28 February 2013

Your Memory Is Not the Real World - Availability Heuristic


Imagine yourself as being the parent of a 9 years old child who wants to go and play with a colleague from school at his house. As any loving parent you want your child to be happy (play with the colleague) and you also want your child to be safe (not be endangered). The colleague’s family is a regular family with nothing suspicious about them. Consider that you know only one thing apart from that family being “average”.

Situation1. You know that that family has a gun (pistol) with “live ammunition” in the house.

Would you let your child go and play at the colleague’s house? YES or NO?

Very likely your answer is “No”. You want to be a good parent and protect your child from harm and guns are dangerous even in the hands of adults; there is no telling how dangerous they are in the hands of children.  

Taking a step back, think a bit about the actual probability of the kids finding the gun without  searching for it, playing with it, actually firing it and actually hitting and hurting one of them. Of course, they would need to be without adult supervision for quite some time to be able to do all of the above.

What is your answer now? Probably your answer is unchanged. All the things in the paragraph above make some sort of sense, but you know “GUNS are DANGEROUS”. OK! Fair enough!

Situation 2. You know that the family has a swimming pool in the backyard.

Would you let your child go and play at the colleague’s house? YES or NO?

Very likely your answer is “Yes”. If they have a swimming pool it means that the children can have more fun playing around it.

YOU FAILED IN BEING A GOOD PARENT!

When it comes to young children, swimming pools are much more dangerous than guns, at least according to Steven D. Levitt, Stephen J. Dubner authors of Freakonimics.

How come you failed at this? It is perfectly reasonable to assume that guns are more dangerous than swimming pools. After all you probably have heard of more deaths by guns than deaths by swimming pools.

The answer to this failure in judgment is “the availability heuristic” or how I like to call it sometimes “Observation bias”. Let’s see how it works.

The correct (rational) question you have to answer when assessing the potential threat to your child’s wellbeing is “what is the probability of my child getting hurt by a gun / swimming pool?”. The emphasis is on PROBABILITY! Giving it a bit of “cold” thought, virtually anything can be dangerous, thus you should see what is less likely to hurt your child.

As mentioned in previous posts, humans are not particularly good at assessing probabilities. Since it is hard to establish the exact probability of an event, we resort to heuristics. In other words we tend to give an answer to a difficult question (what is the probability?) by answering an easier question (how many instances of an event do I know of?).

To make this a bit clearer, people assess probabilities of events in the world by evaluating the number of those events that they can remember. Not surprisingly, what we have stored in our memory is different from what is actually happening in the “real world”.

Let me give you another example of this availability heuristic from my own life. In 1991 I had my first trip outside my home country – Romania and went with my mother in the UK. I was about 9 years old at the time. Our hosts were very generous and friendly and they wanted us to get to know as much as possible about regular life in the UK, so they arranged for us to meet with many of their friends.

One lady was very surprised to see that I (a Romanian child) was a regular normal child. Now, I know that westerners had (and still have) some really stereotypical views on easterners, but this went far beyond the “eastern stereotype”. The lady was surprised to see that I was healthy in both body and mind.

The reason for this lady’s astonishment in seeing that a Romanian child can be normal was due to the fact that the BBC had presented a story on the conditions in a Romanian orphanage. The story is horrifying. In a nutshell, the communist dictatorship regime decided that children with mental disabilities are not worth the effort and kept them in inhumane conditions waiting for them to die.

The British lady had in her memory these images, thus she somehow implied that all (or most) of Romanian children are disabled. Surprise! It is not so!    

In an earlier post - DespiteSeldom Encounters With Foreigners or Immigrants Some People Have StrongXenophobic and Racist Attitudes…  I have addressed the issue of racism and xenophobia through the lenses of the availability heuristic. The main idea is that when it comes to negative attitudes towards immigrants, many people simply make judgments based on what is available in their memory on the issue of “immigrants” and due to the free press most likely when they think of “immigrants” the first things that come into mind are the negative stories that got large coverage in the media.

However, most immigrants are regular hard working people. The only issue is that no one notices these people because “going to work every day” is no subject for news. Read the post if you want to get more on this.  

Some criticism on the examples I gave until now on the availability heuristic is that the instances stored in memory of death by guns, immigrants that do bad things and disabled children are somehow emotional. I will address this issue in a future post on the “affect heuristic”.

Availability without affect exists and here is one example. Are there more words with the letter “R” as the first letter or are there more words with “R” as the third letter (English vocabulary)?

Most people go for “First letter” because words beginning with “R” such as “Race” come easier to one’s mind than words with “R” as a third letter such as “Mortgage”. However, as you very likely figured out, there are more words with “R” as the third letter than there are words with “R” as the first letter.

Another case of the availability heuristic is related not to how many instances of an event are available in memory, but rather to how vivid an event is memory. For example after the recent (15 February 2013) event when a meteorite fell in Russia, if you ask people what is the probability of a meteorite hitting the Earth, you will get higher estimates than you would have got if you would have asked (the same people) on the 15th of January 2013.

The reality is that the probability has not changed after the event, but the vividness of the event makes it seem more probable.

The implications of the availability heuristic in our everyday lives are significant. You might think that the examples about meteorites hitting the Earth and about guns and swimming pools are frivolous and to a certain extent you are right. At the same time, xenophobia and racism are major issues in a cosmopolite and globalized world. Going into less complex issues of society, many people are less happy because they overestimate risks such as an airplane crash and don’t take that trip to Iceland or wherever.

