The Beginning of the End (Again)

John Martin - The Great Day of His Wrath

I have noticed this pattern for years now, and I confess I am not entirely immune to it myself. The moment something starts going wrong — markets wobble, a war breaks out, banks begin to fall — conversations shift in a very predictable direction. People stop asking what might happen and start declaring what will definitely happen. And almost always, that declaration goes one way.

“This is the beginning of the end.”

There is something genuinely comforting about that sentence. It removes uncertainty. It gives the chaos a name and a direction. It makes you feel like you understand what is happening — even if what you understand is that everything is about to collapse.

I know not why we do this. Perhaps it is easier to prepare for a definite catastrophe than to live with ambiguity. Perhaps the end of the world simply makes for better conversation than its stubborn continuation. The problem, of course, is that reality has shown very little interest in cooperating with this tendency. 

Big events do change the world — let us not be naive about that. But rarely in the clean, dramatic, everything-breaks-on-Tuesday manner that our minds prefer. More often, systems bend, adapt, patch themselves up in unglamorous ways, and keep going. Not unchanged — but not unrecognizable either. 

If you are skeptical of my skepticism, consider the evidence, some of which you may recall from school textbook and most you would have erased from your memory as something that never happened.

1. The Population Bomb (1968–1985)

Hypothesis: Population growth will cause mass starvation, with hundreds of millions dying and the global food system collapsing.

Expected Date: 1970–1985

What actually happened: Population exploded. Food production grew faster. The crisis… inverted.

2. Acid Rain Will Destroy the Forests (1970s–1980s)

Hypothesis: Acid rain will destroy ecosystems — dead lakes, dying forests, irreversible environmental damage.

Expected Date: 1980s–1990s

What actually happened:  Damage appeared. Then policy, technology, and regulation quietly reduced it. 

3. The Ozone Layer Will Be Destroyed (1980s)

Hypothesis: Ozone depletion will make Earth uninhabitable — radiation spikes, ecosystem collapse Expected Date: 1990s–2000s

What actually happened: Global coordination. Montreal Protocol. Slow recovery.

4. Y2K Systemic Collapse (2000)

Hypothesis: Computer systems will fail globally, collapsing infrastructure

Expected Date: January 1, 2000

What actually happened: Nothing dramatic. Which proves either panic… or preparation.

5. Post-9/11 End of Globalization (2001–2010) 

Hypothesis: Globalization will reverse — borders harden, trade shrinks, nations retreat

Expected Date: 2002–2010

What actually happened: Security increased. Trade didn’t stop.

6. Peak Oil Collapse Narrative (2005–2015)

Hypothesis: Oil decline will end growth — energy scarcity leading to economic stagnation.

Expected Date: ~2010

What actually happened: Technology found more oil. Apocalypse postponed.

7. The Great Financial Crisis Will “Reset Everything” (2008–2012)

Hypothesis: The global system will fundamentally change — end of big banks, reckless finance, possibly capitalism itself.

Expected Date: 2009–2012

What actually happened: For a moment, it felt broken. Then intervention. Then bailouts. Then continuity.

8. Eurozone Breakup (2010–2015)

Hypothesis: The euro will collapse, fragmenting Europe.

Expected Date: 2012–2015

What actually happened: It bent. It negotiated. It survived.

9. China Hard Landing (2013–2017)

Hypothesis: China will collapse under debt, triggering global recession.

Expected Date: 2014–2017

What actually happened: China slowed. Reality declined to call it collapse.

10. COVID Will Permanently Kill Cities (2020–2022) 

Hypothesis: Cities will die — urban life ends, offices disappear.

Expected Date: 2020–2022

What actually happened: Cities paused. Then resumed.

11. Global Banking Collapse After SVB (2023)

Hypothesis: Banking crisis will spread into system-wide collapse.

Expected Date: 2023

What actually happened: A few tense days. Then intervention. Then stability.

So why does this pattern repeat? 

