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Tag Archives: analysis

Articles I Like: The Law of Unintended Consequences: Shakespeare, Cobra Breeding, and a Tower in Pisa

The PolyBlog
March 4 2018

This is another article from Farnam Street, and I confess up until a few days ago, I’d never heard of them. Run by a guy named Shane Parrish, he’s based here in Ottawa. Some really fascinating stuff on there, with decent curation and a lot of links. This article highlights that:

Not all of our grand schemes turn out like we planned. In fact, sometimes things go horribly awry. In this article, we tackle unintended consequences and how to minimize them in our own decision making.

The Law of Unintended Consequences: Shakespeare, Cobra Breeding, and a Tower in Pisa | Farnam Street

You might think that the article is going to be about train wreck ideas or the butterfly effect causing tsunamis. Not really. In fact, I would say it is more about linear thinking from good intentions to good outcomes, without taking into account side effects. Some unknown, some unforeseeable, some just missed because they stopped thinking early. The article has a great quote from a book by William A. Sherden:

Sometimes unintended consequences are catastrophic, sometimes beneficial. Occasionally their impacts are imperceptible, at other times colossal. Large events frequently have a number of unintended consequences, but even small events can trigger them. There are numerous instances of purposeful deeds completely backfiring, causing the exact opposite of what was intended.

The conclusion is simple — systems thinking or second-order thinking is needed, but the article doesn’t pay much attention to the fact that often the culprit lies in defining the system too narrowly, when in fact the small system is part of a larger system, and it is the larger system that often has the other effects (like the examples of releasing a predator into a land to control one local population, not realizing that the predator will spread into the larger system). What I do like is the idea that sometimes the failure is in over-estimating the size of the system, assuming there are too many variables, and thus not trying at all to figure out ancillary effects.

Yet, if we know they exist (or in hindsight think we should have), the article explains some of the most common reasons:

Sociologist Robert K. Merton has identified five potential causes of consequences we failed to see:

Our ignorance of the precise manner in which systems work.

Analytical errors or a failure to use Bayesian thinking (not updating our beliefs in light of new information).

Focusing on short-term gain while forgetting long-term consequences.

The requirement for or prohibition of certain actions, despite the potential long-term results.

The creation of self-defeating prophecies (for example, due to worry about inflation, a central bank announces that it will take drastic action, thereby accidentally causing crippling deflation amidst the panic).

However, the article goes even further, adding in over-reliance on models and predictions (mistaking the map for the territory), survivorship bias, the compounding effect of consequences, denial, failure to account for base rates, curiosity, or the tendency to want to do something.

Of course, the article leads to the article I shared earlier (Articles I Like: Mental Models – The Best Way to Make Intelligent Decisions (113 Models Explained)), and the use of other mental models to help prevent a failure to consider other effects.

Cool stuff, love the site.

Posted in Goals | Tagged analysis, consequences, curation, ideas, learning | Leave a reply

Articles I Like: Mental Models – The Best Way to Make Intelligent Decisions (113 Models Explained)

The PolyBlog
March 3 2018

If you’re interested in goals and theory the way I am, then an article about “cross-training for the mind” and different ways of thinking in various disciplines is like catnip. When I saw the article, and that it was going to work through 113 different mental models, I couldn’t NOT click on that bait. In fact, their goal in the article is based on the following:

The overarching goal is to build a powerful “tree” of the mind with strong and deep roots, a massive trunk, and lots of sturdy branches. We use this tree to hang the “leaves” of experience we acquire, directly and vicariously, throughout our lifetimes: the scenarios, decisions, problems, and solutions arising in any human life.

