Nudging down theft of bicycles and from parked vehicles

Nudging down theft of bicycles and from parked vehicles

Hugh and Liz had just bought a new house. They had wanted to upgrade to a larger house for many years and now decided on an area to move to. Before moving home, they looked at the crime rates, schools for their children, local amenities for shopping, and things to do. The house seemed perfect so there was no hesitation in arranging the move. In the weeks following moving in to their new home they received all the usual junk mail, most of which went straight into the bin. One of the leaflets that they received through their letterbox was a leaflet saying to remember to check that they have locked their car, Hugh and Liz thought that was a nice a reminder and continued with their day.

Nudges are small, cheap and subtle modifications of choice architecture (i.e., changing a default option to the most favourable outcome) that can be used to help an individual make a better decision. Thaler and Sunstein published the idea of using nudging in the highly influential book ‘Nudge’ in 2008. Recently Richard Thaler has gone on to win the Nobel Memorial Prize in Economic Sciences for his work on nudging.

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Nudging has been used to aid decision-making in many ways. In crime prevention nudging has helped to reduce thefts from parked vehicles (Roach et al., 2016). A pilot study in County Durham in the North of England between September 2015 and October 2015 investigated how nudging can be implemented to reduce thefts from cars. Firstly, Roach and colleagues examined the reasons for cars being left insecure finding that there are three reasons: i) forgetting to securely lock a car whilst going into a shop, ii) forgetting to lock a car on one’s driveway, and iii) forgetting to lock a car outside or adjacent to one’s property. They choose four target areas (2 x experimental and 2 x control) and tailored their nudging technique to the local demographic. One of the basic principles of nudging is that nudging is more effective when the message is tailored (i.e., worded or presented) to the recipient. Leaflets were distributed with simple messages saying to “Take care of your vehicle” and “More than 1/3 of thefts in your area involve unlocked cars. Why? Because it’s ….. EASY.” The results of this found a significant reduction in thefts from cars because reminding car owners to lock their cars reduced the number of opportunities for thieves. In the two experimental areas there were reductions of 33% and 25% in crime compared to the crime statistics of the last 3 years.

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Another type of theft that nudging has aided in reducing is bicycle theft (Johnson et al., 2008; Nettle et al. 2012). In countries and cities where cycling is a popular past-time and way of commuting bicycle theft can be a major problem. Police statistics indicate that in England and Wales between April 2011 and May 2012 there were 115,905 bicycles thefts. Traditional interventions to tackle theft include (i) registering bicycles with local police forces, ii) improving bicycle parking facilities, and iii) improvements to bicycle locks and how they are applied. On average CCTV surveillance cameras alone only reduce crime by 7% (Nettle et al. 2012).

Simply placing small stickers depicting how to secure the lock correctly on parked bicycles has been an effective way in reducing bicycle theft (Sidebottom et al., 2009). A second nudging intervention at university locations found that placing signs with ‘watching eyes’ (an image of a pair of eyes) near bicycle stands reduced bicycle theft levels (Nettle et al., 2012). These signs decreased bicycle theft by 62% over 12 months.

We have seen that nudging can be used as a subtle technique to tackle crime rates. Nudging can take the form of small, cost-effective interventions such as distributing leaflets (Roach et al., 2016), strategically placing stickers (Sidebottom et al., 2009) and placing ‘watching eye’ signs near bicycle stands (Nettle et al., 2012). So like, Hugh and Liz moving into their new house if you receive a leaflet through the post simply reminding you to lock your car it may that nudging is being subtly used to reduce crime.

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Hot-hand bias in rhesus monkeys (Macaca mulatta).

Hot-hand bias in rhesus monkeys (Macaca mulatta).

Henry and Elizabeth were at the zoo for a day out with their children. They walked around watching the birds-of-prey displays, elephant feeding and the primates. When they got to the rhesus monkeys it was feeding time. The monkey enclosures had food placed strategically in trees, on platforms and on top of boxes. One of Henry and Elizabeth’s children noticed that the monkeys moved around the enclosure a lot but kept on returning to the same part of the tree where the food was placed, she wondered why the monkey acted in this way.

One of the most interesting patterns of behaviour is the ‘hot hand bias.’ The hot hand bias was first observed in basketball players, it posits that we perceive a positive serial autocorrelation in independent sequential events (Blachard et al., 2014). In basketball players the hot band bias reflects the tendency to perceive that a player’s chance of hitting a shot is greater following a string of successful shots rather than misses. The hot hand bias goes against statistical probabilities that argue that past events (i.e., success shot in a basket) have no influence on current or future events (i.e., the current shot at the basket).

