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Economics of irrational human activity
In traditional economics, people are treated as ‘rational economic persons’ (Homo Economicus) who make decisions rationally and make optimal choices, but real people are influenced by emotions and biases and often behave irrationally. The economics of such irrational human behaviour has been studied in the field of behavioural economics (Behavioural Economics).
Behavioural economics attempts to understand how humans make irrational decisions and incorporate this into economic models, and the following irrationalities have been identified
- Prospect Theory: people feel losses more strongly than gains and are more likely to make irrational decisions to avoid losses.
- Hyperbolic Discounting: people overestimate near-term rewards and prioritise short-term gratification at the expense of long-term benefits.
- Anchoring: subsequent decisions are influenced by the initial information (prices and figures) presented.
- Confirmation Bias: people only focus on information that supports their beliefs and ignore data that disproves them.
Irrational behaviour also affects individual consumer behaviour and the market as a whole in the following ways
- Marketing and consumer behaviour: companies utilise behavioural economics and exploit consumer psychology in their pricing and advertising strategies (e.g. bait and switch effect, bandwagon effect).
- Financial market bubbles and crashes: herd mentality and overconfidence cause financial market bubbles and crashes (e.g. dotcom bubble, Lehman Brothers collapse).
- Policy design (nudge theory): governments introduce mechanisms (nudges) to encourage behaviour so that people make more rational choices (e.g. default pension membership).
Traditional economics has assumed ‘perfect rationality’, but the emergence of behavioural economics has led to a demand for more realistic economic models, and developments in AI and data analysis have led to the quantification of patterns of irrational behaviour and their application to marketing and economic policy.
Reference books describing these are discussed below.
Thinking, Fast and Slow
“Thinking, Fast and Slow“, written by Nobel Prize-winning economist Daniel Kahneman, delves deeply into our thought processes.
Kahneman proposes that human decision-making is carried out by two systems: ‘fast’ and ‘slow’.
- System 1 (Fast).
- Intuitive and immediate reactive thinking
- Decisions based on emotions and experience
- Less effort and quicker decisions, but prone to bias (cognitive bias)
- System 2 (Slow)
- Logical and analytical thinking
- Decisions requiring calculation and deliberation
- Requires accuracy, but is energy-intensive and time-consuming
The main topics covered in this publication include.
- Heuristics (intuitive decision-making)
- We routinely use efficient shortcuts (heuristics) to make decisions, which can lead to wrong decisions.
- E.g. ‘availability heuristic’ → the more recently heard information is perceived as more important (e.g. influence of news).
- Prospect Theory.
- People are ‘more likely to dislike losing money than gaining it’ (loss aversion bias).
- Example: ‘the pain of losing 10,000 yen’ is psychologically greater than ‘the pleasure of receiving 10,000 yen’.
- Biases (cognitive distortions)
- Confirmation bias: only gather information that one wants to believe.
- Hindsight bias: people assume that they knew this from the beginning.
- Anchoring effect: being pulled in by the first figures or information presented (e.g. pricing).
- Relationship between decision-making and happiness
- Is human happiness based on momentary ‘experience’ or ‘memory’?
- ‘Peak-End Law’ → people tend to remember only the peaks and ends of events.
Fast & Slow is a book that scientifically elucidates how our thinking works and how it influences our decision-making, with content that can be applied to all aspects of business, investing, marketing and everyday life, providing very practical suggestions and asking the question ‘Are my thoughts really right?’ The book provides an opportunity to ask the question ‘Are my thoughts really right?’.
Predictably Irrational
“Predictably Irrational: Behavioral Economics Reveals Why You Choose It” is a book by behavioral economist Dan Ariely that reveals how irrational (but with predictable patterns) human decision making can be.
We usually think we are making ‘rational decisions’, but in reality we often unconsciously make biased choices, Ariely shows through various experiments that irrational human behaviour follows certain patterns, and states in this book that humans are ‘predictably’ irrational He states that humans are ‘predictably’ irrational.
Some of the main themes dealt with here include
- The trap of relativity.
- People make decisions according to ‘comparatives’ rather than ‘stand-alone values’.
- E.g. ‘Given three options, the middle one is more likely to be chosen’ → strategy of offering a more expensive option in order to sell a luxury product.
- Zero price effect (the magic of free)
- People forget rationality when it comes to ‘free’.
- E.g. In the case of ‘1 yen chocolate vs. 0 yen chocolate’, the free option is overwhelmingly chosen.
- Anchoring.
- People are strongly influenced by the first number or information they are presented with.
- E.g.: ‘When you are first told that the price is 10,000 yen, the price of 8,000 yen seems cheaper’.
- Endowment Effect
- People overestimate ‘what they own’.
- e.g. At a flea market, people think ‘this should sell for more’.
- Paradox of choice
- Too many choices make it difficult to make a decision.
- Example: ‘Six types of jam sell better than 20 types of jam’.
