Why are women always talking to men in novels? A conversation about debiasing books using data analytics

Debiasing has become a much-debated topic in the world of AI and data analytics, and its time to talk about it in publishing. Together with the software team Granthinka, we have begun developing tools that can allow editors to assess their manuscripts for different kinds of bias, whether it's how much space men and women characters take up, the presence or absence of visible minorities within fiction, the familiarity of actions or descriptions ascribed to different types of characters, down to the titles that are used to estimate "comparability" when it comes to marketing. Debiasing is important because it challenges the common stereotypes that govern how individuals are represented in creative works today. But it also raises a host of challenging questions: When is bias part of the story? Are we limiting authors' freedom? How might readers react to these changes? What kinds of new markets do less "familiar" books open up (or close down)? How can we work with authors to think about little changes that gradually add-up to building new imaginary worlds? This talk is geared towards editors, authors, and publishers. It's about conveying what is currently possible when it comes to content analytics in books, and about hearing how audience members feel about the important and complex questions surrounding bias when it comes to the content of books.