Lotteries are also known as “stupidity tax”; a nod to their improbable odds. In India, lotteries are often run by state governments – its an easy way to cover for their budget deficits. What these governments don’t realize is that they are fueling an addiction.
But what are the reasons behind this addiction? In the article, I talk about the behavioral science of lotteries.
Lotteries generate many ‘near misses’ thus making people believe that she is a winner even when she has lost, thus inducing a a dopamine fueled craving. I also talk about the incorrect application of ‘regression to the mean’ mental model, and how governments make it easy for someone to rationalize their lottery addiction.
India is often referred to as the diabetes capital of the world, with around 41 million people living with diabetes in 2007, and projected to reach 68 million by 2025. In one of our engagements we were trying to understand how people living with diabetes manage this disease. One of the perplexing observations was that many people had the belief that their diabetes is under control. This conflicts with most data and expert opinion which suggests that majority of diabetes cases are uncontrolled.
We were trying to understand the source of this belief and started interviewing close family members of patients. One of the most interesting factors that we heard when we spoke to family members of these patients was that these patients “prepared” themselves before going for a blood glucose test. A week before they get their blood sugar tested, they would change their lifestyle – they would exercise, go for walks and control their diet. So when testing happens they get a more favorable result than their actual condition. It looks so irrational that people would cheat themselves into believing that their condition is better than it actually is, thereby putting themselves at risk of not getting the right treatment.
What explains this seemingly irrational behavior? Why would intelligent people who are aware of the dangers of the disease that they have, not want to know the truth and provide their physician with more accurate data for better decision making?
One of the moderators of decision making is the kind of mental models that people create in life that helps them simplify the world. While this is often great to improve efficiency of decision making, it could be deadly if used in the wrong context. A very popular example of a mental model being used in the wrong context is in the case of diarrhea. As Sendhil Mullainathan explains in this video, 35-50% of the mothers in Rural India think that they should reduce fluids if their child has diarrhea. They use an intuitive mental model of a leaky bucket – that you should not pour water into a leaky bucket if it has to stop leaking. This makes diarrhea, something that can be easily managed to the status of a deadly condition.
In the case of diabetes, the mental model that patients have is that one should not to fail a test. People look at each blood test as a test of how well they are managing their condition, thereby framing the issue as a judgment on their own capabilities. And not one that objectively measures the status of their condition and as an input into a treatment regimen that would help their doctor take better decisions.
How do we address such a condition? Breaking mental models is often a high-investment long-term game. One of the approaches that we take at Final Mile is to see how one can work with existing mental models rather than fight it. In this case, simply by encouraging people to adopt HbA1C instead of a spot test can help address this behavioral issue and get a more accurate measure of their condition. It is a simple intervention, but one that addresses the inherent risks of misdiagnosis. The other intervention is to address how doctors and counselors frame the test – it is important that patients do not see this as a test that they fail or pass but one that helps calibrate the medication for a chronic condition.
Around 400 people lose their lives on Indian roads every day. In order to reduce this death count and improve road safety, we need to identify the root causes and then determine solutions. Accurate data capture is critical for this.
The road incident data in India is collected through local police and recorded in FIRs (First Information Report) at the police stations. The investigation reports from the local police stations are sent to the State Governments, who in turn send their report to the Central Government. The police data is used in publishing annual reports of ‘Accidental Deaths and Suicides in India’ and ‘Road Accidents in India’ by two government organizations, National Crime Records Bureau and Ministry of Road Transport and Highways respectively.
Data collected by the police could be subjective as it depends on how the police personnel interpret and ascribe reasons for the incident during investigation at the site. A motor vehicle collision could happen due to faulty road design, pedestrian’s fault, driver’s fault, poor visibility and many other reasons, but more often than not, the driver is blamed. To address this bias and to make crash investigation more objective, an effective and efficient data collection system should be in place.
The route patrolling team (RPT) is usually the first responder for incidents on national or state highways. They record the details of the incidents – the people involved, vehicles involved, cause and type of the incident, date and time of the incident, etc. Because of their ‘first responder’ status, many a times, RPT data forms the basis for the police report. For our Road Safety projects, we designed Crash Investigation Form for the RPT (route patrolling team) with a goal of making the form more objective.
To illustrate the problem of subjectivity, let us look at some examples from our Road Safety projects.
While interacting with a truck driver involved in an incident, the driver revealed that he lost control as he was blinded for a second due to glare of headlights in the opposite lane and rammed into the median opening structure. The RPT classified the cause of this incident as ‘driver was sleepy.’