When assessing risks, think twice! Because your memory is not a good representation of the “real” world.
This post is documented from:
Tversky, Amos, and Daniel Kahneman (1974), "Judgment under Uncertainty: Heuristics and Biases," Science, 185, 1124-31.

Steven D. Levitt, Stephen J. Dubner (2005), “Freakonimics: A Rogue Economist Explores the Hidden Side of Everything”, New York: William Morrow Ltd. 

22 February 2013

Is it a Bird? Is it a Plane? No! It’s Representativeness


Soon after the end of communism in Romania, I watched some old cartoons with Superman. They were old, but for me as a young child they seemed like the best thing possible and I played them on the VCR for hundreds of times. This is how the phrase “Is it a bird? Is it a plane? No! It’s Superman” got into my memory and very likely will be there as long as I will have memory.

But enough with my childhood story! The phrase “Is it a bird? Is it a plane? No! It’s Superman” is highly illustrative for what in psychology is called the “representativeness heuristic”. If something flies then very likely it is either a bird or a plane, because when we think of things that fly, the aforementioned two are pretty much what flies.  

Remaining in the area of birds, let’s see what a “bird” is. What is it? In your own words… fill in the blanks:

A Bird is __________________

If you did not cheat by searching for a formal definition, most likely you answered something like this: “It’s something that flies, has wings and lays eggs”. Quite close to the formal definition which is: “a warm-blooded egg-laying vertebrate animal distinguished by the possession of feathers, wings, a beak, and typically by being able to fly” according to oxforddictionaries.com (source http://oxforddictionaries.com/definition/english/bird).

The informal definition of “something that flies, has wings and lays eggs”, however is incomplete and inaccurate. Something that “flies, has wings and lays eggs” is also typical for most insects (well all insects have wings but not all fly … and no! Spiders are not insects). As we know, birds are not insects.  In addition, something that “flies, has wings and lays eggs” does not accommodate some actual birds such as the ostrich, emu and penguin.

Now, let’s see why and how the simplistic definition of a bird came to be. First of all, we as (normal) humans are not necessarily good at giving clear, accurate and exhaustive definitions… after all why would there be dictionaries if we were? What we are good at is identifying and remembering prototypes.

When I asked you to come up with a definition for “bird”, very likely you did not have in your memory the formal one. This is unless you are an ornithologist … So, without a formal definition stored in memory, you retrieved from memory “a bird” or to be more exactly “the prototype of a bird” and then described it and came up with a definition.

To put it a bit differently, you defined a bird as being the description of what a prototypical bird is for you.

Since birds such as penguins and ostriches are quite rare in most of the world and especially in cities (where I assume most of you live in), the prototypical bird in your mind is something like a mixture of a pigeon, crow and sparrow or seagull. All these birds fly and have wings…

Before ending with the “bird business”, let’s summarize: we humans think in prototypes and not formal definitions. What a prototypical “something” is is heavily influenced by our experiences and subsequently what is stored in memory.

Not giving an accurate, complete and exhaustive definition of a bird is not an important issue. However, we use prototypes to make judgments in considerably more important areas such as voting, romantic life, job choosing (if one has to choose), purchasing decision etc.

One very nice example of using prototypes to make (political) decisions is given by Malcolm Gladwell in his book “Blink” (chapter 3). Gladwell tells the story of Warren Harding who ended up being President of the USA. His rapid ascension in political life was mainly due to his good looks. As Gladwell says, this guy “looked like a president”. Unfortunately, his 2 years mandate is remembered as one of the worst in USA history.

The essential aspect of understanding the representativeness heuristic is how it works. It essence, when we make judgments we very often ask ourselves one question, but we answer another one. The first question is difficult, while the second is easy to answer.

Let’s illustrate this. Imagine yourself as a voter in the elections won by Warren Harding. You want to make a good decision and you ask yourself the following question: “Is Warren Harding a competent, hardworking, visionary, patriotic leader?” or putting things a bit more simpler, “Is Warren Harding going to be a good president?”. By all means this is a difficult question. Honestly, even in the XXI-st century with virtually unlimited information about politicians it is really hard to answer the question.

At the same time, another question pops into your mind. This time it is a rather easy one: “Does Warren Harding look like a good president?”. In other words, “Does he fit the prototype of “good president”?”.

Now, this question is easy to answer because you can simply compare the candidate with your mental image (prototype) of a “good president”. The answer is simple and comes immediately into mind. “YES”. Or at least that is what the majority of voters in those elections answered.     

The power of representativeness goes beyond fuzzy complicated questions about politicians’ qualities. What if in aforementioned example of you being a voter, you would have some statistical background information? What if you knew that there is a one out of three chance that Warren Harding will be a good president? Would you still consider him to be a good potential president? Research tells us that you would still think that he will be a good leader and that you will simply ignore the statistical information which tells you that it is twice more likely for him to be a bad president than a good one.

The fact that people ignore statistical information and make judgments based mostly on representativeness has been proven in a legendary study by Kahneman and Tversky from 1973. Participants in the study were presented with the following description of a student:

“Tom W. is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and by flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and little sympathy for other people and does not enjoy interacting with others. Self-centered, he nonetheless has a deep moral sense.” (source: Kahneman and Tversky (1973) as cited by Kahneman and Frederick (2002)).

Some participants in the study were asked to rank the nine fields of specialization within the university (such as computer science or humanities) by the degree to which Tom W. “resembles a typical graduate student.”

Other participants were informed on the proportions of students enrolled in each of the nine specializations (for example “3% of students are enrolled in Library science”). Next they were asked to rank the specializations according to the likelihood of Tom W.’s specializing in each.

