ycliper

Популярное

Музыка Кино и Анимация Автомобили Животные Спорт Путешествия Игры Юмор

Интересные видео

2025 Сериалы Трейлеры Новости Как сделать Видеоуроки Diy своими руками

Топ запросов

смотреть а4 schoolboy runaway турецкий сериал смотреть мультфильмы эдисон
Скачать

31 - Risk Policies

Автор: The pinnacle of synthesis

Загружено: 2026-02-28

Просмотров: 0

Описание: This chapter introduces the concept of risk policies—pre-established rules that guide decisions across multiple similar situations—as an antidote to the narrow framing that leads to poor choices. Kahneman argues that adopting consistent risk policies can overcome loss aversion and help individuals and organizations make more rational decisions over time.

The chapter opens with Samuelson's problem, a famous puzzle in economics. Paul Samuelson offered a colleague a bet: a 50% chance to win $200 or lose $100. The colleague rejected the single bet, saying "I won't bet because I would feel the $100 loss more than the $200 gain. But I'll accept 100 such bets." This response reveals how narrow framing—evaluating each decision in isolation—leads to loss aversion dominating. When viewed broadly, across 100 bets, the aggregate outcome is almost certainly positive. Samuelson proved mathematically that rejecting a single favorable bet while accepting 100 identical bets is irrational.

Kahneman explains that this inconsistency arises because humans naturally evaluate gains and losses one at a time rather than aggregating outcomes. Loss aversion—the principle that losses loom larger than equivalent gains—makes each individual bet feel risky and unappealing. However, when considering the distribution of outcomes across many trials, the law of large numbers ensures that favorable bets will, in aggregate, produce gains. The problem is that System 1 focuses on the immediate emotional response to each potential loss, not the long-term statistical reality.

The solution is to adopt a risk policy: a standing decision to accept all favorable gambles of a certain type. By committing in advance to take statistically advantageous risks, individuals can escape the tyranny of loss aversion on each individual decision. This approach is particularly powerful in business contexts. Richard Thaler advised an executive whose division managers were all risk-averse, turning down small positive-expectation projects because they feared failure would harm their careers. The executive adopted a portfolio perspective, telling managers he would judge them on their overall success rate, not individual project failures. This risk policy liberated managers to take sensible risks.

Kahneman acknowledges that adopting risk policies requires System 2 discipline and is difficult because each individual decision still triggers System 1's loss aversion. The chapter emphasizes that broad framing—thinking about decisions as part of a portfolio rather than in isolation—is essential for rational risk management. Individuals should view decisions about investments, career moves, and personal risks as part of a larger ensemble.

The chapter concludes that most people would benefit from being more risk-seeking in their aggregate behavior, particularly in domains where they face many similar decisions over time. Risk policies provide a practical tool for overcoming the emotional pull of loss aversion, allowing System 2 to impose rationality on System 1's fearful intuitions. The key insight is that consistency across similar decisions matters more than perfecting any single choice.

Не удается загрузить Youtube-плеер. Проверьте блокировку Youtube в вашей сети.
Повторяем попытку...
31 - Risk Policies

Поделиться в:

Доступные форматы для скачивания:

Скачать видео

  • Информация по загрузке:

Скачать аудио

Похожие видео

32 - Keeping Score

32 - Keeping Score

LLM и GPT - как работают большие языковые модели? Визуальное введение в трансформеры

LLM и GPT - как работают большие языковые модели? Визуальное введение в трансформеры

FairLight TV #144 - Беседа о линейном рисовании Quiss/Reflex от Fjalldata.

FairLight TV #144 - Беседа о линейном рисовании Quiss/Reflex от Fjalldata.

As the 2026 midterm elections approach

As the 2026 midterm elections approach

Дж. С. Холдейн в качестве побочного проекта изобретает теорию декомпрессии.

Дж. С. Холдейн в качестве побочного проекта изобретает теорию декомпрессии.

27 - The Endowment Effect

27 - The Endowment Effect

JPMorgan's Dimon on Iran War, Inflation, Credit Cycles

JPMorgan's Dimon on Iran War, Inflation, Credit Cycles

Практический опыт работы с ИТ — Учебное пособие по группам Microsoft 365

Практический опыт работы с ИТ — Учебное пособие по группам Microsoft 365

19 - The Goldilocks Rule: How to Stay Motivated in Life and Work

19 - The Goldilocks Rule: How to Stay Motivated in Life and Work

07 - The High Price of Ownership

07 - The High Price of Ownership

Понимание GD&T

Понимание GD&T

Как говорить о результатах бизнеса на английском языке | Изучение делового английского

Как говорить о результатах бизнеса на английском языке | Изучение делового английского

16 - How to Stick with Good Habits Every Day

16 - How to Stick with Good Habits Every Day

06 - The Problem of Procrastination and Self-Control

06 - The Problem of Procrastination and Self-Control

01 - Our Picture of the Universe

01 - Our Picture of the Universe

Музыка для работы за компьютером | Фоновая музыка для концентрации и продуктивности

Музыка для работы за компьютером | Фоновая музыка для концентрации и продуктивности

18 - The Truth About Talent (When Genes Matter and When They Don't)

18 - The Truth About Talent (When Genes Matter and When They Don't)

17 - How an Accountability Partner Can Change Everything

17 - How an Accountability Partner Can Change Everything

10 - The Power of Price

10 - The Power of Price

Why Income Never Creates Freedom — Systems Do | Wealth Mindset Audiobook

Why Income Never Creates Freedom — Systems Do | Wealth Mindset Audiobook

© 2025 ycliper. Все права защищены.



  • Контакты
  • О нас
  • Политика конфиденциальности



Контакты для правообладателей: [email protected]