“It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
— Sherlock Holmes, A Scandal in Bohemia
For years, we have believed in the rational theory of economics that is all important decisions are made basis sound rational thoughts with an objective of maximising utility. Daniel Kahneman, winner of the Nobel Prize in economics criticises the rational theory and familiarizes the readers with different kinds of biases and their potential influence on human judgments. He has proved his arguments through scientific research during his long career.
Key distinctions:
1. Humans Vs Econs:
a. Econs are rational agents
b. Humans are prone to judgment errors
2. System 1 Vs System 2: Two systems (not physical) in human mind
a. System 1 is quick, requires less energy consumption, confident and is in charge most of the time. It is gullible and quickly jumps to conclusions. It has a long evolutionary history and is very essential for survival of humans.
b. System 2: The lazy system which requires much more energy to activate. This system is uncertain and is doubtful. System 2 is evoked when complex decisions are to be made. This system is also limited by the knowledge (or the lack of it) of the individual
3. Experiencing Vs Remembering Self:
a. Experiencing self can be thought as the sum total of experiences of the individual
b. Remembering Self: Responsible for remembering the stuff and influencing future decisions. Results mostly depend on the peak and the end of the experience rather than the whole experience
Ten Key concepts:
1. What you see is all there is (WYSIATI): WYSIATI or the availability bias is the cognitive bias in which a person makes decisions basis information that is easily available or top of the mind without doubting many things that they don’t know enough about. Ex: People will be willing to pay more for an insurance post a disaster because of excessive media coverage. They will think that a disaster is highly likely which might not be the case
2. Anchors: Cognitive bias to influence decisions basis a reference point. Ex: Brands offer discount on MRP where MRP acts an anchor. Similarly, if your last mobile phone costed you INR 30k, next one would be judged basis this anchor.
3. Base rate neglect: Cognitive bias where underlying base is neglected and an easier more intuitive information is used to make judgements. Ex: Suppose we know that 1% of asymptomatic Indians are COVID positive at any point in time. If an asymptomatic person gets his RTPCR test positive (assume accuracy of RTPCR (both for +ve & -ve result) to be 80%), can you guess the probability of him being actually COVID positive? If you are guessing anything above 10%, you are neglecting the base rates
4. Confirmation Bias: We look for information that is coherent with our prior beliefs and reject information that contradicts. Ex: On social media, we are comfortable with news that aligns with our prior biases than which challenges our biases. I believe the Machine learning algorithms used by social media giants would be utilising this trait to improve engagement and thus it is better to read news from sources which are not personalised
5. Substitution: Humans tend to substitute a difficult question with an easy one. Ex: When asked whether you are an above average driver, majority of drivers respond yes, because it is a very complex question to estimate average and compare; and thus, they substitute it with a very easy one; Do I find driving easy?
6. Prospect Theory: The value function of gains and losses passes through the reference point and is s-shaped and asymmetrical. The value function is steeper for losses than gains indicating that losses outweigh gains.
7. Components of Prospect Theory:
a. Reference Point: The perceived value of losses or gains not only depends upon the final state but also on the reference point. Ex: Athletes with bronze medal are usually happier than athletes with Silver medal in Olympics. Athletes appearing in gold medal match already have a silver medal and thus a silver medal is their reference point whereas for athletes appearing in a bronze medal match, reference point is no medal.
b. Loss Aversion: More emphasis is given to avoid losses than to achieve equal probable gains.
c. Possibility effect: Cognitive bias where extremely high importance is given to a highly improbable event compared to a zero-probability event. Ex: A 0.05% chance of becoming an IAS officer attracts ~15 L UPSC applicants each year; 0% would make it 0.
d. Certainty Effect: Cognitive bias where certain events are given much more weight than events with high probabilities. Ex: Which bonus structure will you choose? 12% of your yearly salary subject to company meeting business targets with 95% probability (no bonus if company fails to meet the target) vs 10% of your yearly salary irrespective of company’s performance.
8. Endowment Effect: Value of what you own increases and the loss from losing it is perceived higher than the value of the object. Ex: Apple stores let people use their products as much as they want to create a sense of ownership and hence utilising endowment effect
9. Narrow framing: Cognitive ease associated with not looking things holistically as comparing all options together can be a very complex task. Ex: When required, we tend to sell stocks which have been profitable for us as of now rather than looking at the entire portfolio
10. Planning Fallacy: Author argues that planning happens mostly based on best case scenarios rather than the practical possibilities; He proposes that a pre-mortem of what could possibly go wrong (taking cues from such projects in the past) would help planning realistically. Ex: Almost all major projects are finished post the initial committed date
While reading these you must be thinking that this is not you, you are not susceptible to such nonsensical biases. But believe me, the book talks about experiments done on best of the minds (Ivy league college students/policy makers/subject matter experts) to validate these theories.
Link to Kahneman’s talk at Google: https://youtu.be/CjVQJdIrDJ0
Disclaimer: Explanation of the concepts/examples in this article are as per my understanding of the book and thus might be inaccurate/different from the book.
