The main ways readers discover books today are generally echo chambers: Other people who bought this also bought that; other people who liked this also like that; best-seller lists; recommendations from friends.
All of these methods have the effect of the same popular, top-selling books being recommended repeatedly.
A new piece of software takes aim at this issue. Booksai, a project in development around the world, uses machine learning and artificial intelligence to recommend books that are like the books you like – with some surprising results. Booklamp, which calls itself the Pandora for books, tries to do much the same.
The question for publishers is, will recommendation engines like this take off and, if so, will they help sell more books that aren’t on best-seller lists?