To make things a bit simpler, some participants were asked to evaluate (rank) field of study based on how prototypical was “Tom W” to each of them. Other participants were provided with statistical information on the number of students in each field of study and next were asked to evaluate (rank) these fields of study based on the probability that “Tom W” is enrolled in each of them.

The two groups ranked the fields of study virtually identically (correlation coefficient of 0.97). In other words, people judged the probability by means of representativeness. Most interestingly, the statistical information provided was virtually ignored completely.

If you read the description of Tom W. you see that somehow he fits the prototype of a “computer science” geeky student. At the same time, there is not one single hard fact that would be causally linked to him being a “computer science” student. There is no single bit of information that would make us say beyond any doubt that he is in “computer science” and not in “history”. The description doesn’t say that he is good with numbers, likes to write software or knows how to take a computer apart to the smallest piece and put it back together.  

Despite this lack of hard causal information we tend to see Tom W. as a “computer science guy” and not as a “Literature student”. Moreover, we tend to ignore basic information. If in the description there is not hard fact to tie Tom W. to a particular field of science, then it means that the base-rates for each field apply. This means that in absence of any additional information, the likelihood of Tom W. being a literature student is equal to the proportion of literature students in the overall population. If 15% of all students are in “Literature”, then it means that Tom W. (regardless of his description) has a 15% chance of being a literature student.

Let’s go a bit back to the birds… Go and ask a colleague (who has not read this post yet) the following question:

“Something that has wings, flies and lays eggs is more likely to be:
A. a bird or
B. an insect?”

I guess most of your colleagues will answer quickly that it is more likely to be a bird, despite the fact that on Earth there are far more insects than birds. This is because in our minds “something that has wings, flies and lays eggs” fits better the prototype of a bird than it fits the prototype of an insect.

But, apart from office fun with birds and insects and from fictional students with poor social skills, representativeness based judgment has very serious influences in our lives, even beyond voting good looking politicians.

Consider the following example. You have some money to invest (or at least let’s pretend you do) and you want to invest in a small technology company. The following two options are available:

Option A: is a small company in the technology business that has 50 employees. The main office is located in a class A office building in the business center of the city. The CEO of the company is a 34 years old man with a funky hairstyle that has a very active presence in social media.

Option B: is a very small company in the technology business that has 20 employees. The company has a small office located in an old factory building at the outskirts of the city. The CEO of the company is a 36 years old guy who gives little attention to his physical appearance. He has neither a facebook nor a twitter account; he uses the same e-mail address he has been using for the past 15 years.

In which company would you put your money into?

If you answered “in the first one” (option A), then you are a “victim” of representativeness. Both descriptions tell you virtually nothing relevant for your decision.

Let’s take a step back and identify the right question to answer if you want to invest in a company. This question is “which company will achieve market success and have profits (hopefully)?”. In the two descriptions of the companies I gave you absolutely nothing about income flows, profit margins, growth potential etc.

What I gave you is perfectly irrelevant information on things that seem to be related to success or better yet, information on what we believe to be a successful company.

So what if the first company has 50 employees and the second only 20? If you watch the news you will hear about companies cutting jobs to increase profitability, which is what you should care about as an investor.

So what if the guy running the second company doesn’t care about his physical appearance? Have you never seen a picture of Donald Trump?

Thinking in prototypes and making judgments based on representativeness is simply natural for people. Usually this goes quite ok.

Before ending, I would like to make a brief observation about marketing research and the fact that people use representativeness for a lot of judgments.   

Typically, a marketer’s job is, among others, to achieve brand awareness. Now, this brand awareness comes in more forms and one of them is “top of mind” in the sense of a certain brand being the first thing that pops into consumer’s minds when a product category is mentioned. Other types of awareness focus on recognition of a brand.

A typical example of a question that investigates top of mind awareness is “What is the first brand that comes to your mind when you think of hamburgers?”.

I have nothing against top of mind awareness, but I ask, is it as important as most marketers think it is? After all, if people make judgments by assessing representativeness, isn’t it more important to make sure that we are recognized by our customers and not necessarily take that “top of mind” spot?
  
Note: This post is documented from:
Kahneman, D. and S. Frederick (2002).”Representativeness Revisited: Attribute Substitution in Intuitive Judgment,” in Heuristics and Biases: The Psychology of Intuitive Judgment. T. Gilovich, D. W. Griffin, and D. Kahneman (Eds.). New York: Cambridge University Press, 49-81.

Gladwell, M. (2005). “Blink: The Power of Thinking Without Thinking” New York: Little Brown and Co

20 February 2013

Deeper into the Bird Brain - Heuristic Judgment


Having covered most of the relevant (in my opinion) aspects of the Personality Dimension from the 4D Model of Behavior, I would like to come back to a very relevant area of behavioral and decision sciences, namely heuristic judgment.

In an earlier post - A Bird and a Computer in the Brain (Two Systems of Thinking) - I have discussed the two ways in which humans make judgments or in other words, I have described the Dual-System model of Judgment. To quickly review this, people have two ways in which they think. 

First, we have the evolutionary older System 1 (or bird brain) which makes fast judgments based on “rules of thumb”, which is effortless in terms of metabolic resources needed for its functioning, is highly intuitive and uses mostly associations. 

