When it comes to movie endings, my favourite is the last scene of the classic western Butch Cassidy and the Sundance Kid. In this scene Butch Cassidy and the Sundance Kid have taken cover in a building which is surrounded by dozens of Bolivian policemen.
Both Butch and the Kid are seriously injured. Butch suggests to the Kid that after this they should move to Australia. And this is where the movie ends, in a freeze frame shot, in sepia tone, showing the pair charging out of the building they are hiding in, with all guns blazing. The Bolivian policemen are also repeatedly firing at them.
Earlier in the movie, Butch and the Kid are shown fleeing the United States where they are in trouble. They move to Bolivia because they believe that the country has a lot of gold and silver. Or as Butch says in the movie “You wouldn’t believe what they’re finding in the ground down there. They’re just fallin’ into it. Silver mines, gold mines, tin mines, payrolls so heavy we’d strain ourselves stealin’ ’em.”
But that is not how things turn out. As Duncan J Watts writes in Everything is Obvious – Once You Know the Answer “when they finally arrive (in Bolivia) after a long and glamorous journey abroad a steamer from New York, they are greeted by a dusty yard filled with pigs and chickens and a couple of run-down stone huts. The Sundance Kid is furious… “You get much more for your money in Bolivia,” claims Butch optimistically. “What could they possibly have that you could possibly want to buy?” replies the Kid in disgust.”
Things end badly for Butch and the Kid and in the last scene they are presumably killed. So was their decision to go to Bolivia a good one or a bad one? “Intuitively, it seems like the latter because it led inexorably to Butch and the Kid’s ultimate demise. But…that way of thinking suffers from creeping determinism – the assumption that because we know things ended badly, they had to have ended badly,” writes Watt.
Creeping determinism is also referred to as outcome bias. Nobel Prize winning psychologist Daniel Kahneman (he got the Nobel prize for economics) explain outcome bias in his book Thinking Fast and Slow. It is a situation in which “observers…asses the quality of a decision not by whether the process was sound but by whether its outcome was good or bad.”
Mahendra Singh Dhon, the captain of the Indian cricket team, i has become the most recent victim of the outcome bias. He has been criticized for asking Ishant Sharma to bowl the 48th over of the third one day international against Australia, which was played on October 19, 2013. Before Sharma bowled, Australia needed 44 runs to win of 18 balls. India was in the driver’s seat. In this over Sharma gave away 30 runs and India consequently lost the match.
Shashi Tharoor, the minister of state for human resources development, tweeted immediately after the match “Why Ishant & not Vinay for 48th over when VK(i.e. Vinay Kumar) had 2 left?” This is a clear case of sounding wise after something has happened or to put it more technically Tharoor was promulgating the outcome bias.
Michael Mauboussin and Daniel Callahan of Credit Suisse explain this brilliantly in a research paper titled Outcome Bias and the Interpreter – How Our Minds Confuse Skill and Luck released on October 15, 2013. They define outcome bias as a situation in which “people take outcomes into account in a way that is irrelevant to the true quality of the decision.”
This is exactly what Shashi Tharoor did when he questioned Dhoni’s decision of bowling Sharma in the 48th over. Lets look at some numbers. Ishant Sharma has played 68 matches and has conceded runs at the rate of 5.7 per over. Vinay Kumar has played 29 matches and has conceded runs at the rate of 5.7 per over (This takes into account their performance on October 19, 2013, I couldn’t find numbers for before that).
So as far as runs per over are concerned both Kumar and Sharma are on an equal footing. But what about their career averages? Sharma averages 31.36 runs per wicket whereas Kumar averages 36.25 per wicket. So I am not surprised that Dhoni went for Sharma even though Kumar also had two overs left. Given the choice he had at that point of time, bowling Sharma was a better bet than Kumar, numbers clearly show that.
Bhuvneshwar Kumar, the other fast bowler in the team, had already bowled his quota of ten. But assuming he had an over left, Sharma still would have been a better bet. A recent piece on Cricinfo pointed out that Sharma’s concedes runs at the rate of 7.38 runs per over in the last 10 overs. His average is at 24.22 per wicket. In contrast Bhuvneshwar concedes runs at the rate of 8.46 runs per over. While Bhuvneshwar is an excellent bowler during the initial overs, his bowling during the death overs, still needs to improve a lot.
This is not to defend Ishant Sharma. I personally feel he shouldn’t be in the team at all. All I am trying to say is that on October 19, 2013, Dhoni made the correct decision while bowling Ishant in the 48th over, even though India lost the match in the process.
Another factor that would have influenced Dhoni’s decision would be the fact that Sharma brought India back into the Champions Trophy final against England, by dismissing Eoin Morgan and Ravi Bopara of consecutive balls.
The moral here is that even good decisions can lead to bad outcomes. As Mauboussin and Callahan point out “Every day, people who make good decisions with bad short-term outcomes risk losing their jobs. This might include the head of a studio in Hollywood who failed to deliver a blockbuster, a chief executive officer who made a reasoned investment that soured, or a money manager with poor results for a quarter or two. The career risk in making better but bolder decisions can be too high for many professionals to handle.”
When such decisions go wrong, people who made them, are heavily criticised, as Dhoni has been And that’s because of the outcome bias. As Kahneman puts it “When the outcomes are bad, the clients often blame their agents for not seeing the handwriting on the wall – forgetting that it was written in invisible ink that became legible only afterward.”
In fact, Mauboussin and Callahan share a very interesting experiment which shows how human brains are tuned towards the “outcome bias”. This experiment was run by Jonathan Baron and John Hershey, two scholars of decision science.
In this experiment, the subjects of the experiment were told about a 25 year old man who was unmarried and had a steady job, and who had won a prize. The prize was essentially choice between winning $200 for sure or an 80% chance of winning $300 and a 20% chance of winning nothing.
The subjects were then told that the man selected the gamble. “The researchers then showed the subjects two different outcomes. In one the man won $300 and in the other he won nothing. They then asked the subjects to rate the quality of the man’s decision on a scale from 30 (clearly correct, the opposite decision would be unacceptable) to -30 (incorrect and inexcusable)…When the subjects were told that the man had won the money, they rated the quality of his decision a 7.5. When the researchers told the subjects that the man had earned nothing, they rated his decision a -6.5,” write Mauboussin and Callahan.
What does the result tell us? “These ratings are clear evidence that the outcomes deeply influenced how the subjects assessed the decision. Somehow, the subjects didn’t distinguish between two independent issues: the quality of the decision and the outcome from the decision,” explain Mauboussin and Callahan.
In fact, worse the consequence the greater is the outcome bias. The attacks carried out by al-Qaeda on the World Trade Centre on September 11, 2001, are a very good example. On July 10, 2001, the Central Intelligence Agency(CIA) came to know that al-Qaeda might be planning a big attack against the United States. “George Tenet, director of the CIA, brought the information not to President George W Bush but to National Security Advisor Condoleeza Rice. When the facts later emerged, Ben Bradlee, the legendary executive editor of The Washington Post, declared “It seems to me elementary that if you’ve got the story that’s going to dominate history you might as well go right to the president.” But on July 10, no one knew – or could have known- that this tidbit of intelligence would turn out to dominate history,” writes Kahneman.
Hence, it is always easier to be wise after the event and criticise people. But its worth remembering what Mauboussin and Callahan point out “We know that when we see an outcome and don’t know what information the decision maker had, our minds assume that good outcomes are associated with good decisions and bad outcomes are linked to poor skill.”
(Vivek Kaul is the author of Easy Money. He tweets @kaul_vivek)
The residents of the island of New Guinea first saw the white man in 1930. The white men were strangers to New Guineans. The New Guineans had never gone to far off places and most of them lived in the vicinity of where they were born, at most making it to the top of the hill around the corner. Given this, they were under the impression that they were the only living people.
This impression turned out to be wrong and the New Guineans started to develop stories around the white men who had come visiting. Jared Diamond writes in The World Until Yesterday that the New Guineans told themselves that “Ah, these men do not belong to earth. Let’s not kill them – they are our own relatives. Those who have died before have turned white and come back.”