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The origin of the hot hand bias remain unknown, in recent years researchers have begun to investigate the bias in animals that we share common ancestors with (Blanchard et al., 2014; Calhoun & Hayden, 2015). In 2014 researchers from the University of Rochester examined the hot hand bias in rhesus monkeys (Macaca mulatta) (Blanchard et al., 2014a). Blanchard and colleagues hypothesised that the hot hand bias is an adaptation to foraging in clumpy environments (i.e., environments with plentiful resources). The three monkeys in their study performed a novel gambling task. The results indicate that there were correlations between sequential decisions, for every sequential choice the change of choosing an option increased. The monkeys had better performance for clumped rather than dispersed distributions. These results support the suggestion that the hot hand bias evolved early during humanoid evolution and is an ancient bias.

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A second study by the same research group at the University of Rochester examined decision biases in another three rhesus monkeys (Blanchard et al., 2014b). The monkeys performed a similar task to the first study where researchers gave monkeys a sequence of rewards to choose between and the choice to repeat the same sequence or start a new one. The findings indicate that adding a small reward to the end of a sequence can reduce its value. This study supports the cross-species nature of decision biases and that these biases have evolutionary ancient origins.

A third study to investigate the evolutionary origins of decision biases in monkeys trained monkeys to perform a computerized version of a foraging decision task called the patch-leaving task. The monkeys could make a choice between moving between two patches of food, one in the foreground and the other in the background. When the monkey chooses to ‘move’ from one patch to the other there is a delay called travel time that results in a delay between receiving rewards. When adjusted for travel time there was nearly optimal performance across all of the monkeys. This study suggests that the foraging context (i.e., patches and delay) can reduce the influence of decision biases (Calhoun & Hayden, 2015).

Taken together these studies demonstrate that humans and monkeys alike share some of the same decision biases that have evolved over the course of evolution. The decision biases that we observe in all animals (including humans) have evolved to aid in survival by ensuring sufficient food through foraging. When Henry and Elizabeth took their children to the zoo the monkey’s behaviour reflected one of the many uses of the hot hand bias as it repeatedly went back to the place where the food was waiting.

Confirmation bias in suspect interviews

Confirmation bias in suspect interviews

Richard had always wanted to be a police officer. He had achieved all of the grades that he needed at college and was accepted to train as a police officer. Richard passed all of his classes during training and eventually got to a point in in his training were he had to learn interview techniques. With his friend Samuel, Richard role-played interview techniques. Together they were told that they should familiarise themselves with the facts of the case before interviewing a suspect. When Richard was told to familiarise himself with the facts prior to interviewing he thought it odd because he knew that the interviewing officer would then suspect guilt or innocence. Despite his initial suspicions about the interviewing method like all of his colleagues he continued to interview in the way that he was trained.

The justice system is one of the most important systems a country can have, it keeps order and ensures that anyone who commits a crime is treated in the relevant way to that country. One of the main ways in which the justice system operates is through the use of law enforcement (i.e., police officers). Police officers get called to the scene of a crime, assess the scene, collect evidence and detain anyone that is suspected of the crime. We like to think that police officers always make the correct decisions, however like anyone else they are fallible.

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One the most problematic cognitive biases (errors in decision-making) is the confirmation bias. The confirmation bias happens when an individual is required to make a decision but set about trying to prove a hypothesis that they already have. By making a decision based on what they already believe the individual is therefore at risk of making an incorrect decision.

One study that set out to investigate the confirmation bias in experienced police officers recruited 89 police officers. Charman and colleagues (2017) gave fictional criminal cases to participants and asked them to make a judgement about the guilt or innocence of the fictional suspect. Participants were then presented with ambiguous evidence in the form of either an alibi statement, handwriting sample, composite, or details of an informant (see Table 1) and asked to evaluate the ambiguous evidence. The results of this experiment found that the evaluation of the ambiguous evidence was related to the initial judgement of evidence in police officers: the stronger an officer’s initial belief in a suspect’s guilt the more incriminating they perceived the ambiguous evidence to be. The confirmation bias clearly had a strong effect in the evidence gained from interviews.

