Science 2.0

I liken cognition to a hill-climbing search on the landscape of theories/models/maps that explain/predict reality.  It’s easy to get stuck on peaks of local maximality.  Injecting randomness creates a sort of Boltzmann machine of the mind and increases my chances of finding higher peaks.

But I have to be prepared to be more confused — and question more assumptions than I intended to — because chances are my new random placement on the landscape is initially lower than the local maximum I was on prior.  This part is scary.  People around me don’t understand what I’m saying initially because I necessarily need new words, new language, to describe the new landscape.

And rather than start totally afresh with a new lexicon, I notice it’s more productive (personally and in communication) to overload old terms and let them slowly blend into their new meanings.  We all resist the strain, especially those who did not sign up for the jump through hyperspace.  They use the hill-climbing techniques that incrementally achieve higher ground (logical deduction, reductionism) in order to deny that we are in new territory at all and “prove” every new claim as false.  But unless we eliminate most or all of our old assumptions and embrace the new ones, these techniques will always yield inconsistency.

Thus, it seems like a good idea to resist the urge to bring to in the heavy logical artillery until it’s clear we are on the upslope.  In practice what this means is adding more novelty — but not as much as last time.  This is the Boltzmann technique of simulated annealing: start with a high degree of heat/randomness and turn it down slowly, all the while pounding away with the tools of logic and reduction.

What I mean by Science 2.0 is an intentional (and methodological) injection of novelty into the scientific method.  This is the beginning of a series of posts on the hows and whys of such activity.  I hope you will join in constructively and creatively.

  • Alex Golubev

    I think we all signed up for the jump through hyperspace, therefore I am. :)

    “‘Because in our brief lives we catch so little of the vastness of history, we tend too much to think of language as being solid as a dictionary, with a granite-like permanence, rather than as the rampant sea of metaphor which it is.’
    (The Origin of Consciousness in the Breakdown of the Bicameral Mind, 1976).” From
    (the last three paragraphs are worth checking out)

    Syntience, Inc is highly relevant as well:
    “When a problem is too complicated to be solved using any known Reductionist method, the Reductionist simpli-
    fies the problem by ignoring more of the context and by subdividing – reducing – the problem into simpler parts
    (if the problem is in fact reducible). In contrast, the Holist goes in search of more information in larger and larger
    contexts, hoping to discover patterns that match their prior experience. This can obviously be done even in irreducible
    domains.14 To a Reductionist, context “dependency” is something bad, something to discard. To a Holist,
    context is the whole point. These differences between Reductionist Science and Holistic problem solving in
    everyday life are very significant. A comparison of Reductionist approaches to machine based cognition against
    these new insights about Bizarre Systems and MFMs uncovers little overlap.”

    I highly recommend the videos available on their site. I know they’re very long in internet time, but don’t you wanna know Google’s secret (Neo learned kungfu relatively quickly). It looks like Google is moving into voice and environment recognition (through video) from text. This is the best video especially the QnA:

    Peter Norvig discusses how non-parametric models can be applied to vision and language problems in data-rich environments:

    Hiking does get old. We Were Promissed Jetpacks! :) (odd coincidence that i just saw this band 4 days ago… and that they are a band).

  • Rafe Furst

    I’ll check out the Syntience videos, thanks.

    Here’s an apropos quote from Stuart Kauffman’s new blog on NPR:

    reductionism is so rigid in its hopes to "entail" everything in the unfolding of the universe, that it leaves little room for creativity anywhere. I think reductionism is incomplete.

    • Alex Golubev

      I’m starting to see hope in the way expertise seems to be gaining density on the web. I’m seeing more and more intelligent posts on:
      – breaking up big banks, reducing leverage. – Creating transparency on the internet (not yet stressing focus on watching the watchers unfortunately)
      – shortcomings of reductionism

      I sure hope the understanding can get converted into constructive action somewhat soon. a giant awakening

  • kevindick

    I have three caveats to your approach:

    (1) Sometimes you _will_ jump to parts of concept space that have already been explored. In fact, I think an argument can be made that this will be the most common outcome. In which case, you _should_ listen to people who tell you so.

    (2) When you do arrive in a new territory, it’s important to be careful and precise. You don’t want to stumble around blindly. You want to observe with as much detail as possible and make as good of a map as you can. This argues against purely overloading existing terms. Reasoning by analogy is all fine and good, but you should qualify your terms too.

    (3) Eventually, you have to show some results. You can’t just sit in the new territory and exhort its endless possibilities forever. Where’s the slope to climb and how steep does it appear to be?

    • Alex Golubev

      this reminds me of how music used to borrow from older genres and now dj’s are mashing it all together:

      “Jurvetson believes that real breakthroughs come “at the intersections between the sciences.” In other words, “a chemist working on a chemistry problems is less likely to change the world. The real insights from outside, from the edge.”
      For example, Jurvetson points to how ideas from life sciences have cross-polinated into to create new engineering concepts (for example, winglets on airplanes). Combining life sciences (microbiology and mycology in particular) with industrial processes, he says, yields “wonderful workhorses” for food and energy production as well as waste management. “You gotta love the bug,” he says. “And if you can borrow a process from nature, chances are it’s going to be less polluting.””

      • kevindick

        I would call such scientific field mashups “Science 1.5”. Yes, there’s lots of low hanging fruit, but it’s not revolutionary.

        I think what Rafe is advocating is a reworking of scientific process altogether. To extrapolate rather than interpolate.