Lifting and arithmetic

At a party we hosted recently, we ended up talking a lot about lifting heavy weights in the gym. In the middle of the conversation, my wife wondered loudly as to why “so many intelligent people are into weightlifting nowadays”. A few theories got postulated in the following few minutes but I’m not going to talk about that here.

Anecdotally, this is true. The two people I hold responsible for getting me lift heavy weights are both people I consider rather intelligent. I discuss weights and lifting with quite a few other friends as well. Nassim Taleb, for a long time, kept tweeting about deadlifts, though now he has dialled back on strength training.

In 2012 or 2013 I had written about how hard it was to maintain a good diet and exercise regime. While I had stopped being really fat in 2009, my weight had started creeping up again and my triglyceride numbers hadn’t been good. I had found it hard to stick to a diet, and found the gym rather boring.

In response, one old friend (one of the intelligent people I mentioned above) sent me Mark Rippetoe’s Starting Strength (and a few other articles on cutting carbs, and high-fat diets). Starting Strength, in a way, brought back geekery into the gym, which had until then been taken over by “gym bros” doing bicep curls and staring into mirrors.

It’s been a long time since I read it, but it’s fascinating – I remember reading it and thinking it reminded me of IIT-JEE physics. He draws free body diagrams to explain why you should maintain a straight bar path. He talks about “moment arms” to explain why the bar should be over your mid-foot while deadlifting (ok this book we did discuss at the party in response to my wife’s question).

However, two incidents that happened last week gave me an idea on why “intelligent people” are drawn to lifting heavy barbells. It’s about challenging yourself to the right extent.

The gym that I go to (a rather kickass gym) has regular classes that most members attend. These classes focus on functional fitness (among other things, everyone is made to squat and press and deadlift), but I’ve for long found that these classes bore me so I just do my own thing (squats, press / bench and deadlift, on most days). Occasionally, though, like last Friday, I decide to “do the class”. And on these occasions, I remember why I don’t like the class.

The problem with the gym class is that I get bored. Most of the time, the exercises you are doing are of the sort where you lift well below capacity on each lift, but you do a lot of lifts. They train you not just for strength but also for endurance and metabolic conditioning. The problem with that for me is that because every single repetition is not challenging, I get bored. “Why do i need to do so much”, I think. Last Friday I exited the class midway, bored.

My daughter is having school holidays, and one of the things we have figured is that while she has grasped all her maths concepts rather soundly (the montessori system does a good job of that), she has completely failed to mug her tables. If I ask her what is “7 times 4” (for example), she takes half a minute, adds  7 four times and tells me.

Last Monday, I printed out (using Excel) all combinations of single digit multiplications and told her she “better mug it by Friday”. She completely refused to do it. There was no headway in her “learning”. I resorted to occasionally asking her simple arithmetic questions and making her answer immediately. While waiting to cross the road while on a walk, “what is six times eight?”. While waiting for the baker to give us bread “you gave him ?100 and the bread costs ?40. How much change should he give you?”. And so on.

She would occasionally answer but again her boredom was inherent. The concept learning had been challenging for her and she had learnt it. But this “repetitive practice” was boring and she would refuse to do it.

Then, last Friday, I decided to take it up a notch. I suddenly asked “what is four and a half times eight?” (she’s done fractions in school). This was a gamechanger.

Suddenly, by dialling up the challenge, she got interested, and with some prodding gave me the correct answer. An hour earlier, she had struggled for a minute to tell me what 8 times 7 is. However, when I asked her “what is eight times seven and a half?” she responded in a few seconds, “eight times seven is fifty six..” (and then proceeded to complete the solution).

Having exited my gym class midway just that morning, I was now able to make sense of everything. Practicing simple arithmetic for her is like light weight lifting for me. “Each rep” is not challenging in either case, and so we get bored and don’t want to do it. Dial up the challenge a little bit, such as bringing in fractions or making the weights very heavy, and now every rep is a challenge. The whole thing becomes more fun.

And if you are of the type that easily gets bored and wants to do things where each unit is challenging, barbell training is an obvious way to exercise. and “intelligent” people are more likely to get bored of routine stuff. And so they are taking to lifting heavy weights.

I guess my wife has her answer now.

