Exploring the Horizon of Computation for Creativity2023

that utilize artificial intelligence. Chung proposes for AI-powered tools to effectively support artistic processes, they must seamlessly integrate into existing workflows and enable the expression of subtle intentions through gradual changes. For Chung, designers hold, therefore, a crucial role, as these tools will influence whether such technologies benefit or harm society. Professor Lydia Chilton’s examines the use of AI in the design process, which provides further insights into this topic. She analyzes both the successes and failures of designing with AI and concludes that, while AI can be helpful, it requires human guidance to truly become a powerful creative tool. To reach this conclusion, she shares her journey in demystifying the “magic” of the design process and the role generative AI systems can play in that process. Chilton describes neither of these is magical, but instead requires work to execute or understand. She identifies the “flare” portion of the design process as a place where AI can support the design process by providing access to a wide range of inspiration. T he advent of machine learning models, such as DALL-E, Midjourney, and ChatGPT, has prompted artists and researchers to revisit the concept of creativity. As with any new technology being introduced in practice, reactions diverge, ranging from the enthusiastic embrace of new possibilities to apprehensive avoidance. This current time exacerbated by social media echoes Walter Benjamin’s criticisms regarding reproduction technologies such as photography and film [1]. With the democratization of art-making through these technologies, will art lose its “aura,” its uniqueness? Of course, it won’t! Art is founded on human expressivity and spirituality and its value is ultimately validated through its potential to create emotional connections between artists and audiences. While tools like machine learning models can certainly support artistic expressiveness, art transcends mere tool usage and remains a testament to human creativity. In this issue, we explore the various ways in which computation can assist in creating media, art, design, and craft. With our selection of authors, we wished to encompass a broad spectrum of computational support that ranges from practitioners manually creating most of the outcome with light forms of computer automation to practitioners minimally guiding the outcome with fully generative computational processes. To examine this spectrum, we have brought together artists, designers, and researchers with diverse expertise to discuss their respective practices, spanning digital fabrication to support craft practices, human-robot collaborative performance, and AIgenerated visual design. The objective is to present perspectives acknowledging both the potential advantages and drawbacks of integrating automation to support creativity. These perspectives are presented with a focus on understanding how artists and researchers define their interactions with computers and how these interactions affect their creative process. Specifically, these articles will investigate the different roles taken by computational technologies within this creative spectrum: a tool for reducing tedium, a guide for exploring a creative space, a creative medium for enabling new forms of art, a collaborator with its own intentions, or a nuanced combination of these different roles. Our investigation starts with discussing the role and implication of AI for creativity support. Our first article, authored by Dr. John Chung, draws parallels between AI-powered tools for art production and the introduction of technology (AI or not) in creative domains. They democratize both the distribution and production of creative outputs. He further delves into the crucial role of designers of creativity-support tools Exploring the Horizon of Computation for Creativity