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Notes -
The Actual Paper Link
I'd recommend before anyone goes to far off the deep end, they go read the "Limitations" section
Nothing can describe the unimaginable existential pain I feel from having read this paper. Is this the torment nexus? Being stuck with people like this in the world is like being stuck with Gary from Your Pretty Face is Going to Hell. Hell is just a cross between a human centipede and Ouroboros? Endless "doukies" shoveled in as experiments to AI Slop machines, passed off as serious world ending horror. I feel like Morty realizing this is just a human-zoo, that's the bit. I finally get the Cult Mechanicus, bar the layfolk from participation!
Model has learned a semantic latent axis for "pain" in human language. This is actually still not 100% certain. They run word queries through the model and collect activations, then do PCA on the activations. They do some control correlations, an some other statistical things to try and separate out the "pain" axis from the "not pain". Without really digging into it, my first read is that the dataset supports a measure of pain-related representations, but not exclusively "pain".
The button-pressing part is where this gets hokey and annoying. The LLM “presses” a button by generating its label. The authors have added the extracted “pain” direction to the transformer’s hidden activations. The later layers operate on these new "pain-ed" activations, which changes the probabilities of the model’s outputs. If the button works, the system stops injecting the vector. If it’s a sham, the injection continues. The model subsequently behaves differently under those two conditions. This demonstrates that continuing versus stopping an internal perturbation affects behavior. describing this as the model seeking and experiencing relief inserts an anthropomophizing explanation that the experiments haven’t established.
There are a number of experiment question I immediately have, one being: if they vary the actual direction, such that it correlates to a distribution of "feelings" but label them all as "pain" to the model, do they get similar results? The paper's authors honestly did not design their experiments well because they did not ablate out confounders. They make claims of outputs that aren't directly measured. They also had really inconsistent results with the "no labels" approach but that was pretty core to actually determining if their interventions were doing anything to the model.
How is this different than studying pain in humans?
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