 

Muggoos and overfitting

Back when I was a student, there was this (rather large) species of students who we used to call “muggoos”. They were called that because they would have a habit of “mugging up the answers” – basically they would learn verbatim stuff in the textbooks and other reading material, and then just spit it out during the exams.

They were incredibly hardworking, of course – since the volume of stuff to mug was immense – and they would make up for their general lack of understanding of the concepts with their massive memories and rote learning.

On average, they did rather well – with all that mugging, the downside was floored. However, they would stumble badly in case of any “open book exams” (where we would be allowed to carry textbooks into the exams) – since the value of mugging there was severely limited. I remember having an argument once with some topper-type muggoos (with generally much better grades than me ) on whether to keep exams in a particular course open book or closed book. They all wanted closed book of course.

This morning, I happened to remember this species while chatting with a friend. He was sending me some screenshots from ChatGPT and was marvelling at something which it supposedly made up (I remembered it as a popular meme from 4-5 years back). I immediately responded that ChatGPT was simply “overfitting” in this case.

Since this was a rather popular online meme, and a lot of tweets would have been part of ChatGPT’s training data, coming up with this “meme-y joke” was basically the algorithm remembering this exact pattern that occurred multiple times in the training set. There was no need to intuit or interpolate or hallucinate – the number of occurrences in the training set meant this was an “obvious joke”.

In that sense, muggoos are like badly trained pieces of artificial intelligence (well, I might argue that their intelligence IS artificial) – they haven’t learnt the concepts, so they are unable to be creative or hallucinate. However, they have been “trained” very very well on the stuff that is there in the textbooks (and other reading material) – and the moment they see part of that it’s easy for them to “complete the sentences”. So when questions in the exams come straight out of the reading materials (as they do in a LOT of indian universities and school boards) they find it easy to answer.

However, when tested on “concepts”, they now need to intuit – and infer based on their understanding. In that sense, they are like badly trained machine learning models.

One of the biggest pitfalls in machine learning is “overfitting” – where you build a model that is so optimised to the training data that it learns quirks of the data that you don’t want it to learn. It performs superbly on the training dataset. Now, when faced with an unknown (“out of syllabus”) test set, it underperforms like crazy. In machine learning, we use techniques such as cross validation to make sure algorithms don’t overfit.

That, however, is not how the conventional Indian education system trains you – throughout most of the education, you find that the “test set” is a subset of the “training set” (questions in examinations come straight out of the textbook). Consequently, people with the ability to mug find that it is a winning strategy to just “overfit” and learn the textbooks verbatim – the likelihood of being caught out by unseen test data is minimal.

And then IF they get out into the real world, they find that a lot of the “test data” is unknown, and having not learnt to truly learn from the data, they struggle.

PS: Overfitting is not the only way machine learning systems misbehave. Sometimes they end up learning the entirely wrong pattern!

Creative Grit!

This, by Annie Murphy Paul is a very interesting blogpost I came across today. This one is on “creative grit”.

There are two very interesting things that the blogpost talks about.

The first is that there are two ways to creativity – the “traditional way” (the way I’ve always seen it) is to think about the problem, internalise it and then somewhere “wait for inspiration to strike”.

The other method that the author talks about, referring to artist Franz Kline, is to “just keep trying”. Kline would make hundreds of paintings every night. And he would find that one (or few) of them would be good enough to work further on. So this form of creativity comes from repeated practice.

Then later in the blogpost, she also talks about some research on when creativity hits. Again, “traditionally” we are trained to think that if creativity has to “hit” us for a particular problem, that is much more likely to occur early on in our effort. Based on this, a lot of us creative people have come up with heuristics where if solution doesn’t occur within a few iterations of trying, we just give up and move on.

Annie Murphy Paul says that this is the incorrect approach. Quoting from her post:

Lucas and Nordgren call this the “creative cliff illusion”: we imagine that, after an initial upward leap, our creativity will then fall off a cliff—when in reality our creativity capacities are just getting ready to ascend.

We also misjudge the thoroughness of our search. In one study, people estimated that they had explored 75 percent of the solution space—when in fact they had covered only 20 to 30 percent of the relevant domain.

I sure should try the second method that she recommends – keep trying and occasionally you’ll be happy with the result. Or maybe I already do that with all my writing (this blog, my newsletters, etc.) – basically “spray and pray”. The reason I’ve managed to write so much is that I have a low bar for myself. So I write a lot of rubbish. And occasionally I end up writing something people like. On the other hand when I’m paid to write, I don’t “spray and pray”. And in trying to limit my downside I limit my upside as well.

