EMIL POLYAK
New Media and Animation Artist​
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Associate Professor
Program Director of the MS in Digital Media
Drexel University
Recent updates:​
Machines and Imagination: Navigating the Challenges of Generative AI in Foundational Art and Design Education The rapid integration of generative artificial intelligence (genAI) into art and design practices marks a transformative shift, presenting a critical juncture for foundational education. This paper examines the implications of genAI as a transformative technology on the development of future artists and designers, focusing on its potential impact on essential cognitive processes, particularly heteromorphic imagination. We argue that the uncritical adoption of genAI in art and design education may inadvertently alter the free flow of imaginative thought, crucial for innovative and original solutions. GenAI, while revolutionizing the production of prototypes, may influence students to focus prematurely on concrete outcomes, potentially bypassing the exploratory stage of heteromorphic imagination. This fluid, non-linear phase of ideation is fundamental to developing diverse, innovative concepts and is intrinsically linked to the phenomenological experience of the creative process. The paper addresses concerns about potential idea homogenization, cognitive development impacts, and the ethical implications of using AI-generated content, including the use of machine learning models trained on artists' work without permission. In response, we propose that foundational art and design education must evolve to nurture heteromorphic imagination while thoughtfully considering genAI. This approach involves developing pedagogical strategies that emphasize open-ended exploration, embrace ambiguity, and cultivate unique human creativity aspects while addressing ethical concerns. By confronting these challenges, we aim to contribute to developing artists and designers who can harness AI's transformative power while maintaining essential human creative thinking and ethical consideration.
Upcoming:
3D Gaussian Splat of Jack Lenor Larsen's Study This project integrates multiple computational photogrammetry and point-based rendering techniques to explore alternative methods of 3D capture for artifacts in situ. Our test bed is the personal collection of renowned American textile designer Jack Lenor Larsen, amassed during his 60-year career working globally with Indigenous craftspeople and contemporary craft industries. It resides in the LongHouse Reserve, Easthampton, NY, the home Larsen designed with architect Charles Forberg as a case study to exemplify a creative approach to contemporary life. Larsen believed that visitors experiencing art in living spaces have a unique learning experience (LongHouse Reserve, 2025). This phase of the project focuses on Larsen’s study. Walls, tables, bookshelves are covered with artifacts. The furniture and fittings are part of the collection of the LongHouse Reserve, some of which were designed by Larsen and some of which were Indigenous products. We use 3D Gaussian Splatting (3DGS) to represent the uniqueness of the objects and their relationships in situ, presenting a multi-layered view of those objects (Biedermann, 2021). Our process demonstrates how point-based rendering, particularly 3DGS, can complement traditional photogrammetry for preserving complex interior spaces and for sharing Larsen’s creative approach to contemporary life through interaction with the collection in virtual space.