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Mass murderers have long attracted macabre groupies, but, like many ugly human tendencies, the phenomenon has been accelerated and amplified by the internet. According to law enforcement, the Texas girls were participants in the T.C.C., short for True Crime Community, an online fandom that celebrates perpetrators of mass violence. In the past two years, at least nine attacks and sixteen disrupted plots have been linked to the T.C.C., according to the Institute for Strategic Dialogue, a nonprofit think tank with a focus on hate and extremism.
In the aftermath of the arrests, law enforcement announced that the girls’ plot had been discovered through their online activity. “Everyone was, like, ‘Oh, so the F.B.I. really is spying on us?’ And, no, it’s not the F.B.I.,” Baimbridge said. The initial tip had come from a little-known team inside Meta that has spent the past decade honing a method to identify potential school shooters. Algorithmic social media, which has helped create the conditions for the spread of online content that might inspire such shootings, is reckoning with how it can become part of the solution.
Before Emily Vacher was recruited by Meta, in 2011, she was an F.B.I. agent specializing in crimes against children. At Meta, Vacher began working with the law-enforcement-outreach team, which she now helps lead. In the immediate aftermath of high-profile incidents, such as the Sandy Hook school shooting, in Newtown, Connecticut, the team would make contact with law enforcement to offer assistance. “You know, are there any co-conspirators? Is there any other impending danger they need to know about?” Vacher said.
As an agent, Vacher had spent time working with the behavioral-analysis unit in Quantico, the heavily mythologized home of the Bureau’s criminal profilers. There, she studied the work of Mary Ellen O’Toole, a longtime profiler with a specialty in school shooters. O’Toole had come to realize that many people who commit mass violence telegraph their intentions in advance, a phenomenon she referred to as “leakage.” School shooters, it turned out, were particularly prone to it: an F.B.I. study of active-shooter attacks between 2000 and 2013 found that nearly nine out of ten shooters under the age of eighteen had leaked their intent.
If would-be perpetrators were dropping hints about imminent violence online, Vacher thought, it should be possible to detect and stop them—“to think about disrupting attacks, not just investigating them,” she said. In 2018, she helped assemble a group of people with expertise in school shootings, including former journalists and police investigators, to study the online footprints of past attackers and to identify behavioral patterns. They worked with a team of engineers to build systems that use A.I. tools in order to scan for signals. Content flagged by the automated systems is passed along to a human for further review of the user’s online behavior: the posts they make and share, their interactions with others, the prompts they feed into A.I. chatbots. When there is evidence of “substantial steps, overt acts,” as Vacher put it—a list of targets or a manifesto, say—the investigations team provides relevant information to law enforcement. Last year, Meta did so around eight hundred times worldwide.
The process can unfold rapidly. According to prosecutors, last fall, a student at Benjamin N. Cardozo High School, in Queens, posted a photograph on Instagram of schoolwork with a text overlay that read “boutta shoot the school up.” The post was flagged by Meta, which passed the user’s information along to the F.B.I., which in turn notified the N.Y.P.D. After law enforcement matched the I.P. address associated with the post to a phone number and a name, they searched the student’s backpack and found a loaded pistol. Just over two hours after posting the picture, the student was taken into custody. (The student was charged with gun possession and making a terroristic threat.)