We are storytelling creatures. “This is the beginning of the end” is a better story than “things will continue in a complicated and mildly disappointing way.”

There are probably other reasons too. Old systems do not die easily — they adapt in ways that are too unglamorous to attract much attention. Stress forces the kind of innovation that comfort rarely would. Fear triggers interventions that were not visible before the crisis. And the distance between "this could happen" and "this will definitely happen" collapses faster than it should, in both media and in our own minds.

And the part that is easy to miss.

Pessimistic predictions are not useless. They often point to real risks, sometimes force real action. The ozone layer is arguably the clearest example — the catastrophe was not averted by luck or by the system's natural resilience, but by deliberate, coordinated human effort, and it was the warnings that made that effort possible.

But across most of these cases, the predictions consistently overestimated the speed, the scale, and the finality of collapse. Reality is slower. More stubborn. More willing to patch itself together and keep going than any good collapse narrative requires.

Things do not fall apart on schedule. They stretch, adjust, negotiate with themselves, and continue — often frustratingly so, for those who had predicted otherwise.

And now, the Iran war

Hypothesis: The Iran conflict will fundamentally reshape the global order — World War III, de-dollarization, bifurcated financial systems, persistent inflation/stagflation, fragmented globalization, shift to a multipolar world order, end of cheap energy, weaponized trade/finance. 

Expected Date: 2026–2028

The risks are real, some of these outcomes are genuinely possible. But if history is any guide — and I say this with appropriate humility — the more interesting question is not “whether the world will break?” but “How will it quietly rearrange itself, patch the damage, and keep going in ways that nobody quite predicted and nobody will fully explain until after the fact.”

Olympics 2012 - Another Perspective II

Courtesy: Geckoam

(Not) A Game of Money
Continuation of Olympics 2012 - Another Perspective I

Does rich nations play more sports? And do they win more than their poor counterparts? Let's analyze the data for answers to these questions.

GDP Per Participant:  If I have more money at disposal, I would spend more time and money on sports and hence, would rank higher in terms of number of participants and medals. A poor country which secured one medal would have done it against innumerable odds compared to a wealthy nation and should actually rank higher. Taking the wealth of the citizens into account, we can rank nations based on how many athletes it produced per dollar of their gross domestic product (GDP).

For this purpose, I used GDP at Purchasing Power Parity Per Capita instead of nominal GDP. The reason being the GDP in itself would reflect the national wealth, not general prosperity of its citizen. A per capita GDP (PPP), though not equivalent to per capita income, does reflect the wealth of citizen while adjusting for varying cost of living across geographies. Now, getting to the ranks.

Best GDP to Athlete Ratio: China - 22 USD per capita per participant.

Worst GDP to Athlete Ratio: Liechtenstein - 47,033 USD per capita per participant.

So, China produces the maximum number of participants per dollar whereas Liechtenstein, the richest participating nation, produced the least. And India? Well, India did a rather good job here, standing at 7th position, spending 45 USD per capita per participant!

Correlation Coefficient - GDP and No. of Participants: 0.2626

Does rich nations play more? Yes, they do, but poor countries do as much too. The correlation coefficient which, even though positive, is just a quarter and signifies that the correlation is not that strong. Even though sports requires money, we can play with little money as well. Next time you are told that the lack of fund is sololy responsible for the pathetic state of Indian hockey, tell them about the correlation and I bet they would still continue their rant because it is easy to understand what lack of fund means but not correlation coefficient.

GDP Per Medal: Whereas GDP Per Participant tells us about how efficienctly the nation uses its resources to promote sports, GDP Per Medal tells us about the financial efficiency in winning games. Again, just like Population Per Medal, we are comparing only the 85 nations that won any medals.

Best GDP to Medal ratio: China - 95 USD per capita per participant.
Worst GDP to Medal ratio: Qatar - 51,350 USD per capita per participant.

China did it again, winning maximum number of medals per dollar of GDP. The filthy rich Qatar did worst on GDP to medal ratio amongst the 85 countries that won any medal.

