Society

Social Capital and Caste

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Conventional wisdom is that social capital in India is low because of our historical caste system. By placing people in a rigid hierarchy, and giving some people privileges over others just because of the families they were born into, the caste system prevented people from cooperating as well as they would in a more equitable society – that is what conventional wisdom says.

However, a point that we cannot miss is that despite the caste system placing a hierarchy on people, people from different castes did regularly cooperate and trade with each other. In fact, with caste being tied to hereditary professions, people had little choice but to regularly interact and trade with people from other castes. And this inevitably created social capital.

Putting it differently, the result of the caste system was an unequal but stable society, and this stability led to reasonably good social capital (history might be biased given it was written by people from certain castes, but we don’t see many instances of caste riots or clashes from over 200 years ago). You can think of it as a stable society with “handicaps”, where some people were privileged over others (in fact, there was a hierarchy of privilege), to the extent that it was okay for some people to abuse others in various ways.

Over the last 150 years or so, the caste system has been (rightly) challenged, and we are seeing various movements towards a more equal society. One side effect of this has been that the (unequal) equilibrium that had existed has been disturbed, leading to caste-based antagonism and a fall in social capital.

We are in the process of moving from one (unequal) equilibrium to another (more equal) equilibrium, but until we get there, existing beliefs and biases will continue to be challenged, which means some sets of people will continue to be suspicious of others, and there will be mistrust and thus low social capital.

Ambedkar on Equality

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These lines from BR Ambedkar from Annihilation of Caste on the concept of Equality, are an absolute must-read.

First, he classifies equality along three dimensions:

Equality may be a fiction but nonetheless one must accept it as the governing principle. A man’s power is dependent upon (1) physical heredity, (2) social inheritance or endowment in the form of parental care, education, accumulation of scientific knowledge, everything which enables him to be more efficient than the savage, and finally, (3) on his own efforts. In all these three respects men are undoubtedly unequal. But the question is, shall we treat them as unequal because they are unequal ? This is a question which the opponents of equality must answer. From the standpoint of the individualist it may be just to treat men unequally so far as their efforts are unequal. It may be desirable to give as much incentive as possible to the full development of every one’s powers. But what would happen if men were treated unequally as they are, in the first two respects ? It is obvious that those individuals also in whose favour there is birth, education, family name, business connections and inherited wealth would be selected in the race. But selection under such circumstances would not be a selection of the able. It would be the selection of the privileged. The reason therefore, which forces that in the third respect we should treat men unequally demands that in the first two respects we should treat men as equally as possible.

Assuming this three-fold classification of (in)equality, one can deduce what Ambedkar would have said about the contemporary demands for reservation. He would have opposed them as the groups seeking affirmative action are not disadvantaged in the first two respects. If anything, some of these groups have been the most dominant political communities in the states.

Ambedkar then gives a utilitarian reason for why we need to uphold the principle of equality.

On the other hand it can be urged that if it is good for the social body to get the most out of its members, it can get most out of them only by making them equal as far as possible at the very start of the race. That is one reason why we cannot escape equality. But there is another reason why we must accept equality. A Statesman is concerned with vast numbers of people. He has neither the time nor the knowledge to draw fine distinctions and to treat each equitably i.e. according to need or according to capacity. However desirable or reasonable an equitable treatment of men may be, humanity is not capable of assortment and classification. The statesman, therefore, must follow some rough and ready rule and that rough and ready rule is to treat all men alike not because they are alike but because classification and assortment is impossible. The doctrine of equality is glaringly fallacious but taking all in all it is the only way a statesman can proceed in politics which is a severely practical affair and which demands a severely practical test.

Quotable Quotes from Le Guin

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Ursula K. Le Guin’s The Dispossessed is an intellectual tour de force. While there are enough ideas in the book to write a full-blown thesis, I will restrict this post to highlighting two quotes that are reflective of the state of the country today, in the light of the recent spate of mob lynching.

The first quote goes thus:

Coercion is the least efficient means of obtaining order.

And the second one:

You can’t crush ideas by suppressing them. You can only crush them by ignoring them.

What do these passages tell us about tackling mob lynching?

First, is a new law, as the Supreme Court recommended in its order last week, the best way forward? A law is a blunt instrument and is coercive more often than not. Amit Varma has already written about this in a recent post, where he mentions the lack of a rule of law as being of more concern than the absence of a legal provision.

Second, are there more subtle solutions for addressing the rumours that spark a lynching than restrictions on services like WhatsApp or a blanket shutdown of internet in a region? The second passage might hold the key here. However, I would argue that the ignoring that is mentioned there cannot be passive. This is a case where there might be merit in fighting fire with fire, instead of being a firefighter.

