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Rationality, Fairness, Happiness - Book Review

1 August 2013

Dr. Moria Levy

As its name suggests, the book "Rationality, Fairness, and Happiness” compiles essays written by Prof. Daniel Kahneman, most of them in collaboration with research partners such as Amos Tversky. These articles constitute a partial collection of publications spanning 1974 to 2003, appearing in academic journals in psychology, economics, and general sciences. Edited by Maya Bar Hillel, the book was published in 2005.

Reading a collection of articles naturally involves overlaps and repetitions due to interdependent topics and recurring experiments. However, the articles also explore distinct and seemingly disparate subjects, requiring thoughtful consideration to discern the common thread binding them together. A common theme across all of Kahneman's studies is his exploration and proposition of models to understand counterintuitive thought processes.

The book covers the following topics:



Fairness in business processes


The perception of suffering and happiness

Effects on decision-making


While the book is decidedly academic, it is relatively accessible due to Kahneman's engaging writing style and the inclusion of experiment examples. It is recommended for enthusiasts of the genre, offering valuable insights. The book also features an introduction and an autobiography, connecting readers to the author's journey from childhood in Tel Aviv to the moment of receiving the Nobel Prize.

Happy reading!


People often underestimate probabilities, a bias influenced by factors such as representations, availability, and anchors. Here are specific presentations of these influences:


  1. Insensitivity to the probability in the first place of a sample: When informed about a professional with a specific trait, individuals tend to assess the profession based on the trait rather than considering the probability of that profession in the first place. For example, if told the person is modest and hidden and asked to evaluate whether he is a lawyer or an author, many will overlook the statistical rarity of librarians and incorrectly identify him as a lawyer.

  2. Insensitivity to sample size: When asked to evaluate the feasibility of an event in a sample of size X, individuals often overlook the sample size, consistently providing the same answer regardless of size. For instance, when presented with information about two hospitals recording the daily percentage of boys born over a year and asked where more days with at least 60% boys occurred, most would erroneously point to the same probability. From a probabilistic perspective, larger samples result in more minor deviations from the mean, making such estimations inaccurate.

  3. Misconceptions of chance: People often expect a specific sequence of events to represent overall probability. For instance, when asked about the higher chance between the birth sequence of daughter, son, daughter, and son, or the birth of four daughters, many tend to believe the second option is more likely, associating it with probability and "fairness." However, the likelihood of both events is the same.

  4. Insensitivity to predictable dimensions: Some issues are predictable, while others are not (e.g., share value). Individuals often do not attach significant importance to whether something can be predicted, expressing the same confidence even in subjects where prediction based on available data is not feasible. This creates an illusion about the validity of their predictive abilities even when not applicable.


  1. Ease of retrieval of examples: When examples are easily retrievable, we tend to perceive them as more common. For instance, if presented with a list of names equally split between men and women but with more famous individuals of one gender, we might incorrectly assume that this gender dominates the list.

  2. (i) Search format efficiency/ease of imagination: When assessing the prevalence of one thing over another, we scan mental examples, and the ease of retrieval influences the outcome. For example, when asked whether a specific letter is more common as a first or third letter in words, our brain's search pattern may lead us to find more examples of it as a first letter, basing the result. Ease of imagination, a similar bias, occurs when we attempt to illustrate examples without actively seeking an answer. Examples that are easier to explain, such as those from smaller groups, may erroneously appear more common.

  3. Pseudo-correlation: People often overestimate the frequency of two events occurring together if they have an associative relationship. The stronger the association, the more likely we perceive these events as happening together.

Anchoring and Adjustments:

  1. Insufficient adjustments: Adjustments are often inadequate as they are based on anchoring to an initial value or partial result. When estimating, an initial value is an anchor, and the order of data provided affects the assessment. For instance, the first data presented tends to be used for partial calculations, impacting the final estimate.

  2. Cutting events and consolidation events: People tend to overestimate the probability of two phenomena occurring together (cutting events) and underestimate events where only one of two phenomena occurs (consolidation events).

  3. Subjective probability distributions and contexts: Subjective probability estimates are influenced by how questions are framed, with the definition of the question affecting the answer. Results are tied to the anchoring in the question, shaping the thought process.