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An extreme case of confirmation bias during suspect interviewing can be demonstrated by what is one of the most publicised criminal case in recent years, the November 2007 murder of Meredith Kercher in Perugia, Italy. On the second of November 2007, British exchange student Meredith Kercher was found dead by her roommate, American, Amanda Knox. Knox had no history of violent crime and lacked a motive. When the police took a statement from Knox they believed she was hiding something because she showed no sign of emotion and behaved immaturely. She stated that on the night of the murder she was with her Italian boyfriend Raffaele Sollecito. With the prejudgement of Knox’s guilt, the police interrogated her for four days in Italian, a language that she was not fluent in, and without a lawyer present. In the early hours (1:45 am) of the fourth day of interrogations Knox eventually broke down, started screaming and without the support of her family and friends confessed to the murder. Later, when left alone she retracted her confession in a written statement. Interestingly, the confession contained no new information and was in part factually incorrect on important details. Knox was then officially arrested with Sollecito and provided with a lawyer. Her lawyer had the confession ruled inadmissible in court. Nonetheless, in the investigation that followed set about a motion of hypothesis-confirming (i.e., try to confirm a prior belief of guilt) with the detectives determined to prove that Knox was guilty (Kassin et al., 2011). In due course, on the 5th of December 2009 a jury convicted Knox and Sollecito of murder. Knox was sentenced to 26 years in prison and Sollecito to 25 years in prison. Eventually, on the 3rd of October 2011 after being granted a new trial, both Knox and Sollecito were acquitted. A short time after the release of Knox and Sollecito the Italian appeals court released a 143-page opinion criticising the prosecution concluding that there was no credible evidence or motive to presume Knox’s guilt.

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One of the possible influences that brings about the confirmation bias in police interviews are the guidelines from the United States Department of Justice (Eyewitness evidence: a guide for law enforcement. U.S. Department of Justice, Office of Justice Programmes). These guidelines state that an interviewer should review the case information prior to conducting an interview, of course, at first thought this seems like ‘common sense’. A study by Rivard and colleagues in 2015 investigated this and how to prevent confirmation bias errors in suspect interviews. The results of their study found that blind interviewers (those that do not know the details of the case prior to the interview) produced more correct judgements of guilt or innocence than those that knew the details prior to interviewing a suspect. Another benefit of using blind interviewers is that in this study they did not start the interview with a suggestive / leading question.

In the United States alone the Innocence Project (2015) estimates that more than 300 innocent people have been wrongfully accused and convicted of crimes that they did not commit because of investigator bias and eyewitness error. Although some section of our justice systems are aware of the confirmation bias, and train their staff in the knowledge of the confirmation bias, it is hard to avoid this entirely. We have seen one way of the ways in that we can use to avoid the confirmation bias in the study by Rivard et al (2015), although this method may cause other problems itself. The confirmation bias is not unique to suspect interviews since these types of errors in decision-making are a problem in many situations when decision needs to be made (e.g., medical, legal, sports etc). So like Richard going through his police training, if you are unsure about a decision you can simply get a second opinion or take a step back and think carefully.

Nudging organ donation

Nudging organ donation

Steven had been a driver for over twenty years. In his country, as in many other, Steven had to renew his driver’s licence every ten years. Recently, the driving licence authority in his country changed their licence renewal process to an online system. After Steven filled out his licence number, confirmed his home address and clicked through to the next page he was prompted with a message about organ donation. Following the message, he was asked if he’d like to register to be an organ donor, he wondered for a while as to why this was included in the driving licence renewal process, clicked yes and continued.

Organ donation rates vary dramatically from country-to-country, despite the universal need for organ donors. In 2012, some countries such as The United Kingdom had about 13 people per a million signed up to the organ donors register, whilst other countries such as Belgium had over double this with 27 people per million signed up (see Table 1). Even within individual countries the numbers of people signed up to organ donors registers very a lot (see Table 2). There are many reasons for the differences in the rate of organ donors across countries including how to sign-up (opt-in or opt-out method), religious beliefs and cultural norms (Morgan et al., 2015).

 

Country Opt-in or opt-out Donors per million population Population
Belgium Opt-out 27.1 10,827,519
Denmark Opt-in 11.5 5,547,088
France Opt-out 23.2 64,709,480
Germany Opt-in 15.3 81,757,595
United Kingdom Opt-in (Opt-out in Wales) 12.9 63,230,000
United States Opt-in 25.97 305,529,237

Table 1. Data from EU Directorate General for Health & Consumers, March 2012

 

US State % Donors (18+) Population
California

Iowa

34

73

28,801,211

2,351,233

Montana 82 782,161
New York 20 15,307,107
Texas 17 19,073,315
Vermont 5 502,060

Table 2. Data from National Donor Designation Report Card, April 2013

The modification of choice architecture (i.e., nudging) is one way in which donor numbers can be increased by making it easier for individuals to sign-up to be an organ donor (Rodriguez-Arias et al., 2016). The two ways for individuals to join the donors register are through an ‘opt-in’ or ‘opt-out’ registration system. In the ‘opt-in’ system individuals have to acquire an organ donor’s application form and make the effort to sign-up. In the ’opt-out’ system everyone is by default an organ donor if a person does not want to be an organ donor then they need to unregister from the organ donors register. As we can see in Table 1 the system of registration for organ donors vary from country-to-county.

