The language of photography in the age of AI

Text-to-image algorithms based on Deep Learning are central to content creation in multiple application domains. In the last few years, the capacity of Neural Networks to generate increasingly realistic images quickly has blurred the boundary between authentic and realistic content, making genuine and false data less and less distinguishable. This condition leads to a profound reflection on the application of photographic images as a tool for communication and storytelling, trying to answer simple questions. Can today’s Neural Networks generate content comparable and indistinguishable from a photograph in both formal and compositional terms? Can artificial intelligence algorithms replace the photographer’s ability to design and obtain images that preserve the story and the place’s intangible culture? From a set of photographic rules framed in specific workflows, the research analyses some results obtained using text-to-image algorithms within the Midjourney program. The experiment aims to determine the pros and cons of using text-to-image algorithms to automatically generate photographic images, highlighting the potential and current limitations in constructing content subject to specific formal rules.