This article introduces the concept of image "culturization", i.e., defined as the process of altering the "brushstroke of cultural features" that make objects perceived as belonging to a given culture while preserving their functionalities. First, we propose a pipeline for translating objects' images from a source to a target cultural domain based on Generative Adversarial Networks (GAN). Then, we gather data through an online questionnaire to test four hypotheses concerning the preferences of

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... Italian participants towards objects and environments belonging to different cultures. As expected, results depend on individual tastes and preference: however, they are in line with our conjecture that some people, during the interaction with a robot or another intelligent system, might prefer to be shown images whose cultural domain has been modified to match their cultural background.