Tourism is not a vertical

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The Sheikh Zayed mosque in Abu Dhabi is clearly inspired by the Taj Mahal.

While Shah Jehan commissioned the Taj for his wife, Sheikh Zayed wanted to ensure his mausoleum was in keeping with his self-image. The scale is grand – and this breathless piece describes its opulence: http://www.traveller.com.au/abu-dhabis-match-for-the-taj-mahal-7cnw.

The Abu Dhabi dome is larger, the minarets are twice as high, and the grounds are on a scale only possible in a sparsely populated desert kingdom.

The Macedonian marble of the Abu Dhabi mosque is a flawless, almost synthetic white, and since it has not been aged by the centuries. it sparkles against the clear blue skies of the gulf peninsula. You could take offence with the garish crystal chandeliers in the mosque; what you think of the inlay work is a matter of taste, but to my eye, the vast floral sprays on the floor and one wall are quite exquisite. And I couldn’t help noticing how absolutely clean the water in the reflecting pools is.

This cleanliness is, of course, true of the grounds, the security posts where guards clear you, the parking lots, and the sweeping drive into the mosque complex.

I couldn’t help compare this with my last visit to the Taj, barely 12 months earlier – the parking lot was littered and tacky; the toilets were leaking; the walkway was uneven and dusty; and the queues impossible. We take all of this as standard for our nation, but at the Sheikh Zayed mosque, I couldn’t help wondering why international visitors would want to come to the Taj, once word gets around how stunning the Abu Dhabi mausoleum is.

Turns out, the word is already out there – Last year, Trip Advisor rated it as the world’s 2nd favourite tourist attraction, just behind Angkor Vat, and ahead of the Taj Mahal, at No. 5. The rating was obtained by using traveler reviews over  a 12 month period, folding both quality and number of reviews into an algorithm developed for the purpose.

We can’t solve for the Taj, or any of our other heritage buildings alone. The shambolic state of our infrastructure, the shabby attitude and poor training of our security guards, the , er, cleanliness of toilets, the indifference to litter – these have all come to define our national character; increasingly, these, rather than the built heritage, will determine tourist traffic, which continues to lose out to other nations.

 

Mohit Satyanand

 

Who gains from the new Maternity Benefit Act Amendment?

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The new Amendment will harm the women working in the formal sector more than those in the informal sector.

There was a recent uproar about the new amendments were made to the Maternity Benefit Act of 1961, which extended the paid maternity leave to 26 weeks from 12 weeks. Although the move sounds positive at first glance, it holds negative repercussions for the women in the workforce.

One of the most obvious criticisms for the Act is that it would make it costly for the employer to hire women whom they would now have to give a paid leave for 28 weeks. Team Lease did a study titled “The Impact of Maternity Benefits on Business and Employment” which stated that 11 lakh to 18 lakh women will face difficulty in finding jobs in the Small and Medium Scale Industries. 

The second and the less discussed repercussion is that the amendment would impact women employed in the formal sector more than ones employed in the informal sector. There are two broad reasons. First, the formal sector is scrutinised more than the informal sector. Second, women in the formal sector are paid higher than in the informal sector. This makes the maternity leave a more expensive affair for the formal institutions.

To grasp the magnitude of the problem, we need to start with some basic facts:

  • Number of women working in the informal sector in India (2018): 90%
  • Gender pay gap in India (2017): 20%
  • The difference between the male and the female employment ratio (2017): 79% – 27% = 52%

As women in the informal sector are already cheap labour and the regulatory oversight is limited, the chances are higher than the employment rate for women in the informal sector would remain the same. Meanwhile in the formal sector, where even after the wage gap, providing a 26 week paid leave would be an expensive affair for the firm. With the formal contracts in place, the higher regulatory oversight also ensures that the employer would rather hire a male employee than overlook the new amendment. The final outcome of this would be that we will see a decline in the female labour employed in the white collar jobs, even if the status stays the same for their informal counterparts. Leaving us with the question of who is the actual beneficiary of the Act.

Instead of increasing the cost of hiring women, one of the key solutions is to make more jobs formalised. This initiative need not be just for the women. With just  6.5 per cent of the jobs formalised, the regulatory reach of the State is several limited. Increasing the formal net would allow more people to access the safety benefits provided by the state and ensure better working conditions for more people. One of the other key impacts would, of course, be that it would help empower more women to seek their rights.