Correlation Coefficient - GDP and Medals: 0.1938

Does rich nations win more than poor folks? As it is evident from the correlation coefficient, there is little correlation between individual wealth and games won. In other words, wealthy first world countries are very slightly more likely to win games than underdeveloped countries.

Even though money is a crucial factor in playing sports, there may be other factors at play which compensate for lack of money. What are those factors? The numbers won't tell that. And what is your guess?

As the numbers talk, it is evident that there is no clear relation between performance in sports and wealth. The potential of a middle-class kid next door transforming into a sport star is only slightly less than that of wealthy folks. At least, this is what the Olympics data suggests. To know the actual probability of it and the correlation between a wealthy family and sports performance, we would need a different set of data.

Participant Per Medal: A nation can field a large number of participants. Though it does improve the probability of winning more medals, the quality of participants have a rather major role to play. In my opinion, a nation which fileded ten participants and won 5 medals should rank higher than a nation which fielded hundred participants but won only 30 medals. Here is a comparison of nations based on how many quality participant they produced worth their salt.

Best Participant to Medal ratio: Botswana, China, Iran, Jamaica, Kenya - 4 participants per medal.
Worst Participant to Medal ratio: Portugal - 77 participants per medal.

India had a participant to medal ratio of 14 and ranked 47 out of 85 medal-winning nations.

In summary, China seems to have done well whether it is about utilizing money or about producing quality participants.

Correlation Coefficient - Participants and Medals: 0.897774

Now, this is an obvious conclusion. The more the number of participants, the more the medals. However, the point to point finger would be that there is no perfect correlation between the number of participants and medals and in fact, it is a tad less than 1. What it implies is nations with higher number of participants won less medals per participant when compared to the averages.

For a detailed look on the numbers, check out the spreadsheet below.

Download Spreadsheet

Related Post: Olympics 2012 - Another Perspective I

Olympics 2012 - Another Perspective - I

Courtesy: Geograph

Number Games

Which country did best in London Olympics 2012? Does bigger countries play more sports than smaller ones? India performed its best ever in Olympics, but was it really best performance? We would try to answer all these questions with a pinch of statistics and I bet, answers will surprise you.

Olympics is an interesting event, not just from perspective of sports but also from statistical perspective as well, for example, to compare relation between sports, population, and GDP. If you take Cricket World Cup or FIFA World Cup, you get a skewed comparison because very few countries play cricket and in case of football, many countries might have competitive advantage in some other sports giving a wrong interpretation of data.

However, unlike Cricket World Cup or FIFA World Cup, we get a wider representation of countries and sports in Olympics allowing for a rather fair comparison.

Secondly, looking the medal tally, we cannot judge a nation's sports spirit because of varying factors such as population and economy. Here, I have tried to plug in those numbers and rank nations in a more justifiable way.

Finally, while the news papers are full of the wonderful performance of India and while the social media can't stop cheering the athletes even after the event is over, it is worth to introspect and find out where we actually stand and whether we are game for the games.

Let's get started with the basics stats of London Olympics 2012.

Maximum Number of Participants: Great Britain - 541 athletes
Maximum Number of Medals: United States - 104 medals
Most Populous Nation: China - 1.35 bn people
Wealthiest Nation (GDP Per Capita - PPP): Liechtenstein - 141,100 USD

Now, the more interesting (and more complex) stats.

Population Per Participant / Athlete Density: This number is the total number of participants divided by nation's population which gives an idea about how popular sports is in the given nation. In a populous country like China, there would definitely be many athletes and they would rank higher, but if you find higher density of athletes in nation, it implies people play more sports there. As the title suggests, it is simply the number of citizens out of which we would get one athlete.

Best Athlete Density: Cook Islands - 2224 people per athlete.
Worst Athlete Density: Bangladesh - 30,503,603 (3 mn) people per athlete.

What about India? It's third worst, 14,580,644 (1.4 mn) people per athlete, right above Bangladesh and DR Congo.