The New Guineans tried to place the strange looking Europeans into “known categories of their world view”. But over a period of time they did come to realise that Europeans were human after all. As Diamond writes “Two discoveries went a long way towards convincing New Guineans that Europeans really were human were that the feces scavenged from their campsite latrines looked like typical human feces (i.e., like the feces of New Guineans); and that young New Guinea girls offered to Europeans as sex partners reported that Europeans had sex organs and practiced sex much as did New Guinea men.”
To the men and women of New Guinea, Europeans were what former American defence secretary Donald Rumsfeld called the “unknown-unknown”. As Rumsfeld said “[T]here are known knows; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown-unknowns-there are things we do not know we don’t know.”
People take time to adjust to unknown-unknowns, like the New Guineans did. But there are also situations in life in which individuals, institutions and even countries tend to ignore the chance of something that they know can happen, just because it hasn’t happened in the recent past or it hasn’t happened to them specifically. For such people, institutions and countries, the option tends to become an unknown-unknown even though it is not one in the specific sense of the term.
Take the case of film director Sajid Khan whose most recent movie was Himmatwala. Before the movie was released the director often said “I can’t say I am a great director but I am the greatest audience, since childhood I have done nothing other than watching films. Cinema is my life. I can never make a flop film because I make film for audience and not for myself .”
Of course this statement was right before Himmatwala released. Khan’s previous three outings as director Heyy Babyy, Housefull and Housefull 2 had been a huge success. Himmatwala fizzled out at the box office and its first four day collections have been nowhere near what was expected. As the well respected film trade website Koimoi.com points out “The numbers are too bad for a film like Himmatwala, which was expected to create shattering records at the Box Office being a ‘Sajid Khan Entertainer’ and moreover due to the coming together of two successful individuals – actor Ajay Devgn and director Sajid Khan for the first time. However, the formula didn’t work this time it seems!”
Khan’s overconfidence came from the fact that none of his previous films had flopped and that led him to make the assumption that none of his forthcoming films will flop as well. He expected the trend to continue. Khan had become a victim of what Nobel prize winning economist Daniel Kahneman calls the ‘availability heuristic’.
Kahneman defines the availability heuristic in Thinking, Fast and Slow as “We defined the availability heuristic as the process of judging frequency by “the ease with which instances come to mind.”” In Khan’s case the instances were the previous three movies he had directed and each one of them had been a superhit. And that led to his overconfidence and the statement that he can never make a flop film.
Nate Silver summarises the situation well in The Signal and the Noise. As he points out “We tend to overrate the likelihood of events that are nearer to us in time and space and underpredict the ones that aren’t.” And this clouds our judgement.
Another great example is of this are central banks around the world which have been on a money printing spree. As Gary Dorsch, Editor, Global Money Trends points out in a recent column “So far, five central banks, – the Federal Reserve, the European Central Bank, Bank of England, the Bank of Japan and the Swiss National Bank have effectively created more than $6-trillion of new currency over the past four years, and have flooded the world money markets with excess liquidity. The size of their balance sheets has now reached a combined $9.5-trillion, compared with $3.5-trillion six years ago.”
This money has been pumped into various economies around the world in the hope that banks and financial institutions will lend it to consumers and businesses. And when consumers and businesses spend this borrowed money it will revive economic growth. But that has not happened. The solution that central banks have come up with is printing even more money.
One of the risks of too much money printing is the fact it will chase the same number of goods and services, and thus usually leads to a rise in overall prices or inflation. But that hasn’t happened till now. The fact that all the money printing has not produced rapid inflation has led to the assumption that it will never produce any inflation. Ben Bernanke, the Chairman of the Federal Reserve of United States, the American central bank, has even gone to the extent of saying that he was 100% sure he could control inflation.
Mervyn King, the Governor of the Bank of England, has made similar statements. “Certainly those people who said that asset purchases would lead us down the path of Weimar Republic and Zimbabwe I think have been proved wrong ,” he has said. What this means is that excess money printing will not lead to kind of high inflation that it did in Germany in the early 1920s and Zimbabwe a few years back.
