This is a thoughtful new review of the “interactive explanation” milieu: distill.pub/2020/communica. I’m a friend of the format—I’ve written articles like this myself—but I worry it’s trapped in a limited framing, selling short the potential of computational representations.
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Here's my crux: The Cartesian plane was not invented to disseminate mathematics, or to make math more engaging. It was invented to help *do math*.
The same point can be made about John Snow’s cholera map, Feynman QED diagrams, and our other most powerful representations.
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If you create an interactive representation which amplifies original research, then you can often *also* use it for dissemination, journalism, etc. But if your design goal is “communicating to others,” it’s very unlikely that the representation will amplify original research.
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This is what we see in practice, with almost all these articles: representations designed to introduce an audience to an idea, and no more. Many other “explorable” authors have confided uncertainty to me about the impact of this work. With love: I suspect they’re right to worry.
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A more aspirational goal is to help decision-makers make complex decisions by “shipping the model”. This aims closer to the mark. But it’s usually lip service: pieces like The Atlas of Redistricting (projects.fivethirtyeight.com/redistricting-) are more for idle play than serious analysis.
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Even Jupyter-based “executable books” erect huge barriers between embedded figures and ongoing use. Try extracting a model from an article-notebook to use in “real” work. It’s rarely easy, and I think that illustrates the medium’s priorities.
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In summary, there’s a reason these articles usually feel like one-offs, and that the field doesn’t seem to be accreting: the representations are rarely deep enough to stand on their own and build upon each other. They’re too often for showing, not for thinking. Bret put it well:
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(This topic really deserve a full essay—there are many other important problems and opportunities in this space—but my queue is full enough that tweets are all I can afford for now…)
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I just ctrl+f'd "education" in Augmenting Human Intellect and there are essentially no results, which I have to admit surprised me. You could title the article "back to the basics" or something?
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Beautiful work from @unconed. Imagine these visuals not as "explainers" but just "the stuff you work with every day"
acko.net/files/gltalks/
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also, this thread:
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My fav part of Nicky's latest is his twitter reply where he links a custom interactive sim to illustrate his point. twitter.com/ncasenmare/sta
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It seems like the challenge is to create a representation while you're still working with it, and aren't finished with it. Typically these are only teaching tools because that's usually when we revisit an idea where the user has less than a full understanding.
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It's probably less common to have situations where:
1. You can make a good representation with less than a complete understanding
2. Once you've made it, the problem is complex enough that the tool keeps yielding surprises.
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This is essentially my motivation for working on tools like Apparatus. It's not about making it easier to make polished explanations. It's about making it worth people's time to create & modify interactive representations as part of their day-to-day work.
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I definitely share an interest in this space (communicating complexity) and working on it via strategic comms approach. Thanks for the tip and cc
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