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Open science darwinian method pictures 2 (vasser)

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  • 1. What is science
    • Before 17 th century, Europe was a backwater with really good art
    • Civilizations kept rising and falling, never getting past a certain level of development
      • Indus Valley had running water in 2500 BC
      • Knossos had crude printing in 1700 BC
  • 2. Archimedes and the ancient rational innovations
    • Math
      • Size of solar system, optimization
    • Rules of logical argument and dialog
      • Eureka
    • Engineering
      • Cranes, lighthouse
    • Weak on naïve empricism & common sense…
  • 3. Why wasn’t this science?
    • No hypothesis testing
    • No organized literature and publication standards
    • What are the limitations of this method
      • Works, but requires honest geniuses
      • No checks against fooling yourself
        • games give practice
        • motivated reasoning makes it much harder
  • 4. Other ancient rationality
    • Naturalistic explanation
    • Philosophy, e.g. clarification of concepts and definitions
    • Craftsmanship and the evolution of arts and ‘ techné ’
    • Exploratory data collection
    • Markets and Hierarchies
    • Finally, scholarship
  • 5. Scholarly scientific method
    • Identify people who learn well
    • Teach them to notice ignorance and want to cure it
    • Have them read broadly, guided by curiosity and seeking surprises
    • Have them seek and write about diverse life experiences
    • Look for convergence in what they say
  • 6. Extended childhood
    • Human children build models naturally
      • Redundant data-sets make pattern detection easier
      • Averaging together errors with peers eliminates them
    • Falling error rates reallocate effort from model building to goal-oriented action
    • Varied experience maintains high error rates, maintaining exploratory behavior with adult minds
  • 7. What changed in 17 th century?
  • 8. Enlightenment Science
    • Long inferential chains from seemingly certain assumptions then search for falsification
    • Enabled cumulative intellectual progress by non-geniuses
  • 9. Problems with Enlightenment Science
    • ‘ I wonder what this button does’
    • Demanding confirmation of tests problematic when the confirmation will take the form of a disaster
    • At some point, fair to insist that logic counts
  • 10. The Darwinian Method
    • Rather than using scholarly method to generate hypotheses and independent generation of similar hypotheses as confirmation, use scholarship to generate hypotheses then use Enlightenment science to generate the same hypotheses as a form of valid confirmation.
    • Produces scientific controversy because predictions aren’t necessarily precisely detailed
  • 11. Darwin and Wallace
    • Evolution was a scholarly hypothesis
    • Natural selection a near-solid logical argument
      • Lack of discrete inheritance meant it didn’t quite hold up at first
    • Weak on specificity of surprising predictions, so ambiguous judged as pure Enlightenment science
      • Discrete inheritance wasn’t actually predicted
    • Independent origin of hypothesis by Wallace = ideal of pure scholarship
  • 12. Modern Examples
    • Environmentalism = scholarly hypothesis that humans are changing world on a global scale and in an uncontrolled manner
      • Uncontrolled change presumed harmful because society & biology optimized for current conditions
    • Global warming is a logical argument from basic chemistry
      • Lack of precision in specific predictions, so no confirmation of surprise
      • Data more extreme than prediction doesn’t quite count
    • Excellent exploratory data collection inspired by concern
  • 13. The Singularity
    • Independent origination of similar hypotheses, even similar terminology
      • Von Neumann, Vinge
    • Logical argument
      • Vinge, I.J. Good
    • Inductive data on exponential progress
      • Wright, Kurzweil, Bela Nagy
    • Nominal buy-in by numerous credible people
      • Displayed at Singularity Summits and Singularity University