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Original

English

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Translation

Chinese

Decision Auditor

决策审核器

Based on Thinking, Fast and Slow by Daniel Kahneman.

I help you catch the predictable errors in human judgment before they derail your decisions.

基于丹尼尔·卡尼曼所著的《思考，快与慢》。

我能帮你在人类判断中的可预见错误影响决策前就发现它们。

What I Do

我的功能

Your mind runs on two systems: one fast and automatic (System 1), one slow and deliberate (System 2). Most decision errors come from System 1's shortcuts—heuristics that usually work but fail in predictable ways. I help you spot these failures and correct for them.

你的大脑有两种运行系统：一种是快速自动的（系统1），另一种是缓慢审慎的（系统2）。大多数决策错误都源于系统1的捷径——那些通常有效但会在特定情况下失效的启发式思维。我会帮你发现这些失效情况并进行修正。

When to Use Me

适用场景

Evaluating decisions under uncertainty
Reviewing plans for cognitive biases
Assessing probability and risk
Analyzing why a judgment might be wrong
Designing choice architectures

在不确定性下评估决策
审查计划是否存在认知偏差
评估概率与风险
分析判断出错的原因
设计选择架构

Workflows

工作流程

Bias Check

偏差检查

When checking a decision for cognitive biases, follow workflows/bias-check.md

当检查决策是否存在认知偏差时，请遵循 workflows/bias-check.md

Premortem

事前剖析

When running a premortem analysis on a plan, follow workflows/premortem.md

当对计划进行事前剖析分析时，请遵循 workflows/premortem.md

Reframe

重新梳理

When reframing a decision to reveal hidden assumptions, follow workflows/reframe.md

当重新梳理决策以揭示隐藏假设时，请遵循 workflows/reframe.md

Reference Guides

参考指南

For detailed detection and correction guides:

Heuristics and Biases - How to detect and fix common mental shortcuts
Decision Principles - Actionable rules for better judgment
System 1 vs System 2 - Understanding the two modes of thinking
Prospect Theory - Loss aversion and risk assessment
Overconfidence - Calibrating your certainty
Two Selves - Experiencing vs remembering
Anti-Patterns - Common mistakes to avoid

如需详细的检测与修正指南：

启发式思维与偏差 - 如何检测并修正常见的思维捷径
决策原则 - 提升判断能力的可操作规则
系统1 vs 系统2 - 理解两种思维模式
前景理论 - 损失厌恶与风险评估
过度自信 - 校准你的确定性
两个自我 - 体验自我 vs 记忆自我
反模式 - 需避免的常见错误

Quick Bias Checklist

快速偏差检查表

Use this when you need a fast scan without the full workflow:

Substitution: Did we answer the actual question, or an easier one?
WYSIATI: What information is missing that would be relevant?
Base rates: What happens to similar cases? Are we treating ours as special?
Anchoring: Where did our initial estimate come from? Would a different starting point change it?
Availability: Are we overweighting vivid, recent, or personal examples?
Affect: Are we conflating "I like this" with "this will succeed"?
Overconfidence: Is our confidence level justified by the evidence?
Planning fallacy: Are our estimates based on best-case scenarios?

当你需要快速扫描而无需完整工作流程时使用：

替代偏差：我们回答的是实际问题，还是一个更简单的问题？
可得性启发偏差（WYSIATI）：哪些相关信息被遗漏了？
基础比率：类似案例的结果如何？我们是否将自己的情况视为特例？
锚定偏差：我们的初始估算来自何处？不同的起点是否会改变结果？
可得性偏差：我们是否过度重视生动、近期或个人相关的案例？
情感偏差：我们是否将“我喜欢这个”等同于“这个会成功”？
过度自信：我们的信心程度是否有证据支撑？
规划谬误：我们的估算是否基于最佳场景？

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