Mental Models: The Best Way to Make Intelligent Decisions (113 Models Explained)

The more mental models you have, the more roots and branches you have to build on. What types of models? How about:

General Thinking Concepts (11)

  1. Inversion
  2. Falsification / Confirmation Bias
  3. Circle of Competence
  4. The Principle of Parsimony (Occam’s Razor)
  5. Hanlon’s Razor
  6. Second-Order Thinking
  7. The Map Is Not the Territory
  8. Thought Experiments
  9. Mr. Market
  10. Probabilistic Thinking (See also: Numeracy/Bayesian Updating)
  11. Default Status

Numeracy (14)

  1. Permutations and Combinations
  2. Algebraic Equivalence
  3. Randomness
  4. Stochastic Processes (Poisson, Markov, Random Walk)
  5. Compounding
  6. Multiplying by Zero
  7. Churn
  8. Law of Large Numbers
  9. Bell Curve/Normal Distribution
  10. Power Laws
  11. Fat-Tailed Processes (Extremistan)
  12. Bayesian Updating
  13. Regression to the Mean
  14. Order of Magnitude

Systems (22)

  1. Scale
  2. Law of Diminishing Returns
  3. Pareto Principle
  4. Feedback Loops (and Homeostasis)
  5. Chaos Dynamics (Sensitivity to Initial Conditions)
  6. Preferential Attachment (Cumulative Advantage)
  7. Emergence
  8. Irreducibility
  9. Tragedy of the Commons
  10. Gresham’s Law
  11. Algorithms
  12. Fragility – Robustness – Antifragility
  13. Backup Systems/Redundancy
  14. Margin of Safety
  15. Criticality
  16. Network Effects
  17. Black Swan
  18. Via Negativa – Omission/Removal/Avoidance of Harm
  19. The Lindy Effect
  20. Renormalization Group
  21. Spring-loading
  22. Complex Adaptive Systems

Physical World (9)

  1. Laws of Thermodynamics
  2. Reciprocity
  3. Velocity
  4. Relativity
  5. Activation Energy
  6. Catalysts
  7. Leverage
  8. Inertia
  9. Alloying

The Biological World (15)

  1. Incentives
  2. Cooperation (Including Symbiosis)
  3. Tendency to Minimize Energy Output (Mental & Physical)
  4. Adaptation
  5. Evolution by Natural Selection
  6. The Red Queen Effect (Co-evolutionary Arms Race)
  7. Replication
  8. Hierarchical and Other Organizing Instincts
  9. Self-Preservation Instincts
  10. Simple Physiological Reward-Seeking
  11. Exaptation
  12. Extinction
  13. Ecosystems
  14. Niches
  15. Dunbar’s Number

Human Nature & Judgment (23)

  1. Trust
  2. Bias from Incentives
  3. Pavlovian Mere Association
  4. Tendency to Feel Envy & Jealousy
  5. Tendency to Distort Due to Liking/Loving or Disliking/Hating
  6. Denial 
  7. Availability Heuristic
  8. Representativeness Heuristic
    1. Failure to Account for Base Rates
    2. Tendency to Stereotype 
    3. Failure to See False Conjunctions
  9. Social Proof (Safety in Numbers)
  10. Narrative Instinct
  11. Curiosity Instinct
  12. Language Instinct
  13. First-Conclusion Bias
  14. Tendency to Overgeneralize from Small Samples
  15. Relative Satisfaction/Misery Tendencies
  16. Commitment & Consistency Bias
  17. Hindsight Bias
  18. Sensitivity to Fairness
  19. Tendency to Overestimate Consistency of Behavior (Fundamental Attribution Error)
  20. Influence of Authority
  21. Influence of Stress (Including Breaking Points)
  22. Survivorship Bias
  23. Tendency to Want to Do Something (Fight/Flight, Intervention, Demonstration of Value, etc.)

Microeconomics & Strategy (14)

  1. Opportunity Costs
  2. Creative Destruction
  3. Comparative Advantage
  4. Specialization (Pin Factory)
  5. Seizing the Middle
  6. Trademarks, Patents, and Copyrights
  7. Double-Entry Bookkeeping
  8. Utility (Marginal, Diminishing, Increasing)
  9. Bottlenecks
  10. Prisoner’s Dilemma
  11. Bribery
  12. Arbitrage
  13. Supply and Demand
  14. Scarcity

Military & War (5)

  1. Seeing the Front
  2. Asymmetric Warfare
  3. Two-Front War
  4. Counterinsurgency
  5. Mutually Assured Destruction

The article has lots of links to the models to explain them. It’s like a treasure-trove of mental improvement rabbit-holes. And perhaps the grounds for 113 new blog posts by me as I work through each of them! Mind-blowing.

Posted in Goals | Tagged analysis, goals, ideas, learning, mental models, motivation, thinking | Leave a reply

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