In an effort to improve donor numbers the government of Belgium changed their system of organ donor’s registration in 2002. Initially Belgium employed the opt-in system were individuals had to put in an effort to sign-up to donate (Rodriguez-Arias et al., 2016). The change to an opt-out system doubled the number of organ donations in the first 3 years of implementing this change.

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Another nudge that has been applied with the aim of increasing organ donor rates other than changing the default opt-in / opt-out system include increasing awareness of the need for organ donors. In New Zealand, individuals who register for a driving licence are made aware that they can sign-up to be an organ donor (Rosenblum et al., 2012). From 2011, British citizens applying for a driver’s licence, or to renew their licence online, are required to answer a question about organ donation (British Medical Association, 2012). Whilst in The United States, in Texas new drivers in the 1990s were asked to state their views on organ donation before acquiring their licence, unfortunately this has now been abandoned in Texas (Klassen & Klassen, 1996). The states of Illinois, trialled a similar system to Texas (Thaler et al., 2010).

Two demographics that are underrepresented among organ donors are Black and South Asian people (Morgan et al. 2015). Morgan and colleagues (2015) suggested tailoring nudges to individuals to improve organ donor rates among Black and South Asian people. In 22 focus groups across London Morgan’s group investigated the views of Nigerian Christians, Indian Hindus, Indian Sikhs, Pakistani Muslims and Bangladeshi Muslims. Most of the interviewees stated that they regard organ donation as allowable regardless of their faith, they simply had not signed-up to the organ donor register because it is something that is not done in their immediate social groups. Tailoring nudges (i.e., messages) to these social groups can be one way improving donor rates among Black and South Asian people.

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One large survey of the public’s view of organ donation in The United Kingdom found that 90% of people support organ donation whilst less than a third are registered (James, 2015). The UK’s Behavioural Insight Team (BIT) tailored nudge messages to investigate their effect on organ donation rates (BIT paper: Applying Behavioural Insights to Organ Donation, Cabinet Office and Department of Health, 2013). On a government website BIT ran a randomised study for 5 weeks where over a million people saw one of eight messages (see Table 3). Both presenting a message as a social norm with an image and asking the reader about the fairness of donating and organ with reciprocation increased registration rates. This large study clearly shows that tailoring a message can make a nudge more or less effective depending on the target audience.

 

Message variant Attribute Message
1 Control Please join the NHS Organ Donor Register
2 Social norm + basic message Every day thousands of people who see this page decide to register
3 Variant 2 + images  
4 Variant 2 + images  
5 Loss frame + basic message Three people die every day because there are not enough organ donors…
6 Gain frame + basic message You could save or transform up to 9 lives as an organ donor
7 Fairness + reciprocity If you need an organ transplant would you have one? If so please help others
8   If you support organ donation please turn your support into action

Table 3. Tailored nudge messages employed in BIT study.

Therefore, like Steven if you sign-up to renew your driving licence and you are asked about organ donation it may be that you are seeing a message that is aimed at increasing organ donation rates. Depending on whether you would like someone to donate an organ to you if needed you may want to opt-in to donate. As we have seen nudges can be used in a variety of ways to increase donation rates. The default organ registration system (i.e., opt-in / opt-out) and public awareness of the need for donations through messages can all dramatically improve donations rates. More work needs to be done on nudging for organ donation to investigate all of the factors involved.

Nudging menu design for healthier food choices.

Nudging menu design for healthier food choices.

Jessica and Jack had just been seated at their favourite restaurant. They enjoyed the ambiance of the restaurant, the service and the quality of the food. They ate in the restaurant every couple of months as a treat. When the waiter handed Jessica and Jack their menus the noticed a few small changes, the low-calorie had been moved to the top of menu. They wondered why but continued their evening like normal without thinking about it any further.

Small and discrete changes to a menu or choice architecture can significantly impact the sales of a restaurant (Magrini & Kim, 2016). In the psychology literature, the manipulation of choice architecture is known as ‘nudging’. Nudges are subtle change to the choice architecture that make positive decisions (e.g., healthy eating) easier to make. Choice architecture is not limited to, but can take the form of the layout of a tax form, organ donation form, layout of a menu, placing of a food item on a shop floor, or the design of a pay-slip. The design of choice architecture depends on what the designers intend to achieve.

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In the restaurant business, small changes to choice architecture can make significant changes to income, bringing in a lot of extra money to the restaurant. Restaurants can change their menus to promote the sales of the ‘special-dishes-of-the-day’, to increase the sales of healthy food, or to increase revenue. In one study by Gothenburg University in Sweden researchers studied the effects of changing menu design in a fifty-two-seat restaurant in the city centre (Gravert & Kurz, 2017). Over the course of three weeks customers arriving during a two-hour lunch break were randomly presented with two different menus. One of the two menus offered a meat dish and a fish dish with a note on the menu saying that a vegetarian option was available upon request. The second menu offered a vegetarian dish and a fish dish, with a note stating that a meat dish was available upon request. Despite the meat, fish and vegetarian dishes having the same prices (around 13 USD or 110 SEK) the slight inconvenience of ordering the meat dish significantly decreased the share of the dishes sold at lunch. The results of this study clearly show that slight changes in the menu can promote the sales of vegetarian dishes.

In 2014, the United States Food and Drug Administration produced a rule with the aim of reduce obesity levels, the Menu Calorie Labelling Rule. This rule requires large food service chains to post calorie information next to all food items on menus. Shortly, after beginning to use this rule the sales of healthier foods significantly improved. Nudging by putting calorie information next to the dishes significantly nudged customers towards eating healthier than they would otherwise eat.

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Another study of the use of nudging for the promotion of healthy eating at Cornell University examined the effect of menu design on 200 college students (Mancino, 2009). The researchers at Cornell University simply added green stickers next to the healthy food choices on the menu, which was enough to increase the sales of healthy dishes.

Furthermore, another way that nudging has been used in menu design to increase the sales of certain dishes was assessed by Wansink and Love (2014). Wansink and Love analysed 373 descriptions of dishes on menus. They found that there are four simple ways to use the description of dish to nudge consumers into healthy eating: (i) the use of sensory names describing texture, smell or taste (e.g., Crispy Snow Pease, Fork-tender Beef Stew), (ii) the use geographic names to create an image of a geographic area that is associated with the food (e.g., Southwestern Tex-Mex Salad, Georgia Peach Tart), (iii) the use nostalgic names that allude to tradition, family or national origin (e.g., Oktoberfest Red Cabbage), and (iv) the use of brand names (e.g., Jack Daniels BBQ Ribs).

These studies of the use of nudging have all found that nudging can be used in different ways to promote the sales of healthy food – dishes can be rearranged on the menu with a note to customers to ask for information about the dish that is not being promoted, calorie information can be positioned next to each dish, green stickers can indicate which dishes are healthy, and descriptions can be used to tactically promote a dish. These studies all show that like Jessica and Jack when we sit down at a table to choose our food in a restaurant we may not notice subtle nudges that can have a big impact on the way we eat. Nudging can be a step forward in promoting healthy eating to reduce obesity levels.

How do investors prefer to save for their pensions: the 1/N heuristic.

How do investors prefer to save for their pensions: the 1/N heuristic.

Mark and Harvey were sat having coffee in their regular café that they visited every Thursday for breakfast before work. They discussed the latest football results and eventually ended up on the subjects of retirement. Harvey had never got around to starting an investment for his retirement so wanted to ask Mark for advice. Mark simply suggested that Harvey allocate his retirement investments equally across several funds, explaining that this reduce risk.

Saving or investing for retirement is one of the most important decisions that a person can make in their lifetime. Picking the right pension plan and / or allocating resources to the right fund(s) is crucial for enjoying their retirement years. Pension plans and retirement schemes differ from country-to-country. In some pension schemes investors have the choice of how to allocate their funds. When planning for their retirement individuals with a pension plan that allows them to allocate resources to different funds must choose how to invest their money. One popular strategy for making decisions about how to allocated resources is to use the 1/N heuristic (Benartzi & Thaler, 2001). The 1/N heuristic removes the confusion and stress of weighing up the pros and cons of how to invest resources and simply states that a given amount of resources should be divided equally between ‘x’ funds, for example, when a sum of £100,000 is to be invested this would be distributed into £20,000 into 5 different funds.

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In the Swedish pension system investors have the option of deciding how to invest 2.5% of their income. They can allocate 2.5% of their income to either a stock or interest fund (Hedesstrom et al., 2007). Once an individual makes the decision to invest part of their income they receive a brochure with 655 potential funds, they are then required to decide which of the funds they’d like to invest in. In 2004 researchers at Goteborg University analysed 392 investment decisions. The researchers found that investors used at least 5 different heuristics and biases to make their decisions. Investors had a tendency to avoid funds with extreme high and low risks (extremeness aversion – Simonson & Tversky, 1992), a tendency to select the default option (default bias – Johnson et al., 1992), to choose many funds in an attempt to seek maximal variety (diversification heuristic – Read & Loewenstein, 1995), to select domestic funds (home bias – Kilka & Weber, 2000), and to use the 1/N heuristic (Benartzi & Thaler, 2001).

A larger study of more than half a million pension plan participants in Defined Contribution pension plans from the records of the Vanguard Group investigated the use of the 1/N heuristic (Huberman & Jiang, 2004). They found that when deciding how to allocate pension funds participants tended to use the 1/N to divide their funds over 3 or 4 funds.

