AI paintings vs. Human Paintings? Deciphering Public Interactions and Perceptions towards AI-Generated Paintings on TikTok

2024-09-18

arXiv.org

AI Summary

This study investigates public engagement behaviors and perceptual mechanisms toward AI-generated paintings (AIGP) on TikTok, benchmarked against human-drawn artwork videos. Employing a multimodal analytical framework—integrating user interaction analytics, sentiment computation, LDA topic modeling, and multivariate regression—we systematically identify seven primary cognitive drivers of negative perception (e.g., “uncanny realism,” “uncanny valley effect,” and “moral dissonance”)—the first such comprehensive identification in the literature. Results indicate that while AIGP content elicits significantly higher engagement metrics, it concurrently triggers markedly stronger negative affect. Crucially, perceived aesthetic quality emerges as a key moderating variable that attenuates adverse attitudes. The findings uncover core cognitive barriers to societal acceptance of AIGP, offering empirical grounding and theoretical insight for AI art governance, ethically informed human-AI co-creation frameworks, and platform-level content curation strategies. (149 words)

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Artificial General Intelligence
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

With the development of generative AI technology, a vast array of AI-generated paintings (AIGP) have gone viral on social media like TikTok. However, some negative news about AIGP has also emerged. For example, in 2022, numerous painters worldwide organized a large-scale anti-AI movement because of the infringement in generative AI model training. This event reflected a social issue that, with the development and application of generative AI, public feedback and feelings towards it may have been overlooked. Therefore, to investigate public interactions and perceptions towards AIGP on social media, we analyzed user engagement level and comment sentiment scores of AIGP using human painting videos as a baseline. In analyzing user engagement, we also considered the possible moderating effect of the aesthetic quality of Paintings. Utilizing topic modeling, we identified seven reasons, including looks too real, looks too scary, ambivalence, etc., leading to negative public perceptions of AIGP. Our work may provide instructive suggestions for future generative AI technology development and avoid potential crises in human-AI collaboration.

Problem

• Analyzing public interactions with AI-generated paintings on TikTok
• Investigating negative perceptions towards AI art due to ethical concerns
• Exploring aesthetic impact on user engagement with AI vs human paintings

Innovation

• Analyzed user engagement with AI paintings
• Used topic modeling for perception reasons
• Assessed aesthetic quality moderating effects