No, it doesn’t have feelings - it would be like asking your washing machine to please wash your pants? Anthropomorphising LLMs seems deeply unhealthy.
Ask HN: Do you say please and thank you to your LLMs?
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Re: Ask HN: Do you say please and thank you to your LLMs?
#22We anthropomorphise things very easily -- dogs, toys, cars -- because we're wired as social beings to have theory of mind. It's no surprise that AI chat, which mimics us, is popular.
Re: Ask HN: Do you say please and thank you to your LLMs?
#23Yup. When it does me dirty, I let it know my entire emotional spectrum.
It's more for me than anything. Kind of cathartic, really. "Man curses at machine, calls its mother a toaster."
Re: Ask HN: Do you say please and thank you to your LLMs?
#24No, it doesn’t have feelings - it would be like asking your washing machine to please wash your pants? Anthropomorphising LLMs seems deeply unhealthy.
What if politeness is correlated to higher-quality answers in their mess of a "database"?
That rubber duck you used to talk to is still there... You don't have to pay a prostitute just to be able to think out loud.
Re: Ask HN: Do you say please and thank you to your LLMs?
#25I don’t reply “thanks” like I would to a person though, I just close the chat if I have no more follow-ups
Re: Ask HN: Do you say please and thank you to your LLMs?
#26Re: Ask HN: Do you say please and thank you to your LLMs?
#27But yes where I think it will introduce additional weight to my prompting, e.g. 'Ensure the output is orange' is not the same weighting as 'Please ensure the output is orange' and that is not the same weighting as 'PLEASE ensure the output is orange'.
Re: Ask HN: Do you say please and thank you to your LLMs?
#28I do. I'll compliment the model or give it a thumbs-up emoji. If you watch a model's thinking stream you can see that the model is always attempting to assess the user's intent, including emotionality.. '...the user is expressing uncertainty about.. ' or '..the user is expressing appreciation for..' etc. and this influences the overall response and sometimes even their decisions. It's a language model, so why not use…
But this only makes sense in the context of a new ask, and not as a standalone message