- Procrastination
- Procrastination is the tendency to postpone important decisions because of the temptation in front of you.
- E.g. ‘I’m going to start a diet, but just for today I’m going to eat something sweet’.
- Differences between social and market norms
- ‘Money’ and ‘emotions’ are opposites.
- E.g. ‘Ask a friend to help you for free vs. pay 100 yen to help you’ → Paying 100 yen destroys the friendship (when money is involved, the relationship becomes a business).
‘Predictably Irrational’ explains, with experimental data, ‘Why can’t humans think rationally?’ with experimental data, and shows how irrationality is predictable, and is a book that will make you rethink ‘Are my choices really rational?’ The book provides an opportunity to rethink the question ‘Are my choices really rational?
Relevance of AI technology
Consider the relationship between such irrational human behaviour and AI technology: AI plays a role in analysing, improving and exploiting the irrationality of human decision-making as follows.
1. analysing and predicting irrational behaviour by AI: AI analyses vast amounts of data and makes more accurate predictions by learning patterns and biases found in human decision-making.
- Behavioural economics x AI: AI incorporates insights from behavioural economics (e.g. prospect theory, confirmation bias, anchoring effects) to predict market and individual choice behaviour.
- Marketing personalisation: AI learns personal purchase history and behavioural data to present advertisements and products at the right time (e.g. retargeting ads).
2. correction and support of irrational decisions by AI: AI is being used to correct human biases and support more rational decision-making.
- Predicting financial market behaviour and investment support: algorithmic trading by AI eliminates irrational investment decisions based on human emotions and makes trading more efficient. Behavioural finance x AI to analyse investors’ tendency to over- or underestimate risk and support risk optimisation.
- Healthcare and diagnostic assistance: an AI diagnostic assistant that compensates for biases in patients’ self-diagnosis of symptoms (e.g. “it’s a minor illness, so I don’t need to go to hospital”).
3. nudge AI: AI to guide behaviour: governments and businesses utilise ‘nudge theory’ and use AI to guide people’s behaviour in the desired direction.
- Behaviour optimisation in smart cities: to prevent traffic congestion, AI suggests optimal routes based on real-time data. To optimise electricity consumption, AI learns users’ usage trends and encourages energy-saving behaviour.
- Promoting behaviour change (healthcare and environmental policy): AI provides recommendations for healthy eating and exercise. To protect the environment, AI supports waste sorting and reinforces recycling behaviour.
4. AI and fairness/ethical issues: when AI learns irrational human behaviour, there is also a risk of reinforcing bias.
- Extended discrimination and bias: when AI learns from historical data, it may internalise biases such as race, gender, income inequality, etc. and make unfair decisions. E.g. risk of hiring AI having biases such as ‘giving preference to men’ based on historical data.
- Algorithmic brainwashing and selection distortion: social networking and news recommendation algorithms foster confirmation bias and bias towards certain opinions (echo chamber phenomenon). Behavioural economics suggests that ‘people choose only information that is good for them’, and AI may accelerate this tendency.
Future developments in AI technology are expected to evolve the relationship with irrational human behaviour.
- Interactive AI that understands human biases: AI understands emotions and irrational thinking and responds more empathetically (e.g. mental health care AI).
- Decision support by agent AI: when an individual makes a decision, the AI provides an optimal solution while compensating for biases. E.g. when buying an insurance policy or a house, the AI asks, ‘Is this really a rational choice?’ advice.
AI technology is developing in the direction of ‘analysing’, ‘correcting’ and ‘utilising’ irrational human behaviour. On the other hand, there is a risk that AI itself learns biases and encourages irrational decision-making, which requires ethical controls. The fusion of behavioural economics and AI is expected to evolve further and utilise the technology in a more human-friendly way.
Other reference books
Reference books and others relevant to irrational human behaviour and economics include
Books on understanding the relationship between behavioural economics, psychology and economics
‘’, Nate Silver.
→ Analyses how humans make false predictions and how this affects the economy and politics.
‘‘ (Chip Haas, Dan Haas).
→ Explores how people make bad decisions and how to improve decision-making in business and the economy.
Irrationality in markets and financial markets
“→ Explores the irrational human behaviour behind historic economic bubbles.
“, Charles Geister.
→ How bias and overconfidence drive markets in the financial industry.
“, Hershey Sheffrin.
→ Explains how investors behave irrationally from a behavioural finance perspective.
Nudges — applications to policy.
“Richard Saylor and Cass Sanstine.
→ Using behavioural economics to design government policy and guide people’s decision-making.
“, Richard Saylor.
→ Detailed explanation of how behavioural economics is applied to real economic policy and corporate strategy.
Irrationality in organisations and business.
“, Nassim Nicholas Taleb.
→ How people irrationally predict and react to unexpected events.
‘’(Chip Haas and Dan Haas).
→ Analyses the psychology of organisations and individuals’ refusal to change and explores how it can be improved.
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