Saisha 's Key Ideas from Thinking, Fast and Slow
by Daniel Kahneman

The availability heuristic causes us to judge probability based on how easily examples come to mind. This creates predictable distortions:

• Vivid incidents seem more common than statistics suggest
• Recent events appear more probable than distant ones
• Personally experienced events feel more likely than abstract data
• Emotional impacts enhance availability, further skewing judgment
• Media coverage amplifies this effect by highlighting dramatic stories

This mental shortcut developed as an evolutionary adaptation for quick threat assessment but misfires in a world of complex, statistical risks. Understanding this bias helps explain both individual anxiety and societal overreactions to dramatic but rare events.

Anchoring occurs when an initial reference value disproportionately influences subsequent judgments. This effect:

• Works even when the anchor is obviously irrelevant
• Persists even when people are warned about it
• Affects experts and novices alike
• Operates in physical judgments, price evaluations, and negotiations
• Functions as an automatic System 1 suggestion that System 2 adjusts insufficiently

The power comes from our tendency to consider the anchor and adjust away from it, rather than evaluating independently. This creates a gravitational pull toward the initial value, explaining why starting numbers in negotiations matter tremendously.

The planning fallacy describes our tendency to underestimate time, costs, and risks while overestimating benefits. This occurs because:

• We focus on the specific case (inside view) rather than statistical averages (outside view)
• We imagine best-case scenarios rather than likely obstacles
• We underweight past experiences in favor of current plans
• Competitors deliberately underbid to win projects
• Optimism is rewarded in organizational cultures

This explains why projects consistently exceed budgets and timelines across domains. The remedy comes from the outside view—looking at statistical patterns from similar projects rather than the details of the current plan.

Loss aversion reveals that losses impact us approximately twice as strongly as equivalent gains. This asymmetry:

• Makes us reject favorable gambles with positive expected values
• Creates the endowment effect where we overvalue what we already possess
• Explains status quo bias and resistance to change
• Drives risk-seeking behavior when facing certain losses
• Produces risk-aversion when protecting sure gains

This fundamental asymmetry evolved as a survival mechanism—losing essential resources could mean death, while additional gains merely improved comfort. The resulting psychological imbalance explains behavior from investment decisions to product pricing to political resistance to reforms.

Regression to the mean describes how extreme outcomes tend to be followed by more average ones. This statistical phenomenon:

• Creates a powerful illusion of causality where none exists
• Explains apparent reversals of good or bad luck
• Occurs in any measure influenced by random factors
• Gets misattributed to interventions that happen between measurements
• Appears in domains from sports to medicine to investments

Humans resist probabilistic thinking, preferring causal explanations even when randomness is the true driver. This leads to false beliefs about the effectiveness of punishments, rewards, and interventions that simply happened to occur before natural regression.

Framing effects demonstrate how presentation dramatically influences decisions without changing substantive information. This occurs because:

• Our automatic System 1 responds emotionally to framing
• Positive frames evoke risk aversion; negative frames trigger risk seeking
• We react to description rather than underlying reality
• Different frames highlight different reference points
• These effects persist even with awareness of the manipulation

The same objective situation—whether medical treatments, financial investments, or policy options—produces significantly different choices depending on whether outcomes are described as gains or losses. This challenges the rational agent model since logically equivalent options should produce identical decisions.

The peak-end rule reveals we judge experiences primarily by their most intense point and their conclusion, largely ignoring duration. This mental shortcut:

• Prioritizes the worst/best moment and the final moment
• Neglects how long an experience lasted
• Creates opportunities to improve experiences by managing endings
• Explains why painful experiences with better endings feel preferable
• Creates a disconnect between real-time and remembered evaluations

This pattern shapes our choices about which experiences to repeat, despite being mathematically irrational. It explains why unpleasant necessities from medical procedures to customer service interactions can be improved dramatically by managing peaks and endings rather than duration.

WYSIATI (What You See Is All There Is) describes our mind's tendency to form judgments based solely on available information while remaining blind to what we don't know. This mental process:

• Constructs coherent stories from limited evidence
• Ignores the quality and quantity of information
• Creates overconfidence in current knowledge
• Generates illusions of understanding through narrative coherence
• Operates automatically without awareness of missing information

The mind doesn't naturally account for unknown information—in fact, it typically fails to recognize that information is missing at all. This explains overconfidence in predictions, blindness to alternatives, and why people can feel absolute certainty despite limited evidence.