Risk and Uncertainty

How to think about probabilities, expected value, and the parts of the future you cannot see.

Risk vs. Uncertainty

The two get used as synonyms. They are not.

Risk: outcomes are unknown, but the probabilities are known or estimable.

• Example: roulette. You know the odds.

Uncertainty: outcomes and probabilities are both unknown.

• Example: will this startup succeed? Hard to estimate honestly.

Most important decisions sit on the uncertainty side. Treat them like risk and you will be confidently wrong.

Expected Value

The probability-weighted average of all possible outcomes.

EV = Σ (probability × outcome)

Example - Job offer:

• 60% chance the company thrives: +$50,000/year value
• 30% chance it stagnates: +$0 value
• 10% chance it fails and you're job hunting: -$30,000 value

EV = (0.60 × $50,000) + (0.30 × $0) + (0.10 × -$30,000)
   = $30,000 + $0 - $3,000
   = $27,000 positive expected value

When EV Thinking Breaks Down

1. You can't survive the downside

• A bet with +EV but 10% chance of bankruptcy might not be worth it
• You need to survive to play again

2. One-time decisions

• EV assumes many trials averaging out
• For single decisions, variance matters

3. Non-financial values

• Some outcomes can't be quantified
• Relationships, health, meaning

The Kelly Criterion

How much to bet when you have an edge.

Kelly % = (bp - q) / b

Where:
b = odds received on the bet (payout/stake)
p = probability of winning
q = probability of losing (1 - p)

Key insight: Even with a positive expected value, you shouldn't bet everything. Optimal bet size balances growth and survival.

Practical application: For major decisions, don't go all-in even when odds favor you. Maintain reserves.

Fat Tails and Black Swans

Normal Distribution (Thin Tails)

Most outcomes cluster around the average. Extreme events are extremely rare.

• Height
• Test scores

Fat Tail Distribution

Extreme events are more likely than normal distribution predicts.

• Stock market crashes
• Pandemics
• Startup success

Implications

In fat-tail domains:

• Don't underestimate extreme events
• Single events can dominate long-term outcomes
• Historical averages may be misleading
• Prepare for scenarios outside "normal"

The turkey problem: Every day confirms the turkey's belief that life is safe, until Thanksgiving.

Asymmetric Risk/Reward

Not all risks are created equal. Look for asymmetry.

Asymmetric Upside (Good)

Limited downside, unlimited upside.

Examples:

• Learning a new skill (time invested, potential lifetime returns)
• Starting a side business (limited capital at risk, potentially large gains)
• Asking someone out (momentary awkwardness vs. potential relationship)

Strategy: Take more of these.

Asymmetric Downside (Bad)

Limited upside, large or unlimited downside.

Examples:

• Driving drunk (minor convenience, potential death/prison)
• Ignoring chest pain (avoid hospital visit, potential heart attack)
• Insider trading (moderate gain, prison)

Strategy: Avoid these regardless of probability.

The Barbell Strategy

Combine extreme safety with extreme risk. Avoid the middle.

Example portfolio:

• 90% in ultra-safe assets (treasury bonds)
• 10% in high-risk/high-reward speculations

Why: You're protected from ruin while maintaining exposure to extreme upside.

Life application:

• Stable income + risky side projects
• Secure job + aggressive investments
• Safety in most areas, calculated risks in few

Dealing with Uncertainty

Scenario Planning

When you can't predict the future, plan for multiple scenarios.

1. Define 3-5 plausible scenarios
2. Determine what you'd do in each
3. Look for actions that work across scenarios
4. Create tripwires for when to shift strategies

Example - Career planning:

• Scenario A: Industry grows (invest in skills)
• Scenario B: Industry stagnates (diversify skills)
• Scenario C: Industry declines (prepare exit path)

Pre-Commitment

Decide in advance what you'll do under certain conditions.

Examples:

• "If the investment drops 20%, I sell."
• "If I don't have product-market fit in 18 months, I shut down."
• "If my net worth reaches X, I retire."

Why: Removes emotion from future decisions.

The Margin of Safety

Build buffers for things going wrong.

• Project takes 50% longer than estimated? Plan for it.
• Emergency costs 6 months of expenses? Have it saved.
• Key supplier fails? Have backup options.

Engineering principle: Design for loads greater than expected.

Probability Calibration

Most people are poorly calibrated. They say "90% confident" when they're right 70% of the time.

Improve Calibration

1. Track predictions - Write them down with probabilities
2. Review outcomes - Were you accurate?
3. Adjust - If you're overconfident, widen your ranges

Probability Vocabulary

Be precise about uncertainty:

The Outside View vs. Inside View

Inside View

Looking at the specific details of your situation.

• "This project is different because..."
• "Our team is especially capable..."
• "We've thought this through carefully..."

Outside View (Reference Class Forecasting)

Looking at what happened to similar situations.

• "What's the base rate for projects like this?"
• "What happened to others who tried this?"
• "How long do projects like this typically take?"

The outside view is usually more accurate. Use it to sanity-check your inside view.

Example:

• Inside view: "Our startup will succeed because we have a great team and product."
• Outside view: "90% of startups fail. What makes us different from the 90%?"

Decision Matrix for Risk

Practical Risk Checklist

Before a risky decision:

□ What's the worst realistic outcome?
□ Can I survive that outcome?
□ What's the probability of the worst outcome?
□ What's the expected value?
□ Is there asymmetric upside or downside?
□ What's the base rate for situations like this?
□ What margin of safety do I have?
□ What's my exit strategy if things go wrong?
□ Have I stress-tested my assumptions?
□ Am I being appropriately uncertain?

Key Takeaways

1. Expected value matters, but so does survival: don't bet what you can't afford to lose.
2. Seek asymmetric upside: limited downside, large potential upside.
3. Respect fat tails: extreme events show up more often than the bell curve suggests.
4. Use the outside view: base rates beat intuition.
5. Build margins of safety: things will go wrong.
6. Calibrate your confidence: you are probably overconfident.
7. Distinguish risk from uncertainty: they need different approaches.

Next Steps

Continue to 04-big-decisions.md to apply frameworks, biases, and risk thinking to the choices that actually shape a life.