Emotional responses to naturalistic and artificial intelligence (AI)-generated affective pictures: A systematic comparison.

Pictures depicting naturalistic scenes are widely used in studies of human emotion. However, the practical use of affective pictures is limited by several factors, including the difficulty of obtaining content-diverse, high-quality, openly accessible, and standardized stimuli that are necessary for specific research questions. The use of artificially generated (AI) pictures could address this limitation, but it is unclear if AI-generated pictures evoke reliable emotional responses. The present study sought to address these challenges by comparing emotional responses to AI-generated pictures with responses to original, standardized pictures. In two iterations of the study, standardized pictures containing pleasant, neutral, and unpleasant content were selected from the International Affective Picture System and other sources. Then, a matched AI counterpart was created for each original picture using generative deep neural networks. A total of 109 participants viewed the picture sets, while pupil diameter and electroencephalography data were recorded. Evaluative ratings of hedonic valence and emotional arousal were also collected. For both AI and original exemplars, pictures depicting emotional content elicited stronger responses than neutral content for ratings and electroencephalography-derived variables, with weaker effect sizes for the AI-generated pictures. Furthermore, picture-level analyses found that ratings and electroencephalography measures were strongly correlated between matched AI and original pictures. Pupil data showed the expected content effects in the second iteration of the study but not in the first iteration. Together, this initial study suggests that AI-generated picture sets can effectively elicit well-established self-reported affect and physiological responses, presenting a promising avenue for future studies of human emotion. (PsycInfo Database Record (c) 2026 APA, all rights reserved).