In a bid to help mitigate the risk of suicide especially among the homeless youth, a team of researchers at University of California (USC) has turned their focus towards Artificial Intelligence (AI). Phebe Vayanos, an associate director at USC's Center for Artificial Intelligence in Society (CAIS), and her team have been working over the last couple of years to design an algorithm capable of identifying who in a given real-life social group would be the best persons to be trained as "gatekeepers" capable of identifying warning signs of suicide and how to respond. "Our idea was to leverage real-life social network information to build a support network of strategically positioned individuals that can'watch-out' for their friends and refer them to help as needed," Vayanos said. Vayanos and study's lead author Aida Rahmattalabi investigated the potential of social connections such as friends, relatives and acquaintances to help mitigate the risk of suicide. "We want to ensure that a maximum number of people are being watched out for, taking into account resource limitations and uncertainties of open world deployment," Vayanos said.

According to the CDC, the suicide rate for individuals 10-24 years old has increased 56% between 2007 and 2017. In comparison to the general population, more than half of people experiencing homelessness have had thoughts of suicide or have attempted suicide, the National Health Care for the Homeless Council reported. Phebe Vayanos, assistant professor of Industrial and Systems Engineering and Computer Science at the USC Viterbi School of Engineering has been enlisting the help of a powerful ally -artificial intelligence- to help mitigate the risk of suicide. In this research, we wanted to find ways to mitigate suicidal ideation and death among youth. Our idea was to leverage real-life social network information to build a support network of strategically positioned individuals that can'watch-out' for their friends and refer them to help as needed." Vayanos, an associate director at USC's Center for Artificial Intelligence in Society (CAIS), and her team have been working over the last couple of years to design an algorithm capable of identifying who in a given real-life social group would be the best persons to be trained as "gatekeepers" capable of identifying warning signs of suicide and how to respond. Vayanos and Ph.D. candidate Aida Rahmattalabi, the lead author of the study "Exploring Algorithmic Fairness in Robust Graph Covering Problems," investigated the potential of social connections such as friends, relatives, and acquaintances to help mitigate the risk of suicide. Their paper will be presented at the Thirty-third Conference on Neural Information Processing Systems (NeurIPS) this week. "We want to ensure that a maximum number of people are being watched out for, taking into account resource limitations and uncertainties of open world deployment.

According to the CDC, the suicide rate for individuals 10-24 years old has increased 56% between 2007 and 2017. In comparison to the general population, more than half of people experiencing homelessness have had thoughts of suicide or have attempted suicide, the National Health Care for the Homeless Council reported. Phebe Vayanos, assistant professor of Industrial and Systems Engineering and Computer Science at the USC Viterbi School of Engineering has been enlisting the help of a powerful ally--artificial intelligence--to help mitigate the risk of suicide. "In this research, we wanted to find ways to mitigate suicidal ideation and death among youth. Our idea was to leverage real-life social network information to build a support network of strategically positioned individuals that can'watch-out' for their friends and refer them to help as needed," Vayanos said.

According to the CDC, the suicide rate for individuals 10-24 years old has increased 56% between 2007 and 2017. In comparison to the general population, more than half of people experiencing homelessness have had thoughts of suicide or have attempted suicide, the National Health Care for the Homeless Council reported. Phebe Vayanos, assistant professor of Industrial and Systems Engineering and Computer Science at the USC Viterbi School of Engineering has been enlisting the help of a powerful ally -artificial intelligence- to help mitigate the risk of suicide. "In this research, we wanted to find ways to mitigate suicidal ideation and death among youth. Our idea was to leverage real-life social network information to build a support network of strategically positioned individuals that can'watch-out' for their friends and refer them to help as needed," Vayanos said.

When it comes to fighting substance abuse, research suggests the company you keep can make the difference between recovery and relapse. So, while group intervention programs can play an important role in preventing substance abuse, especially in at-risk populations such as homeless youth, they can also inadvertently expose participants to negative behaviors. Now, researchers from the USC Center for Artificial Intelligence in Society have created an algorithm that sorts intervention program participants - who are voluntarily working on recovery - into smaller groups, or subgroups, in a way that maintains helpful social connections and breaks social connections that could be detrimental to recovery. "We know that substance abuse is highly affected by social influence; in other words, who you are friends with," says Aida Rahmattalabi, a USC computer science graduate student and lead author of the study. "In order to improve effectiveness of interventions, you need to know how people will influence each other in a group."