Correlation Coefficient - Population and No. of Participants: 0.3439

This number signifies the linear relationship between population and no. of participant of the nations, whether more populous nation field more athletes or not. The short answer is yes, they do. For the long answer, let's understand correlation coefficient first.

Basically, it tells us how two variable are related to each other. This coefficient may have value between -1 to +1. A value of -1 would mean that the variables are inversely correlated, i.e., if one goes up, the other goes down in the same proportion. Similarly, a value of +1 would mean that the variables are perfectly correlated, i.e., if one goes up, the other goes up in the same proportion. What about zero? Well, that means the variables are independent of each other and there is no correlation. Values in between -1 and +1 represents all the shades of correlation in between.

A value of 0.3439 would mean that there is a correlation, but not a perfect one (value of +1). In other words, even though populous nations have more athlete but not as much as less populous nations do when you take their populations into account. In other words, athlete density is more in less populous nations. In yet other words, people play more sports in small countries.

Population Per Medal / Performance Density: Population per participant gives us an idea about popularity of sports in each nation, but it fails to show how good the athletes are in sports. Pupulation per medal shows how good the nations are in the sports. The logic is that a tiny nation winning one medal should be ranked higher than a nation hundred times its population that has won ten medals. Here, we can only compare the 85 nations that has won medals out of the 204 participanting nations. The reason is simple, we cannot compare hair color of two bald people, can we?

Best Performance Density: Grenada - 105,000 people per medal.
Worst Performance Density: India - 201,698,903 (20.1 mn) people per medal.

What about the brouhaha surrounding India's wonderful performance? Well, looking at the athelete density and performance density, all one can make out is that it indeed is brouhaha. We are a nation of spectators and not players. We just want others to play the game and move our bums only when ordered to do so. India would definitely top the medal tally if the Olympic folks consider watching games 24/7 a serious game in itself. Until then, we gotta be content being first from the last.

Download Spreadsheet

Related Post: Olympics 2012 - Another Perspective - II

Doubt - Rene Descartes

Dubito ergo cogito; cogito ergo sum.
- Rene Descartes

Dosa and Morality - How religion fails to preach morality

Courtesy: Wikimedia 

No one likes to have dosa which is not straight out of the tava and so, no one minds to wait in queue when it is severed hot. The queue is generally a tad long for it as the entire office rushes to the cafeteria at exactly nine and they have to be served one at a time. People here are generally lazy and enjoy the conversations while in queue. However, few individuals would rather like to pass their time standing outside the queue and are at times in hurry to bypass it.

On such a Friday morning, two devoutly religious colleagues joined me at the end of such a queue.

Drunken Religion

The fact that a believer is happier than a sceptic is no more to the point than the fact that a drunken man is happier than a sober one. The happiness of credulity is a cheap and dangerous quality.

– George Bernard Shaw

Unknown Knowledge

It's better to know that we don't know rather than not to know that we don't know.

What We Read

There is a column for spirituality and a column for horoscope, but none for rationality, not one for skepticism.

Doubt to Freedom

Ubi dubium ibi libertas: Where there is doubt, there is freedom.

- Latin proverb

Enslaved in Pride

There was a most revealing rule: slaves were to remain illiterate. In the antebellum South, whites who taught a slave to read were severely punished. '[To] make a contented slave,' Bailey later wrote, 'it is necessary to make a thoughtless one. It is necessary to darken his moral and mental vision, and, as far as possible, to annihilate the power of reason.' This is why the slaveholders must control what slaves hear and see and think. This is why reading and critical thinking are dangerous, indeed subversive, in an unjust society.

Source: The Demon-Haunted World by Carl Sagan

Faith in Authority

Faith in human authorities is more dangerous compared to faith in non-existent god.

Argument

To argue with a man who has renounced the use and authority of reason, is like administering medicine to the dead.


