LLMs Homogenize Values in Constructive Arguments on Value-Laden Topics
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866908782081081344 |
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| author | Shahid, Farhana Zhang, Stella Vashistha, Aditya |
| author_facet | Shahid, Farhana Zhang, Stella Vashistha, Aditya |
| contents | Large language models (LLMs) are increasingly used to promote prosocial and constructive discourse online. Yet little is known about how these models negotiate and shape underlying values when reframing people's arguments on value-laden topics. We conducted experiments with 465 participants from India and the United States, who wrote comments on homophobic and Islamophobic threads, and reviewed human-written and LLM-rewritten constructive versions of these comments. Our analysis shows that LLM systematically diminishes Conservative values while elevating prosocial values such as Benevolence and Universalism. When these comments were read by others, participants opposing same-sex marriage or Islam found human-written comments more aligned with their values, whereas those supportive of these communities found LLM-rewritten versions more aligned with their values. These findings suggest that value homogenization in LLM-mediated prosocial discourse runs the risk of marginalizing conservative viewpoints on value-laden topics and may inadvertently shape the dynamics of online discourse. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10637 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LLMs Homogenize Values in Constructive Arguments on Value-Laden Topics Shahid, Farhana Zhang, Stella Vashistha, Aditya Human-Computer Interaction Computers and Society Large language models (LLMs) are increasingly used to promote prosocial and constructive discourse online. Yet little is known about how these models negotiate and shape underlying values when reframing people's arguments on value-laden topics. We conducted experiments with 465 participants from India and the United States, who wrote comments on homophobic and Islamophobic threads, and reviewed human-written and LLM-rewritten constructive versions of these comments. Our analysis shows that LLM systematically diminishes Conservative values while elevating prosocial values such as Benevolence and Universalism. When these comments were read by others, participants opposing same-sex marriage or Islam found human-written comments more aligned with their values, whereas those supportive of these communities found LLM-rewritten versions more aligned with their values. These findings suggest that value homogenization in LLM-mediated prosocial discourse runs the risk of marginalizing conservative viewpoints on value-laden topics and may inadvertently shape the dynamics of online discourse. |
| title | LLMs Homogenize Values in Constructive Arguments on Value-Laden Topics |
| topic | Human-Computer Interaction Computers and Society |
| url | https://arxiv.org/abs/2509.10637 |