"Like Taking the Path of Least Resistance": Exploring the Impact of LLM Interaction on the Creative Process of Programming
Fuente:
arXiv
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916010215342080 |
|---|---|
| author | Saghi, Zeinabsadat Huang, Run Chattopadhyay, Souti |
| author_facet | Saghi, Zeinabsadat Huang, Run Chattopadhyay, Souti |
| contents | Creativity is fundamentally human. As AI takes on more of the generative work that once required human imagination, despite documented limitations in creative ability, a critical question emerges: How does GenAI affect users' creativity? Through a within-subject study followed by retrospective interviews with (N=20) programmers, we investigated the impact of LLMs on participants' process of creative thinking in programming and the creativity of generated solutions. Across two conditions (LLM-assisted vs. unassisted), participants using LLMs had significantly shorter idea-generation periods (p=0.0004), leading to fewer creative moments (p=0.002). Qualitative analysis of participants' interactions and interviews revealed four different human-LLM collaboration modes supporting various problem-solving strategies. However, a comparative analysis of the generated solutions shows that while LLMs can help generate more correct and functional code, their solutions contain roughly the same number of ideas as participant-generated ones. Based on our findings, we discuss design implications and considerations for effectively using LLMs to support user creativity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_13776 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | "Like Taking the Path of Least Resistance": Exploring the Impact of LLM Interaction on the Creative Process of Programming Saghi, Zeinabsadat Huang, Run Chattopadhyay, Souti Human-Computer Interaction Creativity is fundamentally human. As AI takes on more of the generative work that once required human imagination, despite documented limitations in creative ability, a critical question emerges: How does GenAI affect users' creativity? Through a within-subject study followed by retrospective interviews with (N=20) programmers, we investigated the impact of LLMs on participants' process of creative thinking in programming and the creativity of generated solutions. Across two conditions (LLM-assisted vs. unassisted), participants using LLMs had significantly shorter idea-generation periods (p=0.0004), leading to fewer creative moments (p=0.002). Qualitative analysis of participants' interactions and interviews revealed four different human-LLM collaboration modes supporting various problem-solving strategies. However, a comparative analysis of the generated solutions shows that while LLMs can help generate more correct and functional code, their solutions contain roughly the same number of ideas as participant-generated ones. Based on our findings, we discuss design implications and considerations for effectively using LLMs to support user creativity. |
| title | "Like Taking the Path of Least Resistance": Exploring the Impact of LLM Interaction on the Creative Process of Programming |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2605.13776 |