Image generating AI software seems most applicable to fields like animation, where the algorithm is following along a linear progression of predictable movement. In such a circumstance, the system would be fed imagery data of a very specific style, making it a necessity that the outcome be consistent. For artists using AI, there also seems to be a reliance on a tightly cohesive, but baseline, style or aesthetic – even if the definitive components in the render are acutely described through lengthy input prompts. I see this as indicating the need for a preexisting relationship with the generating content and/or individual user — if the intention is to create a very particular imagined ideal. 

The use of open AI image generation theoretically means the data set would be comprised from the internet, at large. Then it can be assumed the resulting styles should be wide in variety with intrinsic poetic misunderstandings due to a lack of an underlying relationship with the individual user. While we have a more predictable result when we implement stiff inputs, I wanted to explore the mechanized comprehension of surface-level suggestions on an open platform.

For my social media accounts, I post a daily art idea on X. Indirectly, I am not trying to curate a unique aesthetic, but an identifying style of conceptual Art; one where the value of text is not signified through the scale of a viewer’s relationship to a gallery wall, but in the kernel of notional creative suggestions. These became optimal prompts to feed into AI image generating software, where I wanted to explore the artificial intelligence’s conceptual comprehensibility in an active way. It also happens to create a visual content stream for Instagram’s platform.