Designing for appreciation: how digital spaces can support art and culture

Thesis

This thesis investigates the intricate dynamics of the intersection of art and computer science, particularly focusing on the roles of creation, curation, and appreciation within digital spaces. As art increasingly interacts with algorithmic curation, understanding how these processes shape audience perceptions and engagement is crucial. We analyze the transformation of artists' mental models into artworks through digitization and algorithmic experiences (AX), emphasizing the impact of these processes on public appreciation of art.

The research centers on four primary initiatives. First, we examine the lived experiences of artists, curators, content creators, and the public regarding "contentification"—the reduction of diverse artistic expressions into generic content. Interviews and surveys reveal four essential features for appreciating art: depth, conversation, connection, and time. Co-design workshops with art experts generated guidelines for enhancing digital art experiences.

Next, we explore the distinctions in perception between human and algorithmic curation through the Algorithmic Pedestal project, highlighting the subjective versus objective interpretations of art. This analysis underscores the inherent limitations of computational methods in capturing the emotional and contextual nuances that human audiences value.

In the third initiative, we introduce AppraiSet, an open-source dataset of art metadata designed to address gaps in current algorithmic processing. This resource facilitates deeper understanding of art through machine learning and highlights how qualitative data can enrich algorithmic art analysis.

Lastly, we present ArtBot, a Socratic LLM prototype aimed at guiding users through artwork analysis. Through experimental evaluations, we demonstrate that ArtBot enhances critical engagement compared to traditional and social media contexts. The findings contribute to a broader discussion on the role of algorithms in shaping art appreciation, advocating for an integration of human agency in algorithmic curation processes.

Overall, this research illuminates the evolving landscape of art curation in the digital age, proposing actionable insights and frameworks for enhancing audience experiences and engagement with art and culture.

Authors: Von Davier, TŞ

• DOI: 10.5287/ora-6qrmqog5b
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: art; recommender systems; human-centered AI; prototype; algorithms; artificial intelligence (AI); human-computer interaction
• Subjects: Art; Artificial intelligence; Human-computer interaction