|
|
|
|
|
by thicknavyrain
352 days ago
|
|
I'm a popular science writer with eight year's experience doing exactly this (SciShow, Crash Course, Veritasium and recent winner of the Wellcome Collection Non Fiction Awards) without AI. Done right, the right coverage of even a pre-print reached hundreds of thousands/millions of people. But I've experimented with every SOTA model since 2022 with the most detailed and specific prompting I can think of (including multiple examples of transcripts of work already in the public domain) to see if it can replicate good quality science communication. The content is usually reasonably strong but the tone is always off and it never quite understands what it is a reader/viewer needs to really get to grips with the topic if they don't already have a prior foundational understanding (though I notice this about a lot of other media outlets with professional science communicators too). It also has poor editorial thinking around what bits are most likely to be interesting and cohesive when considered as part of the whole piece. But I'm still reasonably convinced as AI improves it ought to be able to replace me with the right workflow/context/prompting. I think there will always be a demand for my (and many other writers') talents as they are so it doesn't really bother me, but it'd be great to extend the work to all the many scientific discoveries that don't get the same attention. If anyone is serious about developing something like this, I'd be interested in partnering with them as someone with domain expertise on science communication and familiar with prompt engineering (email in bio). |
|
I think you're right about the editorial thinking + what do people find interesting parts. But that doesn't have to be solved by directly by AI, it's easy enough to sidestep the problem and provide a nice interface for the human-in-the-loop part. I'd imagine that would save you a ton of time by having a nice starting point depending on how much you have to rewrite for tone.