[motohagiography]

Super cool. Would add this as a company gmail feature.

However, I also write emails to reduce time spent in conversation, so while I have learned to be more terse, when I'm not, it's to provide references so that I can shorten or preclude a conversation.

An ML email shortener is a fantastic idea for business comms, with the caveat that short email culture can also reward vagueness.

[jschwartzi]

Shortness shouldn't be the goal. Clarity should be the goal. The problem is that clarity is a much harder thing to test for.

I would pay money for a tool that checks my technical writing for reading level and warns me when passages go above Nth grade. Most people in the US graduate high school with an 8th grade reading level, and some people may not be able to read above a 5th grade level. That means tiny words and short sentences are king.

There are also metrics for clarity and simplicity that proxy on number of syllables. Those are really useful and don't require a complex ML model.

[yoavz]

https://readable.com/ is an interesting tool I came across in my research you might be interested in. It relies on the Flesch–Kincaid readability tests [1] and has found sustained usage.

Actually, now that I think about it... this might be a good source for bootstrapping further training data.

[1] https://en.wikipedia.org/wiki/Flesch%E2%80%93Kincaid_readabi...