This content originally appeared on Adactio: Journal and was authored by Adactio: Journal
Large language models have reaped our words and plundered our books. Bryan Vandyke:
Turns out, everything on the internet—every blessed word, no matter how dumb or benighted—has utility as a learning model. Words are the food that large language algorithms feed upon, the scraps they rely on to grow, to learn, to approximate life. The LLNs that came online in recent years were all trained by reading the internet.
We can shut the barn door—now that the horse has pillaged—by updating our robots.txt files or editing .htaccess. That might protect us from the next wave, ’though it can’t undo what’s already been taken without permission. And that’s assuming that these organisations—who have demonstrated a contempt for ethical thinking—will even respect robots.txt requests.
I want to do more. I don’t just want to prevent my words being sucked up. I want to throw a spanner in the works. If my words are going to be snatched away, I want them to be poison pills.
The weakness of large language models is that their data and their logic come from the same source. That’s what makes prompt injection such a thorny problem (and a well-named neologism—the comparison to SQL injection is spot-on).
Smarter people than me are coming up with ways to protect content through sabotage: hidden pixels in images; hidden words on web pages. I’d like to implement this on my own website. If anyone has some suggestions for ways to do this, I’m all ears.
If enough people do this we’ll probably end up in an arms race with the bots. It’ll be like reverse SEO. Instead of trying to trick crawlers into liking us, let’s collectively kill ’em.
Who’s with me?
This content originally appeared on Adactio: Journal and was authored by Adactio: Journal
Adactio: Journal | Sciencx (2024-06-15T15:03:04+00:00) The machine stops. Retrieved from https://www.scien.cx/2024/06/15/the-machine-stops/
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