Introduction

In Algorithms to Live By, Brian Christian and cognitive scientist Tom Griffiths reveal a surprising truth: some of life’s toughest decisions can be improved by thinking like a computer scientist.

From choosing the right apartment or job to scheduling your calendar or cleaning out your closet, the authors explore how tried-and-tested algorithms used in computer science can help humans make better, faster, and more rational decisions. By blending artificial intelligence, behavioral psychology, and decision theory, this book shows that data-driven logic doesn’t just belong in code — it belongs in daily life.

But this isn’t a technical manual. It’s a practical, often witty guide to understanding how concepts like “explore vs. exploit,” “Bayesian inference,” and “optimal stopping” can reduce overwhelm, boost efficiency, and help you become a more deliberate thinker — no programming background required.

Whether you’re a startup founder, knowledge worker, or just someone who wants to be more productive and less stressed, Algorithms to Live By offers a unique framework for approaching life’s messiest problems with clarity.

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Top 10 Lessons from Algorithms to Live By

1. Use the 37% Rule to Make Smart Choices

When making a decision from a list (like hiring or dating), explore options without committing until you’ve reviewed 37% of them. Then pick the next one that’s better than all before. It’s the mathematically optimal stopping point.

2. Embrace “Explore vs. Exploit” for Better Life Balance

Life is a constant tradeoff between trying new things (exploration) and sticking to what works (exploitation). Early on, explore more; as time runs out, focus on exploiting what you know works best.

3. Sort Less, Search Smarter

Sometimes it’s more efficient to accept a bit of mess. In computing, sorting data takes time — and the same applies to your desk or inbox. If you search infrequently, don’t waste time perfectly organizing everything.

4. Caching Isn’t Just for Computers

Your brain, like your browser, benefits from caching. Prioritize mental and physical access to frequently-used items or ideas. This applies to your workspace, digital tools, or even morning routines.

5. Leave Room for Randomness

Algorithms often use randomness to avoid getting stuck in suboptimal solutions. Likewise, humans benefit from serendipity — trying a new route, task, or idea can lead to breakthrough outcomes.

6. Minimize Regret, Not Mistakes

Computers often calculate what would cause the least long-term regret, not just immediate success. Apply the same logic to your own life — you can’t avoid all mistakes, but you can reduce future regrets with thoughtful decision-making.

7. Apply Game Theory to Social Dilemmas

Understanding algorithms behind cooperative games can help you navigate negotiations, collaboration, and even dating. Tit-for-tat, fairness, and incentives all play a role in human behavior.

8. Bayesian Thinking Beats Snap Judgments

Update your beliefs based on new evidence, not assumptions. Bayesian inference encourages flexible thinking, which is especially powerful in a world flooded with uncertainty and changing data.

9. Don’t Over-Optimize Everything

Optimization is powerful, but comes with costs. Knowing when to accept “good enough” saves time and mental energy. Sometimes satisficing (satisfy + suffice) beats maximizing.

10. Algorithms Help You Accept Uncertainty

One of the most liberating takeaways? Even the best algorithms can’t guarantee perfect outcomes. That’s not failure — that’s reality. Learning to work with uncertainty, rather than fight it, makes life less stressful and more productive.