An Intent of Collaboration: On Agencies between Designers and Emerging (Intelligent) Technologies

• URL: http://arxiv.org/abs/2603.12018v1
• Date: Thu, 12 Mar 2026 15:00:18 GMT
• Title: An Intent of Collaboration: On Agencies between Designers and Emerging (Intelligent) Technologies
• Abstract summary: Three designers embarked on a three-month journey with Google's LLM to investigate how it will influence their creativity.<n>We found that a power dynamic of agencies exists between the LLM and the designer, in which the designer can easily lose their creative agency.<n>We propose paying attention to the designer's inner world and parties of agencies when engaging with emerging intelligent technologies.
• Score: 6.699291133590307
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Amidst the emergence of powerful intelligent technologies such as LLMs and text-to-image AIs that promise to enhance creative processes, designers face the challenges of remaining empowered and creative while working with these foreign digital partners. While generative AIs offer versatile, informative, and occasionally poetic outcomes, their lack of embodied knowledge presents an even greater challenge to designers in gaining fruitful outcomes, such as in the field of Digital Craftsmanship. In this project, three designers embarked on a three-month experimental journey with an intention to co-create with Google's LLM as a potential intelligent partner to investigate how it will influence the designers' creativity. We found that a power dynamic of agencies exists between the LLM and the designer, in which the designer can easily lose their creative agency. Regaining the designer's creative agency involves introspection into their own creative process, a structural understanding of the specific emerging technology involved, and deliberate adjustments to the dynamics of the human-technology relationship. We propose paying attention to the designer's inner world and parties of agencies when engaging with emerging intelligent technologies through three aspects: the sensitivity towards a creative process as cognitive activities; the active investigation into specific technology's capability; and the adjustment towards an appropriate working relationship between the designer and the emerging technology.

Related papers

• Architectural practice process and artificial intelligence -- an evolving practice [0.0]
  Article explores the multifaceted roles of AI in the architectural process.<n>It emphasizes its potential to enhance creativity and efficiency while addressing its limitations.<n>Findings reveal that AI is increasingly integrated across various stages of the architectural process.
  arXiv  Detail & Related papers  (2025-07-31T15:33:28Z)
• AI Flow: Perspectives, Scenarios, and Approaches [51.38621621775711]
  We introduce AI Flow, a framework that integrates cutting-edge IT and CT advancements.<n>First, device-edge-cloud framework serves as the foundation, which integrates end devices, edge servers, and cloud clusters.<n>Second, we introduce the concept of familial models, which refers to a series of different-sized models with aligned hidden features.<n>Third, connectivity- and interaction-based intelligence emergence is a novel paradigm of AI Flow.
  arXiv  Detail & Related papers  (2025-06-14T12:43:07Z)
• Extended Creativity: A Conceptual Framework for Understanding Human-AI Creative Relations [0.6031721946649193]
  We identify three fundamental modes by which AI can support and shape creative processes.<n>Support, where AI acts as a tool; Synergy, where AI and humans collaborate in complementary ways; and Symbiosis, where human and AI cognition become so integrated that they form a unified creative system.<n>We examine how each configuration influences different levels of creativity from everyday problem solving to paradigm shifting innovation.
  arXiv  Detail & Related papers  (2025-06-12T00:16:52Z)
• Probing and Inducing Combinational Creativity in Vision-Language Models [52.76981145923602]
  Recent advances in Vision-Language Models (VLMs) have sparked debate about whether their outputs reflect combinational creativity.<n>We propose the Identification-Explanation-Implication (IEI) framework, which decomposes creative processes into three levels.<n>To validate this framework, we curate CreativeMashup, a high-quality dataset of 666 artist-generated visual mashups annotated according to the IEI framework.
  arXiv  Detail & Related papers  (2025-04-17T17:38:18Z)
• Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems [132.77459963706437]
  This book provides a comprehensive overview, framing intelligent agents within modular, brain-inspired architectures.<n>It explores self-enhancement and adaptive evolution mechanisms, exploring how agents autonomously refine their capabilities.<n>It also examines the collective intelligence emerging from agent interactions, cooperation, and societal structures.
  arXiv  Detail & Related papers  (2025-03-31T18:00:29Z)
• Empowering Clients: Transformation of Design Processes Due to Generative AI [1.4003044924094596]
  The study reveals that AI can disrupt the ideation phase by enabling clients to engage in the design process through rapid visualization of their own ideas. Our study shows that while AI can provide valuable feedback on designs, it might fail to generate such designs, allowing for interesting connections to foundations in computer science. Our study also reveals that there is uncertainty among architects about the interpretative sovereignty of architecture and loss of meaning and identity when AI increasingly takes over authorship in the design process.
  arXiv  Detail & Related papers  (2024-11-22T16:48:15Z)
• 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)
• Can AI Be as Creative as Humans? [84.43873277557852]
  We prove in theory that AI can be as creative as humans under the condition that it can properly fit the data generated by human creators. The debate on AI's creativity is reduced into the question of its ability to fit a sufficient amount of data.
  arXiv  Detail & Related papers  (2024-01-03T08:49:12Z)
• Designing Participatory AI: Creative Professionals' Worries and Expectations about Generative AI [8.379286663107845]
  Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. This paper presents the results of a qualitative survey investigating how creative professionals think about generative AI.
  arXiv  Detail & Related papers  (2023-03-15T20:57:03Z)
• 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)
• Guru, Partner, or Pencil Sharpener? Understanding Designers' Attitudes Towards Intelligent Creativity Support Tools [4.812445272764651]
  Creativity Support Tools (CST) aim to enhance human creativity, but the deeply personal and subjective nature of creativity makes the design of universal support tools challenging. Artificial Intelligence (AI) and Machine Learning (ML) techniques could provide a means of creating 'intelligent' CST which learn and adapt to personal styles of creativity. This paper details the results of a survey of professional designers which indicates a positive and pragmatic attitude towards collaborating with AI tools.
  arXiv  Detail & Related papers  (2020-07-09T14:52:52Z)

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.