Viswanathan K's Thoughts

This blog is based on two interesting titbits from Harish Mehta’s The Maverick Effect . ~~   A surprising cameo in the NASSCOM story is the actor, Shammi Kapoor. Even though he was in his 70’s, he was connecting to the Internet (long before the Internet took off in India) to access world news. “He was an Internet enthusiast with an incredibly curious mind. He took to new technologies like a fish to water.” NASSCOM tried to enlist him to pitch the benefits of the Internet in India to bureaucrats and policy makers in government. He agreed to do it. For free. His celebrity status was a big attraction. He spoke passionately of the world it could open up, how he connected to his kids abroad via the Internet. “His personality and presentation skills helped us communicate the potential of the Internet to even bureaucrats.” ~~   In the 80’s and 90’s, there was the huge problem of terribly slow data links from the West to India. Even the laughably slow 64 kbps link could not b

NASSCOM (National Association of Software and Service Companies) is a trade association. It started by serving the needs of the still-in-infancy software companies, but has expanded to include BPO’s, R&D centers, and startups. “(NASSCOM is) India Inc brand builder, a think tank, a lobbyist group, an interventionist or more.”   This may sound like a reviled lobbying and backroom dealing entity, but as Harish Mehta writes in The Maverick Effect , back in 1988 (when NASSCOM was founded), it was a necessity. “NASSCOM was incubated at a time when it was an uphill battle to even get software recognized as a tangible product or a service, and something different from computer hardware.” Hard to even imagine such a confusion today…   Back then, the Indian body representing software companies was really a body for computer hardware companies, MAIT. MAIT treated software as the poor cousin. Mehta and a few others wondered if the only way was to form a dedicated body to represen

In Accelerating India’s Development , Karthik Muralidharan says: “The centrality of data for governance is seen by noting that the very origin of the word ‘statistics’ comes from its crucial role in managing the affairs of the state.” But India’s data systems are outdated. They are designed to track national progress, not for supporting day to day governance. The focus is on measuring visible inputs (how many schools?) rather than harder to measure outcomes (quality of education). The actual citizen’s experience is barely measured (was the service easy or convenient?).   Even worse, any data that is gathered is by the respective departments themselves. Who have a vested interest in making themselves look good. And who may not have the right data analysis or statistical skills anyway.   The lack of investment in our measurement infrastructure thus has many consequences: (1) money is spent on the wrong policies, (2) a focus on easily measured inputs instead of harder to q

Is India’s population still growing? Or does the answer vary drastically across its states? This blog is not about the political (and therefore emotional) connection of those questions to the topic of delimitation. Instead, it is about the at-times surprising answers to the questions, without the political and moralising aspects .   Rukmini S’s post presents the data on this superbly. Even without China or Sanjay Gandhi-like birth control measures, the following has happened. “There was certainly a time when India's population was growing very fast. In the three decades after Independence, India's population had doubled. But from the 1980s, population growth began to slow down.” Today, India’s population growth rate is below the global average !   Unintuitively, all states are slowing , though they slow at different rates : “Until the 1970s, population growth rates in different states were quite similar. However, since the 1980s, India's southern states have

How do we define ourselves, asks Gurwinder Bhogal? Sure, we have internal drivers and ideas, but we also temper that with feedback from others. Are we overdoing it? Is it acceptable? Are we fitting in or becoming outcasts? This approach made sense since time immemorial when the feedback we got was from a small set of people with whom we interacted regularly.   But in the age of the Internet and social media, that approach is not working, argues Bhogal. We now get feedback from people we barely know. Even the famous people we listen to online, well, what they say online may not be “indicative of who they are”.   Who doesn’t like to be popular? But popularity online carries a new risk: “They often find that their more outlandish behavior receives the most attention and approval, which leads them to recalibrate their personalities according to far more extreme social cues than those they'd receive in real life. In doing this they exaggerate the more idiosyncratic facets of

In his book, Accelerating India’s Development , Karthik Muralidharan looks at the role of bureaucrats in India’s poor public service systems. As mentioned in earlier blogs, democracy forces politicians to over-promise. To deliver on those promises, they need a capable bureaucratic system. To improve the bureaucracy, investments have to be made. But we are a poor country – so there isn’t enough money to invest. Even worse, any investments in improving the bureaucracy will take a long time to translate into visible actions, but a politician’s re-election cycle comes within 5 years, why then would a politician invest in the bureaucracy?   In addition, politicians want to have pliable bureaucrats who will do their bidding. So they have actively undermined the professionalism and capability of the bureaucracy.   A lesser-known fact is that the Indian bureaucracy is understaffed . Not a typo. As a ratio of public servants to the population, India’s ratio is lower than China’s or a We