And thinking about it, the reason this method works is that in creative pursuits only the wins matter. As long as you produce sufficient wins, no one cares about your duds!

While on the topic of creativity, here is an ancient lecture (maybe my first ever recorded “speech”) I gave on why “quality takes time”. This clearly shows that at least as of mid-2004 (coincidentally just before I started this blog) I used to strongly believe in the “wait for inspiration to strike” model of creativity.

Oh and btw, read the whole post. It’s worth it.

Paying doctors

Back in 2011-12, when I was about to go freelance, a friend told me about a simple formula on how I should price my services. “Take your expected annual income and divide it by 1000. That will be your hourly rate”, he said. I followed this policy fairly well, with reasonable success (though I think I shortchanged myself in some situations by massively underestimating how long a task would take – but that story is for another day).

The longer term effect of that has been that every time I see someone’s hourly rate, I multiply it by 1000 to guess that person’s approximate annual income (the basis being that as a full time worker, you “bill” for 2000 hours a year. As a freelancer you have “50% utilisation” and so you work 1000 hours).

And one set of people who have fairly transparent hourly rates are doctors – you know the number of appointments they give per hour, and what you paid for that, and you can back calculate their annual income based on that. The interesting thing is, for most doctors I’ve seen, based on this metric, what they earn for their level of eduction and years of experience seems rather low.

“So how do doctors earn?”, I wonder. Why is it still a prized profession while you might have a much better life being an engineer, for example?

Now you should remember that consultations are only one income stream for doctors. Those that practice surgery as well have a more lucrative stream – the hourly rates for surgeries far exceeds hourly rates of consultation. And so surgeons make far more than what I impute from what I’ve paid them for a consultation.

One possible reason for this arbitrage is the way insurance deals are structured – at least in India, out patient care is seldom paid for by insurance. As a consequence, hospitals and doctors cross-subsidise consultations with surgeries. They are able to get away with higher rates for surgeries because insurers are bearing the cost. Consultations, where patients generally pay out of their own pockets, are far more elastic.

This, however, leads to a problem for doctors who don’t do surgeries. Psychiatrists, for example. If they have to make money solely through consultations, their hourly rate must be far higher than that of doctors who also do surgeries. But then, is the market willing to bear this cost?

Now, I’m getting into conspiracy theory mode. If the amount non-surgeon doctors make is limited (thanks to market dynamics), the only way they can make sure they earn a decent living is by limiting supply. Could this be one reason India is under-supplied in a lot of non-surgical doctors? Again this is pure pure speculation, and not based in any fact.

Continuing with conspiracy theories, even for doctors who are surgeons, the only way to make a certain income is to have a threshold on the ratio of surgeries to consultations. And if this ratio (surgeries / consultations) goes too low, the doctors’ income suffers. Again, hippocratic oath aside, do hospitals try to game this metric, based on the current incentives?

On a more serious note, this distortion in the hourly earnings for surgeries versus consultations is one reason that India is also undersupplied with good general practitioners (GPs). Because GPs don’t do surgeries (though the Indian system means they are all licensed to perform surgeries, to the best of my knowledge), their earning potential is naturally capped. So the better doctors don’t want to be GPs.

How can we fix this distortion? How can we make sure we have better GPs? Insurance cover for outpatient care is one thing, but I’m not sure it is the silver bullet I’ve been making it out to be (and it will come with its own set of market distortions).

This entire post is me shooting from my hip. So please feel free to correct me iff I’m wrong.

Intelligent and Diligent

For whatever reason, when I was a schoolboy and first learnt of the word “diligent”, I assumed that it should be the opposite on intelligent. “Only people who are not intelligent need to be diligent”, the young I had reasoned.

And nearly thirty years later, I came across this stellar 2×2 on intelligence and diligence. I’ve read it in many places now, but will link to the version on farnam street blog. I’m copying this quote from the blog, which is apparently credited to two different military officers.

I divide my officers into four groups. There are clever, diligent, stupid, and lazy officers. Usually two characteristics are combined. Some are clever and diligent — their place is the General Staff. The next lot are stupid and lazy — they make up 90 percent of every army and are suited to routine duties. Anyone who is both clever and lazy is qualified for the highest leadership duties, because he possesses the intellectual clarity and the composure necessary for difficult decisions. One must beware of anyone who is stupid and diligent — he must not be entrusted with any responsibility because he will always cause only mischief.

