Paper Number
ICIS2025-1182
Paper Type
Short
Abstract
The integration of generative AI (GenAI) tools into open-source software development fundamentally transforms trust dynamics between collaborators. This study examines how AI-mediated trust, the reconfiguration of trust formation and evaluation when GenAI tools mediate software contributions, operates in OSS communities. Using a sequential mixed-methods approach including interviews with OSS developers, GitHub data analysis, and discourse examination, we develop a conceptual framework that captures trust transformation across three dimensions: peer assessment, self-efficacy, and artifact evaluation. Our findings reveal that GenAI creates competence ambiguity that disproportionately affects newcomers, while established contributors benefit from reputation buffers. Developers also experience shifts in self-trust and develop new mechanisms to evaluate AI-assisted contributions. This process-oriented framework identifies both trust disruption mechanisms and adaptive practices emerging in response, providing implications for OSS governance and platform design as communities navigate the integration of AI assistance while preserving core meritocratic principles.
Recommended Citation
Sokiyna, Munsif; Herfurth, Anne; Das, Sethu; and Sharma, Pratyush, "When AI Writes the Code: Trust and Community Cohesion in Open Source software Development" (2025). ICIS 2025 Proceedings. 5.
https://aisel.aisnet.org/icis2025/gen_ai/gen_ai/5
When AI Writes the Code: Trust and Community Cohesion in Open Source software Development
The integration of generative AI (GenAI) tools into open-source software development fundamentally transforms trust dynamics between collaborators. This study examines how AI-mediated trust, the reconfiguration of trust formation and evaluation when GenAI tools mediate software contributions, operates in OSS communities. Using a sequential mixed-methods approach including interviews with OSS developers, GitHub data analysis, and discourse examination, we develop a conceptual framework that captures trust transformation across three dimensions: peer assessment, self-efficacy, and artifact evaluation. Our findings reveal that GenAI creates competence ambiguity that disproportionately affects newcomers, while established contributors benefit from reputation buffers. Developers also experience shifts in self-trust and develop new mechanisms to evaluate AI-assisted contributions. This process-oriented framework identifies both trust disruption mechanisms and adaptive practices emerging in response, providing implications for OSS governance and platform design as communities navigate the integration of AI assistance while preserving core meritocratic principles.
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12-GenAI