Astrologers, Homeopaths & Economists

Astrologers, homeopaths and economic forecasts cannot be trusted because the so-called science they practice is fuzzy at best and hocus-pocus at worst.

Consider, for instance, this delightful anecdote recounted by a senior journalist at a popular Mumbai-based newspaper. Sometime in 1998 or 1999, he wrote on his Facebook wall, the hugely popular astrologer Marjorie Orr took a break. Fearing a backlash from readers, his editor suggested the young man, along with two of his colleagues, ghost write the column until Orr got back to work. Some trepidation later, he got down to follow orders. He did it for six weeks until the astrologer got back from her vacation. Not a single reader from the newspaper’s erudite, English-speaking community wrote in with an angry word that his predictions were off the mark.

The post attracted a barrage of amused comments from other journalists who’ve ghosted for popular astrologers like Peter Vidal in Indian newspapers. Vidal apparently recycles his column by replacing the text for one star sign with something he’s written in the past for another star sign. Most people don’t notice. Then there is Panditji from Jaipur who misses his deadlines every once a while and the poor sub-editor at the desk had to think up “good" days of the week, “lucky" colours to be worn and “numbers to bet on" for each star sign.

“The trick," wrote this veteran desk hand at the magazine in response to the Facebook post, “was to make people believe they were on the verge of a quantum leap in life."

Then there is homeopathy: Generous column inches are devoted to it in newspapers and magazines, and practitioners make a pretty damn good living out of it. The premise around which this tub of crock continues to exist — in spite of a mountain of evidence to prove homeopathy is indeed crock — is that water molecules have memory. 

But even Class VIII students exposed to elementary chemistry and concepts like Avogadro’s number know water molecules have no memory. This is because by then, they are taught the mechanics of dilution. Whatever botanical compound goes into making a homeopathic drug is diluted to an extent that there would be no trace of the molecule left in the drug — except the sugary coating made of powdered lactose, of course.

In homeopathic parlance, on average, most compounds are diluted by 30C. That is 10 to the power of 60, or one followed by 60 zeroes.

To understand how much of a dilution that is, imagine a drop of water with a diameter of 150 million km — the distance from the earth to the sun. It takes light eight minutes to travel that distance. Now imagine a drop of water with one molecule of a substance in it. That is a 30C dilution. 

It is entirely possible that Samuel Hahnemann, who thought up modern homeopathy, had figured he’d gotten it all wrong in the face of this evidence. That is perhaps why he continued to argue water has memory and that even after dilution of the kind he propagated, water retains a “spirit-like" essence of the original compound that is “no longer perceptible to the senses".

Ben Goldacre writes sardonically in his superb book Bad Science: “If water has a memory, as homeopaths claim…water has been sloshing around the globe for a very long time, after all, and the water in my body as I sit here typing in London has been through plenty of other people’s bodies before mine. Maybe some of the water molecules sitting in my fingertips as I type this sentence are currently in your eyeball. Maybe some of the water molecules fleshing out my neurons as I decide whether to write ‘wee’ or ‘urine’ in this sentence are now in the Queen’s bladder (God bless her): water is the great leveler."

Both of these disciplines are similar to another perverted discipline—economic forecasts. It draws from the worst of astrology and homeopathy. While the chances of getting a prediction right using astrology are as good as flipping a coin, homeopathic remedies are no better than placebos where there is no relationship between cause and effect. But economic forecasting relies on both of these to get by and there are suckers by the millions buying into them.

To sift through why economic forecasting is fraught with inconsistencies, Nate Silver’s outstanding book, The Signal and the Noise is a good place to start. He argues this discipline faces three fundamental challenges:

“First, it is very hard to determine cause and effect from economic statistics alone. Second, the economy is always changing, so explanations of economic behaviour that hold in one business cycle may not apply to future ones. And third, as bad as their forecasts have been, the data that economists have to work with isn’t much good either."

To get a sense of how difficult this really is, let’s consider the most reliable data we have on the US economy (because it is the most closely tracked). The US government puts out 45,000 indicators each year and private data providers track as many as four million statistics. Since World War II though, they have witnessed only 11 recessions. How in the world is anybody to choose 11 outputs specifically from the data on hand that caused these recessions?

By way of example, consider the maxim “co-relation does not imply causation". What it means is that just because two variables have a statistical relationship with each other, it does not mean one is responsible for the other. For instance, Silver points out, ice cream sales and forest fires are related because both occur more often in summers. But there is no causation. You don’t set off a bush fire in some desert when you buy a tub of ice cream.

On the face of it, there seem to be three reasons why economic forecasts go horribly wrong. The first is arrogance on the part of a large majority of economists. The Economic Cycle Research Institute (ECRI), based out of New York and London, is widely respected. In 2011, the firm predicted double-dip recession, which is a recession followed by a short recovery and leading into another recession.

When quizzed on the prediction, the firm threw up a lot of data that seemed incomprehensible to most people and obfuscated it with jargon that made no sense. Like this: “ECRI’s recession call isn’t based on just one or two leading indexes, but on dozens of specialized leading indexes including the US Long Leading Index…to be followed by downturns in the Weekly Leading Index and other shorter-leading indexes. In fact, the most reliable forward-looking indicators are now collectively behaving as they did on the cusp of full blown recessions." 

Silver tracked their approach to a stance articulated to their clients as far back as 2004: “Just as you do not need to know exactly how a car engine works in order to drive safely, you do not need to understand all the intricacies of the economy to accurately read those gauges." 

When looked at from this prism, the only thing that matters is data and more complex data—and not even an attempt to get to the story. “There were certainly reasons for economic pessimism in September 2011—for instance, the unfolding debt crisis in Europe—but ECRI wasn’t looking at those. Instead, it had a random soup of variables that mistook co-relation for causation," concludes Silver.

The second reason economic forecasts are notoriously difficult to handle is that the society and the systems they try to predict are dynamic. Nobel Prize winner  F.A. Hayek, in his acceptance speech in 1974, had explained why these systems are difficult to deal with.

Physical scientists can observe and measure the things that drive systems they are studying. But society, and therefore, the economy, is not a physical system. There are millions of variables that cannot be measured or seen. For instance, how will an individual respond to a set of stimuli in a given set of circumstances? There are no universal answers.

But economists, in their attempt to be rigorous, infuse techniques and models used by physical scientists. This is fundamentally flawed because in doing that, they have to ignore that which cannot be measured, in spite of it being integral to economics. The outcomes are incorrect predictions and actions that can harm society.

The third is that humans and the institutions they build are inherently biased. As an experiment, Silver conducted economic polls across organizations that engage in forecasting. Given the same data, he figured that the lower an entity’s reputation, the wilder its predictions. And if your reputation in the markets is higher, chances are your estimates are conservative.

The dichotomy is explained by the fact that if your reputation is on the lower side, you have little to lose. So perchance you hit bull’s eye, the chances of drawing attention is higher. If reputation is high on the other hand, there is an incentive to protect it and you’d much rather err on the side of caution.

Perhaps these are the reasons why Ezra Solomon, an influential US economist and professor at Stanford University, once caustically said: “The only function of economic forecasting is to make astrology look respectable."

This piece was originally published in Mint on Dec 05, 201

Homeopathy, astrology & economic forecasts

Astrologers, homeopaths and economic forecasts can’t be trusted. Because the so-called science they practice is fuzzy at best and hocus-pocus at worst.

Consider, for instance, this delightful anecdote recounted by a senior journalist at a popular Mumbai-based newspaper. Sometime in 1998 or 1999, he wrote a few days ago on his Facebook wall, the hugely popular astrologer Marjorie Orr took a break. Fearing a backlash from readers, his editor suggested that the young man, along with two of his colleagues, should ghost write the column until Orr got back to work. Some trepidation later, he got down to following orders for six weeks until the astrologer got back from her vacation. Not a single reader from the newspaper’s erudite, English-speaking community wrote in with an angry word that his predictions were off the mark.

The post attracted a barrage of amused comments from other journalists who’ve ghosted for popular astrologers like Peter Vidal in Indian newspapers. Vidal apparently recycles his column by replacing the text for one star sign with something he’s written in the past for another star sign. Most people don’t notice. Then there is Panditji from Jaipur who misses his deadlines every once a while and the poor sub-editor at the desk had to think up “good” days of the week, “lucky” colours to be worn and “numbers to bet on” for each star sign. “The trick,” wrote this veteran desk hand at the magazine in response to the Facebook post, “was to make people believe they were on the verge of a quantum leap in life.”

Then there is homeopathy: generous column inches are devoted to it in newspapers and magazines, and practitioners make a pretty damn good living out of it. The premise around which this tub of crock continues to exist—in spite of a mountain of evidence to prove homeopathy is indeed crock—is that water molecules have memory.

But even Class VIII students exposed to elementary chemistry and concepts like Avogadro’s number know water molecules have no memory. This is because by then, they’re taught the mechanics of dilution. Whatever the botanical compound that goes into making a homeopathic drug, it is diluted to an extent that there would be no trace of the molecule left in the drug—except the sugary coating made of powdered lactose, of course.

In homeopathic parlance, on average, most compounds are diluted by 30C. That is 1060 , or one followed by 60 zeroes. To understand how much of a dilution that is, imagine a drop of water with a diameter of 150 million km—the distance from the earth to the sun. It takes light eight minutes to travel that distance. Now imagine a drop of water with one molecule of a substance in it. That is a 30C dilution.

It is entirely possible that Samuel Hahnemann, who thought up modern homeopathy, had figured he’d gotten it all wrong in the face of this evidence. That is perhaps why he continued to argue water has memory and that even after dilution of the kind he propagated, water retains a “spirit-like” essence of the original compound that is “no longer perceptible to the senses”.

