# When Discourse Stalls: Moving Past Five Semantic Stopsigns about Generative AI in Design Research

arXiv: https://arxiv.org/abs/2503.08565 · HTML: https://mlsanity.com/paper/2503.08565/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 90 references that are in the map.
- First posted on arXiv 11 Mar 2025.

## Builds on (most cited first, 21 of 21)

- [Energy and Policy Considerations for Deep Learning in NLP](https://mlsanity.com/paper/1906.02243/) (2019)
- [The Effects of Generative AI on Design Fixation and Divergent Thinking](https://mlsanity.com/paper/2403.11164/) (2024)
- [CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI](https://mlsanity.com/paper/2312.11949/) (2023)
- [Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance](https://mlsanity.com/paper/2206.11922/) (2022)
- [UICoder: Finetuning Large Language Models to Generate User Interface Code through Automated Feedback](https://mlsanity.com/paper/2406.07739/) (2024)
- [Understanding Nonlinear Collaboration between Human and AI Agents: A Co-design Framework for Creative Design](https://mlsanity.com/paper/2401.07312/) (2024)
- [Cultural Incongruencies in Artificial Intelligence](https://mlsanity.com/paper/2211.13069/) (2022)
- [Meaningful human control: actionable properties for AI system development](https://mlsanity.com/paper/2112.01298/) (2021)
- [DesignGPT: Multi-Agent Collaboration in Design](https://mlsanity.com/paper/2311.11591/) (2023)
- [Green AI: Exploring Carbon Footprints, Mitigation Strategies, and Trade Offs in Large Language Model Training](https://mlsanity.com/paper/2404.01157/) (2024)
- [Generative AI Models for Different Steps in Architectural Design: A Literature Review](https://mlsanity.com/paper/2404.01335/) (2024)
- [The Myth of Culturally Agnostic AI Models](https://mlsanity.com/paper/2211.15271/) (2022)
- [No Longer Trending on Artstation: Prompt Analysis of Generative AI Art](https://mlsanity.com/paper/2401.14425/) (2024)
- [Patterns of Creativity: How User Input Shapes AI-Generated Visual Diversity](https://mlsanity.com/paper/2410.06768/) (2024)
- [Experiments on Generative AI-Powered Parametric Modeling and BIM for Architectural Design](https://mlsanity.com/paper/2308.00227/) (2023)
- [Improved Emotional Alignment of AI and Humans: Human Ratings of Emotions Expressed by Stable Diffusion v1, DALL-E 2, and DALL-E 3](https://mlsanity.com/paper/2405.18510/) (2024)
- [Gaud'i: Conversational Interactions with Deep Representations to Generate Image Collections](https://mlsanity.com/paper/2112.04404/) (2021)
- [Responding to Generative AI Technologies with Research-through-Design: The Ryelands AI Lab as an Exploratory Study](https://mlsanity.com/paper/2405.04677/) (2024)
- [AI Royalties -- an IP Framework to Compensate Artists & IP Holders for AI-Generated Content](https://mlsanity.com/paper/2406.11857/) (2024)
- [Recommendations for public action towards sustainable generative AI systems](https://mlsanity.com/paper/2402.01646/) (2024)
- [The Unbearable Lightness of Prompting: A Critical Reflection on the Environmental Impact of genAI use in Design Education](https://mlsanity.com/paper/2501.16061/) (2025)

## Abstract (arXiv)

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.