The Double-edged Effect of Banning Generative AI on Online Question-and-Answer Communities Evidence from Stack Exchange

Jul 16, 2026

Upload by Maeve

Investigates how banning generative AI-generated content (AIGC) changes knowledge seeking, knowledge contribution, and contribution efficiency in online Q&A communities. After ChatGPT’s late-2022 launch, multiple Stack Exchange communities introduced official AIGC bans, motivated by concerns about reliability and reduced social engagement. Using full-network Stack Exchange data and a difference-in-differences design, results show a double-edged effect: more posted questions but lower answer-throughput efficiency, measured by fewer questions receiving satisfactory answers within expected time. Impacts appear mainly in non-STEM communities, driven by shifts in information reliability and social interaction.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages38

Reading Time1 h 36 min

Introduction

Background and Motivation

Platform Trade-offs and Governance Response

Research Design and Empirical Approach

Findings: Double-edged Effects and Heterogeneity

Mechanism Exploration and Implications

The Double-edged Effect of Banning Generative AI on Online Question-andAnswer Communities: Evidence from Stack Exchange Yuanhong Ma 1 *, Qinglai He2 *, Xitong Li3 , Lynn Wu4 Revised Date: February 28, 2026 Abstract We investigate how banning generative artificial intelligence-generated content (AIGC) affects knowledge seeking, knowledge contribution, and contribution efficiency in online question-and-answer communities. After the launch of ChatGPT in late November 2022, several Stack Exchange communities implemented official bans on AIGC over concerns such as less reliable and socially engaged content. Leveraging data from the full network of Stack Exchange communities, we employ a difference-in-differences (DID) approach to examine the impacts of these bans. Our results reveal a double-edged impact: while the AIGC ban increases knowledge seeking, as evidenced by a higher volume of posted questions, it simultaneously reduces contribution efficiency, reflected in a lower proportion of questions receiving satisfactory answers within the expected time frame. Notably, these impacts are only evident in non-STEM communities. We take a socio-technical perspective to explore information reliability and social interactivity as two plausible underlying factors driving the observed changes. Our mechanism exploration reveals that the AIGC ban spurs question volume in topics where AIGC is less reliable and where social interaction is highly expected. In contrast, the ban hampers answer efficiency in communities where LLMs are capable of producing reliable answers and where social interactivity is minimal. Additionally, our results indicate the increased human involvement from knowledge seekers and contributors following the ban. They adapt their behavior by posting questions and answers that are more informationally rich and socially engaging. Overall, our findings offer actionable implications for platform managers, community moderators, and policymakers of online Q&A communities. Keywords: Generative AI, Online Q&A Community, AIGC, Large Language Models, Knowledge Exchange, Platform Competition 1 Department of Management Science and Technology, Harbin Institute of Technology; Harbin, Heilongjiang, China. 2 Department of Operations and Information Management, University of Wisconsin–Madison; Madison, WI, USA. 3 Department of Information Systems and Operations Management, HEC Paris; Jouy-en-Josas, France. 4 Operations, Information and Decisions Department, The Wharton School, University of Pennsylvania; Philadelphia, PA, USA * These authors contributed equally to this work. The Double-edged Effect of Banning AI-generated Content on Online Question-and-Answer Communities: Evidence from Stack Exchange 1. Introduction Generative artificial intelligence (AI) has rapidly transformed digital knowledge production (OpenAI 2023, Brynjolfsson et al. 2025, Noy and Zhang 2023, Eloundou et al. 2024) . Large language models (LLMs), such as ChatGPT and Gemini, generate human-like content in response to natural language prompts and increasingly serve as both alternative sources of information and tools for content creation (Burtch et al. 2024; Quinn and Gutt 2025) . Online question-and-answer (Q&A) communities, including Stack Exchange and Quora, facilitate large-scale knowledge exchange and rely heavily on human contributions (Goes et al. 2016; Xu et al. 2020) . As LLM use proliferates, platform operators face growing challenges in managing AI-generated content (AIGC), which may alter participation dynamics and content production processes. A common governance response has been to ban AIGC. For example, within four months of ChatGPT’s release, eighteen Stack Exchange communities prohibited AI-generated answers due to concerns about reliability, plagiarism, and diminished social authenticity. Similar restrictions were adopted in several Reddit communities. Platform performance in online knowledge exchange depends on active kn

FAQs

What question does the study investigate about AIGC bans in online Q&A communities?

It examines how banning generative AI-generated content affects knowledge seeking, knowledge contribution, and contribution efficiency in online Q&A communities.

What are the main empirical results of banning AIGC on Stack Exchange?

The ban increases knowledge seeking, shown by a higher volume of posted questions, but reduces contribution efficiency, reflected in a lower proportion of questions getting satisfactory answers within the expected time frame.

Why do the effects differ across communities, and what mechanism does the paper propose?

The impacts are only evident in non-STEM communities. The paper proposes that information reliability and social interactivity changes explain the observed shifts: the ban increases question volume where AIGC is less reliable and social interaction is expected, while it hampers answer efficiency where LLMs can produce reliable answers and social interactivity is minimal.

Jul 16, 2026

Upload by Maeve