人工知能で美術史の新生面を開く Reimagining Art History with Artificial Intelligence : Navigating Limitations and Pioneering New Paths for Innovation

著者名：Cempellin, Leda (EDT)/Geiger, Melissa (EDT)

Palgrave Macmillan（2026/07/12発売）

• 言語：ENG
• ISBN：9783032216847
• eISBN：9783032216854

Description

This anthology examines how AI and Art History intersect across research, museums, pedagogy, and global perspectives, revealing potential and limits in the interpretation of visual culture. Chapters explore new models for art, artificialism, deskilling, prosumption, AI‑generated imagery, and questions of sentience, alongside studio-sourced datasets and representational tools. Museum‑focused essays address AI’s catalogue raisonné, curating algorithms, and explainable AI, while teaching‑focused contributions analyze digital art history, computer vision, and Tree‑of‑Thought prompting. Global case studies consider the colonial gaze, information literacy, cultural constraints of text‑to‑image generation and text‑prompted image retrieval. The volume highlights Art History’s leadership guiding critical, ethical, empathetic AI uses.

Table of Contents

Chapter 1: Introduction. Towards an Integrated Ecosystem: AI and Art History as a Synergic Professional Landscape across Research, Museums, Pedagogy, and Global Perspectives.- PART I: Reframing Art History: Theoretical and Aesthetic Foundations in the Age of AI.- Chapter 2: New Models for Art: AI as a Representational Tool.- Chapter 3: The Human Glitch or Artificialism.- Chapter 4: AI Art, Deskilling and Prosumption.- Chapter 5:Not Touched By Human Hands: Misattributed AI Sentience and the Power of Images.- Chapter6: AI Interventions with a Studio-Sourced Dataset.- PART II: When Art History Meets AI in Museum Practices.- Chapter 7 : AI’s Catalogue Raisonné: Co-Curatorial Approaches to Digital Documentation of Art Collections.- Chapter 8: Curating the Algorithm: An Educational Encounter with AI and Art Exhibitions.- Chapter 9: Recognition as an Epistemic Glass Box: Explainable AI in Museum Contexts.- PART III: AI-Enhanced Pedagogy: Transforming Art History Education.- Chapter 10: From Digital Art History to Artificial Intelligence.- Chapter 11: Computer Vision, Human Vision, and Future Visions: Lessons from AI in the Liberal Arts Classroom.- Chapter 12: Utilising Tree-of-Thought Prompting to Facilitate Self-Reflective Analysis in Undergraduate Media Studies Students.- PART IV: AI-Driven Imagery: Global Insights for the Responsible Advancement of Art History.- Chapter 13: AI and the Colonial Gaze.- Chapter 14: Contextual and Cultural Limitations of Text-to-Image Generators: The Case of East Asia.- Chapter 15: Contextual and Cultural Limitations of Text-to-Image Generators: The Case of East Asia.- Chapter 16: Generative AI for Image-based Academic Use: An LLM-supported Assignment for Information Literacy and Visual Analysis of Indigenous American Fibre Arts.- PART V: Conclusion.- Chapter 17: Looking Ahead: Art History’s Call for Ethical Uses of AI To Build a More Thoughtful, Empathetic, and Responsible Society.