Dialogue with the Machine and Dialogue with the Art World: Evaluating Generative AI for Culturally-Situated Creativity

• URL: http://arxiv.org/abs/2412.14077v1
• Date: Wed, 18 Dec 2024 17:21:14 GMT
• Title: Dialogue with the Machine and Dialogue with the Art World: Evaluating Generative AI for Culturally-Situated Creativity
• Authors: Rida Qadri, Piotr Mirowski, Aroussiak Gabriellan, Farbod Mehr, Huma Gupta, Pamela Karimi, Remi Denton,
• Abstract summary: Drawing on sociologist Howard Becker's concept of Art Worlds, this method expands the scope of traditional AI and creativity evaluations. Our method involves two mutually informed dialogues: 1) 'dialogues with art worlds' placing artists in conversation with experts such as art historians, curators, and archivists, and 2)'dialogues with the machine,' facilitated through structured artist- and critic-led experimentation with state-of-the-art generative AI tools.
• Score: 3.8440908669202676
• License:
• Abstract: This paper proposes dialogue as a method for evaluating generative AI tools for culturally-situated creative practice, that recognizes the socially situated nature of art. Drawing on sociologist Howard Becker's concept of Art Worlds, this method expands the scope of traditional AI and creativity evaluations beyond benchmarks, user studies with crowd-workers, or focus groups conducted with artists. Our method involves two mutually informed dialogues: 1) 'dialogues with art worlds' placing artists in conversation with experts such as art historians, curators, and archivists, and 2)'dialogues with the machine,' facilitated through structured artist- and critic-led experimentation with state-of-the-art generative AI tools. We demonstrate the value of this method through a case study with artists and experts steeped in non-western art worlds, specifically the Persian Gulf. We trace how these dialogues help create culturally rich and situated forms of evaluation for representational possibilities of generative AI that mimic the reception of generative artwork in the broader art ecosystem. Putting artists in conversation with commentators also allow artists to shift their use of the tools to respond to their cultural and creative context. Our study can provide generative AI researchers an understanding of the complex dynamics of technology, human creativity and the socio-politics of art worlds, to build more inclusive machines for diverse art worlds.

Related papers

• Art-Free Generative Models: Art Creation Without Graphic Art Knowledge [50.60063523054282]
  We propose a text-to-image generation model trained without access to art-related content. We then introduce a simple yet effective method to learn an art adapter using only a few examples of selected artistic styles.
  arXiv  Detail & Related papers  (2024-11-29T18:59:01Z)
• Alien Recombination: Exploring Concept Blends Beyond Human Cognitive Availability in Visual Art [90.8684263806649]
  We show how AI can transcend human cognitive limitations in visual art creation. Our research hypothesizes that visual art contains a vast unexplored space of conceptual combinations. We present the Alien Recombination method to identify and generate concept combinations that lie beyond human cognitive availability.
  arXiv  Detail & Related papers  (2024-11-18T11:55:38Z)
• Visions of Destruction: Exploring a Potential of Generative AI in Interactive Art [2.3020018305241337]
  This paper explores the potential of generative AI within interactive art, employing a practice-based research approach. It presents the interactive artwork "Visions of Destruction" as a detailed case study, highlighting its innovative use of generative AI to create a dynamic, audience-responsive experience.
  arXiv  Detail & Related papers  (2024-08-26T21:20:45Z)
• Diffusion-Based Visual Art Creation: A Survey and New Perspectives [51.522935314070416]
  This survey explores the emerging realm of diffusion-based visual art creation, examining its development from both artistic and technical perspectives. Our findings reveal how artistic requirements are transformed into technical challenges and highlight the design and application of diffusion-based methods within visual art creation. We aim to shed light on the mechanisms through which AI systems emulate and possibly, enhance human capacities in artistic perception and creativity.
  arXiv  Detail & Related papers  (2024-08-22T04:49:50Z)
• Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre [48.19823828240628]
  This study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. We explore the technical capabilities and constraints of on-the-spot multi-party dialogue. Our human-in-the-loop methodology underlines the challenges of these LLMs in generating context-relevant responses.
  arXiv  Detail & Related papers  (2024-05-11T23:19:42Z)
• Equivalence: An analysis of artists' roles with Image Generative AI from Conceptual Art perspective through an interactive installation design practice [16.063735487844628]
  This study explores how artists interact with advanced text-to-image Generative AI models. To exemplify this framework, a case study titled "Equivalence" converts users' speech input into continuously evolving paintings. This work aims to broaden our understanding of artists' roles and foster a deeper appreciation for the creative aspects inherent in artwork created with Image Generative AI.
  arXiv  Detail & Related papers  (2024-04-29T02:45:23Z)
• Exploring the Intersection of Complex Aesthetics and Generative AI for Promoting Cultural Creativity in Rural China after the Post-Pandemic Era [13.763608420284195]
  This paper explores using generative AI and aesthetics to promote cultural creativity in rural China amidst COVID-19's impact. The study finds artworks often fail to resonate locally, while reliance on external artists limits sustainability. Our approach involves training machine learning on subjective aesthetics to generate culturally relevant content.
  arXiv  Detail & Related papers  (2023-09-05T11:27:16Z)
• Art and the science of generative AI: A deeper dive [26.675816750583138]
  generative AI can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation. We argue that generative AI is not the harbinger of art's demise, but rather is a new medium with its own distinct affordances.
  arXiv  Detail & Related papers  (2023-06-07T04:27:51Z)
• Pathway to Future Symbiotic Creativity [76.20798455931603]
  We propose a classification of the creative system with a hierarchy of 5 classes, showing the pathway of creativity evolving from a mimic-human artist to a Machine artist in its own right. In art creation, it is necessary for machines to understand humans' mental states, including desires, appreciation, and emotions, humans also need to understand machines' creative capabilities and limitations. We propose a novel framework for building future Machine artists, which comes with the philosophy that a human-compatible AI system should be based on the "human-in-the-loop" principle.
  arXiv  Detail & Related papers  (2022-08-18T15:12:02Z)
• Understanding and Creating Art with AI: Review and Outlook [12.614901374282868]
  Technologies related to artificial intelligence (AI) have a strong impact on the changes of research and creative practices in visual arts. This paper provides an integrated review of two facets of AI and art: 1) AI is used for art analysis and employed on digitized artwork collections; 2) AI is used for creative purposes and generating novel artworks. In relation to the role of AI in creating art, we address various practical and theoretical aspects of AI Art and consolidate related works that deal with those topics in detail.
  arXiv  Detail & Related papers  (2021-02-18T01:38:11Z)
• Art Speaks Maths, Maths Speaks Art [53.473846742702854]
  Our interdisciplinary team Mathematics for Applications in Cultural Heritage (MACH) aims to use mathematical research for the benefit of the arts and humanities. Our ultimate goal is to create user-friendly software toolkits for artists, art conservators and archaeologists.
  arXiv  Detail & Related papers  (2020-07-17T10:24:23Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.