Ben Goldacre writes sardonically in his superb book Bad Science: “If water has a memory, as homeopaths claim…water has been sloshing around the globe for a very long time, after all, and the water in my body as I sit here typing in London has been through plenty of other people’s bodies before mine. Maybe some of the water molecules sitting in my fingertips as I type this sentence are currently in your eyeball. Maybe some of the water molecules fleshing out my neurons as I decide whether to write ‘wee’ or ‘urine’ in this sentence are now in the Queen’s bladder (God bless her): water is the great leveler.”

Both of these disciplines are similar to another perverted discipline—economic forecasts. It draws from the worst of astrology and homeopathy. While the chances of getting a prediction right using astrology are as good as flipping a coin, homeopathic remedies are no better than placebos where there is no relationship between cause and effect. But economic forecasting relies on both of these to get by and there are suckers by the millions buying into them.

To sift through why economic forecasting is fraught with inconsistencies, Nate Silver’s outstanding book, The Signal and the Noise is a good place to start. He argues that this discipline faces three fundamental challenges: “First, it is very hard to determine cause and effect from economic statistics alone. Second, the economy is always changing, so explanations of economic behaviour that hold in one business cycle may not apply to future ones. And third, as bad as their forecasts have been, the data that economists have to work with isn’t much good either.”

To get a sense of how difficult this really is, let’s consider the most reliable data we have on the US economy (because it is the most closely tracked). The US government puts out 45,000 indicators each year and private data providers track as many as four million statistics. Since World War II though, they have witnessed only 11 recessions. How in the world is anybody to choose 11 outputs specifically from the data on hand that caused these recessions?

By way of example, consider the maxim “co-relation does not imply causation”. What it means is that just because two variables have a statistical relationship with each other, it does not mean one is responsible for the other. For instance, Silver points out, ice cream sales and forest fires are related because both occur more often in summers. But there is no causation. You don’t set off a bush fire in some desert when you buy a tub of ice cream.

On the face of it, there seem to be three reasons why economic forecasts go horribly wrong. The first is arrogance on the part of a large majority of economists. The Economic Cycle Research Institute (ECRI), based out of New York and London, is widely respected. In 2011, the firm predicted double-dip recession, which is a recession followed by a short recovery and leading into another recession.

When quizzed on the prediction, the firm threw up a lot of data that seemed incomprehensible to most people and obfuscated it with jargon that made no sense. Like this: “ECRI’s recession call isn’t based on just one or two leading indexes, but on dozens of specialized leading indexes including the US Long Leading Index…to be followed by downturns in the Weekly Leading Index and other shorter-leading indexes. In fact, the most reliable forward-looking indicators are now collectively behaving as they did on the cusp of full blown recessions.”

Silver tracked their approach to a stance articulated to their clients as far back as 2004: “Just as you do not need to know exactly how a car engine works in order to drive safely, you do not need to understand all the intricacies of the economy to accurately read those gauges.”

When looked at from this prism, the only thing that matters is data and more complex data—and not even an attempt to get to the story. “There were certainly reasons for economic pessimism in September 2011—for instance, the unfolding debt crisis in Europe—but ECRI wasn’t looking at those. Instead, it had a random soup of variables that mistook co-relation for causation,” concludes Silver.

The second reason economic forecasts are notoriously difficult to handle is that the society and the systems they try to predict are dynamic. Nobel Prize winner F.A. Hayek, in his acceptance speech in 1974, had explained why these systems are difficult to deal with.

Physical scientists can observe and measure the things that drive systems they are studying. But society, and therefore, the economy, is not a physical system. There are millions of variables that cannot be measured or seen. For instance, how will an individual respond to a set of stimuli in a given set of circumstances? There are no universal answers.

But economists, in their attempt to be rigorous, infuse techniques and models used by physical scientists. This is fundamentally flawed because in doing that, they have to ignore that which cannot be measured, in spite of it being integral to economics. The outcomes are incorrect predictions and actions that can harm society.

The third is that humans and the institutions they build are inherently biased. As an experiment, Silver conducted economic polls across organizations that engage in forecasting. Given the same data, he figured that the lower an entity’s reputation, the wilder its predictions. And if your reputation in the markets is higher, chances are your estimates are conservative.

The dichotomy is explained by the fact that if your reputation is on the lower side, you have little to lose. So perchance you hit bull’s eye, the chances of drawing attention is higher. If reputation is high on the other hand, there is an incentive to protect it and you’d much rather err on the side of caution.

Perhaps these are the reasons why Ezra Solomon, an influential US economist and professor at Stanford University, once caustically said: “The only function of economic forecasting is to make astrology look respectable.”

First Published in Mint on Dec 5, 2014. Copyrights rest with HT Media Ltd

Big Data and the India Story

Distance provides perspective. I figured that on the airplane back home to Mumbai earlier last week after a short trip through the Middle East. I was mandated to talk to a select audience behind closed doors about the India story. 

The reason I was among those invited was because for two years now, my colleague N.S. Ramnath and I have been researching the ecosystem evolving around Project Aadhaar. Between the both of us, we have been interviewing multiple sets of people and asking questions like what does this means for India, what may the geopolitical implications of it all be, how should people think about it and why does it attract such fierce reactions from people. One of the outcomes of this research is intended to be the first in a series of books that Founding Fuel has commissioned.

On the back of primary research and conversations with people who hold diverse points of view, I felt compelled to assert when on stage that it is true that multiple hiccups in the project exist. For instance, there is much political bickering over which party must be seen as the one that gave legitimacy to Project Aadhaar. Then there are government departments falling head over heel over to please those in power and make it mandatory that citizens link their accounts to this identity number, by a deadline that sounds out of whack, if they need uninterrupted access to services. 

It is inevitable then that civil society raise their voice. In any case, making it mandatory violates the spirit of Project Aadhaar. That is because it was originally crafted on the back of what technologists call a “consent architecture”. Simply put, it ought not to be imposed on anyone or made mandatory. That is also why I believe the judiciary will step in at some point. 

That is also what makes me optimistic about the outcomes of Project Aadhaar, and the precedents it can set for the world to follow on how must an individual’s fundamental right to privacy be protected in the longer run. 

Why? Because when examined deeply, Project Aadhaar combines, on the one hand, the idealism of people like Richard Stallman, whom I have had philosophical differences with in the past, and on the other hand, the pragmatism of Linus Torvalds. Between the both of them, they made open source software, collaboration and Linux palatable propositions. Google, for instance, has Linux at its heart and most mobile phones in the world are powered by Linux at their cores. 

Men like Stallman have always argued that some things like art, music and software must be “free”. Free like freedom, not free like free beer—as he likes to put it. It took me a long while wrap my head around his ideas.

It is much the same thing with Aadhaar and India Stack. That is why it was not difficult to figure why questions from the audience were fast and furious. While there, I thought it was because they were stunned by the audacity of attempting to provide a unique identity to over 1.3 billion people. If I were an outsider, I would have felt much the same way too. 

Before we dwell on the “India” story, what about the other story?

Most Americans I spoke to while in the Middle East—all of whom were from the diplomatic corps and CEOs of various entities—are terribly embarrassed about their president, Donald Trump. So much so that one of the key speakers who was part of the former president Bill Clinton’s administration, served as an advisor to President Barack Obama, and is now part of a global lobbying group, went on to paint a dismal picture of the US. That is why he said he is among those who are at work to initiate impeachment proceedings around Trump’s presidency. 

Then there is the China story. I continue to wonder: how does China continue to grow at a scorching pace? What can India do to catch up? Some Chinese officials and diplomats based out of Beijing condescendingly nodded their heads at my naivety for imagining all is well there. 

In conversations over dinner, and on the sidelines, they suggested the China story is a hyped one. And that the truth does not get reported. The stories we read are on the back of numbers vetted by the state apparatus. I pushed some, whom I thought may be amenable to open up, and asked what they think real growth rates are like. Nobody seemed to know—but in their reckoning, China is in a recession. But no one is willing to say that in the public domain in as many words. Instead, it is couched as a question on whether or not China may be headed into one.

As for those in the UK and Europe, they seem utterly devastated at how things have come to such a pass. British diplomats articulated their concerns over how wretched the economy looks. And those from Germany and other parts of Europe suggested they had never imagined a time would come when Europe would reach the impasse it has. Through their eyes, they cannot comprehend why Indians want to migrate to their part of the world.

In the Middle East, where we were having these conversations, local diplomats thought it a good place to have a picnic. But when heavy lifting is called for, the big boys from the White House swing into action and issue instructions on what is to be done. But everyone is acutely aware that they live in a filter bubble, and that the gleaming glass facades do not represent the political and economic morass the region has descended into. 

Multiple fissures between various kingdoms exist, power struggles between them have to be mediated upon, economic battles are being fought in the region, and new sources of revenues for each kingdom must be thought up because oil wells have practically dried up. 

That is why many seemed most curious about India and what I had to say. On the one hand, their newspapers are gushing about “this thing you guys are implementing called Aadhaar and India Stack”. Then on the other hand, reports emanating from India argue it is part of a larger conspiracy on part of the Indian government to “snoop on its citizens”. 

What sense are they to make of it?

My submission is this. That, much like my understanding of what a lovely place the US and Europe is basis rosy pictures painted on multiple media platforms, Aadhaar and India Stack as reported from India is also a badly reported story.

By way of example, many critics argue the system isn’t a perfect one because it excludes potential beneficiaries from the system. The most recent cases of pig-headed officials throwing the rule books at the underprivileged in Jharkhand to deny them subsidies is a case in point. But this argument must be scrutinized. 

Unlike most developed democracies where every citizen is conferred with a unique identity, like a Social Security Number (SSN), for instance, in the US, the Indian system is such that people can acquire multiple identities. 