When making uncertain decisions, individuals often rely on three heuristics: presentation, availability, and anchoring. While these heuristics are generally efficient and helpful, they can lead to systematic and predictable errors. Recognizing and understanding these biases can enhance the decision-making process.


Individuals making decisions often involve an assessment, as discussed in the previous section. However, many choices also incorporate an element of preference. Two significant preferences that intricately influence decision-making are risk and loss. People exhibit an aversion to risk when it comes to gains; even with the possibility of a safe, albeit lower, profit, individuals prefer it over higher profits. Studies reveal that risk aversion remains nearly constant irrespective of the size of the risk. Conversely, in situations involving loss, people tend to prefer risk over certainty, aiming to avoid the impending loss, which they strongly dislike. Losses pose a more significant threat than gains, leading individuals to lean towards conservatism in the face of potential losses.

Preferences also extend to how information is presented. For instance, a study on lung cancer demonstrated variations in poll results among patients and physicians based on how questions were framed concerning mortality or survival rates.

Ownership also plays a role in preferences. The "ownership effect" suggests that individuals attribute high value to possessions, making it challenging to part with them. This effect is closely tied to the previously mentioned loss aversion.

People tend to prefer considering sub-decisions separately to streamline the decision-making process, even though combined decisions often indicate an advantage for a particular alternative, not necessarily the one chosen when decisions are made independently. Research on preferences shows that individuals approach each choice problem as if it is the last decision they will ever face.

Regarding managers and organizations, loss aversion doesn't diminish in organizational decision-making; rather, it intensifies. Organizations exhibit increased risk aversion, particularly when employees and managers anticipate scrutiny of their choices. Simultaneously, there is a contradictory trend towards high risk-taking driven by optimistic assessments of future success, termed "bold predictions" in the study. The bottom line reflects inconsistency – a devaluation of risks juxtaposed with a redundancy of risks. There is no apparent correlation between the risk level and the decision size.

Fairness in business processes

Decision-making and judgment play integral roles in the business world, where the notion of "fairness" significantly influences these processes. Organizations and companies are shaped by perceptions of fairness, striving to avoid actions deemed unfair by customers and the public to prevent potential long-term repercussions. However, numerous biases are associated with this sense of fairness:

  • Charging an additional fee is considered unfair, whereas canceling a discount is viewed more leniently.

  • Lowering wages for an existing employee is perceived as unfair, yet offering a lower salary to a replacement worker is deemed acceptable.

  • A wage cut is generally considered unfair, but a partial increase below inflation is deemed plausible.

  • Raw price increases driven solely by customer or partner decisions are considered fair, whereas simultaneously raising prices on existing inventory is considered dishonest.

  • A business owner's price increase to cover a direct sale-related loss is considered reasonable, but increasing prices for other losses by the same owner is perceived as unfair.

These biases significantly influence how companies operate and formulate their strategies. Companies may prefer offering bonuses over salary increases to maintain flexibility and avoid the perception of unfairness if the bonus is later revoked. They might provide discounts through specific channels to retain flexibility in removing them later. Additionally, companies may consider replacing workers instead of reducing wages for existing employees.

It's important to note that the initial reference transaction forms the basis for fair judgment and establishes a norm, even if it may not be inherently fair or just. Research suggests that any steady-state will eventually be accepted if no equivalent alternatives exist. For instance, if raising prices in the summer is initially perceived as dishonest, but several hotels adopt this approach successfully, creating a situation of high summer prices, the sense of unfairness diminishes, and the price difference between seasons becomes perceived as fair.

Studies indicate that adherence to fairness rules is almost independent of enforcement, such as tipping in a restaurant. In conclusion, fairness, as perceived in the market, is a crucial component influencing economic conduct and must be considered in various financial calculations. Since fairness judgments often hinge on presentation, companies are inclined to present themselves to appear "fair" in the market.


Analyzing donation economically poses challenges, especially when waiting seems futile, and there is no traditional market to study. Despite these complexities, Kahneman delves into this unique activity environment and provides insights based on studies:

  1. Uniform Valuation: In the realm of donations, individuals are willing to contribute a similar amount regardless of the vastly different scopes of causes. For instance, respondents would express a willingness to donate the same amount for hunger relief in Ethiopia as they would for hunger relief across the entire African continent or for the broader goal of draining swamps.