Maybe I was up to something interesting back in the 1990s, even if it was rather self-serving. And maybe it is this concept I reprised in the late 2000s when I came up with “studs and fighters“. It was possibly my irritation with the “stupid and diligent” variety.

Now I’m thinking of this “stupid and diligent” 2×2 in terms of our schooling and education. Maybe there is this general feeling among parents, teachers and suchlike that intelligence is something you are “born with”, and you cannot become intelligent.

So the moment they spot a kid who is stupid and lazy, they decide that the best way to “improve” this kid is to make him/her more diligent, rather than more intelligent. In the short run this might work, since the kid is now able to do better in the school exams (which is what most teachers are optimising for). The long run effect, though, is that the kid, instead of ending up in the numerous but harmless “general staff” (stupid and lazy), ends up in the seemingly more competent but actually “dangerous, and only causing mischief” stupid and diligent quadrant.

In other words, our general schooling makes our adult population much more dangerous!

When Institutions Decay

A few weeks back, I’d written about “average and peak skills“. The basic idea in this blogpost is that in most jobs, the level of skills you need on most days (or the “average skill” you need) is far far inferior to the “peak skill” level required occasionally.

I didn’t think about this when I wrote that blogpost, but now I realise that a lot of institutional decay can be simply explained by ignoring this gap between average and peak skills required.

I was at my niece’s wedding this morning, and was talking to my wife about the nadaswara players (and more specifically about this tweet):

“Why do you even need a jalra”, she asked. And then I pointed out that the jalra guy had now started playing the nadaswara (volga). “Why do we need this entire band”, she went on, suggesting that we could potentially use a tape instead.

This is a classic case of peak and average skill. The average skill required by the nadaswara player (whether someone sitting there or just operating a tape) is to just play, play it well and play in sync with the dhol guy. And if you want to maximise for the sheer quality of the music played, then you might as well just buy a tape and play it at the venue.

However, the “peak skill” of the nadaswara player goes beyond that. He is supposed to function without instruction. He is supposed to keep an eye on what is happening at the wedding, have an idea of the rituals (given how much the rituals vary by community, this is nontrivial) and know what kind of music to play when (or not play at all). He is supposed to gauge the sense of the audience and adjust the sort of music he is playing accordingly.

And if you consider all these peak skills required, you realise that you need a live player rather than a tape. And you realise that you need someone who is fairly experienced since this kind of judgment is likely to come more easily to the player.

The problem with professions with big gaps between average and peak skills, and where peak skills are seldom called upon, is that penny-pinching managers can ignore the peak and just hire for average skill (I had mentioned this in my previous post on the topic as well).

In the short run, there is an advantage in that people with average skills for the job are far cheaper than those with peak skills for the job (and the former are unlikely to suffer motivational issues as well). Now, over a period of time you find that these average skilled people are able to do rather well (and are much cheaper and much lower maintenance than peak skilled people).

Soon you start questioning why you need the peak skill people after all. And start replacing them with average people. The more rare the requirement of peak skill is in the job, the longer you’ll be able to go on like this. And then one day you’ll find that the job on that day required a little more nuance and skill, and your current team is wholly incapable of handling it.

You replace your live music by tapes, and find that your music has got static and boring. You replace your bank tellers with a combination of ATMs and call centres, and find it impossible to serve that one customer with an idiosyncratic request. You replace your software engineers with people who don’t have that good an idea of algorithmic theory, and one day are saddled with inefficient code.

Ignoring peak skill required while hiring is like ignoring tail risk. Because it is so improbable, you think it’s okay to ignore it. And then when it hits you it hits you hard.

Maybe that’s why risk management is usually bundled into a finance person’s job – if the same person or department in charge of cutting costs is also responsible for managing risk, they should be able to make better tradeoffs.

Biennale!

I’m starting to write this at the beginning of today, as we go through the biennale.

