‘Data poisoning’: How artists are fighting back against Artificial Intelligence image generators

Imagine this. You need an image of a balloon for a work presentation and turn to a text-to-image generator, like Midjourney or DALL-E, to create a suitable image.

You enter the prompt: “red balloon against a blue sky” but the generator returns an image of an egg instead. You try again but this time, the generator shows an image of a watermelon.

What’s going on?

The generator you’re using may have been “poisoned”.

What is ‘data poisoning’?

Text-to-image generators work by being trained on large datasets that include millions or billions of images. Some generators, like those offered by Adobe or Getty, are only trained with images the generator’s maker owns or has a licence to use.

But other generators have been trained by indiscriminately scraping online images, many of which may be under copyright. This has led to a slew of copyright infringement cases where artists have accused big tech companies of stealing and profiting from their work.

This is also where the idea of “poison” comes in. Researchers who want to empower individual artists have recently created a tool named “Nightshade” to fight back against unauthorised image scraping.

The tool works by subtly altering an image’s pixels in a way that wreaks havoc to computer vision but leaves the image unaltered to a human’s eyes.

If an organisation then...

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