The Psychology of Choice: Understanding How Heuristics Shape Decision-Making
Let’s dive into the secrets of our minds, especially the part that thinks without us even realizing it.
Did you know that a huge 90% of what we think is influenced by this sneaky subconscious? Daniel Kahneman breaks it down in his awesome book “Thinking, Fast and Slow”. He explains how our brains work in two different ways – one is quick and instinctive, while the other is slow and thoughtful.
Get ready for a cool ride exploring how our minds make decisions!
In this article, I aim to shed light on how our thinking processes and the hidden shortcuts called heuristics play a crucial role in shaping our decision-making.
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| Photo by Caleb Jones on Unsplash |
The Illusion of Validity
A study shows that a lot of trading (in the context of shares) often leads to failure.
Brokers engaging in frequent buying and selling typically experience poorer outcomes than those who buy and hold. In the realm of stock markets, there is often a tendency for humans to assign greater importance to the skill of brokers than to mere chance, a common cognitive error (not thinking of the regression to the mean).
As brokers work in a “low validity environment” (there is a long time between an action and an effect and there are many variables) their ability to learn is limited. Hence, thy cannot build up true expertise.
Intuitions and Formulas
Formulas are in many cases (especially in an environment of high variability) more accurate than expert judgment. Different studies address this topic:
- In a study, Meehl makes a comparison of statistical formulas and experts’ opinions. He concludes that the formulas perform significantly better or, at worst, as well as the experts (but are significantly cheaper to produce).
- Here is an interesting study about martial success: Success of a marriage = frequency of sexual intercourse - frequency of arguments.
- A study by Ashenfelter addresses predicting future prices of Bordeux wines. A simple formula based on statistics was significantly better then the results experts achieve.
But is experts’ intuition always worse than pure statistics?
The researcher Gary Klein does not think so. He is an advocate of a school that assumes that expert opinions based on intuition are better than predictions made by algorithms. This contradicts the standpoint of Daniel Kahneman and the studies shown above.
Nevertheless, Gary Klein and Daniel Kahneman collaborated on the topic “experts’ intuition”.
The results suggest that experts can certainly have good intuitions and that they can even outperform algorithms. However, whether experts can really acquire true expertise depends on the field:
- Experts in fields with high variability (economics, stock pickers, clinicians, …) have a very hard time. The forecasts are usually long-term, and they work in environments where it is difficult to learn (it takes a long time to get feedback).
- Experts in areas with low variability and fast feedback (good learning opportunities) can acquire expertise much faster. Examples are chess players, fire department incident commanders, etc.
Furthermore, it turns out that short-term anticipation and long-term forecasts are two different things.
Through many hours of talk therapy, psychologists acquire an intuition of how a patient is currently feeling and learn to anticipate how they will feel in the next few minutes of the therapy session. This usually works well. However, some psychologists make the mistake of also believing that they have a good intuition about the patient’s long-term development - but again, this is an environment with high variability - valid predictions are very difficult to make.
Overconfidence and Overestimation
Optimism is healthy.
It comes with traits such as having a higher life expectancy and being less likely to suffer from depression.
However, optimism can be counterproductive when it comes to forecasts: estimates made by optimistic experts in their field are more likely to be wrong than those made by less optimistic experts. In our society, however, the more optimistic (self-confident) experts carry more weight.
The New Expectancy Theory
The work on this topic was part of why Daniel Kahneman earned the Nobel Prize in Economics.
For a long time (and still today in simple models), the “homo economicus” is used as a model for a person. It is a person who always makes rational decisions with complete information.
However, this has little to do with reality.
The first work on the subject of incompletely rational economic decisions goes back to Daniel Bernoulli. His theorem explains why people tend to make a lower-risk decision in a lottery or even pay a premium for the low-risk alternative. Daniel Kahneman and his fellow researcher Amos Tversky criticize Bernoulli’s work for not taking the reference point into account: someone who is wealthy is willing to make decisions with higher risk than someone who is not wealthy.
A main factors of the New Expectancy Theory is the loss aversion. It describes the fact that we weigh losses more heavily than gains. This can be seen, for example, in two-sided lotteries. Would you take the following lottery:
- You lose 100$ with 50% and win 102$ with 50%.
This lottery has a positive expected value. However, it also has the potential of losing you 100$ and as most people are risk averse they do not take it. Actually, the premium needs to be higher for people to accept it (e.g., lose 100$ but win 150$).
Let’s do another lottery. Choose one of the following two lotteries:
- You earn 1000$ with 90% probability or get nothing 10% of the time.
- You receive a fixed 900$.
The expected value is the same, but most people would choose the second option.
When it comes to avoiding losses our behavior pivots and we are prepared to take risks in order to avoid losses.
- You lose 1000$ with 90% probability or lose nothing 10% of the time.
- You lose a fixed 900$.
In this case most people tend to take the risk and go for the first option.
Rare Events & Risk Strategies
We are willing to pay a premium for certainty and we give more weight to low probabilities. The effects are referred to as:
- Possibility effect and hope effect: in contrast to a probability of 0%, a small probability creates hope (even it is just the fraction of a percent). These small probabilities are overweighted as e.g. in lotteries.
- Certainty effect and safety effect: We are willing to pay a premium in order to produce a safe effect, even if this may not be rationally optimal.
- To increase the probability of winning a million from 95 % to 100 %, we are prepared to spend significantly more than 50,000$.
- A 98 % probability of winning 10,000$ vs. 100 % probability of winning 9,500$. The expected value of the second option is lower, but is preferred.
Our irrational decision-making in these situations is driven by emotions. In the initial scenario, we envision the emotional distress of being unlucky (5%) and not winning the million. To circumvent this emotional state, we end up paying a premium well above the expected value of the lottery.
Terrorism is, for example, a method that focuses on the possibility effect. Although we know that the probability of becoming a victim of an attack is very low, certain situations trigger thoughts in our minds that are unpleasant and we give the danger a higher weighting.
This biases are reversed in the loss zone. We are more likely to take risks, even if the probabilities of being successful with this strategy are rather low (hope effect).
- A settlement at a court hearing: pay 50,000$ vs. litigation and pay 60,000$ with 90%. Here we are more likely to prefer the trial because there is a glimmer of hope of avoiding the loss.
The human behavior in this cases can be summarized to: In the profit zone we are risk-averse and in the loss zone we are risk-seeking.
Keeping (virtual) Accounts
Virtual accounting means that we keep different accounts for different expenses, even though the following actually applies: money = money.
For example, we are reluctant (loss aversion) to realize losses in the stock market. We are, however, more likely to sell shares that have made profits than those that have made losses. From an economic point of view, it makes more sense to sell the losers. Winners are prone to generate further gains in the future, whereas losers tend to fare worse in subsequent performance.
A mental distortion in this context is the “sunk costs” (cf. article about the Scottish Parliament): Instead of admitting losses and, for example, terminating projects that are not going well, we invest more and more, because “we’ve come too far and invested too much to stop now.”
Reversals
Preference reversal describes the fact that decisions depend in part on the context in which they are made.
As an example, Kahneman cites a study in which donations are collected for (i) dolphins and (ii) farm workers.
Viewed independently of each other, people are willing to donate more for dolphins. However, when the questions are asked simultaneously, this is reversed: people tend to donate more for farm workres than to dolphins.
The explanation is that the moral component is taken into account - morally speaking, it makes more sense to donate to humans than to animals.
We have two Selves
To describe what our two selves are I want to share an experiment from Daniel Kahneman involving cold water exposure. Participants had to place their right hand in a container of unpleasantly cold water and record how unpleasant it felt with their left hand using arrow keys.
- The first experiment lasted 60 seconds with 14°C cold water. Afterwards, the participants were allowed to dry their hands with a warm towel.
- The experiment was then repeated: this time a valve was opened after 60 seconds and warm water was added - but only enough to raise the temperature to 15°C. The participants then had to keep their hand inside for another 30 seconds.
Objectively speaking, the second experiment is worse than the first because it is the same as the first with an additional 30 seconds in a weakened form.
The participants had to do a third experiment. They were asked which of the experiments they wanted to repeat. 80% opted for the second experiment.
Objectively, this does not make sense.
This can be explained by the fact that memories are stored differently than we experience them and the duration is not taken into account. In our memories the maximum value (pain or pleasure) and the final value are averaged. As the end of the second experiment was somewhat more pleasant, most people opted for it.
Daniel Kahneman uses the study’s results to introduce the concept of two selves: the experiencing self and the remembering self. Despite experiencing well-being differently, decisions often favor the remembering self. We are willing to let our experiencing-self suffer to form good memories.
Thank you for reading!
This was the second part of my in-depth series exploring “Thinking, Fast and Slow” by Daniel Kahneman. Check out the entire series here: