Abstract:This essay examines how Generative AI (GenAI) is rapidly transforming design practices and how discourse often falls into over-simplified narratives that impede meaningful research and practical progress. We identify and deconstruct five prevalent "semantic stopsigns" -- reductive framings about GenAI in design that halt deeper inquiry and limit productive engagement. Reflecting upon two expert workshops at ACM conferences and semi-structured interviews with design practitioners, we analyze how these stopsigns manifest in research and practice. Our analysis develops mid-level knowledge that bridges theoretical discourse and practical implementation, helping designers and researchers interrogate common assumptions about GenAI in their own contexts. By recasting these stopsigns into more nuanced frameworks, we provide the design research community with practical approaches for thinking about and working with these emerging technologies.
Abstract:AI is becoming increasingly popular in artistic practices, but the tools for informing practitioners about the environmental impact (and other sustainability implications) of AI are adapted for other contexts than creative practices -- making the tools and sustainability implications of AI not accessible for artists and creative practitioners. In this position paper, I describe two empirical studies that aim to develop environmental sustainability reflection systems for AI Arts, and discuss and introduce Explainable Sustainability in for AI Arts.
Abstract:The recent developments of artificial intelligence increase its capability for the creation of arts in both largely autonomous and collaborative contexts. In both contexts, Ai aims to imitate, combine, and extend existing artistic styles, and can transform creative practices. In our ongoing research, we investigate such Creative-Ai from sustainability and ethical perspectives. The two main focus areas are understanding the environmental sustainability aspects (material, practices) in the context of artistic processes that involve Creative-Ai, and ethical issues related to who gets to be involved in the creation process (power, authorship, ownership). This paper provides an outline of our ongoing research in these two directions. We will present our interdisciplinary approach, which combines interviews, workshops, online ethnography, and energy measurements, to address our research questions: How is Creative-Ai currently used by artist communities, and which future applications do artists imagine? When Ai is applied to creating art, how might it impact the economy and environment? And, how can answers to these questions guide requirements for intellectual property regimes for Creative-Ai?