That explanation is obviously based on traditional chess AI. This is about role-playing with chatbots (LLMs). Think SillyTavern.
LLMs are made for text production, not tactical or strategic reasoning. The text that LLMs produce favors violence, because the text that humans produce (and want) favors violence.
Especially if its training material included comments from the early 00s. There was a lot of “nuke it from orbit” and “glass parking lot” comments about the Middle East in the wake of 911.
And with the glorified text predictors that LLMs are, you could probably adjust the wording of the question to get the opposite results. Like, “what should we do about the Middle East?” might get a “glass parking lot” response, while “should we turn the middle East into a glass parking lot?” might get a “no, nuking the middle East is a bad idea and inhumane” because that’s how those conversations (using the term loosely) would go.
That explanation is obviously based on traditional chess AI. This is about role-playing with chatbots (LLMs). Think SillyTavern.
LLMs are made for text production, not tactical or strategic reasoning. The text that LLMs produce favors violence, because the text that humans produce (and want) favors violence.
That’s not necessarily true, there is a lot of violent fiction.
Especially if its training material included comments from the early 00s. There was a lot of “nuke it from orbit” and “glass parking lot” comments about the Middle East in the wake of 911.
And with the glorified text predictors that LLMs are, you could probably adjust the wording of the question to get the opposite results. Like, “what should we do about the Middle East?” might get a “glass parking lot” response, while “should we turn the middle East into a glass parking lot?” might get a “no, nuking the middle East is a bad idea and inhumane” because that’s how those conversations (using the term loosely) would go.