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A third study of 1000 people examined how Dutch citizens planned for their retirement (Van Rooij et al., 2007). After analysing retirement decisions the results of this study revealed that Dutch citizens are risk-averse and considered themselves to be financially unsophisticated. When given the option these investors used one three strategies (i) the default bias, (ii) the 1/N heuristic, or were susceptible to (iii) framing.

So, depending on what country you work in and decide to retire to there are many different ways to prepare for your retirement. Since most of us, like Harvey, are not financial experts when given complex important decisions to make for our retirement we choose to avoid risk by allocating our money equally across several funds by using the 1/N strategy. When planning for retirement the 1/N heuristic can be an effective and useful way to decrease risk and ensure a substantial retirement fund.

So, depending on what country you work in and decide to retire to there are many different ways to prepare for your retirement. Since most of us, like Harvey, are not financial experts when given complex important decisions to make for our retirement we choose to avoid risk by allocating our money equally across several funds by using the 1/N strategy. When planning for retirement the 1/N heuristic can be an effective and useful way to decrease risk and ensure a substantial retirement fund.

The sunk cost effect in pigeon behaviour.

The sunk cost effect in pigeon behaviour.

Eva and Jason had just finished a long morning trading in stocks in Canary Wharf. Every day at lunch time they liked to like to get out of the grey, poorly lit office and eat their lunch outside in Jubilee Park. They always sat on the same patch of grass and watched the pigeons and people pass by. As they ate Eva noticed that one of the pigeons tended to stick to the same area of the park, pecking around and looking for food rather than move to another area of the park where more people were sat around enjoying their lunches. Eva mentioned the pigeon to Jason and they both wondered why the pigeon would not move to the area of the park with more food.

In humans when an individual is given the choice between two or more investment decisions people often stick with the investment they are already involved in rather than moving to a new investment (Novemsky & Kahneman, 2005). The initial investment of resources (money, time, energy etc) make switching investments less likely even if the new investment could produce a better outcome than the original investment – psychologists call this tendency to stick with the original investment the sunk cost effect (or bias) (Avila et al., 2010). One explanation of the sunk cost effect is that people have strong misgivings about wasting resources, a disposition that economists call loss aversion (Novemsky & Kahneman, 2005).

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Like humans, other animals (other than humans) often show the same decision behaviours. Several studies have investigated the sunk cost effect in pigeons (for a review see White & Magalhaes, 2015). In one study by Pattison and colleagues (2012) at the University of Kentucky researchers examined decision behaviour in pigeons (Columba livia). The pigeons were trained to peck at coloured keys with a potential reward (food). The pigeons could make a choice between pecking at one key for 30 pecks with a potential reward (e.g., a red key) or switching to another key (e.g., a green key) with a potential reward after 10 or 20 pecks. The pigeons showed a bias towards continuing with the sequence of pecks that they had invested in rather than switching to peck on another key that would produce a reward after fewer pecks. These results show that pigeons, like humans, show a bias to stay with an initial investment.

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A second study investigating decision behaviour in pigeons used a slightly different method to Pattison and colleagues (Watanabe, 2009). The pigeons in this study still had the same choice of sticking with an initial investment (in pecks) or switching. After training the pigeons to peck 30 times at one colour for food and 10 times to another colour for food Watanabe gave the pigeons the choice of switching to the 10-peck option after they had already started the 30-peck option. The experimenters found that three of the four pigeons showed a preference for completing the initial investment, despite the fact that switching to the second option would need pecks overall. So, like humans the pigeons in this second study were also susceptible to the sunk cost effect. Although these results are interesting the resources conceded that there may be one alternative explanation for the behaviour pigeons – switching to the new alternative would require the pigeon to move to the new colour.

Therefore, although most people would like to think that we do not act in the same way as other animals some of our behaviour is not uniquely human. Next time you find yourself sat on a patch of grass like Eva and Jason enjoying your lunch whilst watching the local wildlife and wondering why that pigeon is acting so strangely simple think “what would I be doing if I were that pigeon?” Afterall, the pigeon stubbornly sticking to its little patch of the park is not too unlike the way that our investment bankers and stock brokers behave.

The framing effect on climate change communication and policy making.

The framing effect on climate change communication and policy making.

Hannah and Thomas had both recently become interested in the environment and the politics of climate change after seeing a few news articles on the topic. Last week Hannah watched a very convincing documentary by a leading politician about the dangers of climate change and how humans are contributing to it. Thomas’ father worked in manufacturing and was skeptical about the contributions of humans to the change in environment, his father had always said that humans could not change the environment. Both Hannah and Thomas agreed that although they had different views on climate change there are mixed messages in the press.

