Jess Martin

⚠️ Warning! This is an in-progress research note exported directly from Jess's note-taking system. The ideas in this note are still under active development.

Last Updated: August 05, 2020

Learning from Alan Kay

Summary of Alan's Thoughts

A Critique of Modern Computing

Alan Kay participated in the foundational age of modern computing. He worked with the computing pioneers who were making the breakthroughs in physics, cognitive psychology, information theory, mathematics, and computer science. He built systems and brought them to life for the first time. He witnessed the adoption of the computer in the commercial and eventually the consumer space.

But perhaps more importantly, Alan was one of the casters of the original vision of modern computing. He saw what could be. Having seen what has come of computing so far, his main message is: we can do better. We must do better. Humanity depends on it.

The original vision for modern computing, espoused by J.C.R. Licklider but also widely shared by those at PARC, was: "The destiny of computers is to become interactive intellectual multipliers for all humanity, all networked and working together."

And what we have today instead is Candy Crush.

Alan shares several reasons for why we got here and also an antidote. We can still "take the blue pill", shake off this mortal coil, and refocus our aim on greater feats.

Alan's reasoning for why computing has seen little fundamental innovation:

  • The industrial revolution
    • makes it possible to extract tremendous profit from serving the center of the bell curve.
    • most "middle of the bell curve" solutions are derivative, not transformative.
  • Humanity's flawed thinking capacity
    • Unfortunately, most of us identify perception with reality. We don't think critically about what we receive. We're satisfied with far less than we should be.
  • Computing is largely driven by fad, unlike science
    • The hard sciences have hard limits - physics and math and the like - and thus are not (as much) driven by fad.
    • Computing, on the other hand, is synthetic. There are fewer hard limits. Thus, computing in general is heavily susceptible to fad and popularity. Why does one programming language win over another, for example?
  • Communities of science doing foundational science research have disappeared
    • There used to be far more funding available for doing scientific research. This was partly due to the times (WWII and the Cold War) and partly due to the what the government chooses to invest in.

How do we get back to doing transformative work at the "edges of computing"?

  • Study the computing pioneers and learn to see their vision
  • Start thinking from first principles
  • Focus on research over engineering
  • Learn to see what's wrong with the systems around you
  • Rebuild the communities of science

Alan's Big Ideas

  • Replicated computing
  • Objects as virtual machines

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