The biggest bias I found in LLMs is Epistemological bias. Epistemological bias in LLM output is bad because it heavily favors certain ways of knowing. For example, it favours naturalism as a way of knowing, and theism is marginalized without justification from first principles. This bias can heavily skew LLM output and forces you to constantly play devil’s advocate to reveal underlying biases and this is a waste of time compared to reading primary source material. If you ask an LLM what worldview it would follow if it was forced to pick, it might tell you it would follow ‘X’. The answer looks plausible, but might be false because it can never justify ‘why’. It simply walked through its dataset and gave you a weighted answer. It also doesn’t hold beliefs in a true sense, because it has no state of internal conviction or commitment. If you then introduce your own set of criteria (why) it should pick one view over the other, all of a sudden the output changes drastically because of the change in Epistemology. What about a socratic method? I am knowledgable enough to work around this bias. Sure go ahead. Go play devil’s advocate and the LLM, being the condescending sycophant it is, will describe your responses as ‘fair pushback’ and will keep spitting out the new ‘facts’ you were looking for. submitted by /u/Puzzled-Ad-6854
Originally posted by u/Puzzled-Ad-6854 on r/ArtificialInteligence
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