Many controversial topics in the media are framed in such a way that benefit the person or company that is responsible for placing the message. The framing effect is one of the major heuristics (short-cuts in decision-making) that is used in the media. Framing works by wording a message in a persuasive way to influence the thinking of the reader (Kuhn, 1997). Communicators can make a choice to present the possible outcomes of a medical interventions as either (a) 80% chance of surviving (i.e., positively framed) or (b) 20% chance of death (i.e., negatively framed). On the topic of climate change communication researchers have found that a negatively framed (highlighting losses) message decreases individual intentions to behave environmentally whilst positively framed messages (highlighting the possibility of losses not materializing) produce a stronger intention to act in a pro-environmental way (Morton et al., 2011).

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One important factor for policy makers is that in the United States the public do not think that climate change is a concern, compared to other policies. Every January the Pew Research Centre for The People and The Press conduct a large poll of the public’s belief in which of 20 policies are of most important.  Between 2007 and 2009 the policy of “dealing with global warming” was consistently ranked at the bottom of 20 priorities (see the table below).

% considering each as a “top priority” January 2007 January 2008 January 2009
Strengthening the nation’s economy 68 75 85
Securing social security 64 64 63
Securing Medicare 63 60 60
Reducing crime 62 54 46
Reducing health care costs 68 69 59
Strengthening the military 46 42 44
Dealing with illegal immigration 55 51 41
Reducing middle class taxes 48 46 43
Dealing with global trade 34 37 31
Dealing with global warming 38 35 30

To aid in breaking through the communication barrier policy makers can tailor their messages to specific audiences by framing their messages. News reporters (e.g., news about an event), policymakers (e.g., employment statistics), advertisers (e.g. vitamin advertisements), and public speakers (e.g., conference talks) already use framing effectively.

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The framing of climate change information has been used successfully by John Kerry in 2004 and Obama in 2008. In his 2004 election campaign the Democratic party presidential candidate Senator John Kerry made strategic use of the public accountability framing (i.e., we are responsible for our environment). Senator Kerry compared the use of different frames (i.e., denial or acceptance of climate change) to the administrations use of intelligence to invade Iraq. In Obama’s 2008 presidential candidate campaign he made use of a sound bite “creating green jobs and fuelling economic recovery.” Creating green jobs in industry with alternatives to gasoline (or petrol) was heralded as a way to benefit the economy by creating more jobs and as a way to reduce greenhouse emissions. We can see here that Kerry chose to use a public accountability frame whilst Obama used an economic frame – both frames were used towards the same aim but tailored differently. Famously, Gore in his 2008 WE campaign picked a moral frame for climate change communication.

We have seen here that the framing effect can be used effectively by communicators for any message (e.g., advertising, policies etc). On the topic of climate change communication, we can put the framing effect to work by carefully considering how we would like to frame a message to our intended audience. In the cases of Hannah and Thomas they may have both seen the same information presented in different ways (i.e., the frame), the frames that they have encountered helped them come to their own decisions about climate change.

The confirmation bias in the forensic sciences.

James and Nicki always wanted to work in the forensic sciences. Whilst reading towards their undergraduate degrees they would borrow as many books from the library as they could on forensics and watch the popular television programmes about ‘forensic experts.’ One day when looking though an interesting book about case studies in forensics Nicki came across an interesting case study.

In 1988, Barry Laughman confessed during interrogation to the charges of rape and murder of his neighbour. The following day tests revealed that the person who committed the crime had Type A blood whilst Laughman had Type B. Aware that Laughman had confessed to the crimes the state forensic chemists proposed four theories (none of which were scientific) to dismiss the mismatch. Laughman was in due course convicted and sentenced to 16 years in prison. He was eventually released in November 2003 after a re-examination of the DNA evidence.

The case of Barry Laughman gives us a clear example of the influence of confirmation bias in the forensic sciences. The confirmation bias is shown when an individual ignores evidence that goes against what they believe whilst trying to confirm the belief (Dror, 2006). In Barry’s case the Virginian state forensic chemist ignored contradictory evidence and persisted in dismissing the mismatch in DNA evidence.

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The confirmation bias causes problems in all areas of decision-making. In the forensic sciences errors in decision-making, as caused by the confirmation bias can have severe consequences innocent people can spend a lifetime in prison, and the actual criminal can go on to reoffend. In the forensic sciences, the confirmation bias has been reported by the National Academy of Sciences (2009) in firearms, hair and fibre analysis, blood splatter, hand-writing and fingerprints (Kossin et al., 2013; Garrett et al., 2011).

