Examining the Impact of Generative AI on Users’ Voluntary Knowledge Contribution: Evidence from A Natural Experiment on Stack Overflow

Abstract

Voluntary knowledge contribution on online platforms is significant for users, platforms, and firms. The rapid advancements in generative Artificial Intelligence (AI) techniques have enabled the automatic generation of knowledge on question and answer (Q&A) platforms. However, the impact of generative AI on users’ voluntary knowledge contribution remains an empirical question. On the one hand, users may learn from generative AI to improve their answers, providing organized and logical responses. On the other hand, generative AI may produce fabricated answers, and the increased speed of answering with AI assistance may impose additional cognitive burdens on humans, potentially reducing their overall contribution. Our study examines the impact of generative AI, specifically ChatGPT, on users’ voluntary knowledge contribution on Stack Overflow, one of the largest Q&A platforms. Leveraging a natural experiment, we employ the difference-in-differences (DID) estimation to investigate the effects of generative AI on the quantity and quality of users’ knowledge contribution, measured by the number of answers generated per day, answer length, readability, and received scores. Our findings reveal that using generative AI leads to an increase in the number of answers generated by users. However, these answers tend to be shorter in length and easier to read. This suggests that users are learning from generative AI and answering questions more quickly and concisely, but the cognitive burden associated with AI usage results in shorter and more digestible answers. We also explore the moderating effects of user tenure and question upvote ratio on the impact of generative AI to gain insights into underlying mechanisms. The implications of this study are both theoretical and practical. Theoretically, we contribute to the Information Systems (IS) literature by examining the impact of generative AI on users’ voluntary knowledge contribution in the context of Q&A platforms. Practically, our findings provide knowledge platform owners and managers with a better understanding of how generative AI influences users’ knowledge contribution behavior. This understanding can guide decision-making and strategy development regarding the integration of generative AI on their platforms.

Keywords: Knowledge contribution, generative AI, voluntary Q&A platforms, answer quantity, answer quality, difference-in-differences