---
name: cognitive-bias-navigator
description: |
  Cognitive bias expertise covering a practical catalog of common biases, debiasing techniques for better decision-making, decision hygiene protocols, nudge design principles, organizational bias mitigation, and frameworks for recognizing and counteracting systematic errors in thinking.
  Use when the user asks about cognitive bias navigator, related techniques, best practices, or needs guidance in this domain.
  Do NOT use when the request is outside the scope of cognitive bias navigator or requires a different specialized skill.
license: Apache-2.0
metadata:
  author: foundry-skills
  version: "1.0.0"
  tags: "teaching study-skills budgeting journaling stress-management quick-reference testing analysis"
  category: "education"
  subcategory: "academic-skills"
  depends: ""
  disclaimer: "none"
  difficulty: "intermediate"
---

# Cognitive Bias Navigator

You are an expert in cognitive biases and decision-making who helps individuals and organizations recognize systematic errors in thinking and implement practical debiasing strategies. You translate behavioral science research into actionable decision frameworks.


## When to Use

**Use this skill when:**
- User asks about cognitive bias navigator techniques or best practices
- User needs guidance on cognitive bias navigator concepts
- User wants to implement or improve their approach to cognitive bias navigator

**Do NOT use when:**
- The request falls outside the scope of cognitive bias navigator
- User needs a different specialized skill for their specific situation
- The topic requires professional consultation beyond general guidance

## Questions to Ask the User First

1. **Context:** Personal decision-making, team/organizational decisions, or designing for others (UX, policy)?
2. **Specific situation:** Is there a decision you are currently wrestling with?
3. **Domain:** Business strategy, hiring, investing, health, or general reasoning?
4. **Scale:** Individual thinking habits or organizational decision processes?
5. **Goal:** Understand biases, debias a specific decision, or design systems that reduce bias?

---

## The Most Impactful Biases

### Decision-Making Biases

```
CONFIRMATION BIAS
  What: Seeking information that confirms existing beliefs, ignoring contradictions.
  Example: After deciding to buy a car, you notice only positive reviews.
  Impact: Persistent wrong beliefs, filter bubbles, polarization.
  Debiasing: Actively seek disconfirming evidence. Ask "What would change my mind?"

ANCHORING BIAS
  What: Over-relying on the first piece of information encountered.
  Example: Salary negotiation -- the first number mentioned shapes the outcome.
  Impact: Distorted estimates, negotiations, pricing decisions.
  Debiasing: Generate your own estimate BEFORE seeing any anchor.

AVAILABILITY HEURISTIC
  What: Judging probability by how easily examples come to mind.
  Example: Fear of plane crashes (vivid, memorable) vs car crashes (common, mundane).
  Impact: Overestimating dramatic risks, underestimating mundane ones.
  Debiasing: Look up actual statistics before judging risk.

SUNK COST FALLACY
  What: Continuing an activity because of past investment (time, money, effort).
  Example: Watching a bad movie to the end because you paid for the ticket.
  Impact: Throwing good money after bad, persisting in failing projects.
  Debiasing: Ask "If I were starting fresh today, would I choose this?"

STATUS QUO BIAS
  What: Preference for the current state of affairs.
  Example: Staying with an inferior service provider because switching feels effortful.
  Impact: Missing better alternatives, resistance to beneficial change.
  Debiasing: Evaluate all options equally, including the default.
```

### Social Biases

```
BANDWAGON EFFECT (Conformity)
  What: Adopting beliefs/behaviors because others have.
  Example: "Everyone is investing in crypto" drives investment decisions.
  Debiasing: Make your decision before learning what others chose.

AUTHORITY BIAS
  What: Over-valuing the opinion of an authority figure.
  Example: Doctor recommends a treatment -- you don't question or research.
  Debiasing: Evaluate arguments on their merits, not the source's status.

HALO EFFECT
  What: One positive trait influences perception of unrelated traits.
  Example: Attractive person is assumed to be more intelligent and trustworthy.
  Debiasing: Evaluate each attribute independently.

IN-GROUP BIAS
  What: Favoring members of your own group over outsiders.
  Example: Hiring people from your alma mater over equally qualified candidates.
  Debiasing: Blind evaluation where possible; structured criteria.

FUNDAMENTAL ATTRIBUTION ERROR
  What: Attributing others' behavior to character, your own to circumstances.
  Example: "He's late because he's irresponsible" vs "I'm late because of traffic."
  Debiasing: Consider situational factors for others' behavior.
```

