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Ask HN: DALL-E was trained on watermarked stock images?

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Re: Ask HN: DALL-E was trained on watermarked stock images?

#151

Post by [deleted] »

dmitriid wrote: post #137
kaetemi wrote: post #113

Earlier quoted context omitted.

Try 'poorly drawn ... by a 5 year old using crayons' in Midjourney.

Even then Midjourney is more high-quality :) See https://imgur.com/gallery/U5zJMcU Comparison of two prompts, "poorly futuristic landscape by a 5 year-old" and "poorly drawnn highly detailed futuristic landscape dotted by mahcinery and tall buildings by a 5 year-old" Also, https://imgur.com/gallery/jvEClos Comparison of "poorly drawn red sports car in the street of a city by a 5 year-old" Edit: forgot about crayons :…

[deleted]

Re: Ask HN: DALL-E was trained on watermarked stock images?

#152

Post by visarga »

csmpltn wrote: post #109
dlg wrote: post #30

I am not a lawyer, but I've had to argue about copyright with several. In the United States, there are two bits of case law that are widely cited and relevant: In Kelly v. Arriba Soft Corp (9th), found that making thumbnails of images for use in a search engine was sufficiently "transformative" that it was ok. Another case, Perfect 10 (9th), found that thumbnails for image search and cached pages were also transforma…

Putting aside the core question of the legality of training data on licensed material - what about the false advertising/copyright aspect that comes with slapping a "GettyImages" logo on some random nonsense generated by a "neural network"?

It's not worth discussing about Getty so much. AI labs will collect a dataset to predict if an image is watermarked. They will crawl to index the Getty images to make sure they are not in the training set. Then retrain and in 2 months the problem is solved. They can cut out a sizeable part of the training set without problem, the model will still be good.

They can also OCR the output to make sure there are no blacklisted words and use an index to skip all images that look too similar to the training data. Then the argument of copyright defenders is going to be weakened.

The fact that a prompt and curation are necessary also goes against the "AI works can't be copyrighted" narrative - it's generated by a human-AI team, so human work is part of the process.

The core of the issue I see is that human and AI both learn from the published media but an AI can both "see" and "draw" more than a human, so there is an important distinction there.

Re: Ask HN: DALL-E was trained on watermarked stock images?

#153

Post by whywhywhywhy »

ShamelessC wrote: post #13

> but surely you can't just... use stock photos without paying for the license? They aren't hosting the infringing content. Training on the data is probably covered under fair use. Generations are of _learned_ representations of the dataset, not the dataset itself. This makes it closer to outputting original works (probably owned by the person who used the model). The players involved here are known for being litigio…

What if my dataset is just the one Getty image I don’t want to pay for.

Re: Ask HN: DALL-E was trained on watermarked stock images?

#154

Post by ratonofx »

This copyright "issues" are against the true nature of innovation.

By the means of Artificial INTELIGENCE, we must to accept a mind or intelligence is free to perceive external elements and use every stimulus to execute its own creative process.

The world is a perpetual iteration cycle amongst human beings. Good artists borrow, great artists steal.

Re: Ask HN: DALL-E was trained on watermarked stock images?

#155

Post by Dylan16807 »

srg0 wrote: post #133
dlg wrote: post #30

I am not a lawyer, but I've had to argue about copyright with several. In the United States, there are two bits of case law that are widely cited and relevant: In Kelly v. Arriba Soft Corp (9th), found that making thumbnails of images for use in a search engine was sufficiently "transformative" that it was ok. Another case, Perfect 10 (9th), found that thumbnails for image search and cached pages were also transforma…

It seems it is possible to generate images which are very similar to the existing stock photos if you feed getty images' description into DALL-E. I tried it with a distinctive banana image: https://imgur.com/a/0OrIr6e

"very similar" insofar as it's following the narrow prompt, sure.

> Different runs can generate different size, orientation and placement of the bananas, as well as different shades of pink.

At that point it's definitely the curation causing any possible derivation. The image generator is innocently doing what you ask in an unbiased way.

Re: Ask HN: DALL-E was trained on watermarked stock images?

#156

Post by drcode »

ratonofx wrote: post #154

This copyright "issues" are against the true nature of innovation. By the means of Artificial INTELIGENCE, we must to accept a mind or intelligence is free to perceive external elements and use every stimulus to execute its own creative process. The world is a perpetual iteration cycle amongst human beings. Good artists borrow, great artists steal.

This comment should be on the Wikipedia article for "parody indistinguishable from reality"

Re: Ask HN: DALL-E was trained on watermarked stock images?

#157

Post by BeefWellington »

yreg wrote: post #102
BeefWellington wrote: post #28

Earlier quoted context omitted.

> Training on the data is probably covered under fair use. Generations are of _learned_ representations of the dataset, not the dataset itself. This makes it closer to outputting original works (probably owned by the person who used the model). "Probably" is doing a lot of heavy lifting in that sentence. As for "_learned_", that's pretty debatable considering it's reproducing recognizable trademark infringement. > Th…

Unlike Copilot, DALL-E et al. don't produce verbatim copies of trained data. Copying ideas and styles has always been a fundamental part of art history, so an artwork right holder might have a hard time successfuly sueing a user for the user's generated image looking similar to the right holder's artwork.

