The creative thoughts of a young girl are augmented by the circuitry of an AI neural network.
Neural Network (2023)

Is Copyright Now Under Threat From A.I. Machine Learning?

The emergence of machine learning has given many illustrators and visual artists cause for concern. The techlash has been especially pronounced where artwork is used by A.I. companies to train image making models. This also marks a turn for illustration markets which can now potentially be serviced by A.I. generators.

Unlike the availability of creative software, A.I. does not remove barriers to entry, it removes the need for practical expertise. Text and Data Mining is essential for A.I. development, and governments have granted copyright exceptions to make those inputs available. As a result, text-to-image generators like Stable Diffusion, Midjourney, and DALL·E, are being trained using copyrighted images harvested from the internet.

The Fallout from Machine Learning Outputs

The likelihood is that the A.I. generated outputs are where most first encounter this emergent technology. Though not protectable by copyright, an illustrator’s style is often a crucial part of their stock-in-trade, which has been made easier to coopt with little recourse. The difficulty of enforcement is partly why has been developed by digital artists Matt Dryhurst and Holly Herndon. Rather than react via copyright warnings and takedowns, this digital service allows artists to opt in or out of datasets used in A.I. training.

From a legal perspective, if author attribution can be reassigned by this technology, the bearing on copyright ownership is significant. Litigation involving entertainment companies repeatedly shows us how copyright can be weaponised.

First, can you copyright the output of a generative AI model, and if so, who owns it? Second, if you own the copyright to the input used to train an AI, does that give you any legal claim over the model or the content it creates?

Andres Guadamuz speaking with James Vincent – The Verge

Unsurprisingly the Society of Illustrators has disallowed A.I. work from their annual competitions. Their rationale is that A.I. has been trained using copyrighted images, which they view as “the cornerstone of the illustration community.” Similarly, the Association of Illustration has urged the Intellectual Property Office to reconsider the copyright exception granted for A.I. training.

This exception would mean that creators and rights holders of images would not be able to prevent their work from being scraped for data unless it was protected behind a paywall, which clearly would not be practical for image makers who want potential commissioners to see their work in the easiest way possible (or stock libraries who want to licence images).

The Association of Illustration

Platforms Abetting Machine Learning

Though authorial works are protected by copyright, when original content is published to an online platform those rights can be held hostage. Artist gallery platforms Artstation and DeviantArt have drawn the ire of their user-base for permitting image scraping. The community reaction has led to them introducing opt-in ‘No-AI’ tags, preventing content being used to develop A.I. generators. Meanwhile, A.I. generated images have become viral on social media.

Are A.I. Generated Images the New Stockart

Much concern related to A.I. generated images is around the erosion of illustration’s market value. Once prompted, an image generator can render countless images, making the task one of curation and adjustment. It is disheartening that a person’s creations can be used to undermine the viability of markets for that very work. Author and art journalist Zachary Small writes in Artnet;

Recent developments in machine-learning programs have turned A.I. into an impressive artistic tool capable of outpacing—and underpricing—human artists, touching off an earthquake in creative circles. Anxieties are highest among graphic artists and commercial illustrators whose livelihood is connected to their ability to turn out content to clients’ specification.

Zachary Small – Artnet

The notion that A.I. is a technological tool frames its comparison with other historical technologies. Engravers were made redundant electrotype plates, and illustrators gradually lost the advertising market because of advancements in photography. But the execution of artwork has always been pegged to human authorial intent, which is not the case with A.I. Conceptual artists can often provide a reasonable argument for the superordiante role of creative authorship. But as conceptualism has shown, this does not bode well for human craftsmanship, nor the autographic works of hand and mind working as one.

The Un-new Truths of Our Derivative Culture

In spite of how societies glorify creativity, derivative works are much the norm in our post-digital culture. This coupled with algorithmic bias means little of what we encounter is truly original. Be this as it may, published content once had to be made by people. As emphasised by the AOI, an illustrator’s contribution is not merely the image creation, but also suggesting ideas and exploring a brief to bring about best results. Though cases of progressive work using A.I. are likely, one can imagine how generators trained on chirographic man-made images shall mostly amplify the dominance of derivate images.

Might Legislation Catchup to A.I.

The intersection between A.I. and copyright law is rapidly evolving, and is where many expect to see landmark cases in the coming months. The use of A.I. does recast the role of authorship, and often makes a claim for copyright protection less accessible. However, in spite of its shortfalls, copyright law may be one of the best available deterrents against A.I. enabled plagiarism. The stakes are high. If the cultural products we consume are A.I. generated, the potential for controlling human perception may become centralised in a way that won’t be easily unspun.

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