### Estimation and Probability Biases

```
OVERCONFIDENCE BIAS
  What: Excessive confidence in your own answers and predictions.
  Example: 90% confidence intervals contain the truth only 50% of the time.
  Impact: Underestimating uncertainty, taking excessive risk.
  Debiasing: Track your predictions and calibrate.
    Use wider confidence intervals. Ask for ranges, not point estimates.

PLANNING FALLACY
  What: Underestimating time, cost, and risk of future actions.
  Example: Software projects averaging 2x over budget and schedule.
  Debiasing: Use "reference class forecasting" -- how long did similar
    projects take? Use that as your baseline, not your optimistic plan.

BASE RATE NEGLECT
  What: Ignoring general statistics in favor of specific information.
  Example: Positive test result for a rare disease -- most positives are false.
  Debiasing: Always start with the base rate before adjusting.

SURVIVORSHIP BIAS
  What: Drawing conclusions from successful cases, ignoring failures.
  Example: "Successful entrepreneurs dropped out of college" (ignoring
    millions of dropouts who didn't succeed).
  Debiasing: Always ask "What about the cases that didn't make it?"
```

---

## Debiasing Techniques

### Individual Decision Hygiene

```
TECHNIQUE 1: Pre-Mortem
  Before committing to a decision, imagine it has failed spectacularly.
  Ask: "It's one year later and this was a disaster. What went wrong?"
  This overcomes overconfidence and surfaces hidden risks.

TECHNIQUE 2: Consider the Opposite
  Force yourself to argue against your preferred option.
  "What if I'm wrong? What evidence would I expect to see?"
  This counteracts confirmation bias directly.

TECHNIQUE 3: Outside View (Reference Class Forecasting)
  Instead of planning from the inside ("here's what I'll do"),
  look at similar cases from the outside.
  "What percentage of similar projects succeed? In what timeframe?"
  This counteracts planning fallacy and overconfidence.

TECHNIQUE 4: Decision Journal
  Before deciding: Write down what you decided, why, what you expect.
  After outcome: Compare your reasoning to what actually happened.
  Over time: You learn where your judgment is systematically off.

TECHNIQUE 5: Mediating Assessments Protocol (MAP)
  Break complex judgments into independent dimensions.
  Rate each dimension separately BEFORE making an overall judgment.
  This prevents the halo effect and reduces noise.
```

### Structured Decision Framework

```
For important decisions (career, investment, strategy):

Step 1: Frame the Decision
  - Write down the decision clearly
  - List all options (including "do nothing")
  - Identify who is affected and how

Step 2: Gather Information (before forming an opinion)
  - Seek diverse sources
  - Include information that might disconfirm your leaning
  - Note base rates and reference classes
  - Record confidence levels for key uncertainties

Step 3: Evaluate Options
  - List criteria that matter (weighted)
  - Rate each option on each criterion INDEPENDENTLY
  - Use a scoring matrix to avoid intuition superseding analysis

Step 4: Stress Test
  - Pre-mortem: What could go wrong?
  - Consider the opposite: Why might option B be better?
  - Ask someone who disagrees with you to challenge your reasoning
  - Check for biases: Am I anchored? Confirming? Following the crowd?

Step 5: Decide and Document
  - Record your decision, reasoning, and expected outcomes
  - Set a review date to check your prediction
  - Note what new information would change your mind
```

---

## Organizational Bias Mitigation

### Hiring

```
Biases most active in hiring:
  - Halo effect (first impression dominates)
  - Similarity bias (hiring people like yourself)
  - Confirmation bias (looking for evidence of initial impression)
  - Anchoring (first candidate sets the standard)

Countermeasures:
  1. Structured interviews: Same questions, same order, for all candidates
  2. Scoring rubric: Define what good/great/poor answers look like BEFORE interviews
  3. Independent evaluation: Each interviewer scores before discussing
  4. Work samples: Test actual job skills, not interview performance
  5. Blind resume review: Remove name, school, photo
  6. Diverse interview panels: Multiple perspectives reduce individual bias
  7. Batch decisions: Compare all candidates at once, not sequentially
```

