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 guess this shows a contrast between explanatory simulations (eg a color illustration of a biological system) vs the symbolic "work-media": spreadsheets, scientific computing, code, that practitioners with sufficient conceptual grounding work with.
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Both are increasingly mediated by computers, but:
Simulations only go as far as the authors want them to go and don't necessarily transfer well to "work"-tasks, and
Work-media are capable of being all-enconpassing, but are hardly legible conceptually to a learner.
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That's why spreadsheets are still my favorite kind of explorable explanations
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