Complexity — David Krakauer, Part 5

On: Embracing Complexity for Systemic Interventions

Transmission Series Ep. 5

Episode: 31

Date: May 5, 2020

Evolutionary biologist.

Review of 5 Transmission Essays.

Key Takeaways

  • Complex problems.
    • Broad averages are misleading.
    • Outcomes can be much more volatile than expected.
    • Need to understand local variation.
    • Need to present all possible outcomes.
  • Complex problems require complex interventions.
    • We tend to collapse causality into single causes.
    • Important problems tend to be complex and rarely have simple causes.
    • We poorly understand how to resolve complex problems.
    • We typically don’t look for complex solutions as we prefer simple ones.

Key Concepts

Cristopher Moore on The Heavy Tail of Outbreaks

  • Danger of averages.
    • Consider the variance, as well as the mean.
    • System averages are especially misleading if there is large local variance.
      • Example in COVID-19: impact of super-spreaders on R0.
    • Averages can hide heavy tails.
      • Probability of outliers can be much higher than you anticipate.
    • See “The End of Average“.

Van Savage on The Informational Pitfalls of Selective Testing

  • Constraints: testing capacity.
    • Reporting the number of tests instead of incidence of cases.
      • Can happen when true cases outnumber the testing capacity.
    • Reporting the growth in testing instead of the growth in cases.
      • Can happen when both testing and incidence of cases expands rapidly.
  • Solution: massively expand testing and/or test randomly.

David Tuckett, Lenny Smith, Gerd Gigerenzer, and Jürgen Jost on Making Good Decisions Under Uncertainty

  • Decision making under high uncertainty.
    • Data is not sufficient to support probabilities.
  • Solution: present all possible outcomes: understand potential variance.
    • Counter-factuals, simulations, null models.
  • Recognize the limitation of narratives (subject to cognitive biases).

John Krakauer and Michelle Carlson on COVID and Spiraling Frailty Syndrome

  • Complex problems require complex solutions
  • Difficult to implement, convince people.
    • We are energy-minimizing cognitive systems.
    • If we can find dominant mono-causal explanations, we prefer them.
  • Medicine needs to evolve to allow for more complex interventions.
    • Examples: physical activity, sleep.

Stefani Crabtree on What History Can Teach Us About Resilience

  • All civilizations have experienced and learnt how to cope with pandemics.
    • Often, pandemics have contributed to the downfall of empires.
  • Rarely the case that interesting or dramatic phenomena have simple causes.
    • Always tempting to collapse causality into a single cause.
    • Example COVID-19:
      • Outcomes are not only driven by virus.
      • Pre-existing inequalities hugely affect severity in pathology.
  • Complex causality requires complex control or complex intervention.
    • Things are connected in subtle ways.
    • There are non-linearities.
    • There are different phases and critical transitions.
  • We have a poor understanding on how to intervene into complex systems.
    • Last thing we want to do is pretend that they are simple systems.

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