When Artificial intelligence was used to explain complex science results were mixed.

 Raise your hand if you’ve ever stared at an academic paper, brows furrowed, wondering what the authors were trying to say. Perhaps you’ve even pulled up a separate tab to google any jargon that you came across. 

The good news is that you’re not alone. A 2017 eLife study found that science papers from the mid-2010s were more difficult to read than papers from the 19th century. Features that seem to plague most modern academic papers are poorly constructed sentences and word choices, as well as unnecessary jargon and obscure acronyms. This can make scientific knowledge hard to access, for both junior researchers in the field and for those without a science background.


So can artificial intelligence help? A new AI project called tl;dr papers sought to tackle this challenge by using machine learning to comb through the abstracts of wordy research papers and spit out a pithy summary of its contents that even a 7-year-old can understand. 

The Verge reported that although this program was first created almost two years ago, it went viral over the weekend when academic researchers input their articles into it and shared the summaries it generated on Twitter. Some of the summaries were shockingly accurate and simple, while others were laughably off-mark. 


For example, the AI summarized the concept of the “the glass cliff” as “a place where a lot of women get put” and a “bad place to be.” The paper’s author, Michelle Ryan, director of the Global Institute for Women’s Leadership at the Australian National University, told The Verge that while it was accurate, it didn’t offer a lot of nuance. Ultimately, she and other researchers that The Verge reached out to acknowledged that it was a “fun tool” that could show scientists what it looks like to “write in a way that is more reader-friendly.” 


Despite its popularity, tl;dr papers’ creators have told The Verge that they intend to sunset the product (the site is currently under maintenance), offering alternative tools like the AI summarizer created by The Allen Institute for Artificial Intelligence.