See if I can get BSO tix for Friday -yes!
Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers
- Recent developments in natural language generation (NLG) using neural language models have brought us closer than ever to the goal of building AI-powered creative writing tools. However, most prior work on human-AI collaboration in the creative writing domain has evaluated new systems with amateur writers, typically in contrived user studies of limited scope. In this work, we commissioned 13 professional, published writers from a diverse set of creative writing backgrounds to craft stories using Wordcraft, a text editor with built-in AI-powered writing assistance tools. Using interviews and participant journals, we discuss the potential of NLG to have significant impact in the creative writing domain–especially with respect to brainstorming, generation of story details, world-building, and research assistance. Experienced writers, more so than amateurs, typically have well-developed systems and methodologies for writing, as well as distinctive voices and target audiences. Our work highlights the challenges in building for these writers; NLG technologies struggle to preserve style and authorial voice, and they lack deep understanding of story contents. In order for AI-powered writing assistants to realize their full potential, it is essential that they take into account the diverse goals and expertise of human writers.
- More reading. Need to search each paper for “loop”, “centaur”, and “team” and check those paragraphs at least. As you might think, the reality is more complex. All the papers have some parts of the concepts, but they often don’t use the terms
- Chat with Aaron. Really good. I think I was able to explain my concept. We’re going to write some sections and worry about the structure later
- 9:15 standup
- 2:00 Presentation. Went ok. Steve needs to join Toasmasters
- Roll in more edits – DONE!
- Set up new template?
- Add to the spreadsheet a week of numbers with min/max/avg to see what the pull size should be – done