Ian Moore

Risk, Utility and Probability

January 18th, 2012 - Ian Moore  

UTILITY

For the completely rational human being the concept of the ‘utility’ of a thing (that is its ‘usefulness’) should be directly related to the amount of the thing that they receive. For example £10 should be twice as useful as £5. Two cabbages should be worth twice as much as one cabbage.

Actually the relationship between most items and utility is more like the following diagram which depicts the relationship between utility and money for a typical person:

To demonstrate this, how would you answer the following question:

Which would you prefer?

100% chance of winning £1,500
50% chance of winning £3,000

Most people will choose the $1,500 even though logically they both have the same value.

This is because, as you can see from the graph, twice the amount of money corresponds to less than twice the amount of utility.

This utility/money curve of course varies from person to person and how risk averse they are but similar curves exist for the majority of people.

The curve also implies some other things. The further the amount of the resource increases (in this case money) the less the relative difference. For instance your response to the question above will probably be even less logical (and more risk averse) if the amounts were £10 million and £20 million. The other side of the curve implies that £20 probably has more than 10 times the utility of £2. The exception being if you needed the £2 for a bus home, in which case you would be highly risk averse to any gamble.

RISK AND PROBABILITY

This behaviour is also similar to our risk versus probability curve:

If we have a very low probability of something happening (the left hand side of the curve) then there is little perceived risk because it is very unlikely that we would make that choice. For instance if we could bet £1 at 1 in ten thousand odds of wining £10 we are highly unlikely to take the bet.

The right hand side of the curve also is perceived as low risk. It there is a very high probability of something happening we perceive it correctly as low risk.

The highest risk is at the 50/50 probability where it is totally uncertain if an event will happen or not.

From a purely logical perspective this curve does not make sense, it really should be a triangle with straight lines. It differs from this because humans do not easily perceive very low probabilities as being as low risk as they are (and vice versa for high probabilities.) For a probability of 99.9% that some event will happen there is a small doubt in our minds and this increases the perceived risk. consider the following scenario: your house insurance is normally £500 per year but your insurance company has a strange offer on, for £100 per year you can insure your house for all days starting with a T or an S (that is 4 out of 7 days), would you take out the insurance?

We do not react linearly to utility and resource, logically we should.

We do not estimate risk against probability well.

If we can incorporate an understanding of these behaviours into our decision making we will be able to improve it.

Ian Moore

The Framing Effect

December 14th, 2011 - Ian Moore  

The way that a question or situation is phrased has a strong effect on your answer or decision. We tend to make decisions which are closer to the ’starting point’ which the issue has imprinted on our minds.

For instance in one experiment two groups of people were asked (in 5 seconds and without the use of a calculator) to perform the following calculations:

Group 1:
2*3*4*5*6*7*8

Group 2:
8*7*6*5*4*3*2

Obviously, at least for most people, 5 seconds is too short a time to work out the answer. Most people start working from the left and when their time runs out make an estimate based on what they worked out up to this point. Group 1 answers were smaller numbers than in group 2. Their estimates seem to have been affected by the last number they were able to calculate before their time ran out.

In large numbers of tests Group 1 participants answers averaged at 512, Group 2 participants average was 2,250, nearly four times as much. (It is also interesting to note that since the correct answer is 40,320. Both groups dramatically underestimated.)

Another interesting example of the framing effect is when the people were given the following two scenarios (try this out yourself):

Scenario 1:
An event is expected to kill 6,000 people. You can adopt one of two interventions:
A. 2,000 people will be saved
B. There is a 1/3 chance that 6,000 people will be saved and a 2/3 chance that no one will be saved
Which intervention would you choose?

Scenario 2:
An event is expected to kill 6,000 people. You can adopt one of two interventions:
C. 4,000 people will die
D. There is a 1/3 chance that no one will die and a 2/3 chance that 6,000 people will die
Which intervention would you choose?

There are no right or wrong answers to these but let us first have a look at Scenario 1. If you choose intervention A, then 2,000 people will be saved. If you choose intervention B, either everyone will be saved or no one will but the weighted probability is that 2,000 people will be saved (the same as A). Interestingly the vast majority of people (nearly three quarters) choose A.

In scenario 2, intervention C is exactly the same as intervention A and intervention D is exactly the same as intervention B. However the interventions chosen are reversed with the vast majority of people choosing intervention D (over three quarters).

The only thing that has changed between the two scenarios is ’saved’ to ‘die’.

So the way that a decision choice is phrased has a very strong effect on the decision that people make.

Ian Moore

Contradictory Information

November 23rd, 2011 - Ian Moore  

When we are presented with information that fits with our beliefs or tentative decisions we will tend to accept any information that fits and not investigate further. When presented with information that contradicts we will tend to look further and check the validity of the information.

This leads to a skewing of the information that we take in. Most information will have caveats and situations in which it does not apply. When we dig deeper we may find more information that contradicts our position but we are also bound to find information which confirms our distrust of the initial contradictory information. Of course if the initial situation concurs with our initial ideas we don’t look further and so never find any subsequent information that might contradict us.

Psychologists have shown repeatedly that when people taking part in an experiment are presented with a mixed body of information they will pick out that which confirms their beliefs and find reasons why contradictory information does not apply. In a group with opposing beliefs the same information will be interpreted by both sides as supporting their own positions.

For effective decision making we need to firstly be aware of this behaviour and then develop techniques and approaches to ensure that we investigate supporting and contradictory information to the same depth and apply objective criteria to the assessment of both type of information.

Ian Moore

Decision Making: Handling Information

November 14th, 2011 - Ian Moore  

When planning for resilience the way we interpret information is critical to our planning and decision making. This article looks at some of the ways in which our processing of information is flawed and suggests some ways of countering this.

Our brains have evolved over hundreds of thousands of years to help us survive and to that end they are highly effective decision making instruments. However in modern day situations, and especially in business, these mechanisms for decision making may not be the best. So rather than spending time on developing sophisticated decision making strategies it is bound to be useful to understand some of the mechanisms that our brains have developed to make decisions. By understanding these mechanisms we can become sensitised to their shortcomings and so develop approaches to counteract these shortcomings and thus make better decisions.

The way we process information is critical to our decision making. Unfortunately we do not always process this information correctly. We do not always see what is actually there. If we are basing our decisions on correct information which we have processed incorrectly this will obviously lead to faulty decisions.

We tend to see what we expect to see. Have a look at the following diagram. Which square looks darker, A or B?

The vast majority of people think that square B is lighter than square A. However if we draw some uniform grey bars on the diagram we can see that A and B are exactly the same shade.

In the first diagram without the bars we make the assumption that the cylinder is casting a shadow and our brains automatically make the B square appear lighter than it actually is. Now look back to the diagram without the bars on. Even though you know that squares A and B are exactly the same shade B still appears to be lighter.

Here is another example of how we see what we expect to see rather than what is actually there. Try reading the following:

I cnduo’t bvleiee taht I culod aulaclty uesdtannrd waht I was rdnaieg. Unisg the icndeblire pweor of the hmuan mnid, aocdcrnig to rseecrah at Cmabrigde Uinervtisy, it dseno’t mttaer in waht oderr the lterets in a wrod are, the olny irpoamtnt tihng is taht the frsit and lsat ltteer be in the rhgit pclae. The rset can be a taotl mses and you can sitll raed it whoutit a pboerlm. Tihs is bucseae the huamn mnid deos not raed ervey ltteer by istlef, but the wrod as a wlohe. Aaznmig, huh? Yaeh and I awlyas tghhuot slelinpg was ipmorantt! See if yuor fdreins can raed tihs too.

Even though all the words are seriously misspelt we still impose meaning on them. We are not seeing what is actually there but what we would like to see and what we expect to see.

So that is just a couple of examples of how we see what we expect to see rather than what is actually there. In order to make effective decisions we need to see what is actually there not what we expect to see.

If you would like to improve your decision making by seeing what is actually there, try making a list of the ways that you see what you expect in information rather than the actual information. When you have done this you could go through the list and see if you can develop any techniques that would help you see information as it actually is.

There is another way in which information affects our decision making. That is when we have to much information. The next diagram is a simple picture. It is not animated in any way. However when you look at it, it will appear to be moving.

This is a nice example of how too much data causes confusion. Even though the diagram is not moving it still appears to move because of the way our eyes view the picture. If you don’t believe that it is not moving try focusing on one individual spot. You will see that it is not moving but other areas appear to move. Then try to focus on one of the areas that still seems to be moving. It will now appear to be stationery and other areas will appear to move. Or if you focus on the two small red markers on the two top, middle circles, you will see that these circles are stationery.

If you would like to improve your decision making try making a list of the ways that too much data causes problems for your decision making. When you have done this try going through the list and see if you can devise techniques that would help.

