AI makes unprecedented waves in the creative world with the popularisation of platforms like midjourney, DALL-E 2 and stable diffusion. But how realistic, and how useful is the result?

Simple, accessible, and easy to use, the incredible innovations in open AI technology enables anyone to create high quality visuals in a matter of seconds. From visualising pop-up concepts, brand collaborations and re-imagining existing ones, uses for AI in design has offering alternatives to traditional  processes with spectacular momentum.

Unsurprisingly, the debate around AI is huge and complex.

With laws not developing fast enough to keep up with the quickly evolving technology, issues around intellectual property and copyright are rife, making it undeniably tricky territory to navigate. Other issues like ‘recognisably ai’ results, and limited data pools are all potential limitations on the creative value of AI outputs and the value of AI in design.

Production feasibility also limits the potential applications of AI generated concepts, such as a Nike pop-up concept situated ‘on the top of Everest’. Similarly, visuals created showing AI-imagined alternatives for high profile collaborations such as the Nike X Tiffany’s launch, suggest product concepts that make for a shiny visual but may lack real world feasibility.

Here’s a round up of some of our key takeaways from this innovative software:

Benefits:

• Accessibility:

The platforms are simple and easy to use. Without any training, nearly anyone can produce unique outputs that would have been inconceivable previously. By open sourcing creative tools that don’t require skills, the ability to contribute to creative discourse opens up to the majority.

• Efficient Transfer of Ideas:

Anyone can transform information and ideas into different mediums quickly and easily. This aids human communication and understanding on the highest of levels.

• Optimisation:

Like many technologies, AI software is a time optimisation tool. Not only is the speed of the digital result fast, the imitation of the skills, research time and development is a fraction of what it would be traditionally.

Limitations:

• Lack of Context:

Context gives art meaning. Artwork is developed not devoid of context, but informed by it. AI outputs may produce aesthetically pleasing results, but devoid of any authentic context means they outcome forfeits a large portion of value.

• Intellectual Property:

Using AI in design to directly imitate and merge artist’s and brands signature styles is questionable territory – the process of acquiring and processing these images and styles known as ‘scraping’. As such a quickly developing technology, legislation, application, and common morality surrounding the use of AI is still developing. (In the recent lawsuit against Stability AI, Getty images called it ‘brazen infringement on a staggering scale’.)

• Non-Useful or Generic Outputs:

Without extremely advanced and specialised prompting, many AI generated visuals are aspirational but not feasible for a majority of projects. Translating AI imagined outputs into actionable designs will mostly be more arduous, less efficient, and potentially disappointing for clients than starting from scratch.

AI is making creative outputting ‘quick and easy’ – however often the concepts reflect as such. We don’t know many brands who would openly sacrifice creativity and quality innovation for, when treated as a final product, the design equivalent of fast food. We also see how skilled creatives have been mastering the input process of AI systems, and using these new tools to aid their design process.

However, As a technology that truly cannot be compared to any that have come before it, time is yet to tell how AI will be widely accepted and integrated into design long – term.

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