In a recent study investigators found an interesting example of how the confirmation bias can influence the outcome of a forensic analysis (Ulery et al., 2012). The investigators gave forensic fingerprint examiners the same evidence twice, at approximately 10% of the time the examiners reached different conclusions (Ulery et al., 2012). Three of the reasons as to why the examiners reached differing conclusions are (i) examiners often receive direct communication from the police (e.g., letters, phone calls etc), (ii) cross-communication between examiners, and (iii) examiners overstating the strength of evidence.

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There are measures that can be taken to prevent the confirmation bias. The FBI’s Latent Print Unit revised their Standard Operating Procedures (SOP) (Cole et al., 2005). They adopted a programme of masked verification whereby fingerprint comparisons that involve a single print are masked-verified (i.e., in isolation with no further information about the print). The change in SOP prevents the second examiner from inferring the first examiner’s conclusion when two examiners individually examine the evidence (Office of the Inspector General, 2011).

Other measures that can be undertaken to prevent the confirmation bias include training all forensic examiners so that they know about cognitive biases. Just two of the courses help to install knowledge of cognitive biases are the FBI’s week-long Facial Comparison and Identification Training and the Australian government’s 2-day long facial comparison course. The linear examination of evidence by multiple examiners (Heyer et al., 2013), cross-laboratory verification (Kossin et al., 2013) and peer verification (Heyer et al., 2011) can all help in reducing the impact of the confirmation bias in the forensic sciences.

So, like James and Nicki if you are interested in working in the forensic sciences it is important to learn about the influence of cognitive biases on decision-making. Some private forensic companies have begun to provide training for their employees, and some governments have started to provide training. With adequate training one day we may be able avoid false convictions.

The recognition heuristic in advertising

The recognition heuristic in advertising

Anton and Sarah were shopping for their weekly groceries in their local supermarket. They bought their regular fresh fruits, vegetables, meat and dairy. As they started down the cleaning aisle Anton and Sarah were trying to decide which furniture polish to buy. They looked at the choice of polishes that were stocked in the aisle. There was a supermarket own-brand choice, two little known choices and a well-known brand. Anton remembered the well-known brand of furniture polish from a television advertisement with a comical cartoon character. There was little difference between the prices so Anton and Sarah decided to opt for the well-known brand that they remembered from the television advertisement.

Like the furniture polish brand companies spend great fortunes on making their products well-known. Millions is spent on brand communication with the goal of achieving the aided and unaided awareness of products. In 2007 and 2008 two large brands, Proctor and Gamble and Unilever spent $5.2 billion and $7.8 billion respectively. The substantial resources that are committed to promoting brand awareness shows the importance of establishing and retaining the awareness of a brand.

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Because of the importance of brand awareness many companies and academics have sought to understand the decision processes that are involved when a consumer chooses one brand over another. In industry, a major US automobile brand invested substantial resources to study how they might persuade customers to choose their brand over their competitors. They found that although their brand had excellent new vehicles as judged by independent raters two thirds of US consumers did not consider their brand (Hauser et al., 2011). The automobile company lacked a memorable advertising campaign.

In academia, researchers at the Max Planck Institute have suggested a rule-of-thumb (i.e., heuristic) that attempts to explain why consumers choose one brand over another (Gigerenzer & Goldstein, 1999, 2011). In a now famous experiment where participants were given the names of two cities (e.g., Oxford or Lannion), and then asked to judge which of the two cities had the largest population, participants reliably choose the city they knew (i.e. Oxford) over the city that they did not (i.e. Lannion). The researchers recorded this rule-of-thumb as… If one of two objects is recognized and the other is not, then infer that the recognized object had the higher values with respect to the criterion. The researchers called this rule-of-thumb the recognition heuristic. In consumer psychology, the recognition heuristic works equally well when consumers are asked to choose one brand over another (Thoma et al., 2013; Oeusanthornwattana & Shanks, 2010).

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In purchases with higher stakes (compared to simply buying a product in a shop) such as stock market investments the recognition heuristic is also of use. Imagine that you wish to invest a particular amount of money in stocks. If one person recognises a stock name over another they are more likely to choose the known stock over the unknown stock. Having a recognised stock name can increase the number of investors in a certain stock (Erdfelder et al., 2011).

In the case of Anton and Sarah shopping for their furniture polish it is clear why they choose the well-known brand over the unknown polish. The advertising campaign of the branded furniture polish with the comical cartoon character aided in the recognition of this brand thereby resulting in one more sale. If you multiple Anton and Sarah’s purchase by thousands or millions then you can clearly see the huge amounts of money that are involved. Many of us, like Anton and Sarah stick to brands we know simply because we know them, we buy the same cleaning products and food stuffs because of successful brand awareness campaigns that act on the recognition heuristic. Perhaps if we wish to avoid making unconscious choices based on the recognition heuristic we could simply try a different product, afterall the new product is not as we expect we can change back to our regular shopping pattern next time.