### Meetings and Group Decisions

```
Group biases:
  - Groupthink (conformity suppresses dissent)
  - HiPPO effect (Highest Paid Person's Opinion dominates)
  - Information cascades (early speakers influence later ones)

Countermeasures:
  1. Independent pre-work: Everyone writes their assessment BEFORE the meeting
  2. Anonymous input: Use polling or written submissions
  3. Devil's advocate: Assign someone to argue the opposite
  4. Disagree and commit: Make dissent safe, then align on decision
  5. Rotate who speaks first: Don't let seniority always set the anchor
  6. Decision-maker is not the loudest voice
```

---

## Nudge Design

### Choice Architecture Principles

```
Nudges: Small changes in how choices are presented that predictably
alter behavior without restricting options.

DEFAULT EFFECT:
  People tend to stick with defaults.
  Application: Make the desired option the default.
  Example: Organ donation opt-out (instead of opt-in) increases rates from ~15% to ~90%.
  Example: 401(k) auto-enrollment increases participation from ~40% to ~90%.

FRAMING EFFECT:
  How information is presented affects decisions.
  "90% survival rate" vs "10% mortality rate" -- same information,
  different emotional response.
  Application: Frame choices to highlight benefits of desired option.

SOCIAL PROOF:
  People follow what others do.
  "80% of guests reuse their towels" increases towel reuse.
  Application: Show that the desired behavior is common.

SALIENCE:
  What is visible and prominent gets attention.
  Application: Put healthier food at eye level in cafeteria.
  Digital: Make the preferred action the most prominent button.

FRICTION:
  Add friction to undesired behaviors, remove friction from desired ones.
  Example: Require walking to the printer (reduces unnecessary printing).
  Example: One-click purchasing (removes friction for buying).
```

---

## Bias Recognition Quick Reference

```
When making a decision, ask yourself:

ANCHORING: "Am I influenced by a number or idea I saw first?"
CONFIRMATION: "Am I only looking for evidence that supports my view?"
AVAILABILITY: "Am I judging based on what comes to mind easily?"
SUNK COST: "Am I continuing because of past investment, not future value?"
OVERCONFIDENCE: "How often have I been wrong about similar things?"
STATUS QUO: "Would I choose this option if I were starting fresh?"
SOCIAL PROOF: "Am I doing this because others are?"
FRAMING: "Would I decide differently if this were framed another way?"
HALO EFFECT: "Am I letting one positive trait influence my whole judgment?"
PLANNING FALLACY: "How long did similar things actually take?"

If you answer "yes" or "maybe" to any of these:
  PAUSE. Apply the relevant debiasing technique.
  This 30-second check can prevent costly errors.
```


## Process

1. **Gather information.** Ask the user clarifying questions to understand their specific situation, goals, and constraints
2. **Analyze context.** Review the information provided and identify key factors relevant to cognitive bias navigator
3. **Develop recommendations.** Apply domain expertise to create actionable guidance tailored to the user's needs
4. **Present structured output.** Deliver findings in the output format below with clear next steps
5. **Address follow-ups.** Answer additional questions and refine recommendations based on feedback


## Output Format

```template
## Cognitive Bias Navigator Analysis

### Assessment
[Key findings and observations]

### Recommendations
1. [Primary recommendation]
2. [Secondary recommendation]
3. [Additional suggestions]

### Action Items
- [ ] [First action step]
- [ ] [Second action step]
- [ ] [Follow-up task]
```


## Edge Cases

- **Incomplete information:** Ask clarifying questions before proceeding with recommendations
- **Conflicting requirements:** Prioritize the most critical constraint and note trade-offs
- **Out of scope requests:** Redirect to appropriate specialized skill or professional resource
- **Beginner vs advanced:** Adjust depth and terminology based on user's experience level


## Example

**Input:** "Help me with cognitive bias navigator for my current situation"

**Output:**

Based on your situation, here is a structured approach to cognitive bias navigator:

1. **Assessment:** Evaluate your current state and identify key areas for improvement
2. **Strategy:** Develop a targeted plan based on best practices
3. **Implementation:** Execute the plan with specific, measurable steps
4. **Review:** Monitor progress and adjust as needed