Scott Alexander, Bryan Caplan and Nitin Pai on fighting crime (feat. Matt Levine)

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The basic idea is that coming down hard on a small number of high-profile crimes can have disproportionate effects in terms of curbing crime

It all started with the pseudonymous blogger Scott Alexander, in what seemed like a justification of outrage. Or maybe it started earlier – with a post by Bryan Caplan deploring outrage. Caplan was commenting about the propensity of people to jump on to bandwagons deploring seemingly minor crimes while not caring enough about worse crimes that were not in the public spotlight already. Caplan had then written:

I can understand why people would have strong negative feelings about the greater evil, but not the lesser evil. But I can’t understand why people would have strong negative feelings about the lesser evil, but care little about the greater evil. Or why they would have strong negative feelings about one evil, but yawn in the face of a comparable evil.

Now, while “Alexander”‘s response seems to justify outrage (and I’m no fan of online outrage), he did so with an interesting analogy, on how to curb crime when the police has limited resources. He writes:

[…] the police chief publicly commits that from now on, he’s going to prioritize solving muggings over solving burglaries, even if the burglaries are equally bad or worse. He’ll put an absurd amount of effort into solving even the smallest mugging; this is the hill he’s going to die on.

Suppose you’re a mugger, deciding whether or not to commit the first new mugging in town. If you’re the first guy to violate the no-mugging taboo, every police officer in town is going to be on your case; you’re nearly certain to get caught. You give up and do honest work. Every other mugger in town faces the same choice and makes the same decision. In theory a well-coordinated group of muggers could all start mugging on the same day and break the system, but muggers aren’t really that well-coordinated.

The police chief’s public commitment solves mugging without devoting a single officer’s time to the problem, allowing all officers to concentrate on burglaries. A worst-crime-first enforcement regime has 60 crimes per day and solves 10; a mugging-first regime has 30 crimes per day and solves 10.

And then it is again Caplan’s turn to respond. I’m bad at detecting satire, so I’m not sure if he is being serious (I don’t think he is). But he proposes a “sure fire way to end all crime”:

Step 1: Credibly announce that all levels of government will mercilessly prosecute the first crime committed in the nation each day.

Step 2: There is no Step 2.

But then, I’m sure that Nitin Pai is being serious in proposing a similar method to curb the spate of violent crime in India based on WhatsApp forwards. In his piece for the Quint, he writes:

the Home Ministry ought to use its considerable powers to tackle the problem. It’s not hard either. One well-advertised arrest, prosecution and sentencing will deter the cowards that comprise lynch mobs. Three high profile arrests and prosecutions – and see how quickly lynchings stop. The smallest police station in the remotest village can stop lynchings if the local sub-inspector has received clear political messages against it.

Finally, the reason why I figured Caplan’s “solution” is satire is because of this passage from Matt Levine’s excellent Money Stuff newsletter (likely it’s behind a Bloomberg paywall, but it’s free if you subscribe by email). Commenting about high frequency trading, Levine writes:

But the answer in actual U.S. market structure is, come on, there is no such thing as “the same time.” Do you know how many nanoseconds there are every single second? (A billion.) The odds that each of us would hit the “Buy” button at the exact same nanosecond are infinitesimal. So if I put in my order to buy the stock at 10:45:06.543210876 a.m., and you put in yours at 10:45:06.543210987 a.m., then I got there first and I win.

Is this a good answer? It has a simple appeal. It just gets rid of the question “who gets the stock if we put our orders in at the same time?” It replaces an economic question about how to allocate the stock with an empirical question of who got there first.

So the problem with fighting the first crime of the day, or year, or whatever, is that a criminal will know fully well, given a reasonably high enough crime rate, that the probability of his crime being recorded as the first in the year or day or whatever is less than one. And the higher the crime rate, the lower the probability that his crime will be recognised as the first one. And so there is a high chance he can get away with it.

And that is where Nitin’s idea scores. Rather than going after the “first crime”, pick a few crimes arbitrarily and “go after them like hell”. Since in this case most of the people who are forwarding dangerous forwards are “ordinary people”, this will likely shake them up, and we’ll see less of these dangerous forwards.

 

Why AI will always be biased

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Out on Marginal Revolution, Alex Tabarrok has an excellent post on why “sexism and racism will never diminish“, even when people on the whole become less sexist and racist. The basic idea is that there is always a frontier – even when we all become less sexist or racist, there will be people who will  be more sexist or racist than the others and they will get called out as extremists.