"Verbatim" is an interesting term since I'm not certain it matters. In this case OP here demonstrated DALL-E generating a trademarked watermark on top of an image. I doubt the courts, looking at that, would believe that that's not close enough to their trademark to infringe.

The art world's copyright suits are all over the place in terms of what's sufficient to meet the threshold of "fair use" or "not a copy".

It's hard for me as a layperson to see works by Richard Prince[1] as substantially transformative (clearly one work is derived from the other) and even the different courts couldn't agree on this as it was initially found in favor of the plaintiffs but then Prince won his appeal.

My approach to this kind of thing is simply this: Does this technology inherently open me up to lawsuits in undecided or highly unreliable legal territory? If yes, steer well clear of using it in any capacity.

[1]: https://www.artnews.com/art-in-america/features/richard-prin...

Re: Ask HN: DALL-E was trained on watermarked stock images?

#158

Post by Hnaomyiph »

drcode wrote: post #156
ratonofx wrote: post #154

This copyright "issues" are against the true nature of innovation. By the means of Artificial INTELIGENCE, we must to accept a mind or intelligence is free to perceive external elements and use every stimulus to execute its own creative process. The world is a perpetual iteration cycle amongst human beings. Good artists borrow, great artists steal.

This comment should be on the Wikipedia article for "parody indistinguishable from reality"

Regardless, I think I agree. I use images from all sources as inspiration for my art.

I know people who have used my pieces for inspiration as well. Intelligence and creativity aren’t bound by IP law.

Why should AI be bound by it?

Re: Ask HN: DALL-E was trained on watermarked stock images?

#159

Post by Terretta »

GuB-42 wrote: post #121
ehsankia wrote: post #44

Earlier quoted context omitted.

Top 1% is a bit exaggerated, but there is definitely a lot of not good stuff. I find that Dall-E does especially poorly with underspecified prompts too, unlike something like Midjourney which can give visually pleasing photos for even the most abstract concepts. Dall-E tends to do better with concrete and specific prompts. Here's an example: Stressful Shapes Dall-E: https://i.imgur.com/JBkSh0y.png Midjourney: https:/…

But still "king of belgium giving a speech to an audience, but the audience members are cucumbers" is very specific. And I don't see the king of Belgium anywhere, two pictures have absolutely nothing to do with the prompt (no king, no speech, no audience, no cucumber), one has the speech and audience but no king or cucumber. Graphically, they are deep into the uncanny valley. Only the third image is kind of right, if…

I’ve been comparing Dall-E, MidJourney, and StableDiffusion. Goes to show how much training set and implementation choices matter. But in all cases, you have to think of the underlying labeled text-to-image sets as paint colors to mix, and prepare a palette accordingly. Still haven’t figured out how to get what I want, but to your point, one can get closer.

- - -

Not sure if this is why, but with OpenAI’s Dall-E, you can’t use public figures. You can use proxies, such as “60 year old banker with salt and pepper hair” and then fill in the rest, e.g. “handsome 60 year old banker with salt and pepper hair giving a speech while standing above 12 cucumbers”:

https://i.imgur.com/qYKOWM1.jpg

Telling it oil painting can fudge who the person is, then pick one that’s close and generate variations:

https://i.imgur.com/QRbV7aM.jpg

Or use a reasonable photo and then use edit and in-painting to try to improve the implausible subject. This takes a photo from the first prompt above, erases the lower half of image, and makes a new prompt for the lower half, while keeping just enough of the upper half to orient the collage, e.g. “[photo_edit] + banker giving a speech to cucumbers bin full of cucumbers”:

https://i.imgur.com/OmOK1HF.jpg

- - -

Over on MidJourney, where it’s happy to use public figures so long as you’re not violating terms of service about their use, first a couple prompt experiments with King Philippe of the Belgians.

https://i.imgur.com/KkgIz2w.jpg

https://i.imgur.com/ekf9ypG.jpg

Then one upsized plausible painting from among those, where the actual command was “King Philippe of Belgium talking in a large group of cucumbers --q 2 --uplight” which is pretty basic.

https://i.imgur.com/QWUaNFv.jpg

Re: Ask HN: DALL-E was trained on watermarked stock images?

#160

Post by csmpltn »

visarga wrote: post #152
csmpltn wrote: post #109

Earlier quoted context omitted.

Putting aside the core question of the legality of training data on licensed material - what about the false advertising/copyright aspect that comes with slapping a "GettyImages" logo on some random nonsense generated by a "neural network"?

It's not worth discussing about Getty so much. AI labs will collect a dataset to predict if an image is watermarked. They will crawl to index the Getty images to make sure they are not in the training set. Then retrain and in 2 months the problem is solved. They can cut out a sizeable part of the training set without problem, the model will still be good. They can also OCR the output to make sure there are no blackli…

I understand that there are (both practical and theoretical) ways to reduce the chances of an AI generating an image that has copyrighted elements in it (such as the "GettyImages" logo).

I'm mostly curious about the legal aspects of having a black-box system that can - under some unknown circumstances - attach openly copyrighted or trademarked elements (such as a company logo) to a piece of work.

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