Responsible LLM Use in Conversations

Pasting raw LLM output into conversations gives words, not understanding, and shifts the effort to the other person, according to a post advocating for responsible LLM use. The author suggests using LLMs as learning tools to explain and challenge understanding, then explaining topics in one's own words to improve comprehension and memory. Research cited shows that cognitive offloading to AI can diminish memory and critical thinking skills, emphasizing the need to balance speed with genuine understanding.

Responsible LLM Use in Conversations You have probably received a message like this in a discussion: C A coworker you probably value a lot 2:47 PM ChatGPT said: <A lot of raw LLM output Sometimes even without the label. Someone asked an LLM about the topic you were discussing and pasted the answer straight into the conversation. Chances are you have been on the sending side too - I know I have. The problem: Pasting an answer you don't understand gives you words, not understanding - people confuse reading an answer with understanding it 1 src-1 - and it shifts the effort to the other person. You spend seconds prompting, while they must read the answer, understand it, fact-check it 2 src-2 , 3 src-3 and decide what is relevant. When they reply, all you can do is paste their answer back into the LLM, because you still don't understand what the conversation is about. I have a suggestion for a better way to handle this: Use the LLM as a learning tool. Ask it to explain unclear points, give examples and challenge your understanding. Then put the answer away and explain the topic in your own words . Research shows that this improves understanding and memory. 4 src-4 , 5 src-5 Once you understand the topic, return to the other person with actual knowledge instead of copied words and continue the discussion at eye level. That knowledge goes into your backpack: The next time the topic comes up, you can join the discussion without pulling out your phone - and one day it may even help you solve a problem that has nothing to do with it. Thinking is also a use-it-or-lose-it skill. When you stop doing the thinking yourself, you don't remember what you hand off, 6 src-6 you perform worse without the tool, 7 src-7 and people who lean on AI a lot tend to score worse at critical thinking. 8 src-8 Check important claims and come back when you can explain what you think and why. We're all still figuring this out. We need to find the balance: LLMs make us faster by default, but the ones who come out ahead use them to get smarter. We need to make sure that, when there's no LLM at hand, there's still a capable person - someone who can discuss, think critically and work things out on their own. Sources - Rozenblit & Keil 2002 , The misunderstood limits of folk science: an illusion of explanatory depth. https://cogdevlab.yale.edu/sites/default/files/files/rozenblit%20%26%20keil%20%202002.pdf https://cogdevlab.yale.edu/sites/default/files/files/rozenblit%20%26%20keil%20%202002.pdf - Lin, Hilton & Evans 2022 , TruthfulQA: Measuring how models mimic human falsehoods. https://aclanthology.org/2022.acl-long.229/ https://aclanthology.org/2022.acl-long.229/ - Ji et al. 2023 , Survey of hallucination in natural language generation. https://doi.org/10.1145/3571730 https://doi.org/10.1145/3571730 - Chi et al. 1994 , Eliciting self-explanations improves understanding. https://www.sciencedirect.com/science/article/pii/0364021394900167 https://www.sciencedirect.com/science/article/pii/0364021394900167 - Karpicke & Blunt 2011 , Retrieval practice produces more learning than elaborative studying with concept mapping. https://learninglab.psych.purdue.edu/downloads/2011/2011 Karpicke Blunt Science.pdf https://learninglab.psych.purdue.edu/downloads/2011/2011 Karpicke Blunt Science.pdf - Grinschgl, Papenmeier & Meyerhoff 2021 , Consequences of cognitive offloading: Boosting performance but diminishing memory. https://doi.org/10.1177/17470218211008060 https://doi.org/10.1177/17470218211008060 - Bastani et al. 2025 , Generative AI without guardrails can harm learning: Evidence from high school mathematics. https://www.pnas.org/doi/10.1073/pnas.2422633122 https://www.pnas.org/doi/10.1073/pnas.2422633122 - Gerlich 2025 , AI tools in society: Impacts on cognitive offloading and the future of critical thinking. https://www.mdpi.com/2075-4698/15/1/6 https://www.mdpi.com/2075-4698/15/1/6 correlational, self-report Back ../index.html