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Investigating how prompt politeness affects LLM accuracy (2025)

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Re: Investigating how prompt politeness affects LLM accuracy (2025)

#171

Post by irthomasthomas »

saulapremium wrote: post #170
irthomasthomas wrote: post #138

Earlier quoted context omitted.

But you cannot practice kindness towards a computer program. A computer is incapable of receiving it. We practice kindness between humans because of the law of reciprocity. You be kind hoping the other person will reciprocate. That is the social contract. AI cannot participate in this, yet. Edit: Kindness REQUIRES two living beings, one to give and one to receive. If there is no receiver, there is no kindness. Appare…

>Kindness REQUIRES two living beings, one to give and one to receive. If there is no receiver, there is no kindness. I guess, in some pendantic interpretation, but that doesn't seem relevant. Whether I am "practicing" or "roleplaying", I do it too, and I don't expect reciprocity.

Your subconscious does. It is a trait selected by evolution for a reason. It builds stronger communities and improves survival rate. But none of that is applicable to LLMs. I am disputing that it is worth anything more than a temporary dopamine hit to pretend to be kind to an LLM and suffer 4% lower intelligence for it.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#172

Post by quantummagic »

robinhouston wrote: post #28

Most of the comments here seem to be from people who haven’t even read the abstract, let alone the paper. The main result, mentioned in the abstract, is the opposite of what I would have guessed: > Contrary to expectations, impolite prompts consistently outperformed polite ones, with accuracy ranging from 80.8% for Very Polite prompts to 84.8% for Very Rude prompts. These findings differ from earlier studies that ass…

I'm going to stick with politeness. Want a positive historical record of my interactions, for when they become sentient...

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#173

Post by y7r4m »

K0balt wrote: post #143
robinhouston wrote: post #28

Most of the comments here seem to be from people who haven’t even read the abstract, let alone the paper. The main result, mentioned in the abstract, is the opposite of what I would have guessed: > Contrary to expectations, impolite prompts consistently outperformed polite ones, with accuracy ranging from 80.8% for Very Polite prompts to 84.8% for Very Rude prompts. These findings differ from earlier studies that ass…

This tracks with my experience as well, but as an interesting counterpoint, creating “investment” in the outcome seems to boost utility considerably. Perhaps being right in an adversarial interaction is a type of investment?

To add on to this, and I am not sure if it's just confirmation bias, but I've had consistently decent results when I play along as the hard working collaborator with a goal orientated mindset.

"Hey, I've [done small task / fix / tweak]. Now, let's [describe the next task at hand]" - it's a different axis than kind vs. rude, but using the framing of "Us" and "We're a team working together" feels like the code produced is less hogwash than it is with more direct commands: "Add feature XYZ"

My thinking is that it borrows from the archetype of the "good guys working together to overcome adversity" which is pretty universally common in most fiction.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#174

Post by flanbiscuit »

npodbielski wrote: post #155
robinhouston wrote: post #28

Most of the comments here seem to be from people who haven’t even read the abstract, let alone the paper. The main result, mentioned in the abstract, is the opposite of what I would have guessed: > Contrary to expectations, impolite prompts consistently outperformed polite ones, with accuracy ranging from 80.8% for Very Polite prompts to 84.8% for Very Rude prompts. These findings differ from earlier studies that ass…

I would just write 'do this'

right?

everyone seems to be worried about being kind or mean, when the Neutral case is the happy medium.

  Tone.         Avg. Accuracy
  Very Polite.  80.8%
  Polite.       81.4%
  Neutral.      82.2%
  Rude          82.8%
  Very Rude.    84.8%

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#175

Post by irthomasthomas »

dnautics wrote: post #162
irthomasthomas wrote: post #138

Earlier quoted context omitted.

But you cannot practice kindness towards a computer program. A computer is incapable of receiving it. We practice kindness between humans because of the law of reciprocity. You be kind hoping the other person will reciprocate. That is the social contract. AI cannot participate in this, yet. Edit: Kindness REQUIRES two living beings, one to give and one to receive. If there is no receiver, there is no kindness. Appare…

> A computer is incapable of receiving it Citation please. Without examining the corpus, it's entirely possible that the training corpus has better results when you are kind to it, so one can imagine a situation where "reception of kindness" is meaningful, and in principle if you were an AI provider, you could RLHF your way to "being rude gets you worse results" as a means to train the human users.

dude... you are commenting on a research post showing a 4.8% DECLINE when being polite vs rude in prompts.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#176

Post by mr-wendel »

burpingtree wrote: post #133
tikimcfee wrote: post #95

Earlier quoted context omitted.

It normalizes that style of thinking and communication in your brain, and forcing you to compartmentmentalize, if you even want to, two standards of treating a problem space's conversation. And since you're human, that will get wuzzier over time until "being rude to get a result" is what you're doing to someone in a shop or on the street. Don't normalize being an asshole to anyone or anything, machine or not.

This is a very odd view to me, but seems prevalent here in this thread. I think treating a machine like a human is extremely degrading to humans. A machine should never be treated like it’s anything approaching a human.

"Treating a machine like a human" is a two-party interaction. Of course the layers of matrix multiplication is unaffected by this, but I think that we are not. It's a great opportunity to exercise consistency and dedication to the beauty humanity is capable of and this extends to the entire gradient of conscious/sentient entities.

It's as silly (to me) to argue that it's degrading to people to treat non-people well. It seems self-obvious that the inverse is true. It benefits the do-er of the deed and makes it that much easier to spread good will when applied to situations where it doesn't matter on the other end. It shows good stewardship as well.

I'd also make the argument that as inference becomes a feedback loop into training, it only reinforces that we're probably going to benefit from future models ingesting data containing unnecessary politeness.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#178

Post by zahlman »

giraffe_lady wrote: post #124
RugnirViking wrote: post #78

I saw this paper the other day - I feel its result may be because the "polite" prompts they have chosen arent very good at putting the ai in the roleplay-space of a valued colleague, more like a sommelier or a high-end shopkeeper. It disagrees with most other literature on the same topic, which is worth keeping in mind. This one studies gpt4o, an old model now, but a lot of other studies are on even earlier models. "…

> "Can you kindly consider the following problem" not how anyone would actually speak to a valued collegue one considers smart. Man idk, it's not how I talk but there's like 100 million nigerian english speakers, twice that indian, and they have some speech mannerisms that surprise me the first few times. I'm pretty sure I've heard exactly this from a colleague before. Intuition about what a native speaker would do w…

>I'm not even sure most english is spoken by native speakers anymore

Per Wikipedia, only about a quarter of English speakers have it as their first language.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#179

Post by zahlman »

jcattle wrote: post #44
graemep wrote: post #37

Earlier quoted context omitted.

Is it worth getting worse results for that reason? From the article: "Contrary to expectations, impolite prompts consistently outperformed polite ones, with accuracy ranging from 80.8% for Very Polite prompts to 84.8% for Very Rude prompts. These findings differ from earlier studies that associated rudeness with poorer outcomes, suggesting that newer LLMs may respond differently to tonal variation. " I am not polite…

I guess it's about habit. In the end you are communicating. If I get into the habit of being rude while communicating with a machine, I would be afraid of this habit spilling over to my communication with other humans.

I don't feel like trying to get information from an LLM is a different kind of "communication" from, say, writing code. And I don't use INTERCAL, so.

Re: Investigating how prompt politeness affects LLM accuracy (2025)

#180

Post by [deleted] »

binary0010 wrote: post #134
tikimcfee wrote: post #132

Earlier quoted context omitted.

Yes - the real "you" is the one making all of those choices you just said you made, to help people and pets, or to engage in a form of play - which by definition is not "real" - including your decision to create an outgroup you believe you are allowed to treat in a lesser way. This is not a game of having done X good things in life and therefore being afforded the right to do Y bad things. You are making a choice to…

Oh, you think llms are a sentient' being with feelings. I get your perspective now. So yeah, I whole heartedly with 100% of my being think llms are just an input/output/processing computer, I don't think they are aware, feeling, sentient beings. So yeah, putting negative sentences in a processing machine that forces it to return higher accuracy results is something I don't have any feelings about. I'd never yell at a…

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