Ian Moore

Decision Making and the Brain

September 23rd, 2011 - Ian Moore  

CARRI welcomes Ian Moore as our guest blogger. Mr. Moore specializes in the psychology of decision making and how, by understanding how we make decisions, we can improve the way we make decisions. He is the author of several books on the topic and also runs a variety of workshops, gives keynote presentations, and facilitates group sessions. Today’s blog details the connection between decision making and resilience. For more information please visit http://www.unthinkablethinking.com or email ian@unthinkablethinking.com.

My personal fascination is about how we make decisions, and the articles that I will be writing for this blog are about decision making and how, by understanding some of the ways that we make decisions, we can improve our decision making.

 What has decision making got to do with resilience? When we are planning to create a more resilient group or organization, we are constantly making decisions about how we can best do this and what threats we need to take into consideration. On the personal side when we experience a crisis situation, we are making decisions for ourselves and others. Unfortunately in all these situations our decision making processes are subject to a number  of built in biases; however if we can understand these biases, then we are in a position where we can develop techniques and ways of thinking to counteract these innate biases.

It is difficult to clearly quantify how much poor decisions cost either in monetary terms or in lives and suffering, but it would seem obvious that even a small improvement in our decision making could have really significant benefits. In this article I would like to introduce some of the ideas that I will be developing in future articles.

I will start by stating the obvious – we make decisions with our brains. But let us consider what our brains are for. They have evolved over hundreds of thousands of years to help us survive, and to that end they are highly effective decision making instruments. However, in modern day situations these mechanisms for decision making may not be the best. So rather than spending time on developing sophisticated decision making strategies it is bound to be useful to understand some of the mechanisms that our brains have developed to make decisions. By understanding these mechanisms we can become sensitized to their shortcomings and so develop approaches to counteract these shortcomings and thus make better decisions.

We can make better decisions. The good news is that we have a brain! In our brain we have over ten thousand million neurons, and the number of possible interconnections between these neurons is 10 followed by 100 zeros. We have an immensely complex piece of machinery in our brains. However, is the brain fixed in the way it processes information?

In order to drive a traditional black cab in London, a taxi driver has to pass ‘the knowledge’. This is a test about the streets of London and the best way to navigate around them. It has been known for some time that the hippocampus, an area of the brain, is responsible for processing geographical information. In the year 2000 a team from University College London scanned the brains of some taxi drivers and found that their hippocampuses were bigger than those of normal people. This is a really significant finding! It shows that exercise and practice can physically develop areas of the brain and increase the connectivity of the neurons.

The bad news is that the brain has a very specialist design. It has evolved over hundreds of thousands of years for survival purposes and not necessarily for making the best decisions. Part of the specialist design is our memory systems. When brain scans are done on chess players some interesting results are found. Masters and Grand Masters seem to have activity towards the rear of the brain which is normally associated with our memory systems. Less competent chess players tend to have most activity towards the front of the brain, in the pre-frontal cortex, which is normally associated with decision making. When we make decisions are we using our memory of past situations or analysing each situation anew?

Large areas of our brains have developed for pattern recognition. This is obviously useful for recognizing objects and faces. Unfortunately we also tend to see patterns when there are actually none there.

Our brains are also very good at establishing habits. These are very useful ’short cuts’ to our decision making processes. We don’t need to think about everything that we come across on a daily basis. Let’s have a look at one habit we have developed – how we fold our hands.

So let’s try it out. I’d like to ask you to fold your hands. If you look at your hands you will notice that one index finger is above the other one. When we are young we have to learn to fold our hands like this. Each way is equally likely at this point. However a habit quickly forms and one way becomes dominant. When we are older we will usually only fold our hands in one way. So for most of our lives we have been folding our hands in only one way. You would think that a habit as well established as that would be hard to break. But let’ try this. Try folding your hands so that the other index finger is on top. What does it feel like? Most people find this quite uncomfortable but bear with me for a moment. Let’s try slowly folding our hands back to the original position and slowly back again to the second position. And then back again, and back again, and back again, and back again, and back again, and finally back again. Now just shake your hands. So let’s try it again. I’d like to ask you to fold your hands again. Can you remember if this is the way you did it originally?

What’s interesting about this is that most people, after only five repetitions, feel much less awkward. Some people cannot even tell the difference any more. This is a very simple example of how a life-long habit can be overturned (or at least lessened) by only five practices at doing it a different way.

We have seen that our brains have some limitations when it comes to decision making.

The good news is that if we understand what these limitations are, we can reprogram even long established habits. We can also grow parts of our brain.

So if we can understand how our decision making works, we can spot the deficiencies in our decision making. Knowing what these deficiencies are, we can take countermeasures to improve them.