AI Researcher Bethanie Maples has been reading science fiction since she was given a copy of Dune at 10 years old. Still, two decades and nearly 1,000 books later, the self-described sci-fi fanatic struggles to find books that delve into her most niche interests, like the link between AI and transhumanism. So last year, while working at Stanford’s Human Computer Interaction lab, she teamed up with data scientists Eric Berlow and Srini Kadamati to create a book recommendation tool based on more than 100 salient sci-fi themes, from hyperspace to magical feminism. Using data scraping, network analysis, and machine learning, the resulting Science Fiction Concept Corpus includes more than 2,600 books written since 1900. We made our own voyage into Maples’ sci-fi universe.

Alternate Histories

The Science Fiction Concept Corpus is built on plot descriptions, reviews, and user-generated tags scraped from Goodreads, sci-fi forums, and other sources. “It was interesting to see how sci-fi authors foreshadowed developments in history, like AI winters,” says data scientist Eric Berlow, who helped create the Corpus.

Expand Your Horizons

The Sci-Fi Corpus reveals “first-degree neighbors,” books that share some—but not all—common themes. The tool helps readers discover a broader range of relevant books from the past and present.

Book Recommendation Generator

The Corpus suggests titles based on 108 topics of interest, enabling intelligent browsing rather than algorithm-­driven results, Maples says.