We started with one place near the main venue where some volunteers has made some art. Some fairly trippy stuff, and some risqué stuff

Now on to today’s pertinent observations

  • This is only the fifth edition of the biennale
  • I quite love the artwork I’ve seen so far. And if not for the school I don’t think I would’ve seen all this art at all
  • Some of the art is “vaguely familiar”. And that intrigues me. The familiarity draws me in. The vagueness makes me want to keep seeing more of it. Sidhus quote about the bikini comes to mind
  • The biennale has this concept of “art mediators”. Effectively tour guides who explain the art and concepts around it. Our guide today was Safa. The comment I made about tour guides yesterday doesn’t apply to her. I’m enjoying her commentary.
  • Just now I heard another art mediator explain a piece of art that Safa had just explained. And the two are nearly orthogonal! I guess the thing with art is that it’s in the eyes of the beholder, or maybe the mediator
  • From the biennale venue (aspinwal house) you can see the kochi container port. To me, watching container ships getting loaded and unloaded is also art
  • Ok I finally have a hypothesis on what I consider as good art – something that compels me to keep looking at it. It could be stuff that is hard to interpret. It could be stuff with several dimensions. It could be things that tell a new story every time you look at them. That is the kind of art I like.
    • And so I like Paul Fernandes – so much going on in his art. And why I cut out a page from the times of india on Republic Day and pinned it on my wall
    • And so I like Picasso – it is so hard to interpret what he has done and there are so many dimensions I want to keep looking at it
    • If it gets too abstract though there is no “handle” to latch on to. And so it becomes hard to interpret
    • So far I haven’t been impressed by stuff with too much “messaging” – the message by definition makes it one dimensional and not something I want to keep seeing!
  • Art is fundamentally a “low precision low recall” activity. You can never see anywhere close to all the good art in the world (hence low recall)! Low precision because to find any good art you need to also go through a lot of art you can’t appreciate.

Ok now it’s afternoon and we’re at lunch. The post is long enough as it is and we’re done with the first session of the biennale. And I’m rather proud of the last two things I’ve mentioned here. So I’ll stop here.

Average skill and peak skill

One way to describe how complex a job is is to measure the “average level of skill” and “peak level of skill” required to do the job. The more complex the job is, the larger this difference is. And sometimes, the frequency at which the peak level of skill is required can determine the quality of people you can expect to attract to the job.

Let us start with one extreme – the classic case of someone  turning screws in a Ford factory. The design has been done so perfectly and the assembly line so optimised that the level of skill required by this worker each day is identical. All he/she (much more likely a he) has to do is to show up at the job, stand in the assembly line, and turn the specific screw in every single car (or part thereof) that passes his way.

The delta between the complexity of the average day and the “toughest day” is likely to be very low in this kind of job, given the amount of optimisation already put in place by the engineers at the factory.

Consider a maintenance engineer (let’s say at an oil pipeline) on the other hand. On most days, the complexity required of the job is very close to zero, for there is nothing much to do. The engineer just needs to show up and potter around and make a usual round of checks and all izz well.

On a day when there is an issue however, things are completely different – the engineer now needs to identify the source of the issue, figure out how to fix it and then actually put in the fix. Each of this is an insanely complex process requiring insane skill. This maintenance engineer needs to be prepared for this kind of occasional complexity, and despite the banality of most of his days on the job, maintain the requisite skill to do the job on these peak days.

In fact, if you think of it, a lot of “knowledge” jobs, which are supposed to be quite complex, actually don’t require a very high level of skill on most days. Yet, most of these jobs tend to employ people at a far higher skill level than what is required on most days, and this is because of the level of skill required on “peak days” (however you define “peak”).

The challenge in these cases, though, is to keep these high skilled people excited and motivated enough when the job on most days requires pretty low skill. Some industries, such as oil and gas, resolve this issue by paying well and giving good “benefits” – so even an engineer who might get bored by the lack of work on most days stays on to be able to contribute in times when there is a problem.

The other way to do this is in terms of the frequency of high skill days – if you can somehow engineer your organisation such that the high skilled people have a reasonable frequency of days when high skills are required, then they might find more motivation. For example, you might create an “internal consulting” team of some kind – they are tasked with performing a high skill task across different teams in the org. Each time this particular high skill task is required, the internal consulting team is called for. This way, this team can be kept motivated and (more importantly, perhaps) other teams can be staffed at a lower average skill level (since they can get help on high peak days).

I’m reminded of my first ever real taste of professional life – an internship in an investment bank in London in 2005. That was the classic “high variance in skills” job. Having been tested on fairly extreme maths and logic before I got hired, I found that most of my days were spent just keying in numbers in to an Excel sheet to call a macro someone else had written to price swaps (interest rate derivatives).

