Regarding AI prose suggestions like this, it seems to me that there’s a big divide between documents intended for others and notes intended for personal use. Clearly you wouldn’t want short sentences like “I’m on it” to translate to 2 paragraphs in inkdrop.app (my notes app of choice) or obsidian.md.
One place I have noticed this myself is in Github Copilot - so far, its code suggestions have been more helpful than its comment suggestions. In my limited experience, I get idiomatic, non-flowery code that could have been written by anyone, but I get comments that sound off to me. Sometimes the tone strikes me as actively obnoxious; I think this is just that it doesn’t feel like I wrote it or could identify with it. I rarely use Copilot’s comments.
Worse, I find them distracting. I don’t find its code completion nearly as distracting as how it tries to finish my English sentences in comments. Prior to the latest AI feature rollout from Google, there were ubiquitous short phrase suggestions in Docs and Gmail, which I also found distracting in a similar way. They derail my train of thought, and I end up losing time rather than saving it.
… although I’ve also been thinking of ways such verbose automatic rewrites might be helpful.
One hypothetical: if everyone uses ML suggestions, and everyone knows that everyone is using ML suggestions, then you could imagine spending a lot less time analyzing the tone of professional communication for personal slights. For all but the most overt slights, there’s plausible deniability in “oh well, that was just the AI”. This might make fractious professional relationships less uncomfortable, or prevent them from arising in the first place.
The fact that the appropriateness of a given suggestion is partly determined by its audience prompts the idea that the machine could have many audiences in mind and the user could choose between them. It might have generic heuristics about professional communication or notes to self, or specific training about the way the CEO likes to hear about production problems.
And that idea, of choosing an audience for suggestions, prompts an idea that the AI text generation could happen at the time of reading, rather than the time of writing. I wonder if there will ever be a need for a low level conceptual representation that the AI could translate for any type of target audience, like IR for natural language.
Maybe this starts off by converting the user’s natural language input to something that looks like an English prompt. “Hello, I hope this email finds you well.” -> “greeting, professional, short, top of email, trending on greetingstation, let’s greet step by step”. Or maybe it’s something lower level, some occult binary format that only a dedicated reverser could love.
You’ve gotten to the bottom of the post, so I can admit it here: I didn’t have any artificial help writing this post. I didn’t even reach out to Bing for comment. This way, I get to keep all the mistakes for myself.
