# Empowering Clients -- Transformation of Design Processes Due to Generative AI

arXiv: https://arxiv.org/abs/2411.15061 · HTML: https://mlsanity.com/paper/2411.15061/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 39 references that are in the map.
- First posted on arXiv 22 Nov 2024.

## Builds on (most cited first, 7 of 7)

- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [The Creativity of Text-to-Image Generation](https://mlsanity.com/paper/2206.02904/) (2022)
- [Large-scale Text-to-Image Generation Models for Visual Artists' Creative Works](https://mlsanity.com/paper/2210.08477/) (2022)
- [Using Text-to-Image Generation for Architectural Design Ideation](https://mlsanity.com/paper/2304.10182/) (2023)
- [AI Art in Architecture](https://mlsanity.com/paper/2212.09399/) (2022)
- [Creativity of Deep Learning: Conceptualization and Assessment](https://mlsanity.com/paper/2012.02282/) (2020)
- [Governance of Generative Artificial Intelligence for Companies](https://mlsanity.com/paper/2403.08802/) (2024)

## Abstract (arXiv)

Generative AI (GenAI) is transforming creative fields shaping our culture and our heritage. We focus on widespread interactions between clients and (creative) specialists highlighting a change in interaction patterns leading to a shift from the use of expert creativity towards AI-supported client creativity. More specifically, we explore the case of architecture as designing houses is complex involving extensive customer interaction. We investigate the effects of GenAI on the architectural design process and discuss the role of the architect. Our study involved six architects using a general-purpose text-to-image tool for generating designs and providing feedback followed by expert interviews. We find that AI can disrupt the ideation phase by enabling clients to engage in the design process through rapid visualization of their ideas. In turn, so our thesis, the architect's role shifts towards assessing feasibility of such designs. AI's feedback, though valuable, can hamper creativity and innovation by suggesting altering novel, innovative approaches towards more standardized designs. We find that there is uncertainty among architects about the interpretative sovereignty of architecture and identity when AI increasingly takes over authorship. Our findings can also support the design of future AI systems by pinpointing weaknesses and highlighting a novel design process calling for tighter client integration. In our discussion, we also generalize our findings on a broader societal level elaborating on the change of a number of characteristics such as power, capability and responsibility in the triangle of AI, experts, and non-experts. We also discuss risks such as cultural uniformity when it comes to using AI to design artifacts central to our cultural heritage.