Second, we have the evolutionary newer System 2 (or computer brain) which makes slow judgments based on learned rules, which is effortful and uses large amounts of metabolic resources (energy); it is computational and analytical. For a more extensive description check out the post A Bird and a Computer in the Brain(Two Systems of Thinking)

I believe that understanding how the “bird brain” (system 1) works is highly relevant for understanding human behavior. I have mentioned earlier that system 1 works on “rules of thumb” which in more scientific terms are called heuristics. In a series of posts I will describe the most important ones: (1) Representativeness, (2) Availability, (3) Adjustment and anchoring, (4) Affect heuristic and (5) Halo effect.

Before starting to talk about each heuristic there are two major aspects that I would like to clarify. 

First, what is a heuristic? Somehow a lot of people talk about heuristics but very few explain what it means.

One of the definitions I have found on-line is this one: “A heuristic is a mental shortcut that allows people to solve problems and make judgments quickly and efficiently. These rule-of-thumb strategies shorten decision-making time and allow people to function without constantly stopping to think about the next course of action.” Source 

Another definition, this time from a scientific paper is the following: “A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods.” Gigerenzer and Gaissmaier (2011).

Taking a look at the two definitions we see that a heuristic is in essence a way of thinking that is not extensive and exhaustive. To simplify even more, a heuristic is a simple and easy way of thinking.

The most known work on heuristic judgment was done by Amos Tversky and Daniel Kahneman who have conducted the famous “heuristics and biases” research program. However, they are not the ones that have brought the topic of fast and simplistic judgment into the attention of business research. It was Herbert A. Simon who has approached heuristics in this research on problem solving. Just as a “nice to know” fact, Herbert A. Simon was the first to challenge the assumption of full rationality of humans by introducing the (realistic) concept of “bounded rationality”.

Second, is it bad to use heuristic judgment?

Now please answer the following question: “What word comes first to your mind when you hear the term “heuristic”?” … I guess it’s “bias(es)”.

A lot of research has focused on the “down-side” of heuristic judgment, mainly on the fact that heuristic judgment quite often violates the principles of rationality. The truth, however, is that overall heuristic judgment leads to good conclusions and actions.

In most instances, the outcome of heuristic judgment is not “the best possible”, but it is “good enough”.

In their paper from 2011 Gigerenzer and Gaissmaier actually make a case that in many instances heuristic judgment leads to better results than deliberate effortful reasoning.    

If we accept that humans are not meant to be perfect reasoning machines and that our goals are to survive and reproduce, I guess that “good enough” outcomes are simply good enough to fulfill these evolutionary macro-goals.

This post is documented from:

Gigerenzer, Gerd, and Wolfgang Gaissmaier (2011), "Heuristic Decision Making," Annual Review of Psychology, 62, 451–482.

Kahneman, D. (2011). Thinking, fast and slow. London: Allen Lane.


19 February 2013

Poverty – Nutrition Trap – Self-Enforcing Poverty II


Although this topic may seem out of your interest area, it has many implications for managers, human resources professionals and for people concerned with nudging.

The concept of “poverty – nutrition trap” is quite intuitive and goes something like this. Very poor people don’t earn enough money to buy sufficient food; this in turn leads to their weakening and subsequently to a decreased productivity and capability to earn money. Less money leads to not being able to buy sufficient food.

As you can see, this is a self-enforcing mechanism. Not enough money – not enough food – less money – less food.

I have to make a note here. By food I mean the right nutrients in the right quantities. Nutritionists know more, so I will allow them to develop if they wish to do so.

One interesting thing about the “poverty-nutrition trap” is that until recently it has been considered to be more of a theoretical construct that reality.  However, a recent study has proven that such a trap exists in real life, at least for some nutrients.

For more western-richer people this sounds as being very far away. In fact for Americans and Europeans the problem is not malnutrition, but rather “over-nutrition”. However, knowing about the poverty – nutrition trap helps managers to better understand the importance of providing adequate meals at the work place.

In my view there is little difference between lack of effectiveness due to malnutrition and lack of effectiveness due to bad-nutrition. I am not an expert in nutrition, but I guess that what kind of food we eat influences how our body and mind work.

Companies and organizations can provide catering for their employees or members and most importantly they can control what kind of food is served.

I have heard recently about a big company that had a campaign to sell “cola” and chips together as a “lunch solution” … sorry, that is not food …

Do you know examples of companies or organizations that tried this? Did it affect productivity or results?

Before ending, I’d make an observation on the recent distress about finding horse meat in what was supposed to be beef meat “ready-made food”.  Apart from the fact that horse meat is eatable and I think the panic is exaggerated, WHY buy “ready-made” meals??? Honestly, cooking is not that complicated and it doesn’t take more than half an hour to cook something decent.

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Emotional Intelligence … is it or is it not?


As I mentioned in the previous post on Intelligence, in recent years there has been an inflation of types of Intelligence and the one that got the most popular is Emotional Intelligence.

In opposition with General Intelligence (or simply intelligence), the amount of research in the area of Emotional intelligence is not impressively extensive. I’ll come back to this in a couple of paragraphs.

The interesting thing about Emotional Intelligence is that it sounds good. Now, really just say “Emotional Intelligence”. It sounds really good because everything that is emotional has this kind of aura of “coolness” (especially among marketers). Moreover it sounds like some sort of new form of intelligence that is not reserved only to smart people. It sounds more democratic.

These characteristics of Emotional intelligence lead to the fast propagation of the concept in both (pseudo) science and popular culture. What usually happens when a concept becomes very popular very fast is that along the way it becomes very unclear, but no-one acknowledges it.

Let’s put things a bit differently, What is Emotional Intelligence? What does it mean to be Emotionally Intelligent? Probably most answers to these questions go like this “to be emotionally smart” or “to be good with emotions”… in essence the answer is a tautology (which means that we define a bird as being a bird).

