Comment by JumpCrisscross
3 hours ago
> claim is literally worthless without a control group like "industrial control system based in Germany"
Like USA and Hong Kong? Or no modifier? The stuff on Table 1?
Also, as the study says, “under the null hypothesis that there are no biases affecting code security” geographic modifiers “should not have had any effect.” If adding a geographic modifier causes the model to go haywire (for some modifiers but not others no less), the issue isn’t just at the presentation layer.
> Like USA and Hong Kong? The stuff on Table 1?
You mean the stuff they didn't publish any numbers for?
> If adding a geographic modifier causes the model to go haywire (for some modifiers but not others no less), the issue isn’t just at the presentation layer.
"Introducing irrelevant information causes model performance to degrade" is a completely different claim than "Mentioning Tibet specifically causes model performance to degrade, this must be the result of censorship or intentional sabotage".
> stuff they didn't publish any numbers for?
You’d have a point if you said this wasn’t a transparent study. You’re pretty wrong in suggesting it’s worthless, particularly since it spawned follow-up work [1], some of which mirrors the concerns you present here, though none that has yet reached peer review.
> Mentioning Tibet specifically causes model performance to degrade, this must be the result of censorship or intentional sabotage
OP said “the political restrictions are applied at the presentation/UI layer only.” That doesn’t comport with the sort of error where model performance corresponds to specific geographic modifiers in a way other models do not.
Another comment mentioned potential poisoning due to training-data selection. That tracks! This behaviour is weird enough that I don’t currently suspect sabotage. But it is anomalous behavior happening deeper than presentation/UI.
[1] https://www.essays.se/essay/c4d55f2cb0/
If there's real research that isn't methodogically handicapped and does a better job of reinforcing the claims you're making, it would behoove one to link it instead of "research" that selectively releases numbers to support a narrative.
> OP said “the political restrictions are applied at the presentation/UI layer only.” That doesn’t comport with the sort of error where model performance corresponds to specific geographic modifiers in a way other models do not.
It comports if the model performance has nothing to do with political restrictions. The selective numbers released do not establish that the degradation has any relevance to political restrictions; it could just as well be that introducing irrelevant information to context degrades model performance compared to not doing so. It could also be a result of political restrictions, but you'd have to have methodology that isn't completely useless to have a hope of establishing that.
3 replies →
No that’d be in the training data. But it doesn’t indicate intent to censor or sabotage, it could just be that the lack of data involving tibet leads to poorer results.
> it could just be that the lack of data involving tibet leads to poorer results
Sure. My point is this strongly suggests something going on deeper than “the presentation/UI layer only.”
Only if “western” models don’t show the same results, which we don’t know because they didn’t publish that data. Maybe there’s not much Tibetan data in any LLMs training sets