  2. Goal-Centric Focus: Within donations, people tend to concentrate on the overarching goal and show less concern about the specific interventions required to achieve that goal.

  3. Reason for Deficiency: The reason behind a deficiency significantly influences people's willingness to donate and the extent of their contribution. Individuals are more inclined to contribute (and may advocate for higher state compensation) if the damage is attributable to human actions rather than natural forces.

Despite the absence of a conventional market framework, these insights shed light on the unique dynamics and considerations that shape individuals' decisions in the context of charitable donations.

The perception of suffering and happiness

The inquiry into human happiness and its contributing factors is intricately linked to decision-making. Similar to other domains, the exploration of suffering and happiness reveals systematic biases in decision-making:

  1. Prediction Challenges: Humans cannot predict how their enjoyment of present experiences will evolve in the future. Even when prediction is feasible, decisions are often made without adequately considering this future perspective.

  2. Pleasure Memories: People recall past pleasures, but articulating the reasons behind these memories can be challenging. Retrospective evaluations of events involve remembering both the experiences and the emotional nuances accompanying them. Due to the vulnerability of each component to errors, relying on such retroactive assessments is deemed unreliable. Individuals typically recall emotions tied to specific moments and assess them with outcomes over an extended period.

  3. Adaptation Dynamics: As studies suggest, positive emotions return to normal levels swiftly, with a return to baseline occurring approximately a year after losing a loved one. Surprisingly, minimal differences have been observed between paralyzed individuals and the general populace and between average individuals and lottery winners.

  4. Aspiration Level Adjustment: In less desirable situations, people adapt and modify their aspiration levels to align with realistic expectations. While objective happiness levels may fluctuate, the critical factor is the subjective level of happiness, calibrated to the scale of available possibilities.

  5. Focus Illusion: People's predictions about future happiness under specific conditions vary based on those conditions, such as residing in California or elsewhere. However, practical outcomes reveal minimal effects on happiness due to these conditions. Decisions often hinge on isolated parameters, neglecting the broader context. The illusion of focus can persist after a specific context is introduced, influencing responses to subsequent questions about happiness.

  6. Time Illusion: Examining pain perceptions, studies indicate that our memory of pain is less influenced by the duration of pain and more by the average pain level at the end and the peak pain level. This can lead to irrational biases, as individuals might prefer enduring a lingering sensation of pain, albeit less intense, than immediate removal, even though the total time and extent of pain are more significant.

Effects on decision-making

In addition to the detailed aspects mentioned above that influence decision-making (such as risk aversion, loss aversion, and the sense of loss, fairness, and justice), here are some additional factors impacting our decision-making process:

  1. Accessibility Dimension: This refers to how easily specific content comes to mind. Accessibility is influenced by order (something that is easy to perceive) and prominence (considering factors like first vs. third letter, size, color, etc.).

  2. Changes versus Situations: People find it easier to make decisions based on a change in an existing situation rather than assessing the situation itself.

  3. Attribute Conversion: Individuals tend to convert attributes into more straightforward questions that are easier to answer, even if there is no direct symmetry between the original question and its corrected answer.

  4. Emotion Heuristic: This decision-making heuristic is grounded in the idea that each stimulus triggers an emotional, often unconscious, response. This dynamic aspect is a convertible feature, especially when the question relies on attitudes.

  5. Prototype Heuristics: This involves making inferences from a prototype (something experienced or observed, a sample in observation, etc.) to an entire class that resembles or contains the prototype. Additionally, the ability to engage System 2 (as elaborated in the book "Thinking, Fast and Slow") influences decision-making. For instance, individuals in the morning may miss nuances when making decisions in the evening, and vice versa. Simple yet impactful.


While numerous issues have been discussed, a common theme emerges: decisions deviate from what one might expect in a strictly rational model. Whether the decisions pertain to personal matters, organizational considerations, business acquisitions, or charitable donations, our brains exhibit a level of sophistication beyond our awareness. However, this complexity can be limiting, leading us to only sometimes arrive at the optimal decisions. Undoubtedly, this prompts reflection on a philosophical and moral level, encouraging contemplation on humility (M.L.).

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