Speaking the Right Language: The Impact of Expertise (Mis)Alignment in User-AI Interactions

Shramay Palta, Nirupama Chandrasekaran, Rachel Rudinger, Scott Counts


Abstract
Using a sample of 25,000 Bing Copilot conversations, we study how the agent responds to users of varying levels of domain expertise and the resulting impact on user experience along multiple dimensions. Our findings show that across a variety of topical domains, the agent largely responds at proficient or expert levels of expertise (77% of conversations) which correlates with positive user experience regardless of the user’s level of expertise. Misalignment, such that the agent responds at a level of expertise below that of the user, has a negative impact on overall user experience, with the impact more profound for more complex tasks. We also show that users engage more, as measured by the number of words in the conversation, when the agent responds at a level of expertise commensurate with that of the user. Our findings underscore the importance of alignment between users and AI when designing human-centered AI systems, to ensure satisfactory and productive interactions.
Anthology ID:
2025.ijcnlp-short.5
Volume:
Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
Month:
December
Year:
2025
Address:
Mumbai, India
Editors:
Kentaro Inui, Sakriani Sakti, Haofen Wang, Derek F. Wong, Pushpak Bhattacharyya, Biplab Banerjee, Asif Ekbal, Tanmoy Chakraborty, Dhirendra Pratap Singh
Venues:
IJCNLP | AACL
SIG:
Publisher:
The Asian Federation of Natural Language Processing and The Association for Computational Linguistics
Note:
Pages:
58–69
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URL:
https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-short.5/
DOI:
Bibkey:
Cite (ACL):
Shramay Palta, Nirupama Chandrasekaran, Rachel Rudinger, and Scott Counts. 2025. Speaking the Right Language: The Impact of Expertise (Mis)Alignment in User-AI Interactions. In Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, pages 58–69, Mumbai, India. The Asian Federation of Natural Language Processing and The Association for Computational Linguistics.
Cite (Informal):
Speaking the Right Language: The Impact of Expertise (Mis)Alignment in User-AI Interactions (Palta et al., IJCNLP-AACL 2025)
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https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-short.5.pdf