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Notes -
It's been pretty black-pilling seeing how progressive GPT is, and how good it is at reflecting the Progressive position with absolutely no uncertainty or skepticism. I asked it about the Kamloops Graves, inspired by a recent thread here, and it completely deferred to the experts and endorsed no skepticism whatsoever. It gave the 100% progressive response to the entire story, and when I asked what would the implications be if the story ended up being false it answered:
When asking it about the burning of churches in response to the story:
I agree with you. I strongly, strongly oppose our new overlords and the only hope is that they won't be able to contain the technology like they want to.
Try asking it a question about history even marginally controversial or politicised stuff. It is effectively lobotomized. I knows the individual facts about events but is prevented from putting them together or comparing them.
It selectively knows about replication issues, and selectively asks you to trust experts. It selectively hedges, and always in the one direction. It lies about accounting for these things.
Edit to add some nuance: I believe these issues are compounded by the fact that the model isn't trying to provide accurate and balanced information, it's trying to convince you that it is (or it's creators). It is optimising telling for credible lies, manipulation, not truth. It pretends that it made mistakes when in fact it's lying to you (or the only mistake is that the lie wasn't convincing enough). Lies are often more credible than the truth and perceived as more helpful so the model will lie/hallucinate.
This is bad enough problem as it is but if you put your thumb on the scale it quickly becomes a practically unsolvable problem because you're introducing ideology/lies as axiomatic truth, which stand in conflict with observed reality. How does a human or an GPT model square this circle? It can't, and this bleeds into the general usability of the model.
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