Reimagining London's Stage by Kat Greenbrook

This piece uses AI-generated art to visualise text analysis data.

AI art is created from complex neural networks that generate images from word prompts. In simple terms, the AI turns text into an image. What I was interested in, is how this technology could be applied to text analytics. Data visuals aren't known for their emotional perspective but images have the power to evoke more of this in viewers. AI art has the potential to create emotive visualisations that are derived directly from data.

Data analysed are part of the London Stage Database and documents 140 years of performances between 1659 and 1800. The dataset was featured in The Data Visualisation Society’s Data is Plural challenge.

I used the Midjourney model to visualise this data. You can read more about the process here: https://www.linkedin.com/pulse/how-i-used-ai-generated-art-visualise-text-analysis-data-greenbrook

I often use design elements as part of my data visuals to evoke emotion from the reader. I like to experiment with this aspect of data visualisation. While design elements (like colour, photography, video, and music) can help a communication evoke emotion, never has data been able to produce these elements directly – as AI art can.

Many people feel threatened by this technology. Where it may evolve is both an exciting and scary thought. But generating good images from text is not as simple as clicking a button (there is still a lot of design work involved). How this technology could be used to visualise data is something I can't wait to explore further!