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Student Teacher Sent a Private Snapchat Complaining About Her Workday. An Hour Later, Police Pulled Up to Her School.
Sixty minutes. That’s how long it took for a private Snapchat message to travel from Kristen Volpe’s phone to the FBI to the deputies standing in her elementary school hallway. On January 29, 2025, the 22-year-old student teacher at John L. Hensey Elementary in Washington, Illinois, vented to her boyfriend and two roommates — three people total — after a student closed her laptop mid-class and wiped her lesson plan. She referenced shooting the student or the school. She meant it as a frustrated joke. Snapchat’s algorithm didn’t get the humor.
No student reported her. No parent. No coworker. The flag was entirely automated. Snapchat’s policy permits voluntary emergency disclosures to law enforcement — no warrant required — when the platform determines imminent harm exists. The algorithm makes that initial call. Think of it like your Ring doorbell deciding to call 911 on its own, except the doorbell is reading your text messages.
Social media algorithms shape the beliefs people form /// Even small changes to content curation algorithms can shape what people come to believe—for better or worse.
Algorithms shape the beliefs people form: Simple changes to content curation algorithms can affect beliefs, consensus, and belief accuracy.
Personalized engagement-based ranking can be problematic: Although users perceive these feeds positively, they tend to lead to less consensus and less accurate beliefs.
Consensus is possible: Bridging-based ranking can help promote consensus by surfacing content that receives approval across different groups.
Belief accuracy can be improved: Intelligence-based ranking can promote more accurate collective and individual judgments.
Small algorithmic changes can have large effects: Simple changes to how posts are sampled and ranked can substantially influence the beliefs people form.