- Thomas Paine

Identity of Fear - Why you must name your children as numerals

Courtesy: Behance Network

A body lied on the road, damaged beyond recognition, blood washed the entire width of the road. The mood was tense in the gathering. A motorist passed by, was immediately recognized as having allegiance to the community of the killer. The mob went astray chasing the innocent motorist. Sensing danger, he turned the throttle and speeded ahead. But the road was not to tolerate this speed, no sympathy it had with him or his community. He lost balance, skidded sideways going straight under the giant tires of a truck in the next lane.

Another carcase lied silently, peacefully. Death was faster than he would have ever imagined. The color of blood and the darkness of night were indistinguishable. There was silence all around, within the dead victim, among the assailants.

The group of dogs, who were furious till now, backed away calmly. Were they shocked by the death of their victim? Were they now contemplating the consequences of their act? Was the anger within the dogs overpowered by the fear of revenge, the anger that arose after one of them was run down by a motorist?

Myth of Deception

A Myth - Lying and cheating are immoral.

Deception of Knowledge

There are things we know, things we know we don't know, and things we don't know we don't know.

Irrational Rationality

Reason is, and ought to be, only the slave of the passions.
- David Hume

Unlucky Luck

Superstitions are unlucky for me.

Feeding The Fucklings

Amongst the glitter of Commonwealth Games, a piece of news that received media attention was India's 67th rank on Global Hunger Index. In its atypical ways, the media, be it print or electronic, dedicated most of its time and energy on finding where India stands compared to its peer. "India ranks below Pak, China on hunger index" dictated Times of India. Catchy headlines are not the complete information. We got to dig deeper to unearth the truth.

Wronger Than Wrong

When people thought the earth was flat, they were wrong. When people thought the earth was spherical, they were wrong. But if you think that thinking the earth is spherical is just as wrong as thinking the earth is flat, then your view is wronger than both of them put together.

Isaac Asimov in The Relativity of Wrong

Games Octopuses Play

What is more astonishing, an ugly octopus predicting all 6 games of Germany in FIFA, 2010 or me dying of ulnar hernia?

Courtesy Naim

Paul, the octopus with psychic powers, has become a celebrity after accurately predicting the results of matches involving Germany, all 6 of them. The question that arises is whether this phenomenon was worth the media attention it has got. Say, we flip a coin and it lands heads up. Will it cause hoards of mediamen coming running down with their machines? Certainly not. Its a matter of pure chance, one would say. With that insight, lets examine the odds of octopus phenomenon occurring purely out of chance.

In a match of football, there are exactly two probable outcomes, i.e., “team A wins and team B loses” OR “team B wins and team A loses.” So, the probability of predicting the outcome of a match accurately is ½ (probability equals 1/number of outcomes).

I. Probability of predicting result of Match 1 = ½

II. Probability of predicting result of Match 2 = ½

Hence, probability of correctly predicting results of Match 1 and Match 2 = I x II = ½ x ½ = ¼ (multiplication of probabilities of independent events).

So, probability of correctly predicting results of 6 matches = ½ x ½ x ½ x ½ x ½ x ½ = ¹/₆₄.

In other words, if there are 64 equally smart octopuses trying their hands at predicting all 6 matches in a row, one would eventually predict it correctly just by random chance. In yet other words, if there are 64 men/women predicting results of the games by flipping coin, one out of them would get all the 6 results correctly.

Now, lets examine the probability of me dying. According to US Social Security, the probability of death for a 16-year-old is ¹/₁₃₀₇. Compare that with the rather high probability of ¹/_64. So, it is far more improbable that I would die compared to Paul predicting all the German games.

According to common wisdom, the more improbable an event is the more attention it should harness. However, I (and you too) can be pretty sure that it is highly unlikely that even a line would be printed in the local daily on the auspicious occasion of my departure from this planet. Seems like its better to be an  ugly octopus now a days than a human.

Hope I made you think about the validity of news that we consume each day. Don't forget to carry a pinch of skepticism along.

By the way, you are not predicting the probability of me being a 16-year-old. Are you?