Nightshade, a tool allowing artists to 'poison' AI models

Apparently this is the same team and they claim that the previous one was only intended to prevent training on an artist's style.

ML researcher culture is hard to describe... But its something like "Everything is a research prototype, so why does it matter?"

Source? The authors claim this is not the case, and they have experiments showing it.

Even worse, we are prone to being influenced by the decor or surroundings in ways that we know, but still partake in. Mood lighting would be an easy example. And we are very influenced by our other senses at the same time as purely visual. (Though, I'm always amused by how much the VR experience of racing a car hits, all without too much haptic feedback from the steering wheel.)

Jerks are going to find dumb, lazy, malicious ways to abuse good tools, like they always do, though diffusion does have an conspicuously low effort barrier.

Another HN user summarized my thoughts on this better than I possibly could: https://news.ycombinator.com/item?id=37978805

To quote an artist that I know, "artists already steal. They're the masters at it."

Stealing inspiration and style is how artists learn. It just takes time. They're angry that the time investment is going to zero. And also that their examples are what are being used, despite the fact that other human artists are doing that already.

I'm not sure we should defend any difficulty or complexity. Even that of our own careers.

We'd still be churning our own butter if we were afraid of automation. And what time would that leave us with?

The typical argument against this is that human artists and ML models learn the same way, but the problem is that there's a fundamental difference: humans produce art by abstracting the concepts (think directional lighting, the kinematics of skeletal creatures, color theory, or physics of cloth) from the pieces they've studied and combining that with what they've learned from observing the world around them and by producing original art. This is why a human artist can produce competent art after studying only a handful of art pieces and gain most of their skill through practice.

By contrast, ML models do not learn by producing and have no way to directly observe the world. They don't abstract concepts, they "learn" by memorizing huge numbers of pre-existing images, and they produce images by patching together tiny bits and pieces of of those memorized images.

Where the human artist can function on little to no input, an ML model cannot, and so it's only fair that human artists have the choice to not have their works included in training datasets because if there is no feedstock of art there is no AI generated imagery.

I have a clog you can throw into a loom if it'll make you feel better, but there's no stopping AI art.

I think it seems very likely that that this will always be the case: if it is visually neutral enough to be acceptable for use, there will be a way to train systems to generate art that visually resembles the original based on the output.

One cool project for that> https://github.com/jsvine/markovify

(Personally had the most fun outputs when constructing the corpus from technical articles mixed with esoteric babble)

Active defense!

Given that real art is both incredibly cheap to produce and incredibly cheap to distribute I should think those who are so inspired will continue to produce works to inspire us. I mean the advent of printers, cheap prints, and stock images didn't destroy art so why should AI?