If perspective may be needed, it is entirely possible to subvert the current ecosystem and tax assesses can acquire multiple Permanent Account Numbers (PAN). Incidentally, those who are taxed live at the top of the economic pyramid in India. They live in a country called India One with a population of 180 million people on the outside. But because those who live in this country can acquire multiple identities, one of the many outcomes in unreliable data. Add to this ingenious accounting practices and people can get away without paying taxes. An undesirable outcome of this is a low tax base. By the government’s admission, the latest numbers have it that a little over 22 million people filed tax returns in India. How, and where, did the others disappear? 

It doesn’t stop at that those living in the country that is India One get away without paying taxes, but exploit loopholes in the system to acquire multiple identities to appropriate benefits that may otherwise accrue to those who really need it and live in India Two and Three. 

It is entirely possible that somebody appropriated the identities of those in Jharkhand and kept the subsidies that were due to them. Our ground reporting has shown this is indeed possible. Officials on their part can go the extra mile and throw every rule book to cover their backside.

I can go on and on—but to plug leakages of these kinds, the surest place to begin with is confer every citizen with a unique identity that cannot be duplicated and that benefits be transferred directly. 

That said, it is also inevitable that when technology is deployed at such scale, some will get excluded. Those who have worked on the system ground up are cognizant of these issues and are at work to plug the loopholes and will follow Moore’s Law—that technologically-driven systems will improve exponentially every 18 months. This law has stood the test of time for 50 years now. 

Then there are those who argue that while Aadhaar may be a good way to deliver subsidies, what is the case to link it to PAN cards? I think both are connected. Enhancing state capacity to implement a progressive tax system gives it additional resources to spend on safety nets for the poor.

To that extent, the conversations Ramnath and I have had suggest that this is a model of development unique to India and one that is evolving. The significance of the data it generates must be looked at through the eyes of an underprivileged Indian citizen. 

As for the much-amplified debate around privacy, these are stories that come without an understanding of the technical architecture of the project. Here again, Ramnath and I believe the regulatory authorities and the Supreme Court will intervene and cut past the bluster. I’ll come to that in a bit and try to illustrate why they must do it urgently. Government departments must be reminded they are in office to run a marathon for the people of India—and not running a sprint to please those in power.

The economic case for data

The American model of wealth creation is capitalism. This is of the kind where winner takes all. But it is a brutal one that leaves those at the middle and bottom of the pyramid to fend for themselves. To give the system credit though, this economic system has created spectacularly successful entities like Facebook, Amazon, Netflix, Google (or the FANG quartet, if you will) and Uber. The problem with this system now though is that wealth is concentrated in the hands of a few. 

Then there is capitalism of the kind practiced in Western Europe. It tries to walk the middle path between naked capitalism on the one hand and social markets on the other hand. On paper, all of us like it. But it cannot be scaled. Basis trips through Western Europe and multiple conversations with friends with whom I spend time when there, I have witnessed first-hand the exasperation writ on their faces at the kind of taxes they pay. When past their prime, in their reckoning, what the state provides them by way of welfare isn’t in line with what they spent busting their backsides off. If they’d done as much time in the US, they’d have paid far less in taxes, and may have been better off. 

In Eastern Europe, on the other hand, a part of the world through which I have again had a chance to travel through extensively and interact with people, I have friends who live a brutal life. When looked through their eyes, the Western European model looks like a good one. Work five days a week, get paid leave, the state takes care of you when unwell, and life is good. On their part, the Americans who live at the middle and bottom of the economic pyramid seem to concur too.

But when looked at from the eyes of the Chinese authorities, models like these work in the US and Europe because the governments there deal with a barely a few hundred million people at most. They have no clue what it is like to manage a country that has in excess of a billion people. 

In their mind, to get things to work in China, everything must be imposed. That is why they issue orders without any qualms. The authorities there thought the American quartet of FANG and Uber are not good for China. And that they must create their own ecosystem and narrative to dominate the world. The outcome is a model that has created formidable creatures like Baidu, Alibaba and Tencent (BAT). It is now a trinity that is challenging FANG. 

As for Indians, another bunch of over a billion people, they seem to look like poor cousins who see the FANG quartet and the BAT trinity as creatures worth emulating. But like I said earlier, the FANG quartet was created in a free market where winner takes all. And the BAT trinity is imposed on the back of orders. 

Emerging evidence suggest both are flawed. In a country like India where the population is as dense as it is, inequality as high, and the political system is a democracy, neither will a winner-takes-all-model work nor can a top-down approach be imposed.

Consider the constraints, to begin with, from a geopolitical prism. The FANG quartet and Uber in the US are private enterprises. It is inevitable then that the winner keeps all. This includes the platforms they build, the data that emerges from it, all value that accrues out of it—including the money and the data that resides on it. It is a free market. In a BAT trinity, the state decides and the masses comply. So, both of these are options that don’t sound viable.

