AI is provoking a myriad of reactions in the photography industry, but if we look back at the journey image-making has been on and the seismic shifts that have taken place there is reason for cautious optimism. From the heliograph invented in 1816 to the rise of film, digital and more recently smartphones, we understand that photography has always been entwined with technological, societal and cultural advancement.
It’s fair to say that from day one some image makers have been curious – excited even, about the possibilities presented by using Generative Adversarial Networks (GANs) which created visuals from existing data. This allowed photographers to create customised datasets, drawing on their own bank of images to create new work in their own style.
Text to image generators rely on huge datasets, and this is where the human component in photography is vital. Photography is in a unique position as far as AI is concerned, as AI struggles with reflecting aesthetics of emotion. AI tools cannot replace a human who draws on their expertise and emotional depth to read a situation, thinks creatively on their feet and tells a story. A photographer’s job often involves capturing a spontaneous moment in time and conveying a precise emotion. Nuances and decisions around composition and lighting can lend an image its individuality and a very particular aesthetic. These are areas where AI simply cannot replicate human creativity.
The benefits of creating images of products in a real environment, using real people are considerable because AI generated images lack the all important authenticity; an enormous motivator for consumer engagement. It comes back to the emotional connection which AI struggles with, and it’s exactly that emotional connection between a photographer and their subject that will ensure photographers’ ongoing relevance.
Where AI really does come into its own is its ability to analyse data and automate repetitive tasks. Using deep learning algorithms, AI’s image processing and recognition tools allow photographers to take better photos, and do so more quickly and efficiently. This is because AI can be used to enhance the quality and accuracy of photographs, improving detail and sharpness, adjusting exposure, contrast and colour balance as well as identifying and removing objects if required. Machine learning algorithms can further assist photographers by analysing enormous datasets of images, identifying and differentiating between different objects and subjects. This can be used to create personalised image recognition tools that can help photographers identify certain scenes or objects, and mock up images which can help in the planning of a shoot; these are time saving exercises freeing photographers up to explore other creative directions for a shoot.
If photographers can use AI to assist them, to analyse vast datasets to read the latest trends, or to speed up planning and post production stages, then AI can be a collaborative tool to enhance images and expand the scope of their creative work, while not compromising a photographer’s creative ideas. Essentially, this is about collaboration rather than replacement.
With the advancement of AI and datasets expanding at breakneck speed, the lines of ownership are blurred and fundamental questions of copyright, privacy and ethics must be addressed. A significant ethical issue is the stereotypes and biases witnessed in text to image generators. This suggests a limitation in the datasets around people, and something that the AI developers must review. As AI continues to develop, we must commit to full transparency around usage of AI tools at all stages of production, demand more consciously collected data, and explore how AI is being used in a critical way.
We advise keeping your Professional Indemnity cover up to date at all times to protect yourself against breaches of copyright and Intellectual Property.
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