Giovanbattista Califano , Tianyi Zhang , Charles Spence
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引用次数: 0
Abstract
This study explores people's trust in AI-generated food and drink recipes. AI's ability to create unique recipes with limited ingredients attracts users seeking tailored options, especially for specialized diets or ingredient combinations. The study compares trust in AI-generated versus traditional recipes and examines the impact of dish innovativeness. The results show no differences in trust between AI and traditional recipes for standard dishes, but a significantly lower trust in AI for innovative recipes. The perception of taste, smell, and willingness to try recipes were similar across AI and traditional sources. These findings illuminate current levels of trust in AI-generated recipes.
期刊介绍：
International Journal of Gastronomy and Food Science is a peer-reviewed journal that explicitly focuses on the interface of food science and gastronomy. Articles focusing only on food science will not be considered. This journal equally encourages both scientists and chefs to publish original scientific papers, review articles and original culinary works. We seek articles with clear evidence of this interaction. From a scientific perspective, this publication aims to become the home for research from the whole community of food science and gastronomy.
IJGFS explores all aspects related to the growing field of the interaction of gastronomy and food science, in areas such as food chemistry, food technology and culinary techniques, food microbiology, genetics, sensory science, neuroscience, psychology, culinary concepts, culinary trends, and gastronomic experience (all the elements that contribute to the appreciation and enjoyment of the meal. Also relevant is research on science-based educational programs in gastronomy, anthropology, gastronomic history and food sociology. All these areas of knowledge are crucial to gastronomy, as they contribute to a better understanding of this broad term and its practical implications for science and society.
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