Human vs. Computational Aesthetic Evaluation in Statistical Models of Art Prices

Abstract: This presentation provides a concise survey of the topic, spanning from hedonic regression models developed over the last 15-20 years to contemporary models based on automatic feature extraction and the extensive application of artificial intelligence. Particular emphasis is placed on the comparison between human and computational assessments of the aesthetic characteristics of paintings and their relationship to price. In addition to the mathematical aspects of the problem, numerous illustrative examples of painting evaluations will be presented. [1] Igor Mandel. Predicting Art Market Prices with AI-Based Aesthetic Evaluation, SSRN, 2026. [2] Igor Mandel, Stefano Mastandrea, Ivan Shamshurin, Kirill Rachenkov. Beauty or money? Statistical analysis. Model Assisted Statistical Applications, Volume 16, Issue 2, 2021. [3] Igor Mandel. Aesthetic, Art-Historical and Economic Values in Painting: Empirical Study, in: Integrative Explorations of the Creative Mind, Cambridge Scholars Publishing, 2019.

information theorystatistics theorydata analysis, statistics and probability

Audience: researchers in the topic

( chat )

Comments: Nice paintings will be shown. Prof. Dr. Igor Mandel is a well-known expert in data processing.

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Asymptotic Methods in Statistics

Series comments: One can find video files and slides of talks at the seminar on Asymptotic Methods in Statistics here: www.youtube.com/@SeminarforAsymptoticMethods

A link to a slide is below the description of the video, namely shorturl.at/jUAhL and shorturl.at/6wjUA shorturl.at/rdpqs

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