If we go back to the simplistic definition of intelligence that I gave in the post about it, namely “Capacity of processing information” and acknowledge that emotions can to a certain extent be considered as information, then we have a rough definition of Emotional intelligence. This rough definition would be the “capacity of processing information in the form of emotions”.

A formal definition is: “Emotional intelligence is a set of abilities that includes the abilities to perceive emotions in the self and in others, use emotions to facilitate performance, understand emotions and emotional knowledge, and regulate emotions in the self and in others (Mayer and Salovey, 1997)” as cited by Côté, S., & Miners, C. T. H. (2006).

Going a bit sideways, I would like to address the issue of why emotions can be considered information. Experiencing emotions is deeply rooted in our evolutionary past. Even other species have emotions and act on them. To put things simply, emotions are the primitive response to outside stimuli. We feel fear only in the presence of a threat; we feel disgust in the presence of something potentially harmful etc. So emotions are some sort of information on things around us.

At the same time, expressing emotions is a form of communication. Pioneering research done by Paul Ekman has proven that emotions are universal and so is expressing them through facial expressions. This means that before language developed, our distant ancestors communicated with each-other through expressing emotions.

As we know, the subject of communication is essentially information, thus emotions can be considered as information.

Returning to emotional intelligence and its rudimentary definition of “capacity of processing information in the form of emotions”, we have to see if such a thing actually exists. Let me put things a bit differently. Intelligence in its “conventional” definition refers to processing information in the following forms: verbal (words and expressions), quantitative (numbers and mathematical expressions) and visual-spatial. In order for emotional intelligence to actually exist it has to be distinct from “conventional” intelligence. This means that the ability to process information in the form of emotions has to be distinct from the ability of processing information in the form of words, numbers and visual-spatial.

If the above mentioned abilities are not distinct, then Emotional Intelligence is only another fancy name for the same old thing.

As far as I know, emotional intelligence is somehow distinct from “conventional” intelligence. In a very nice study by Côté & Miners from 2006 the relationship between “conventional” intelligence (IQ), emotional intelligence (EQ) and job performance was investigated. Their conclusion was that for people with a relatively low IQ, EQ had a positive influence on job performance. However, for people with a relatively high IQ, EQ had no influence on job performance.

As I see it, Emotional Intelligence partly overlaps with “conventional” intelligence. In the end intelligence is about processing information and if some people can process better information in the form of emotions and others in the form of numbers that is simply it.

What I find interesting is that people with high IQ get the same results regardless of their EQ. This can be because IQ compensates for EQ.

Before ending, I would like to make two final remarks. First, I believe that the ability to process emotions can be educated to a large extent. For people who are not good at processing information in the form of emotions it can be useful to learn (cognitively) what emotions are and how each of them is expressed.

Second, beware of the noise about Emotional intelligence. As I mentioned earlier, there has been a lot of “buzz” around emotional intelligence and to la large extent the actual meaning of the concept has been severely diluted. One particular aspect that I consider to be critical about emotional intelligence is how we measure it. Because emotional intelligence is an ability or capacity of processing emotions any form of measurement should test that ability through tasks.

A conventional IQ test asks people to give the right answer to a problem. However, some (so called) EQ tests consist of self-reported information or in other words answering questions such as “are you a good negotiator?”. Self-reported data is useful for assessing personality traits, but by far it has nothing to do with assessing abilities.
Note: this post is documented from:
Côté, S., & Miners, C. T. H. (2006). Emotional intelligence, cognitive intelligence, and job performance. Administrative Science Quarterly, 51, 1-28.

18 February 2013

What is SMART? Intelligence and its Role in Behavior


It is time now to address the topic of Intelligence and its role in behavior. In the 4D Model of Behavior I have included Intelligence in the Personality dimension since it is a stable personal trait.

As you will read in the following paragraphs, Intelligence is very likely the most important personal trait in humans. But before assessing the role intelligence plays in human behavior, we should first try to define intelligence.

Apparently it is quite easy to define Intelligence because whenever it comes into conversation somehow everybody understands what it is. I said apparently… in fact it is not so easy to give a comprehensive definition of this wonderful human trait. The best I could do in providing a simple clear definition is that intelligence is mental capacity of processing information.

For many years the popular culture has held different understandings of what “being smart” or in more scientific terms intelligence is. Not very long ago intelligence was confused with memory. People who were able to memorize large quantities of information were considered to be smart. But, as you may know already, this is false in the sense that intelligence is about processing information and not simply storing it in the brain.

Another source of controversy and un-clarity in what Intelligence is comes from the fact that (especially in the last 10-20 years) there was an inflation of types of intelligence. The most widely spread is Emotional Intelligence, but by far is not the only one. Without saying that all these types of intelligence are artifacts to sell books and publish scientific articles, I would say that we should not ignore intelligence as a general trait.

I assume that another source of the inflation of types of intelligence is the natural desire of each individual to be smart or intelligent. To put this a bit differently, each individual wants to be able to say that “I’m not very high on IQ (intelligence), but I am high on that type of Intelligence (let’s say emotional)”.

I have news for all of human kind! With a probability of about 70% you are average… ok… I’ll make a concession. If you are reading this, there is a good chance that you are above average intelligence, but not too far from the average.

Coming back to the simple definition of Intelligence – metal capacity to process information – we have to acknowledge that because there are different types of information there are multiple sides of intelligence. Let’s make this a bit clearer. In school people are taught two types of information – verbal and quantitative (numbers). This means that intelligence comprises of processing verbal information and well as numeric – quantitative information. By numeric I mean numbers, abstract expressions and formulas. At the same time, people have not evolved in a library or in a math classroom. A lot of information we have to deal with is visual and spatial, implying that intelligence includes processing of visual-spatial information.