So the American pre-polls were totally wrong. The race didn’t turn out to be “too close to call”. Instead, as Andrew Sullivan wrote: “It’s not just a Trump victory. It’s a Trump triumph.” How does he come to that conclusion? “There is, yes, a mandate. When one party wins the presidency, Senate, and probably the House, that’s usually the case.” Mandate for what? This one is easy to answer because Trump had easy to understand policy goals, unlike his opponent who seemed to have none. “Americans have voted for much tighter control of immigration, fewer wars, more protectionism, lower taxes, and an emphatic repudiation of identity politics.”   Wait, surely that last point (“an emphatic repudiation of identity politics”) can’t be true? Wasn’t Trump “whiteness personified”, as one political commentator said? Well, that’s not what the data says. Sullivan pulls up some of the relevant stats: (1) Trump won more non-white votes than any Republican since Nixon; (2) He gained massi

The West increasingly sees AI as a dangerous thing, something that is/will be used for bad things, lead to job losses and social upheaval. The extreme versions of such fears involve Terminator like scenarios where AI takes over the world.   On the other hand, India views AI as a means to solve societal problems and gaps for which the country (and thus its government) is too poor to solve. The history of how other countries solved these in the past is often proving irrelevant, like how India achieved huge telecom penetration by bypassing copper wires (history) to wireless (modern and a lot cheaper). AI is like that – it opens the door to find patterns. The Internet in general and the world of sensors that is increasingly integrated with the Internet produces voluminous data on just about everything. How longs are trucks idling at checkpoints? How long does it take for goods to move from A to B? Crunching so much unstructured data is beyond human or conventional software. AI, on the

How do advertisements work, asks Kevin Simler. The conventional theory says that ads create a positive association with the product in hand (love, happiness, attractiveness), and that association eventually nudges us into buying it.   But is that true? If it were, Simler says: “All an advertiser needs to do is show a pretty face next to Product X, and suddenly we're filled with desire for it.” Obviously, things aren’t that simple. While we aren’t perfectly rational: “Neither are we puppets at the mercy of every Tom, Dick, and Harry with a billboard.”   How then do ads work? His theories make for interesting reading. Some ads work by just creating awareness (FYI) that a certain product exists e.g. Fevicol. If that info can be provided in a memorable way, all the better. This approach works for products which are needed infrequently – the aim of the ad is to try and ensure you recall the brand when you do need such a product. Other ads work by trying to give you “ ev

Karthik Muralidharan looks at the role of politicians in the poor state of India’s governance and delivery systems in his book, Accelerating India’s Development . Again, the situation is more complex than what most believe, which is why the title of that chapter is “The Politician’s Predicament”.   To reiterate the point from an earlier blog, India’s choice of “democracy before development” has created unique “political incentives and constraints”. Voters in India can demand welfare and subsidies when India is much weaker, both economically and in government capability. (Remember, the West progressively expanded democracy as it got richer, so by the time the poor started demanding more things via the ballot box, the state had more money and capability). Sadly: “Weak state capacity contributes to vote bank politics.” How? When the state can’t deliver to all, well, it can deliver only some things to some people. In a country where most people lack the most basic of amenities,

Most of us never learnt Western history from a social perspective – how, for example, did the Western welfare state emerge? Prof. Karthik Muralidharan looks into that in his book, Accelerating India’s Development .   Long, long ago, Western governments monarchies were about one thing only – security. After all, it was a time when your neighbor could attack, defeat, loot and occupy you, and enslave or kill your inhabitants. Those were savage times.   The role of the Western state changed only with the Industrial Revolution. As production increased phenomenally, better systems were needed. Roads, ports, railways initially.   As urbanization followed industrialization (people migrated for better paying jobs from the villages), the populations of towns exploded. Sanitation and sewage systems had to be improved. These improvements in turn boosted productivity and the state’s tax revenue, which could further improve infrastructure (and yes, continue to fund the military expansionism

Karthik Muralidharan wrote this long (900+ pages) but excellent book, Accelerating India’s Development , on how to improve India’s governance. He starts by asking the question everyone laments, “Why is the Indian state (government) so ineffective at delivering core services?”   The answer is far more complex than the usual suspects. The first generation of independent India’s leaders had suffered in jail and under British rule: “(This gave them the) motivation and public trust to focus on nation-building investments because electoral success was virtually guaranteed.” As time passed, electoral success was no longer guaranteed. Inevitably then, electoral incentives changed the focus of politicians to “providing visible benefits”. Long-term good, sadly, does not fall in that category. Building new schools is visible and immediate; providing quality education is neither.   In addition, we became a democracy with universal adult franchise right at inception. No Western democr

As the US Presidential election date comes closer, the gap between Kamala Harris and Trump has reduced and they are almost neck to neck now. After the huge enthusiasm when she became the candidate (in money pouring in and in the pre-polls conducted back then), how could this have happened?   Andrew Sullivan feels the root cause is that nobody knows what she stands for: “This is the first presidential candidate who doesn’t seem to want you to know what she’ll actually do, or what she really thinks about anything much.” Normally such a candidate would have never cleared the shortlist (what the Americans call their primaries). But of course, the party never had primaries: “She is there because of a corrupt Democratic clique that hid Biden’s rapid decline until it was too late to have a real primary, then panicked at the thought of a chaotic convention, and simply anointed this hack — because no white male or female would run against a black woman and risk their political future

If decisions are so noisy, how come we rarely hear of it? The authors of Noise say: “The invisibility of noise is a direct consequence of causal thinking. Noise is inherently statistical: it becomes visible only when we think statistically about an ensemble of similar judgments.”   Further, when something is statistical, one doesn’t have a clear target what one is aiming at: “Strategies for noise reduction are… what preventive hygiene measures are to medical treatment: the goal is to prevent an unspecified range of potential errors before they occur.” They compare it the habit of washing your hands – you should do it without worrying about which particular infection you might be avoiding.   Unfortunately, such habits aren’t easy, because of the way we are wired: “Correcting a well-identified bias may at least give you a tangible sense of achieving something. But the procedures that reduce noise will not. They will, statistically, prevent many errors. Yet you will never

The government is terrible at many things. But it has also done other things extremely well. Like polio eradication and conducting elections on massive scales. Is there any pattern? Is the government good at certain types of activities? Which ones? And can it avoid the other kinds?   Pritchett and Woolcock came up with a model to analyze just those questions. It involves splitting proposed activities into a 2 x 2 grid – one axis is the action (Discretionary or Non-Discretionary); the other axis is the number of transactions involved (Huge aka Intensive or Few aka Non-Intensive):   The bottom left corner ( Policies ) is about actions that require discretion but are not done often. Examples include changing tax rates or setting eligibility criteria or location of dams. These are choices and decisions that have to be made, but since they aren’t done often, in theory , a government could use the relevant experts to make the right decision most of the time. But like any discretionary

We know that any technology or invention can be used for good or bad. The bad effect is easy to see when it is a direct consequence – guns kill, for example. Direct. But it is harder to see the bad effect when a technology or invention sets off a chain of effects, and it is the last effect that is bad.   This question in my 13 yo daughter’s History book opened my eyes to this: “How did the Industrial Revolution lead to colonialism?” The answer goes like this. The Industrial Revolution increased production tremendously while also making a lot of items affordable. This set off new needs: (1) more raw materials; and (2) new markets to sell those surplus goods. What started as exploration to find places for the above-mentioned needs eventually resulted in colonialism (Why settle for negotiated bilateral deals? Wasn’t it more advantageous to just rule those places?).   It won’t be wrong to say that the Industrial Revolution was great for the West, and terrible for the rest of

What are the common sources of noise in decision making? Well, people have selective attention, and selective recall of the information, write the authors of Noise . Information is rarely coherent, it is often conflicting, and so people pick and drop parts. Therefore, what goes into the decision varies across individuals.   People are different. Some are strict, others lenient; some are optimistic, others pessimistic. You get the idea. If that sounds like bias, you’re right – it is actually both . It’s noise too because different people have different biases. This is called “level noise” – different people have different base levels.   People makes exceptions to their own rules. They also react differently if the same problem is presented in a different context. All these variations within the same person are called “pattern noise” .   Within pattern noise, there is a subcategory called the “occasion noise” – the mood of the person can produce different decisions. The “

SoHO stands for “substances of human origin” – simply put, it refers to human organs, blood and tissues. While one can donate any of these in India, it is illegal to be paid for it. The reason behind the law making it illegal for money to change hands for such transactions was to prevent desperate folks from making donations for money, without fully understanding the risks.   Pranay Kotasthane pointed out another aspect of SoHO in India – 80% of living organ donations are by women; and 80% of recipients are men. This would seem to be because of our societal bias with women probably being pressurized to donate organs for their male relatives in need.   Does this ban on payments for SoHO have any negative consequence? First, there is a shortage of SoHO in India – one estimate says around 12,000 people die daily because of blood shortage. Inevitably, SoHO-for-cash systems have arisen – they are, of course, illegal. How many people could get blood had the law not been there? Blood

In their book titled Noise , the authors clarify that they understand why real-world decisions are so “noisy”: “Judgment is difficult because the world is a complicated, uncertain place.” However, they continue: “There is a limit to how much disagreement is admissible.” Taken too far: “System noise is inconsistency, and inconsistency damages the credibility of the system.”   Take the fact that different judges give different sentences for the same crime: “This variability cannot be fair. A defendant’s sentence should not depend on which judge the case happens to be assigned to.” Attempts to fix this by issuing guidelines for judges, which restrict the variation among judges, have been resisted by judges. Why? “After all, each case is unique, isn’t it?” Yes, the authors concede, sometimes the need for discretion is important. Their quarrel though is with all the too many cases where “variability is undesirable”. Like different premium quotes by insurance companies