The ability of generative AI tools to analyse huge datasets can also be used to help spark creative inspiration. This can help us if we’re struggling for time or battling writer’s block. For example, if a social media manager is looking for ideas on how to engage alumni on Instagram, they could ask ChatGPT for suggestions based on recent popular content. They could then pick the best ideas from ChatGPT’s response and adapt them. We may use these tools in a similar way to how we ask a colleague for an idea on how to approach a creative task.

We may use these tools in a similar way to how we use search engines for researching topics and will always carefully fact-check before publication.

we will not publish any press releases, articles, social media posts, blog posts, internal emails or other written content that is 100% produced by generative AI. We will always apply brand guidelines, fact-check responses, and re-write in our own words.

We may use these tools to make minor changes to a photo to make it more usable without changing the subject matter or original essence. For example, if a website manager needs a photo in a landscape ratio but only has one in a portrait ratio, they could use Photoshop’s inbuilt AI tools to extend the background of the photo to create an image with the correct dimensions for the website.

This paper maps concepts from AI alignment onto a basic, three step interaction cycle, yielding a corresponding set of alignment objectives: 1) specification alignment: ensuring the user can efficiently and reliably communicate objectives to the AI, 2) process alignment: providing the ability to verify and optionally control the AI's execution process, and 3) evaluation support: ensuring the user can verify and understand the AI's output.

the notion of a Process Gulf, which highlights how differences between human and AI processes can lead to challenges in AI control.

With the comprehensive application of Artificial Intelligence into the creation and post production of images, it seems questionable if the resulting visualisations can still be considered ‘photographs’ in a classical sense – drawing with light. Automation has been part of the popular strain of photography since its inception, but even the amateurs with only basic knowledge of the craft could understand themselves as author of their images. We state a legitimation crisis for the current usage of the term. This paper is an invitation to consider Synthography as a term for a new genre for image production based on AI, observing the current occurrence and implementation in consumer cameras and post-production.