I feel like I’m pretty good at asking questions - in a training environment such as school or a new job, I am pretty good at spotting gaps in the lesson and converying clearly what I want more information on. Carrying this forward to LLMs, I often feel like being really clear on what my question is and even providing examples helps get me a better response. But I have begun to question that assumption. Often when working with an area where the accuracy is immediately tested, I find the answers pretty inaccurate and need to do a lot of work to get it right. For example, I’ve been doing IT Admin for the first time for a small org and frequently run into issues with their hodgepodge of technology from different vendors. Even with a lot of context, the answers pretty inaccurate I get might ask me to check a setting that doesn’t exist or just wasn’t a good place to start. And yet, when I am asking questions where I can’t immediately verify the accuracy, my assumption is that my really detailed prompt is what led to that detailed and high quality answer. So my questino is, is there any research to validate that asking really good questions actually leads to more accurate answers? I think it’s a given that a better question can lead to a more specific answer- the more context it has, the less likely the answer will be irrelivant. But is it any more likely to be correct? Has any research validated this? submitted by /u/Personal_Return_4350
Originally posted by u/Personal_Return_4350 on r/ArtificialInteligence
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