examples of something that I don’t agree with.

And the reason I don’t agree with the view that taking the easy way out is wrong is because it is done if and only if it’s optimal. Notice that in all the above examples, there is no free lunch. Taking the easy way out comes at a cost, and reflects a set of trade offs. To take the car up Tirupati costs money, and the opportunity of experiencing the supposedly electric hillsides – and benefits are uncertain anyway in religious matters. Employing a cook or taking an auto are efficient if you value time and convenience, for example.

While I agree that there might be some cases where taking the easy way out might be short-termist (you might be ignoring “tail risks”, for example, which allows you to use an easy pricing model, or by using a calculator you may not develop your long-term arithmetic skills), in most cases it is considered decision.

In other words, there is no problem with taking the easy way out as long as you have fully understood the costs and benefits (including any tail risks) of the method that you’ve chosen to adopt. There is no absolute virtue attached to labour – labour is always a means to get to an end. Once you digest this, you will have no hesitation in taking the easy way out.