Generative AI and the History of Architecture

TL;DR

This paper investigates the knowledge and limitations of generative AI models in understanding architectural history, analyzing their ability to distinguish styles and their current usage in architectural queries.

Contribution

It provides an analysis of generative AI's understanding of architectural styles and examines real-world usage patterns through a large dataset of user queries.

Findings

AI models can distinguish some architectural styles but often hallucinate details.

Practitioners frequently query generative AI for specific architectural concepts.

Generative AI shows potential as a tool for architectural history and early design tasks.

Abstract

Recent generative AI platforms are able to create texts or impressive images from simple text prompts. This makes them powerful tools for summarizing knowledge about architectural history or deriving new creative work in early design tasks like ideation, sketching and modelling. But, how good is the understanding of the generative AI models of the history of architecture? Has it learned to properly distinguish styles, or is it hallucinating information? In this chapter, we investigate this question for generative AI platforms for text and image generation for different architectural styles, to understand the capabilities and boundaries of knowledge of those tools. We also analyze how they are already being used by analyzing a data set of 101 million Midjourney queries to see if and how practitioners are already querying for specific architectural concepts.