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Notes on Complexity

In Life and Machines

Tanner Lund

Have you ever wondered how to cope with the complexity of modern life? How about modern computing systems? 

This introductory book is a curation of notes on uncertainty, complex systems, engineering trade-offs, and more from some of the best teachers in these fields.

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About

About

About the Book

Several years ago, I began to ask why systems break, what makes them brittle, and how we might better build and operate them. This line of inquiry lead me down a deep rabbit hole comprising multiple fields of research, seminars in Sweden and NYC, invited talks at multiple conferences, and many, many PDFs.

This book is the introduction of roughly 3 years of notes on the subjects of complexity, decision making under uncertainty, risk taking, learning from failure, human factors, and system safety. It is an outgrowth of my desire to understand why things fail, and why so many of our efforts to prevent failure also fail. I don’t want to keep making the same mistakes over again, I want to learn from them.

Don’t you?

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Non-FictionSystem IntegrationSciences

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Author

About the Author

Tanner Lund

I study learning, risk, uncertainty, and error in complex domains.

I've put this into practice in my career operating, supporting, and automating large cloud systems like Microsoft Azure and Adobe Experience Cloud. Now I write and teach about it too.

Maybe there's something we can learn from each other?

Contents

Table of Contents

Introduction

  1. How This Book Is Structured

We Don’t Know Nothin’

  1. Uncertainty and Distributions
  2. System Evaluation
  3. Compulsive Intervention
  4. Fat-Tails and Surprises
  5. Risk Strategies and Aversion
  6. Metrics and Correlation
  7. The Illusion of Stability

The Limits of Knowledge

  1. Expertise
  2. There is no Root Cause
  3. Popper State of Mind
  4. The Social Limits of Scientific Certainty

Second Stories

  1. Trying to Learn from Failure
  2. The Costa Concordia
  3. Implications in Politics and Pop Culture

Error

  1. Human Error
  2. James Reason
  3. Jens Rasmussen
  4. Responsibility, Accountability, Blame, and Causality

Concepts of Complexity

  1. Complexity and Ignorance in Social Science
  2. Complexity: Learning to Muddle Through
  3. Emergence and Scale
  4. Happy Accidents — Serendipity
  5. Computation Complexity and Emergence
  6. Computational Irreducibility

Coping With Complexity

  1. Concavity vs Convexity
  2. The Result is Not The Consequence
  3. Picking Pennies In Front of a Steamroller
  4. Entropy and Distributions
  5. Complex Systems Need Stressors
  6. The Harm is in The Dose (Scale?)
  7. Preventative Maintenance
  8. Pessimism
  9. Optimism
  10. Can Reducing Fragility or Improving Resilience Have Downsides?
  11. Additional Thoughts

Modeling and Reasoning

  1. Tractability
  2. Uncertainty
  3. Perils of Linear Analysis
  4. Three Types of Errors in Models
  5. Some Modeling Approaches
  6. Functional Resonance Analysis Method (FRAM)
  7. Extreme Value Theory (EVT)
  8. Convexity and Fat Tails
  9. Extreme Risk Management Statistics
  10. The World as an Option
  11. Lessons From Disaster Insurance
  12. Some Heuristics
  13. Thought Experiment — Oasis Dwellers

Conclusion

  1. Some Parting Heuristics and Aphorisms
  2. Join The Discussion

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