AI Case Study
Crisis Text Line identifies 85% of high-risk users in need of emergency intervention by applying machine learning to texts
The Crisis Text Line allows users in need of immediate mental health help to text a counsellor. Some of those users need emergency service intervention, so machine learning has been applied to discover relations between text message content and the requirement for immediate intervention, allowing the service to better prioritise users. The system identifies 86% of users at high risk for suicide within the first few messages.
Public And Social Sector
Vox reports: "Traditionally, crisis centers respond to people in the order in which they come into the queue. But if you double your volume instantly, that's going to lead to long wait times. We want to help the people who have the highest-severity cases first: We want to help somebody who's feeling imminently suicidal before somebody who's having trouble with their girlfriend or boyfriend or something. We trained an algorithm. We asked, 'What do texters say at the very beginning of a conversation that is indicative of an active rescue?' So we can triage and prioritize texters who say the most severe things." According to the Crisis Text Line: "Currently, our machine learning only reads the opening messages. An improved model will be able to detect and adjust risk during the course of a conversation. We expect machine learning to detect suicide risk 5-10 minutes faster than a human Crisis Counselor can."
According to Vox, "CTL started in 2013 to serve people who may be uncomfortable talking about their problems aloud or who are just more likely to text than call. Anyone in the United States can text the number “741741” and be connected with a crisis counselor."
According to the Crisis Text Line, the "machine learning layer identifies 86% of people at severe imminent risk for suicide in their first conversations" and that the Line is "now positioned to service 94% of high risk texters in under 5 minutes."
From the Crisis Text Line: "The model, an ensemble of deep neural networks, learned to predict risk of suicide from all conversations tagged with “Suicide” by Crisis Counselors in a survey taken post-conversations. The interplay of model predictions and real-time feedback loop from Crisis Counselors is instrumental in retraining the model.
65M messages, including conversations associated with more than 5,300 active rescues where emergency services have been sent.