HEALER Algorithm Improves HIV Knowledge among Homeless Youth

Описание: For more information, please see: http://cais.usc.edu

Institution: Center for Artificial Intelligence in Society, University of Southern California

Authors: Amulya Yadav, Eric Rice, Robin Petering, Jaih Craddock, Bryan Wilder, Milind Tambe

Researchers at the USC Center for Artificial Intelligence in Society have analyzed data from an ongoing project involving an algorithm to improve HIV knowledge among homeless youth and found some exciting changes. Homeless youth service providers implement social network based peer-leader intervention programs among homeless youth to help prevent HIV infection. In these interventions, a select number of youth, called peer leaders, are taught about how to change their behaviors to reduce the chances of contracting HIV. These leaders are then encouraged to share these messages among their peers in their social circles. We developed HEALER, a decision support system which assists social workers in selecting the most "influential" peer leaders for their social network based interventions. First, HEALER relies on online contacts and friendship based information of homeless youth (provided by social workers) to create a social network of the youth and their connections. This information is then analyzed by HEAL, an algorithm which utilizes state-of-the-art AI techniques from sequential decision making under uncertainty and decision theory, to pinpoint which homeless youth in the network would make successful peer leaders. The social workers then educate these peer leaders about HIV prevention, and encourage them to share their knowledge in their social circles. Finally, social workers are able to gather more data about the network based on feedback from the peer leaders. This information is passed back to HEALER, which enables it to continually refine its results for future interventions. HEALER has proven to be effective in the real-world. The pilot study found that HIV information spread and actual HIV testing rates were greater among the HEALER group, compared to the control group. This demonstrates that HEALER brings significant improvement over current approaches to network-based HIV interventions.

This work was supported by the California HIV/AIDS Research Program and the UCLA Center for AIDS Research Disparities Core.

The USC Center for Artificial Intelligence in Society is a joint venture between the Suzanne Dworak-Peck School of Social Work and the Viterbi School of Engineering. Its mission is to conduct research in artificial intelligence to help solve the most difficult social problems facing the world.

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