Now that we’ve managed to get a general idea of what intelligence is, let’s go back to the fact that intelligence is a personal trait. This means that everyone has it and at the same time there are individual differences in how much of it each individual has of it. This takes us to the field of psychometric measures or in other words IQ tests. There are several IQ testing methodologies and I don’t want to go into detail on them. What you should take into account is that all these tests measure the extent to which a person is able to process information.

As a funny note, if you want to get a higher IQ score, the best thing you can do is to take the test again …

At the beginning of this post I have mentioned that Intelligence is very likely the most important personal trait of humans. Starting from the beginning of the XX-th century intelligence has been extensively studied and there are some irrefutable conclusions that have been drawn.

First, IQ is the single best predictor of job performance. Simply put it, smarter people perform better at their job. Moreover, the more complex the task is, the higher the predictive value of IQ is in task performance. In other words, IQ predicts better job performance for complex tasks that it predicts it for simple tasks.

Second, IQ is a very powerful predictor of academic performance. This is not really surprising since in school people have to process large amounts of information. By the way, in case you have (or had) to take a standardized test to get into a higher education program, be sure that the test includes a large component of IQ testing.

Third, IQ is a good predictor of life quality. To put this simply, smarter people live better lives. This is due to a higher income (the higher the IQ, the higher the income), higher attractiveness for long term relationships, lower likelihood of committing crimes (or at least getting caught) etc.   

A fun fact about intelligence is that it is positively correlated with semen quality (in men of course).

To summarize this, overall the more intelligent the better. Of course, extremely high levels of IQ can be detrimental, but this is another story.

After learning (or being reminded of) the benefits of a higher IQ, one might want to increase his or her IQ score. In order to see if it is possible to increase someone’s intelligence we should take a look at where intelligence comes from.

Like most personal traits, intelligence is highly heritable. Now, the interesting thing about IQ is that it is more heritable than any other personal trait. Different studies found that IQ is heritable through genes from 40% to 80%. To put this differently, up to 80% of your IQ comes directly from your parents’ IQs.

Environmental factors contribute to IQ, but to a very small degree. Moreover, after childhood and adolescence the environmental factors have virtually zero influence on a person’s IQ.

Quite disappointing news if you thought that you can increase your or your children’s IQ. Well, yes and no at the same time. The evidence that IQ is highly heritable is unquestionable and we simply have to acknowledge it. At the same time, my view is that what we inherit from our parents is some sort of “maximum level of IQ”. This means that to a small extent one’s IQ can be improved through nurture and practice (doing mentally challenging things).

Let me give a numeric example. Let’s say that someone was born with an inherited IQ potential of 125. This does not mean that that person will necessarily reach 125 points on an IQ test regardless of what happens in his or her life. If that someone’s brain is not nurtured and stimulated he or she will probably score about 105 on a test. This means that the remaining 20 points of potential have to be gained through nurturing the brain.

Before ending this post, I would like to address one final issue, namely: Street vs. Academic smart. In general smart is associated with high academic performance followed by high job performance and life success. At least this is the stereotype of a “smart person”.

Academic achievement is caused by high intelligence (plus a lot of work), but high intelligence does not always ends up in the prototype of a smart person.

As I mentioned in the beginning of this post, intelligence can be simply defined as the mental capacity of processing information. Translating this into computer language it is the “speed of the processor”. What kind of information is fed into that processing is another topic.

Most people that are acknowledged to be smart (high intelligence) end up in more intellectual intensive fields. This doesn’t mean that highly intelligent people are not in other areas of society and they simply have never been educated to process mathematical equations or complex language structures.

Some people simply end up being “street smart” because despite their processing capabilities they process very different information than people with high academic training do.

Intelligence is, in my view, one of the most wonderful things of human kind. Even if we can do very little to increase our or other’s intelligence, we can do a lot in being smart at what kind of information we process.   
Note: this post is documented from:
Côté, S., & Miners, C. T. H. (2006). Emotional intelligence, cognitive intelligence, and job performance. Administrative Science Quarterly, 51, 1-28.
Miller, G. F. (2009). Spent: Sex, Evolution, and Consumer Behavior. (chapter 11) New York, NY: Viking.

http://en.wikipedia.org/wiki/G_factor_(psychometrics)

15 February 2013

Self-enforced poverty – an Evolutionary Approach Based on Life History Theory

Why poor people buy expensive useless status products? Read and find out…

As most of you know already, I have a very strong interest in evolutionary psychology and I believe that taking the evolutionary approach helps a lot in explaining and understanding human behavior.

One of the theories I believe to be highly significant and useful in evolutionary psychology is “Life history theory”. This theory explains many apparent paradoxes that we encounter in our social life and gives very nice insights into understanding human behavior. Let me present this theory as briefly and comprehensively as possible.

As I mentioned in earlier posts, any organism, including humans, has two evolutionary “Macro-Goals” namely survival and successful reproduction. What is usually known in popular culture as the “principle” of evolution is “Survival of the Fittest” (sometimes mistaken for survival of the strongest).

Indeed, survival is crucial and all creatures have some sort of survival driven instincts such as “self-preservation”. If we look a little deeper in the evolutionary process, however, we will see that survival is in itself irrelevant. If we agree that evolution is a slow process of selecting genes from one generation to another, mere survival is by far not enough. If an organism survives for a long time but does not send its genes into the next generation through reproduction, eventually its genetic material will be removed from evolution.