And being fairly young and immature, I decided this job is not worth it for me, and did not take up the full time offer they made me. And off I went on a rather futile “tour” to figure out what kind of job has sufficient high skill work to keep me interested. And then left it all to start my own consultancy (where others would ONLY call me when there was work of my specialty; else I could chill).

With the benefit of hindsight (and having worked in a somewhat similar job later in life), though, I had completely missed the “skill gap” (delta between peak and average skill days) in my internship, and thus not appreciated why I had been hired for it. Also, that I spent barely two months in the internship meant I didn’t have sufficient data to know the frequency of “interesting days”.

And this is why – most of your time might be spent in writing some fairly ordinary code, but you will still be required to know how to reverse a red-black tree.

Most of your time might be spent in writing SQL queries or pulling some averages, but on the odd day you might need to know that a chi square test is the best way to test your current hypothesis.

Most of your time might be spent in managing people and making sure the metrics are alright, but on the odd day you might have to redesign the process at the facility that you are in charge of.

In most complex jobs, the average day is NOT similar to the most complex day by any means. And thus the average day is NOT representative of the job. The next time someone I’m interviewing asks me what my “average day looks like”, I’ll maybe point that person to this post!

Why social media went woke

When Elon Musk took over twitter recently, one of the “drain the swamp” things he did was to get rid of the platform’s overt bias towards political correctness and “wokeness”. Out went most of the “trust and safety” team. In came Donald Trump (though he hasn’t tweeted since) and the guy who stupidly got himself arrested in Romania.

As some people in my office have never tired of saying, Musk let go of 70% of the company, and the app still largely runs fine (apart from some weird bugs that creep in once in a while). One part of twitter that is NOT running fine, though, is advertising – you might be able to guess that from the quality of ads you are getting served on your timeline nowadays. There are two theories behind this – one is that Musk got rid of most of the ad sales team, and the other is that advertisers don’t want to advertise on twitter given it is more prone to free speech now.

The latter was a bit of a surprising theory to me, since my assumption had always been that what advertisers largely care for is audiences, and relevance of the audiences to their products; and as long as the audiences were there, the advertisers would come.

However, something I heard on a podcast this morning on my way to work made me question this assumption. Listen to this (the link is from the approximate point I want you to listen):

So in this conversation, Jeff Green talks about “brand safety” in the context of advertising. What he effectively says is that advertisers are finicky about what kind of content their ads come next to. He says “right now I would say the value of user generated content has actually gone down dramatically because of brand safety”.

Back in IIMB, there were a couple of fellows who formed a quiz team called “Mary Magdalenes: The Reformed Prostitutes”. During our annual fest Unmaad, they conducted a quiz, which (I think) was sponsored by IBM. I I remember right, the title slide of the quiz said “Unmaad Open Quiz, brought to you by Mary Magdalenes: The Reformed Prostitutes”, with the logo of IBM (or whoever the sponsor was) somewhere on the slide.

The sponsors did not take to it too kindly – I was doing a quiz the following day and the sponsorship coordinators demanded to inspect my deck so that there were no such potentially embarrassing juxtapositions.

As it happens, one, or maybe both, of Mary Magdalenes: The Reformed Prostitutes, went into a career in marketing. However, contrary to the image you get by looking at advertising “creatives”, advertisers are fundamentally boring people. They are insanely risk averse, and very very loathe to bring even the slightest hint of controversy to their brands.

So, this is why social media goes woke. They don’t care about “misinformation” and “fake news” and porn and slander for the sake of you or me – as long as we are visiting their sites and looking at the ads there, they are happy. The reason they clamp down on free speech in the name of “trust and safety” is for the sake of the (normally rather boring) advertisers, who want certainty on the sort of content next to which their ads are shown.

And so, driven by risk-averse advertisers, social media platforms censor free speech and “go woke”, much to the chagrin of people like Musk and me.

Recently I read this fantastic essay by Robin Hanson on why most people are boring. Only a very long quote will do justice, but that too partially. You should read the whole essay.