King and Bernanke like Sajid Khan are just looking at the recent past where excess money printing has not led to inflation. And using this instance they have come to the conclusion that they can control inflation (in Bernanke’s case) as and when it will happen or that there will simply be no inflation because of money printing (in King’s case).
As Albert Edwards of Societe Generale writes in a report titled Is Mark Carney the next Alan Greenspan “King’s assertion that because the quantitative easing(another term for money printing) to date has not yet produced rapid inflation must mean that it will never produce rapid inflation is just plain wrong. He simply cannot know.” Nassim Nicholas Taleb is a lot more direct in Anti Fragile when says “central banks can print money; they print print and print with no effect (and claim the “safety” of such a measure), then, “unexpectedly,” the printing causes a jump in inflation.” Just because something hasn’t happened in the recent past does not mean it won’t happen in the future.
People who make economic forecasts are also the victims of what we can now call the Sajid Khan syndrome. They expect the recent trend to continue. The Indian economy grew by 8.6% in 2009-2010 and 9.3% in 2010-2011. And the Indian politicians and bureaucrats told us with glee that the Indian economy had decoupled from the world economy, which was growing very slowly in the aftermath of the global financial crisis.
Montek Singh Ahluwalia, the deputy chairman of the Planning Commission is a very good example of the same. In a television discussion in April 2012, he kept insisting that a 7% economic growth rate for India was a given. Turns out it was not. The Indian economy grew by 4.5% in the three months ending December 31, 2012. Ahluwalia was way off the mark simply because he had the previous instances of 8-9% rate of economic growth in his mind. And he was projecting that into the future and saying worse come worse India will at least grow by 7%.
It is not only experts who become victims of the Sajid Khan syndrome taking into account events of only the recent past. In the aftermath of September 11, 2001, when aeroplanes collided into the two towers of the World Trade Centre, many Americans simply took to driving fairly long distances, fearing more terrorist attacks.
But driving is inherently more risky than flying. As Spyros Makridakis, Robin Hograth and Anil Gaba write in Dance with Chance – Making Your Luck Work for You “In 2001, there were 483 deaths among commercial airline passengers in the USA, about half of them on 9/11. Interestingly in 2002, there wasn’t a single one. And in 2003 and 2004 there were only nineteen and eleven fatalities respectively. This means that during these three years, a total of thirty airline passengers in America were killed in accidents. In the same period, however, 128,525 people died in US car accidents.” Estimates suggest that nearly 1600 deaths could have been avoided if people had taken the plane and not decided to drive,.
So what caused this? “Plane crashes are turned into video images of twisted wreckage and dead bodies, then beamed into every home on television screens,” write the authors. That is precisely what happened in the aftermath of 9/11. People saw and remembered planes crashing into the two towers of the World Trade Centre and decided that flying was risky.
They just remembered those two recent instances. What they did not take into account was the fact that thousands of planes continued to arrive at their destinations without any accident like they had before. So most people ended up concluding that chances of dying in an aeroplane accident was much higher than it really was.
The same logic did not apply to a car crash. As the authors write “Car crashes, on the other hand, rarely make the headlines…Smaller-scale road accidents occur in large numbers with horrifying regularity, killing hundreds and thousands of people each year worldwide…We just don’t hear about them.” And just because we don’t hear about things, doesn’t mean they have stopped happening or they won’t happen to us.
Another version of this is the probability of dying due to a terror attack. As Kahneman writes “Even in countries that have been targets of intensive terror campaigns, such as Israel, the weekly number of casualties almost never came close to the number of traffic deaths.”
A good comparison in an Indian context is the number of people who die falling off the overcrowded Mumbai local train network in comparison to the number of people who have been killed in the various terrorist attacks in Mumbai over the last few years. The first number is higher. But its just that people die falling off the local train network almost everyday and never make it to the news pages, which is not the case with any terrorist attack, which gets sustained media coverage sometimes running into months.
To conclude it is important to look beyond the recent past and ensure that like Sajid Khan and others, we do not fall victims to the Sajid Khan syndrome.
The article originally appeared on www.firstpost.com on April 4, 2013.
(Vivek Kaul is a writer. He tweets @kaul_vivek)