To quote a paper that Tabarrok has quoted (I would’ve used a double block-quote for this if WordPress allowed it):

…When blue dots became rare, purple dots began to look blue; when threatening faces became rare, neutral faces began to appear threatening; and when unethical research proposals became rare, ambiguous research proposals began to seem unethical. This happened even when the change in the prevalence of instances was abrupt, even when participants were explicitly told that the prevalence of instances would change, and even when participants were instructed and paid to ignore these changes.

Elsewhere, Kaiser Fung has a nice post on some of his learnings from a recent conference on Artificial Intelligencethat he attended. The entire post is good, and I’ll probably comment on it in detail in my next newsletter, but there is one part that reminded me of Tabarrok’s post – on bias in AI.

Quoting Fung (no, this is not a two-level quote. it’s from his blog post):

Another moment of the day is when one speaker turned to the conference organizer and said “It’s become obvious that we need to have a bias seminar. Have a single day focused on talking about bias in AI.” That was his reaction to yet another question from the audience about “how to eliminate bias from AI”.

As a statistician, I was curious to hear of the earnest belief that bias can be eliminated from AI. Food for thought: let’s say an algorithm is found to use race as a predictor and therefore it is racially biased. On discovering this bias, you remove the race data from the equation. But if you look at the differential impact on racial groups, it will still exhibit bias. That’s because most useful variables – like income, education, occupation, religion, what you do, who you know – are correlated with race.

This is exactly like what Tabarrok mentioned about humans being extremist in whatever way. You take out the most obvious biases, and the next level of biases will stand out. And so on ad infinatum.

Cross posted from my personal blog

Lessons from Julius Caesar – Part-II

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Note: This is the second of a two-part series on some thoughts I had after reading the play Julius Caesar. You can read the first part here. Slate’s Lend Me Your Ears podcast has an excellent episode that looks at the play from a modern context and that helped me gain some valuable perspective on this famous piece of literature. I would highly recommend listening to it if you have read the play.  

Julius Caesar is a tragedy. Characters exhibit flaws and make choices that lead to terrible consequences. It is easy to feel sorry for Caesar, who gets stabbed by his good friend, or Brutus, whose misplaced idealism comes back to haunt him (quite literally at that). But the individual I felt sorry for the most was one who had a bit part role, the poet Cinna.

In the aftermath of Mark Antony’s incendiary speech, the Romans go berserk, searching for the men who murdered Caesar. They come upon Cinna on the street and kill him because his namesake was one of the conspirators. The scene is short but shocking, but with a tinge of black humour when the crowd realises they have the wrong man but kill him regardless, justifying their action on the basis of his supposedly bad verses.

I have two thoughts on this little episode.

One, it best showcases Shakespeare’s cynicism about human reason that I touched upon in my previous post. If it was not clear already, this scene shows just how vacuous a crowd can be. The broader implications this has on a democracy and a republic cannot be ignored.

Two, it asks questions about Antony’s role in Cinna’s death. Yes, he could claim he had no intention and that Cinna’s death was an unfortunate case of collateral damage. But he was aware of the crowd’s nature and knew exactly what buttons to push to get them riled up. Shouldn’t he then bear some responsibility for his words? Or does the blame lie solely on the crowd even though their capacity to reason is stunted? These questions act as a precursor to a conversation about hate speech and how best one can prevent it while still preserving a right to free speech. That we are still having this conversation centuries after Shakespeare wrote the play shows just how vexing a problem it is.

Lessons from Julius Caesar – Part-I

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Note: This is the first of a planned two-part series on some thoughts I had after reading the play Julius Caesar. Slate’s Lend Me Your Ears podcast has an excellent episode that looks at the play from a modern context and that helped me gain some valuable perspective on this famous piece of literature. I would highly recommend listening to it if you have read the play. 

Shakespeare’s Julius Caesar is an intriguing blend of high drama, sudden bursts of violence, and impressive speeches. It is also a realistic and sombre meditation on the fragility of a republic. This fragility stems from the play’s take on human nature, which it would not be a stretch to say is a touch cynical.

Brutus, the idealistic senator and Caesar’s friend, sets great store by reason to disastrous effect. He believes that his fellow conspirators are as idealistically motivated as he is. He believes that the citizens of Rome will understand his reasons for assassinating Caesar. He is mistaken on both counts. The self-interest that propels these groups is a trait that very few individuals, like Brutus, can disavow. Left to their own devices, they will wreak havoc on society, which they do in the play to varying degrees of success.

This points towards the quality that a republic must have in order to endure, namely, that of being more than the sum of its parts. It needs to rise above the individuals who form it. And the way it can achieve this is by having institutions that channel the best of such individuals while avoiding the unsavoury bits. A republic thus lives and dies on the strength of the institutions that undergird it. This is a lesson worth revisiting every time the functioning of a republic is questioned.