But India seems to be uniquely placed in that civil society is loud and vibrant. It is also uniquely placed in that it will not allow any private enterprise to dominate public discourse—nor will it allow the state to impose its authority on the people. 

Between these two stories, there is another narrative taking shape. It traces its roots to the idealism of Stallman, the pragmatism of Torvalds and lessons learnt from mistakes made in the US and China. The outcome of which is a model called India Stack, of which Aadhaar is one component.

To understand what India Stack means, imagine a lovely highway. If the government builds one, that development around it will happen is inevitable. But to drive a vehicle on it though, you need to have a license. In much the same way, India Stack is a digital highway. How you choose to build a business on the highway is open to your imagination. To use this highway though, you need a unique identity—and that is your Aadhaar number. 

The intent behind building his “digital highway” is because unlike other parts of the world where “highways” exist to deliver public services and goods to people, what exists in India is something that is either broken or non-existent. To get 1.3 billion people into a formal economy, plug leakages of all kinds, and deliver seamless services, smart solutions lie in adopting the digital route. 

Now, the thing with all platforms (or highways, if you will) built using digital technologies is that it is prized because it contains data about people. Minus data, it is worth nothing. 

What has gone unreported about India Stack is that this framework is a unique one. It allows citizens to own their data and port it to another “highway”, or from one platform to another—an idea that no private entity or government is comfortable with. Not just that, business models are being tested around this idea—all of which are uniquely Indian ones and can be exported to other parts of the world.

We, the people of India

What lends legitimacy to this platform now is that the Supreme Court of India has ruled that privacy is a fundamental right of every Indian citizen. If the architecture of India Stack, of which Aadhaar is the unique number you are identified by, is followed in letter and spirit, this is an easy order to comply with. 

By way of example, let’s say, you apply for a loan. The bank doesn’t know your name. Why does it need to know you name after all? All it needs to know is whether you are eligible for a loan or not. To do that, it needs to access some documents and your credit history. Convention has it that your presence is needed at the bank and documents be presented. 

In the proposed dispensation, only a number needs to be presented at the bank. This can be sent digitally and you may permit the bank to see the documents it may need to view to examine your credit history. If they think it good enough, they can go ahead and process your application. You have the latitude to offer your document to multiple banks at once as well so they can bid for your business. Process done, you can withdraw permissions for them to look at your data again.

What India has to now decide is that if privacy is indeed a fundamental right, then if I decide to move from, say Facebook, to some other platform, can Facebook retain my data from the past? If Indian authorities rule that Facebook (or any entity for that matter) cannot retain my data from the past, and that it belongs to me, the business models of these entities will have to be re-looked at. As things are, it is built on the back of what it knows about me from the past. 

To cite another instance, if you own a fitness tracking device and you stop using the device, the device will not just have to stop tracking your activities, but must hand over your data from the past as well to you. It will then know nothing about you. This is privacy in its purest sense.

On his last visit to Bengaluru, when Bill Gates heard of this, he remarked, “This can kill Facebook.”

When articulated in as many words, the idea sounded unsettling to the Americans, alien to the Europeans, and had those from the Middle East wondering whatever may the implications of all this be. 

I had to leave it at that as an Indian, I stand at an inflection point. Because the issue on hand here is, while the Supreme Court has ruled in favour of privacy as a fundamental right, there is no taking away from the fact that much work remains to be done.

By way of example, as things are, you and I live in the Wild West and much of our future depends on what call the regulatory authorities take. If some more perspective may be needed on why this is the Wild West, the other day, for instance, I saw an ad by a leading financial services company that has just gotten into offering personal loans as well. Until now, it has done very well for itself. The ad claimed if I share my Aadhaar number with them, it can check the backend and tell me in an instant if I am eligible for a loan or not. No paperwork. 

This sounded very disconcerting. All my research has suggested Aadhaar has a very narrow scope. It is a “foundational identity number”. All it does is to tell the other party “I am whom I claim to be”. 

It contains no other information. If they want more details about my name, address, gender and date of birth, they can ask me for those details. I may consent to allow them to view that data stored in an electronic locker called the DigiLocker for a specific period of time. But they cannot download the data, copy it, or disseminate it. That is the how India Stack is architected. So, if anybody suggests they can tell me I am eligible for something basis my Aadhaar number, either their promise is a false one or my research is off the mark. 

Curiosity got the better of me and I clicked the link. A page opened that asked for my mobile number. A one-time password (OTP) was sent to authenticate if the number indeed belonged to me. That done, a page opened up that prompted me to share personal details like where do I live, how much do I earn, and other such assorted things. I filled in some random details. 

When done with sharing, a minute or so later, a screen popped up to suggest I am not eligible for a personal loan. Fair enough. I’m not eligible. That is the company’s call. 

