I literally don't know what the hell you're on about at this point. You already know these programs are effectively black box algorithms, that nobody has access to. We don't know what they're trained on exactly, or how predictions are weighted.
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The alternative is "misinfo outputs might just be the result of randomly selecting the best, but wrong, tokens"
When that happens, rerunning a completion usually produces a different output. In that way, you can determine whether misinfo comes from the attention mechanism or from bad source data.
What we do know is that these programs already give erroneous answers given the datasets they're currently using. If they're generating synthetic data from this dataset which again the entirety of the Internet is what they claim- the obvious conclusion is that synthetic data is erroneous as well
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Ergo, if you found a false claim in the outputs, and traced it back to training data marked as synthetic, you'd be able to prove this relationship.
When that happens, rerunning a completion usually produces a different output. In that way, you can determine whether misinfo comes from the attention mechanism or from bad source data.
The process you're describing is a human manual process that cannot be automated by these programs. These programs cannot tell the truth from fiction.
https://arxiv.org/pdf/2205.11482
Disclaimer, I haven't read this, just showing that this is a studiable problem. We don't have to guess.
Authority laundering via LLM is def a problem and we will need to develop social conventions to combat it.