生成语法
计算机科学
知识管理
质量(理念)
认知
生成模型
信息过载
自然实验
认知负荷
人工智能
人机交互
数据科学
人事变更率
用户界面
自然(考古学)
认知计算
基线(sea)
接口(物质)
堆栈(抽象数据类型)
作者
Guohou Shan,Liangfei Qiu
出处
期刊:Information Systems Research
[Institute for Operations Research and the Management Sciences]
日期:2025-09-24
卷期号:37 (2): 1021-1041
被引量:21
标识
DOI:10.1287/isre.2023.0332
摘要
Practice and policy abstract Generative artificial intelligence (AI) is reshaping online knowledge-sharing, but its effects on voluntary user contributions remain uncertain. This study examines how the usage of ChatGPT influences users’ answering behavior on Stack Overflow, one of the world’s largest question-and-answer platforms. Using a natural experiment, we find that access to generative AI increases the number of answers users provide, whereas those answers are typically shorter and easier to read. These patterns suggest that users are learning from AI outputs, enabling them to share knowledge more efficiently. However, intensive reliance on AI introduces cognitive strain, which can reduce contribution levels. For practice, our findings underscore the importance for platform owners and managers to strike a balance between AI integration and user support. Encouraging AI-assisted learning can expand participation and improve the accessibility of content, but safeguards are necessary to prevent cognitive overload and ensure the quality of answers. From a policy perspective, our study highlights the importance of establishing clear guidelines for the responsible use of AI in community-driven platforms. By designing thoughtful integration strategies, organizations can harness the benefits of AI—enhancing efficiency and readability—while sustaining authentic, high-quality knowledge contributions.
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