If we act interesting, passionate, and opinionated in public, we are likely to seem to claim high status for ourselves, and to touch on sacred subjects, either by word or deed. And this makes us quite vulnerable to accusations of arrogance and violating the sacred. Because: a) the sacred is full of contradictions, so that saying truths clearly does not protect you, b) observers feel free to use complex codings to attribute to you intentions that you did not literally say (or have), and c) observers are much more willing to accept unfair and unproven accusations if they are seen as “punching up” at presumed dominant or evil races, genders, ages, professions, or political factions.

The degree of this danger is made clear, I think by the reaction of the “gods” among us. The public tone of huge powerful firms and other orgs is consistently “officious”, i.e., mild boring supplication.

Mild boring supplication is all okay. Just that they impose upon you and me with their ad dollars, meaning that places where their ad dollars go also tend to mild boring supplication. And thus for us, it is death by a thousand bores.

Ants and grasshoppers and mental health

There is the old fable of the ant and the grasshopper – the ant saves and saves and saves and at the end has plenty. The grasshopper splurges and splurges and enjoys and at the end has nothing. In some versions, the grasshopper dies. In others, he borrows from the ant. Most tellings of the fable don’t end well for the grasshopper.

“Be like the ant”, goes the moral of the story.

I’m not so sure if that is the right strategy for “real life”. Talking about myself, I have spent large parts of my life living like an ant, and a lot of it has not been fun. I’m not talking about money here – credit cards apart, I’m entirely debt-free, and my wife and I paid off our home loan (the only big loan I’ve taken) in a fifth of the term. That has allowed us to take risks in terms of careers, and do more interesting things, so that part of “living like an ant” I don’t regret at all.

It is more on the non-monetary fronts. I might have written about this in the past, likening it to the movie Ganesha Subramanya. The plot there is a classic ant plot – that you “need to achieve something in life” before you can find a girlfriend or get married. And various people making fun of the protagonists for this philosophy.

Quoting from my old blogpost on this:

In the two years prior to going to IIT, it had been drilled into my head that it was wrong to relax or have fun until I had “achieved my goals”, which at that point in time was basically about getting into IIT. I did have some fun in that period, but it usually came with a heavy dose of guilt – that I was straying from my goal.

In any case, I got into IIT and the attitude continued. I felt that I couldn’t relax until I had “finished my work”. And since IIT was this constant treadmill of tests and exams and assignments and grades, this meant that this kind of “achievement” of finishing work didn’t come easily. And so I went about my life without chilling. And was unhappy.

Sometimes I think this problem went away in my twenties, but now that I think deeper about it, whether I think like an ant or a grasshopper is related to my state of mind, and it is self-fulfilling. When I am feeling contented and fine (what I like to think is my “normal state”) I’m a grasshopper. I sometimes bite off too much. I want to do everything. I want to enjoy also. And sometimes that means putting off work (or “borrowing from my future time”).

However, when I’m going through a rough patch or not in the best of mental health, I suddenly go off into ant mode. I don’t want to risk going lower, so I become extra cautious. Extra caution means fulfilling my responsibilities as and when they come, and putting off the fun for later (rather than the other way round). In other words you don’t want to borrow – from your future time!

If you think of utility theory, your “happiness” (or “welfare”) as a function of your “wealth” (need not always be monetary – can be physical or mental health as well) is concave. The more wellness you have, the less the marginal utility of getting more wellness (among other things, this explains why insurance, on average, can get away with offering a lower rate of return).

Among other things, what this means is that the loss of wellness from the loss of a rupee far exceeds the gain of wellness from the gain of a rupee (and this is consistent at all wealth levels – again I’m using rupees only for convenience here). And so when you are in a bad mental state, if you are optimising for not slipping further, you will necessarily follow a low-risk policy. And you become more “anty” (and antsy, of course).

Somewhere you need to break off that cycle. Even when you are otherwise not feeling well, you need to somehow give yourself that stimulus, and that means being a grasshopper. It is a conscious effort that you need to make – that yes, your life is shit and you are not doing well, but being an ant is most likely NOT going to help you get out of it.

And slowly you transition your way out. You will realise that occasionally you CAN borrow from your future time – that maximises your overall happiness over time (while at the same time not shirking). And you start being more of a grasshopper. And so forth until you are in “ground state”.

In some way a lot of fables have their morals the wrong way around – favouring the ant over the grasshopper; favouring the hedgehog over the fox. I guess a lot of them simply haven’t aged well enough to our current context and lifestyles!