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I agree that the number of data points needed for study and the number of variables involved are both key factors. The one area that comes to mind where a approach might be easiest is closed platforms like the hardware Kindle reader -- for example, measuring read times by a large population of the same text, with varying fonts, on the same hardware. Improved typography might reduce read times some modest percentage over baseline due to improved readability.


Sure you can use ML and test subjects to maximize readability, but that's only one part of typography. Akin to Google beta testing shades of blue. http://www.zeldman.com/2009/03/20/41-shades-of-blue/




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