The Application of AI in Aesthetic Resource Allocation

This review explores the emerging role of artificial intelligence (AI) in the allocation of aesthetic resources across multiple domains, including media, design, urban planning, and cultural heritage. It begins by defining the concept of aesthetic resources and identifying key challenges in their distribution, such as subjectivity, resource limitations, and diverse audience needs. The paper then outlines the foundational technologies - such as machine learning, computer vision, and generative models - that enable AI to interpret and generate aesthetic content. Through a survey of practical applications, the review highlights AI's capacity to enhance personalization, support creative collaboration, and broaden access to aesthetic experiences. It also examines critical challenges, including bias in training data, ethical concerns regarding authorship and censorship, and the limitations of current AI judgment frameworks. Finally, the review presents future directions, emphasizing the need for multimodal intelligence, interdisciplinary cooperation, and a more nuanced understanding of aesthetic value in sociocultural contexts. Overall, the paper argues that while AI offers substantial benefits in optimizing aesthetic resource allocation, its responsible development requires ongoing reflection and cross-disciplinary engagement.