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Comment by filterfiber | Hacker News Reader

I've always struggled with where people draw the line.

Video scripts have been near algorythmic for humans already. Does using chatgpt to make your script count as AI made? What if you gave it an outline, walked through it, and guided it to what you wanted - e.g. grammerly?

If you use machine learning to remove background noise, backgrounds in general?

Generated stock images/props/scenes for video essays?

If you made the entire video by hand but use text2speech?

I think that "the script, images, and voice were all chatGPT" is obviously "synthetic", but that's just the extreme. Humans have been using technology to augment their creation abilities forever.

My fear is a large amount of human made content will be called "synthetic" because some specific part used "AI" (which nowadays refers to literally any procedural/statistical/machine learning I guess?)

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It's blurry and will only get blurrier.

Maybe there is no line to draw, and maybe that's OK.

This all feels so new I'm hesitant to form strong feelings, but I do think transparency while not required is appreciated. With knowledge, I can draw my own conclusion. Without it, I may end up feeling "duped."

Generally I want to continue enjoying human-created art. If something is "more" human-made than not, that's a factor I'll weigh as "better" and more authentic in my mind. But I'm also trending towards preferring indie dramas over CG-filled blockbusters, so I'm not pretending to be any sort of bellwether.

Yeah, it seems like the only "general solution" to this problem is to measure the number of "human work hours" that went into the production of a specific type of "content".

Content would then be labeled as "AI generated" if the "human work hours" was less than X hours (like 0.5 hours).

Whereas content would not be labelled as "AI generated" if the "human work hours" was greater than or equal to X hours (like 0.5 hours).

That would likely require sharing with YouTube not just the final work product, but rather all the iterative work product that led to the creation of the final work product (i.e., earlier drafts). When YouTube could calculate the number of "human work hours" based on the incremental creation/edit histories when analyzing all the drafts.

This is a very hard problem and unlikely to actually be solved in this way.

A percentage would be better.

>That would likely require sharing with YouTube not just the final work product, but rather all the iterative work product that led to the creation of the final work product (i.e., earlier drafts).

Not necessarily. YouTube generally trusts the word of the creator. If I upload a video and check the box that says "there is no swearing in this video" then YouTube more or less takes my word for it. They try to do some detection, but it has always been spotty.

I think YouTube would just ask the creator to label the video and that's it. If somebody is found to be in violation too many times then their account gets actioned.

So your solution is proof of work?

Why struggle with where other people draw the line? Draw the line yourself and don't concern yourself with the line other people draw for themselves.

The line is clear, deepfake stuff is supposed to be labeled. This is not a luddite moral panic measure that would label scripts.

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