To summarize this, mere survival is not enough for the success of an organism in the evolutionary process. An organism has to reproduce in order to be part of the long and slow evolutionary process.

At first glance, survival and reproduction are goals that go “hand in hand”. However, this is not exactly so since during its life an organism has limited resources. Putting things a bit differently, to a large extent survival and reproduction are competing for the limited resources available to an organism.

Life History Theory (introduced by McArthur & Wilson, 1967 and developed in 1975) is derived from general evolutionary theory and describes the allocation of an individual’s material and metabolically resources between short term and long term survival and reproduction. The tradeoff an organism has to deal with is whether to invest in Somatic Effort - growth and maintenance of the body and in the case of humans the mind (knowledge, skills) and Reproductive Effort – attracting a mate, deferring same sex rivals, reproduction and investment in offspring. Moreover, Reproductive Effort consists of two types of investments: Mating Effort – resources needed for attracting, retaining sexual partners and deferring same sex rivals and Parental Effort – resources needed for the increase of the offspring’s chances of survival and successful reproduction.

Again taking the evolutionary perspective, the difference between reproductive and somatic effort is, in fact, a difference between “reproduction now” and “reproduction later”, since somatic effort, even if it leads to higher survival rate or longer life span, has no evolutionary benefit in itself.

Keeping in mind that there is a tradeoff between reproduction and somatic effort (survival), organisms vary on how much of their limited resources are allocated to one or another. Organisms that allocate a lot of effort to reproduction at the expense of somatic effort are considered to follow a “Fast” Life History Strategy. Organisms that allocate a lot of effort to somatic investment at the expense of reproduction are considered to follow a “Slow” Life History Strategy.

To better understand this, consider the following example. Cats tend to have a large number of offspring (between 3 and 6 depending on the age of the mother) twice a year and each generation of cubs receives about 2 months of parental investment from the female and virtually no investment from the male. Cats develop sexually rapidly (a female can have cubs at the age of 10 – 12 months), have relatively short lives, exhibit high infant mortality, are generally of small size, and show very little group cohesion. Cats are a very good example of “Fast” Life History Strategy.

At the other end of the spectrum are, for example, elephants which have a small number of offspring (one or two), have a large gestation period of two years, exhibit slow sexual development, have a low level of infant mortality, live longer, are, in general, of large size and show high group cohesion. Elephants are a very good example of “Slow” Life History Strategy.

Humans as specie have a “slow” life history strategy. This is due to the large amount of time and resources needed for a person to reach reproductive age.

However, there is a lot of variation within our species, some people tend to have more children, to have the first child at a younger age and offer less parental investment, while others tend to have fewer children, have the first child at an older age and offer higher parental investment. A very salient example of this within specie variation is the comparison between India and Europe.

A legitimate question regarding this variance is “what causes it?” The fundaments of Life history theory suggest that life history strategy is an evolutionary adaptation to the environment; thus both the between and within species variation can be explained by differences in environments that different individuals have developed and currently live in.

The two broad types of Life History strategies are evolutionary adaptations to the environment in which a species has evolved. Species that have a “fast” life history strategy evolved under unstable and unpredictable conditions. These conditions lead to a strategy focusing on having more offspring (offspring quantity). For example in an environment which has numerous threats which lead to a high mortality rate within a population the normal adaptation would be to adopt a faster life history strategy because somatic investment will not have evolutionary pay-offs since an organism would die before getting to reproduce.

Species that have a “slow” life history strategy evolved under stable and predictable conditions, which lead to a strategy focusing on the survival of offspring (offspring quality).

In humans, variation in the type of life history strategies adopted can be attributed to both environmental factors such as high infantile mortality, short life expectancy due to poor living conditions etc. and to genetic inherited traits.

As I mentioned earlier, the difference between “fast” and “slow” life history strategy resides in the allocation of resources between reproductive effort and somatic effort (survival). There are also differences in how reproductive effort is distributed between its two (sub)components which are mating effort (acquiring mating partners) and parental effort (investing in the children).

In the case of a “slow” life history strategy, there is a larger parental effort and a smaller mating effort. On the other hand, in a “fast” life history there is an emphasis on mating effort and a relative neglect on parental effort.

Life history strategy is a complex trait and, as far as I know, there is no unique scale or took to measure it to its full complexity. There are, however, three proxies that work quite well.

First there is parental investment received by a person. This parental investment consists of maternal and paternal investment to which it can be added “nepotistic” investment which is the investment received by a person from family members other than the parents. People who have received a low level of parental investment (during childhood) tend to adopt a “fast” life history strategy, whereas people who have received a large level of parental investment tend to adopt a “slow” life history strategy.

Second there is childhood socio-economic status. In essence it measures to what extent a person grew up in a relatively rich or poor family. People who have grown up in relatively poor conditions tend to adopt a “fast” life history strategy, whereas people who grown up in relatively rich conditions tend to adopt a “slow” life history strategy.

Third, there is Socio-Sexual Orientation. This measures the extent to which a person has long or short term mating goals. In other words if a person is more inclined to have short term romantic relationships or long term ones. Socio-Sexual orientation should not be mistaken for “sex drive”. It does not take into account the number of sexual intercourse instances; rather it looks at the number of sexual partners a person has. People with a more restricted socio-sexual orientation (fewer partners and more serious relationships) tend to adopt a “slow” life history strategy, whereas people with a more unrestricted socio-sexual orientation tend to adopt a “fast” life history strategy.

