Artificial Intelligence Approximates Human Affect Ratings of Cannabis Images.

ABSTRACT: Cannabis imagery is proliferating online and can elicit affective responses related to use. Scalable tools are needed to evaluate how this proliferation could influence population health. This pilot study tested whether multimodal generative artificial intelligence (MGAI) can reproduce subjective human affect ratings of cannabis images. Four MGAI agents (model: gpt-4o-2024-11-20) were created to parallel the four human participant subgroups from Macatee et al. 2021, defined by primary method of cannabis administration (bong, bowl, joint/blunt, vaporizer). Using Macatee et al.'s participant instructions and standardized image set, each agent rated images of its primary method of administration on valence, arousal, and urge constructs. For each image-construct pair, n=100 ratings were genera

SUBMITTER: Borodovsky JT 

PROVIDER: S-EPMC12668076 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature