AI used for real-time selection of actionable messages for government and public health campaigns

Public health promotion campaigns can be effective, but they do not tend to be efficient. Most are time-consuming, expensive, and reliant on the intuition of creative workers who design messages without a clear sense of what will spark behavioral change. A new study conducted by Penn’s Dolores Albarracín and Man-pui Sally Chan, government and community agencies, and researchers at the University of Illinois and Emory University, suggests that artificial intelligence (AI) can facilitate theory- and evidence-based message selection.

The research group, led by Albarracín, a social psychologist who is the Amy Gutmann Penn Integrates Knowledge University Professor with appointments in the School of Arts & Sciences and Annenberg School for Communication, developed a series of computational processes to automatically generate an HIV prevention and testing campaign for counties in the United States, using real-time social media as a source for messages.

The paper, whose lead author is Chan, a research associate professor at Penn’s Annenberg School for Communication, describes how the method provides a living repository of messages that can be selected based on the team’s theory and AI-generated data about messages that people and institutions circulate on social media.

Read more at Annenberg Public Policy Center.