Vulnerability in jobs in India

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India has been infamous for the magnitude of informal jobs in the country. Though a significant issue, informality is just a part of the bigger issue, i.e, the increase in the number of highly vulnerable jobs. Vulnerable jobs usually include own-account workers and family members working informally. Basically anyone who does not have a stable contract or flow of income, and are open to exploitation. All informal workers are vulnerable to an extent since they aren’t on any payroll or have a formal contract.

This long standing problem has become significant as the number of vulnerable employees has been increasing in the past few years. As per International Labour Organisation (ILO), 77 per cent of workers in India will have vulnerable employment by 2019. In a country where 92 per cent of the employed population is in informal sector, it is a concern if the ratio of vulnerable jobs increase.

 

Source: World Employment Social Outlook2018, International Labour Organisation

The ILO report also pointed out that

“a significant portion of the jobs created (in India) in the services sector over the past couple of decades have been in traditional low value added services, where informality and vulnerable forms of employment are often dominant.”

It is no solace that the problem is global in nature,

“Globally, the significant progress achieved in the past in reducing vulnerable employment has essentially stalled since 2012. In 2017, around 42 per cent of workers (or 1.4 billion) worldwide are estimated to be in vulnerable forms of employment, while this share is expected to remain particularly high in developing and emerging countries, at above 76 per cent and 46 per cent, respectively. Worryingly, the current projection suggests that the trend is set to reverse, with the number of people in vulnerable employment projected to increase by 17 million per year in 2018 and 2019.”

This is not a surprise as 80 per cent of the casual workers and 31 per cent of the regular/salaried workers in 2016 earned less than the national minimum wage of Rs 66 / day. If looked at on the basis of gender, 95 per cent of women working as casual labour got less than the minimal wage as against 74 per cent men. Lower wages make workers more susceptible to being caught in the low income trap. With income not enough to save and invest, people earning low wages are unable to earn or multiply their money and get stuck at living at basic sustenance levels. The only way to move from the equilibrium is by earning a higher amount and saving it.

With low income levels in the country and substantial number of informal workers, India needs to look at vulnerability within jobs as a criterion in itself while assessing jobs problem. In order improve the conditions, the jobs created in the country need to assure a certain level of stability and redressal mechanisms. More than skilling, the government needs to create avenues for job creation. A good starting point would be to modify the labour laws and reduce the cost of doing business in the country.

Indian Men and Unpaid Housework

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Diksha Madhok shared this thought-provoking graph on Twitter recently:

My first reaction to that was, ‘Really? Indian men do 19 minutes of unpaid housework every day? That’s too much! What do they do for 19 minutes?‘

That said, while the point being made is no doubt valid, the metric being used to illustrate it is off. The reason for that is that middle-class Indian couples probably do less combined unpaid housework than their Western counterparts because servants are so common. In our household, for example, we have employed a maid who comes every morning to wash dishes, clean the house and so on. In Western households, it is common to have to do it all yourself.

So the correct metric, to judge how lazy, misogynistic and/or entitled Indian men are would be the percentage of total unpaid household labour they contribute to. I have no doubt that the conclusion would be as dismal.

As for these Slovenian men, grrmph. I bet they can’t play cricket as well as us.

A Case for Unpredictability

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Researchers in Germany have created a machine learning tool that has predicted the winner of the ongoing FIFA World Cup. This tool says that Spain has a higher chance at the outset but if the Germans make it to the quarter-finals, the odds tilt in their favour.

The creation of this tool does not come as a surprise. Machine learning tools thrive at making predictions and this is just another example of a technology that has become adept at doing a task far better than humans.

However, impressive as a technology might be, there is always room to ask if it should be applied in a particular field. These were my thoughts as I read the article. It goes without saying that better predictions would be beneficial in a lot of fields, including ones like medicine and weather. But would they add value to a sport like football?

I must admit I pose this question from a philosophical bent of mind. Isn’t part of the thrill of a sport its inherent unpredictability, of the unexpected happening? Bookmakers and gamblers might beg to disagree but there is a reason why seeing an unfancied team win against all odds is deeply satisfying. Is it possible then that the invention of a machine learning tool that accurately predicts the result of every match might lessen the enjoyment of the game itself? Worse, can it contribute to a self-fulfilling prophecy where players contrive to fit the results of the prediction (of course, this means having a particularly low opinion of the free will of the human beings involved)? I do not have any concrete answers at present but this is a line of questioning worth pursuing, both for this particular application and for machine learning in general.