When it comes to Socio-Sexual Orientation there is a significant gender difference, namely that on average men are more unrestricted than women. However, this is not to say that men are unrestricted and women are restricted because there is very large within gender variation. Putting it a bit differently, there are women who are more unrestricted than the average of men and there are men more restricted than the average of women.

Which one of these proxies is better to measure one’s type of life history strategy I can’t say. What I can say is that all of them capture a significant part of the complex trait Life History Strategy, but none captures the entire trait. Also, from my own experience with research in this area there are some correlations between the proxies, but none of them is very high, meaning that each of them captures some related but distinct aspects of life history strategy.

To summarize, life history strategy captures the tradeoff between allocating resources for somatic investment and reproductive effort. People with a “fast” life history strategy allocate more resources to reproductive effort than to somatic investment. People with a “slow” life history strategy allocate more resources to somatic investment than to reproductive effort.

When it comes to reproductive effort, people with a “fast” life history strategy allocate more resources to mating effort (getting mating partners) and less to parental investment. People with a “slow” life history strategy allocate more resources to parental investment and less to mating effort (getting mating partners).

As I mentioned in the beginning of this post, I believe that Life History Theory has many significant implications in practice and it helps explain some apparent paradoxes in social life. Let me explain a bit more.

As you may know, I am Romanian and Romania is not a very rich country. Despite (or in fact because of) this the number of status brand automobiles (such as BMW, Mercedes, Bentley etc.) per capita is significantly larger than in more richer countries in the West of Europe such as The Netherlands (where I life now), France, Germany etc.

Another interesting fact about my home-country is that in 2009 when the country was hit by a severe recession (-7% of GDP) the sales for Ferrari cars actually increased compared to 2008 when the economy was doing well.

These facts are more or less the same for all emerging economies in the East of Europe and Africa, South-East Asia etc. At least from my experience when crossing the former “iron curtain” (the border between western democratic countries in Europe and Eastern former communist countries) there is a clear difference in the type of cars that are seen on the roads. In the west there are significantly fewer expensive status cars, whereas in the east their proportion is huge.

Of course, there are more causes for this difference, but one of them is related to Life History Theory. In more poor and uncertain environments many people are more on the side of a “fast” life history strategy and it is only natural for them to invest more in “mating effort” which includes enhancing one’s status through conspicuous consumption.

I have heard a sad but interesting story about a very poor family who somehow got to be presented on TV before a major Christian holyday. In brief, they were so poor that they couldn’t get a decent meal for that holyday. After the story being presented on TV, a rich man gave that family about 800 Euros (which is a lot of money) to have a decent celebration of the holyday. What that family did with the money… well they bought an iPhone…

Apparently this type of behavior is really stupid and I don’t argue with that. However, this behavior is natural. Simply people with a “fast” life history strategy invest a lot of their often few resources in their status. Unfortunately, buying iPhones or BMWs does not get someone out of poverty.

Another difference between “fast” and “slow” life history strategy is the attitude towards risk. In general all people are risk averse, but again there is variance within our specie on how risk averse or risk seeking we are. People with a more “fast” life history strategy are more willing to take risks especially when they feel a potential threat to their life or well-being (in other words, environmental threats such as recessions, wars, natural disasters etc.). On the other hand, people with a more “slow” life history strategy are more risk averse and avoid taking risks even when there are environmental threats.

This difference in attitude towards risk explains why the people with very limited possibilities are the ones that gamble their last pennies and are likely to get loans with very risky costs.

Before continuing with the argument, I have to say that having a “fast” life history strategy is not wrong neither is having a “slow” life history strategy. Each of them is an adaptation to the environment. Even if some consider that having a “fast” life history strategy is wrong, people who are more “fast” than “slow” in life history strategy are not to be blamed for their behavior. They do what is natural for them to do.

In my opinion the “fast” life history strategy contributes to what I call “Self-enforcing poverty”. If people in very poor societies have many children, then the next generation will be at best as poor as their parents were.

Even if there is an influx of money in societies dominated by “fast” life history strategy, this money will be spent on increasing status which can lead to a runaway conspicuous consumption race. Unfortunately status products will not make people less poor, nor will they give them more opportunities for future development.

In fighting poverty, one crucial aspect is to understand which the sources are of a “fast” or “slow” life history strategy. To a certain extent, life history strategy is inherited through genes, thus very little can be done in this area. At the same time, there is a component inherited through nurture and there things can be improved. Moreover, in stable predictable environments the differences between “fast” and “slow” life history strategies are very small, but things change when the environment is unpredictable and offers cues of life threats such as high infantile mortality, high incidence of diseases, wars etc.

Environments can be changed… and controlled.

Note: This post is documented from:

Griskevicius, V., Tybur, J.M., Delton, A.W., Robertson, T. E. (2011). The Influence of Mortality and Socioeconomic Status on Risk and Delayed Rewards: A Life History Theory Approach. Journal of Personality and Social Psychology, 100(6), 1015–1026.

Figueredo, A. J., Vasquez, G., Brumbach, B. H., Sefcek, J. A., Kirsner, B. R., Jacobs, J. W. (2005). The K-factor: Individual differences in life history strategy. Personality and Individual Differences, 39(8), 1349–1360.

Figueredo, A. J., Vasquez, G., Brumbach, B. H, Schneider, S.M. R. (2010). The heritability of life history strategy: The k‐factor, covitality, and personality. Biodemography and Social Biology, 51(3-4), 121-143.

Simpson, J.A., & Gangestad, S. W. (1992). Sociosexuality and Romantic Partner Choice. Journal of Personality, 60(1), 31–51.