In another incident, the car driver (admittedly over-speeding) said that in order to avoid running into an auto trying to cut across at the median opening, he turned his vehicle and rammed into the highway guardrail. While investigating the incident, the RPT concluded the reason as ‘driver was over-speeding.’
In both these incidents, the actual causes were ignored – glare in the first incident and a vehicle trying to cut across at high speed in the second incident. We realized that many a times, the RPT interpret the cause of the incident and prepare the report accordingly rather than objectively recording the information, resulting in skewed data and misrepresentation of the incidents.
We redesigned the Crash Investigation Form to nudge the RPT to capture the details in sequence and to hold off analysis of the cause of the incident till the very end of the report. Collecting details like ‘position of the vehicle(s)’ [Fig 1] before and after incident and ‘vehicle damage status’ [Fig 2] is crucial in identifying the cause of the incident and person responsible for the incident.
Also, capturing incident details is a monotonous process due to which the person collecting data might fail to focus on specific details resulting in skewed data. We designed the Crash Investigation Form with visuals [Fig 3] to make the data collection process more engaging, self explanatory and easy.
A new incident recording format for the police has been approved and introduced recently by the Transport Research Wing, Ministry of Road Transport & Highways, Government of India. This report is intended to minimize subjectivity while recording the incident details and to arrive at the actual cause of the incident by capturing the technical details like road surface and traffic control systems in place at the incident site. Will this new format aid the police personnel in accurate collection of crash data and minimize subjectivity?
To begin with, it could be difficult for few police personnel to understand and remember terms like ‘staggered junction,’ ‘four arm junction’ ‘paved/unpaved surface,’ etc., (even though workshops are planned to train the police) while filling the details at the incident site. The process to arrive at the ‘cause of the incident’ in the new format could have been more analytical by capturing details like ‘position of the vehicle(s) before and after incident’ and ‘vehicle damage status’ – this is very crucial as solutions/preventive measures depend on the cause of the incidents. The text-heavy report could also have been made easier with illustrations to aid data-capture and reduce monotony. All these aspects might eventually result in incorrect data collection negating the purpose of designing a new format.
For an unbiased and accurate data collection, it is imperative that the Incident Recording Form should be comprehensive, yet easy to understand; visually more engaging; and follow a sequence in data collection with an objective approach in determining the cause of the incident.
P.S. Only few sections from the Crash Investigation Report designed by us have been published here for reference.
FinalMile works on a number of road safety projects where we are tasked with reducing incidents on highways. A key part of the work is discussions with the safety team and road users. When we ask them to narrate incidents they have seen or been in, many would say, “I was in an accident” or “I saw an accident.” Oxford Dictionary defines‘accident’ as ‘an unfortunate incident that happens unexpectedly and unintentionally.’Is it apt to call all the road incidents, ‘accidents?’
The word ‘accident’ is misleading because accident is something that just happens and is unintentional, whereas most crashes happen because of a bad decision made by a driver on the road. Even the crashes that happen due to over-speeding, distracted driving, or driving under influence (DUI) are referred to as accidents. When a driver responsible for a crash says “it was an accident,” what is implied is this: “I did not intend to do it” or “it was unavoidable” even though it was an active decision/choice made by the driver to over-speed, drive when drunk or text while driving. It is the same when a pedestrian jaywalks or crosses without looking. Calling them ‘accidents’ removes the active role the driver or the pedestrian played.
According to the National Crime Records Bureau (NCRB) report, during the year 2014 in India, 4,50,898 road collisions resulted in 1,41,526 deaths. As per the report, 47.9% of these fatalities were due to over-speeding, 41.5% were due to dangerous/careless driving and overtaking, 5.3% due to poor weather conditions, 2.8% due to mechanical defect and 2.6% due to DUI. If we exclude the fatalities that happened due to poor weather conditions and mechanical failure, 92% of the fatalities were due to driver’s error.
Also, based on a data studied by National Highway Traffic Safety Administration (NHTSA) of US, 94% of the collisions are due to driver’s error. Around 20 years ago, the US Department of Transportation initiated a campaign to eliminate the use of word ‘accident,’ and police departments of New York City and San Francisco have replaced the word ‘collision’ for ‘accident’ while filling out collision reports. According to USNational Highway Traffic Safety Administration, ‘changing the way we think about events, and the words we use to describe them, affects the way we behave. Motor vehicle crashes and injuries are predictable, preventable events. Continued use of the word “accident” promotes the concept that these events are outside of human influence or control. In fact, they are predictable results of specific actions.’
It is not just about control during the event. Language affects the chain of reasoning far beyond the event. People have a more general tendency to attribute their own behavior to situational factors and other’s behavior to dispositional factors – a social bias known as the “fundamental attribution error.” Attribution theory helps us to understand why, in case of a crash, the driver attributes his fault to situational factors such as poor visibility or another vehicle, while ascribing behavior of the other driver to dispositional factors such as reckless/wrong side driving or over-speeding. The word ‘accident’ aids in ascribing the reason of the crash to external factors and makes it easy to rationalize. When the crash is clearly attributable to driver’s error, by calling it an accident, the driver is being excused for his negligence and unsafe behavior.By referring to the crashes as accidents where the driver was not following the posted speed limits, manoeuvring dangerously on the road, or getting behind the wheel drunk, we are not holding the person responsible for the act. It is not that someone has to be blamed or held responsible for every crash, it is to make drivers more responsible and realize that crashes do not happen randomly.
The word ‘accident’ is very colloquial and it is a difficult task for sure to bring about the change in our system, but replacing it with ‘crash’ or ‘collision’ would be the first step to change our perception towards road safety.
The video on how the passengers of the Emirates plane that met with an accident at Dubai airport behaved, holds major lessons on how humans behave at times of high risk.
The foremost reaction to any risk by most humans is denial, unless the risk is very salient. Even with the best of information humans are not capable of evaluating the risk levels of most situations. This optimism bias in times of risk can lead to a ‘business as usual’ attitude and resultant behaviours that are inadequate and inappropriate for an emergency situation.
From the video it is clear that many passengers, instead of rushing to the nearest exit and heading for the escape chute, are more focused on opening the overhead lockers and carrying cabin luggage and laptops with them. In that process, they are causing the biggest hurdle for an evacuation process – blocking of the main aisles. One can hear passengers reassuring each other that nothing critical has happened, and there is no need to worry. The feeling of danger is low in the voices and faces of passengers and there is no sense of urgency in their movements (so much so, that someone has taken his mobile to capture all this!). Then in the 55th second of the video, one hears the voice that is presumably of the flight attendant. In a raised tone, they repeatedly ask passengers to leave their bags and jump out of the plane. Immediately (and finally!) the passengers sense the emergency of the situation that we can hear fellow passengers rushing others to leave the bags behind and get out of the plane as fast as possible. Some are even seeking God’s help. Evacuation now happens at the right pace, in the right manner.
One can be complacent that all the passengers of this Emirates flight got out of the plane in time and that all are safe. But this was clearly a near-miss incident. One cannot be oblivious of some critical mistakes that happened, which could have led to a major disaster. The right behaviour expected of the passengers is – as soon as an emergency evacuation is signalled, all should realise that a dire mishap has occurred, and respond by immediately rushing to the nearest exit, leaving behind their belongings locked in the overhead storage. Instead, in this incident, it is only in the 55th second of the video that people stopped bothering about their bags and laptops and did what was required to do in order to save their lives and the lives of other passengers. The trigger for this change in behaviour of the passengers came from the flight attendant’s tone of voice and the content of the instructions. Which then makes one curiously ponder – why couldn’t have this intervention from the flight attendants happened 55 seconds earlier?
Human beings by nature are overconfident and tend to ignore most risks unless otherwise the proof of risk is very salient. In several situations, more so in emergency situations, the overconfidence of humans should be deflated to generate the right action in them. Merely communicating the information about a risk will not achieve this. Instead, communication about risk should be embedded with right levels of emotions. Humans are driven to immediate action only when there is a FEELING of risk. The first 55 seconds of the video clearly shows that the feeling of risk prevalent inside the airline was inadequate for an emergency situation of this kind.
During emergencies, every second counts. And humans will continue to behave as irrationally as seen here. Therefore, the critical inquiry required from this occurrence is: What can the airline industry learn about human behaviour from this incident? What in the inflight attendants’ training need to be altered, so that they generate the adequate feeling of risk in these emergency situations, which will refrain the passengers behaving either complacent or too panicky? What is the right script and tone of voice should flight attendants use, to initiate the right action among passengers, in emergencies like this? Finally, what is the ideal communication strategy to convey risk that will motivate humans to take appropriate action even a second earlier?