But the larger question here is: what happens to the data it collected about me, from me? It went beyond prompting for my Aadhaar number. Instead, it used my naiveté to use Aadhaar as a tool to willingly part with details about me it may otherwise not have access to. There was no caveat or fine print on what the company plans to do with the data. Will it trade in the data? 

Turns out, it already has. A few hours later, a direct sales agent (DSA) representing a large private bank called me on my mobile phone to pitch a personal loan. And ironically enough, another DSA representing the bank I have my primary account with called to offer me a personal loan and a pitch to open an account as well. The offerings they had was tailored basis the data I had shared a while ago. 

Surely this is proof that my data has been “traded” in violation of the spirit of Aadhaar and India Stack? Regulatory authorities must grapple with the issues on hand. Can I sue the firm that traded my data?

That is why I am keen to hear what the final report of the Srikrishna Committee has to recommend. Ramnath and I believe this report will find its way to the Supreme Court, which in turn may have to rule on the fine print. 

There is much at stake here and I desperately want to the Supreme Court of India to rule in my favour. I don’t want my fundamental right to privacy to remain just on paper. I want to have the latitude in a democracy to move the court and sue an entity that traded my data for a few pennies in the open market. It has compromised me.

Between the Srikrishna Committee and the Supreme Court, I hope they will protect my rights as a citizen of a free country. If they do that, it will have a significant bearing on not just protecting my fundamental rights as a citizen, but to business models that will emerge out of India.

Even as all of these conversations carried on, I had my eye on the gentleman who had delivered the address about Trump’s shenanigans. He was surrounded by many who wanted to talk to him. On his way out, I managed to follow him through the lobby, introduced myself and asked if I may have a word with him. He heard me out for a while, the implications of Aadhaar, the potential of India Stack as a threat to the FANG quartet and its potential implications on big American businesses. I thought I could hear something go off in his head. He got the import of what I was trying to say.

He gave me his business card with his co-ordinates on it, introduced me to his press attaché and suggested we speak on the phone at a later date. This is the kind of thing that has much at stake for too many people across the world. Fingers crossed, the Supreme Court will rule in favour of the people of India.

First published in Mint in December 2017. Copyrights with HT Media

Why not to trust homeopathy, astrology & economic forecasts

Astrologers, homeopaths and economic forecasts can’t be trusted. Because the so-called science they practice is fuzzy at best and hocus-pocus at worst.

Consider, for instance, this delightful anecdote recounted by a senior journalist at a popular Mumbai-based newspaper. Sometime in 1998 or 1999, he wrote a few days ago on his Facebook wall, the hugely popular astrologer Marjorie Orr took a break. Fearing a backlash from readers, his editor suggested that the young man, along with two of his colleagues, should ghost write the column until Orr got back to work. Some trepidation later, he got down to following orders for six weeks until the astrologer got back from her vacation. Not a single reader from the newspaper’s erudite, English-speaking community wrote in with an angry word that his predictions were off the mark.

The post attracted a barrage of amused comments from other journalists who’ve ghosted for popular astrologers like Peter Vidal in Indian newspapers. Vidal apparently recycles his column by replacing the text for one star sign with something he’s written in the past for another star sign. Most people don’t notice. Then there is Panditji from Jaipur who misses his deadlines every once a while and the poor sub-editor at the desk had to think up “good” days of the week, “lucky” colours to be worn and “numbers to bet on” for each star sign. “The trick,” wrote this veteran desk hand at the magazine in response to the Facebook post, “was to make people believe they were on the verge of a quantum leap in life.”

Then there is homeopathy: generous column inches are devoted to it in newspapers and magazines, and practitioners make a pretty damn good living out of it. The premise around which this tub of crock continues to exist—in spite of a mountain of evidence to prove homeopathy is indeed crock—is that water molecules have memory.

But even Class VIII students exposed to elementary chemistry and concepts like Avogadro’s number know water molecules have no memory. This is because by then, they’re taught the mechanics of dilution. Whatever the botanical compound that goes into making a homeopathic drug, it is diluted to an extent that there would be no trace of the molecule left in the drug—except the sugary coating made of powdered lactose, of course.

In homeopathic parlance, on average, most compounds are diluted by 30C. That is 1060 , or one followed by 60 zeroes. To understand how much of a dilution that is, imagine a drop of water with a diameter of 150 million km—the distance from the earth to the sun. It takes light eight minutes to travel that distance. Now imagine a drop of water with one molecule of a substance in it. That is a 30C dilution.

It is entirely possible that Samuel Hahnemann, who thought up modern homeopathy, had figured he’d gotten it all wrong in the face of this evidence. That is perhaps why he continued to argue water has memory and that even after dilution of the kind he propagated, water retains a “spirit-like” essence of the original compound that is “no longer perceptible to the senses”.

Ben Goldacre writes sardonically in his superb book Bad Science: “If water has a memory, as homeopaths claim…water has been sloshing around the globe for a very long time, after all, and the water in my body as I sit here typing in London has been through plenty of other people’s bodies before mine. Maybe some of the water molecules sitting in my fingertips as I type this sentence are currently in your eyeball. Maybe some of the water molecules fleshing out my neurons as I decide whether to write ‘wee’ or ‘urine’ in this sentence are now in the Queen’s bladder (God bless her): water is the great leveler.”

