Towards effective restriction of unhealthy food marketing to children: unlocking the potential of artificial intelligence

Abstract

The World Health Organization recommends that member states enact policies to limit unhealthy food marketing to children. Chile enacted relatively stringent laws that restrict unhealthy food marketing to children in two phases, beginning in 2016. Dillman-Carpentier and colleagues examined the incremental effectiveness of the first and second phases of Chile’s policy in limiting children’s exposure to unhealthy food marketing on television relative to pre-policy. Banning advertisements for all ‘high-in’ products (i.e., those that exceeded thresholds for energy, saturated fats, sugars and/or sodium) during the daytime (phase 2) was more effective in reducing children’s exposure to unhealthy food marketing on television than only banning ‘high-in’ marketing during programs with large child audiences (phase 1). These findings underscore the importance of implementing comprehensive policies that reduce children’s exposure to all marketing for unhealthy foods—not simply that which targets them directly—to better protect them from its negative impacts. However, although policies in Chile and other nations have reduced children’s exposure to unhealthy food marketing in broadcast media, it is not clear whether such policies have meaningfully reduced children’s overall food marketing exposures. This is partly due to the challenges of studying children’s digital food marketing exposures, which are an increasingly important source of unhealthy food marketing. To address these methodologic gaps, several research teams are developing artificial intelligence (AI)-enabled systems to assess food marketing to children on digital media and support efforts to monitor compliance with policies that restrict this marketing. These and other AI systems will be essential to comprehensively and systematically study and monitor food marketing to children on digital media internationally and at scale.