Voice-based debate with an AI adversary is associated with increased divergent ideation
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911549871882240 |
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| author | Jain, Neelam Modi Wang, Dan J. |
| author_facet | Jain, Neelam Modi Wang, Dan J. |
| contents | Concerns that interacting with generative AI homogenizes human cognition are largely based on evidence from text-based interactions, potentially conflating the effects of AI systems with those of written communication. This study examines whether these patterns depend on communication modality rather than on AI itself. Analyzing 957 open-ended debates between university students and a knowledgeable AI adversary, we show that modality corresponds to distinct structural patterns in discourse. Consistent with classic distinctions between orality and literacy, spoken interactions are significantly more verbose and exhibit greater repetition of words and phrases than text-based exchanges. This redundancy, however, is functional: voice users rely on recurrent phrasing to maintain coherence while exploring a wider range of ideas. In contrast, text-based interaction favors concision and refinement but constrains conceptual breadth. These findings suggest that perceived cognitive limitations attributed to generative AI partly reflect the medium through which it is accessed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_27073 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Voice-based debate with an AI adversary is associated with increased divergent ideation Jain, Neelam Modi Wang, Dan J. Human-Computer Interaction Artificial Intelligence Computers and Society Concerns that interacting with generative AI homogenizes human cognition are largely based on evidence from text-based interactions, potentially conflating the effects of AI systems with those of written communication. This study examines whether these patterns depend on communication modality rather than on AI itself. Analyzing 957 open-ended debates between university students and a knowledgeable AI adversary, we show that modality corresponds to distinct structural patterns in discourse. Consistent with classic distinctions between orality and literacy, spoken interactions are significantly more verbose and exhibit greater repetition of words and phrases than text-based exchanges. This redundancy, however, is functional: voice users rely on recurrent phrasing to maintain coherence while exploring a wider range of ideas. In contrast, text-based interaction favors concision and refinement but constrains conceptual breadth. These findings suggest that perceived cognitive limitations attributed to generative AI partly reflect the medium through which it is accessed. |
| title | Voice-based debate with an AI adversary is associated with increased divergent ideation |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2603.27073 |