Automated Aesthetic Evaluation: Can AI Objectively Assess Creative Growth? - A Critical Analysis

Dr Satyamangal Rege

Automated Aesthetic Evaluation: Can AI Objectively Assess Creative Growth? - A Critical Analysis

Authors: Dr Satyamangal Rege

Unique Paper ID: 175188
Volume: 11
Issue: 11
PageNo: 2109-2113

Keywords: AI in Art Art Education Aesthetic Evaluation Automated Critique Artistic Development Creative Growth Human-AI Collaboration Machine Learning Portfolio Analysis Visual Arts

Abstract:
An urgent topic facing the art world is whether artificial intelligence (AI) can objectively assess artistic development as AI becomes more and more integrated into creative workflows. The promise and constraints of AI-driven aesthetic judgment in monitoring and analyzing an artist's creative development are examined in this study. We investigate how AI systems evaluate style, composition, and visual development across artistic bodies of work by utilizing machine learning approaches like generative algorithms and convolutional neural networks. This study assesses how AI may assist with portfolio building, exhibition curation, and self-reflective practices through practical applications and in-depth case studies of modern artists. AI is capable of identifying stylistic changes and visual patterns, but it is not as good at comprehending cultural context, emotional resonance, or philosophical depth—all of which are essential components of creative development. We provide a hybrid paradigm that offers more collaborative, nuanced assessments by fusing human criticism with algorithmic analysis. The purpose of this article is to facilitate an informed discussion among artists, curators, and educators regarding the moral and practical ramifications of letting machines contribute to the interpretation of creative progress.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 2109-2113

Automated Aesthetic Evaluation: Can AI Objectively Assess Creative Growth? - A Critical Analysis

Available:https://ijirt.org/Article?manuscript=175188

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