Both of these disciplines are similar to another perverted discipline—economic forecasts. It draws from the worst of astrology and homeopathy. While the chances of getting a prediction right using astrology are as good as flipping a coin, homeopathic remedies are no better than placebos where there is no relationship between cause and effect. But economic forecasting relies on both of these to get by and there are suckers by the millions buying into them.

To sift through why economic forecasting is fraught with inconsistencies, Nate Silver’s outstanding book, The Signal and the Noise is a good place to start. He argues that this discipline faces three fundamental challenges: “First, it is very hard to determine cause and effect from economic statistics alone. Second, the economy is always changing, so explanations of economic behaviour that hold in one business cycle may not apply to future ones. And third, as bad as their forecasts have been, the data that economists have to work with isn’t much good either.”

To get a sense of how difficult this really is, let’s consider the most reliable data we have on the US economy (because it is the most closely tracked). The US government puts out 45,000 indicators each year and private data providers track as many as four million statistics. Since World War II though, they have witnessed only 11 recessions. How in the world is anybody to choose 11 outputs specifically from the data on hand that caused these recessions?

By way of example, consider the maxim “co-relation does not imply causation”. What it means is that just because two variables have a statistical relationship with each other, it does not mean one is responsible for the other. For instance, Silver points out, ice cream sales and forest fires are related because both occur more often in summers. But there is no causation. You don’t set off a bush fire in some desert when you buy a tub of ice cream.

On the face of it, there seem to be three reasons why economic forecasts go horribly wrong. The first is arrogance on the part of a large majority of economists. The Economic Cycle Research Institute (ECRI), based out of New York and London, is widely respected. In 2011, the firm predicted double-dip recession, which is a recession followed by a short recovery and leading into another recession.

When quizzed on the prediction, the firm threw up a lot of data that seemed incomprehensible to most people and obfuscated it with jargon that made no sense. Like this: “ECRI’s recession call isn’t based on just one or two leading indexes, but on dozens of specialized leading indexes including the US Long Leading Index…to be followed by downturns in the Weekly Leading Index and other shorter-leading indexes. In fact, the most reliable forward-looking indicators are now collectively behaving as they did on the cusp of full blown recessions.”

Silver tracked their approach to a stance articulated to their clients as far back as 2004: “Just as you do not need to know exactly how a car engine works in order to drive safely, you do not need to understand all the intricacies of the economy to accurately read those gauges.”

When looked at from this prism, the only thing that matters is data and more complex data—and not even an attempt to get to the story. “There were certainly reasons for economic pessimism in September 2011—for instance, the unfolding debt crisis in Europe—but ECRI wasn’t looking at those. Instead, it had a random soup of variables that mistook co-relation for causation,” concludes Silver.

The second reason economic forecasts are notoriously difficult to handle is that the society and the systems they try to predict are dynamic. Nobel Prize winner F.A. Hayek, in his acceptance speech in 1974, had explained why these systems are difficult to deal with.

Physical scientists can observe and measure the things that drive systems they are studying. But society, and therefore, the economy, is not a physical system. There are millions of variables that cannot be measured or seen. For instance, how will an individual respond to a set of stimuli in a given set of circumstances? There are no universal answers.

But economists, in their attempt to be rigorous, infuse techniques and models used by physical scientists. This is fundamentally flawed because in doing that, they have to ignore that which cannot be measured, in spite of it being integral to economics. The outcomes are incorrect predictions and actions that can harm society.

The third is that humans and the institutions they build are inherently biased. As an experiment, Silver conducted economic polls across organizations that engage in forecasting. Given the same data, he figured that the lower an entity’s reputation, the wilder its predictions. And if your reputation in the markets is higher, chances are your estimates are conservative.

The dichotomy is explained by the fact that if your reputation is on the lower side, you have little to lose. So perchance you hit bull’s eye, the chances of drawing attention is higher. If reputation is high on the other hand, there is an incentive to protect it and you’d much rather err on the side of caution.

Perhaps these are the reasons why Ezra Solomon, an influential US economist and professor at Stanford University, once caustically said: “The only function of economic forecasting is to make astrology look respectable.”

First Published in Mint on Dec 5, 2014. Copyrights rest with HT Media Ltd

Beginner's Guide to Irrational Behavior

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For all you Dan Ariely fans, here's a treat. Duke University is offering A beginner's guide to irrational behavior, free on Coursera. The course starts today, is eight weeks long, and from what I can make of it, well worth all the time and effort you spend on it.

I just signed up for it. 

Allow me a bit of chest thumping. I'd interacted with him on email end 2010. The outcome of that interaction was a lovely essay, The truth about cheating that I published in my earlier stint at Forbes India.