August 5 was not a normal day for Kaicheng Yang. It was the day after a US court published Elon Musk’s argument on why he should no longer have to buy Twitter. And Yang, a PhD student at Indiana University, was shocked to discover that his bot detection software was at the center of a titanic legal battle.
Twitter sued Musk in July, after the Tesla CEO tried to retract his $44 billion offer to buy the platform. Musk, in turn, filed a countersuit accusing the social network of misrepresenting the numbers of fake accounts on the platform. Twitter has long maintained that spam bots represent less than 5 percent of its total number of “monetizable” users—or users that can see ads.
According to legal documents, Yang’s Botometer, a free tool that claims it can identify how likely a Twitter account is to be a bot, has been critical in helping Team Musk prove that figure is not true. “Contrary to Twitter’s representations that its business was minimally affected by false or spam accounts, the Musk Parties’ preliminary estimates show otherwise,” says Musk’s counterclaim.
But telling the difference between humans and bots is harder than it sounds, and one researcher has accused Botometer of “pseudoscience” for making it look easy. Twitter has been quick to point out that Musk used a tool with a history of making mistakes. In its legal filings, the platform reminde...