宏
计算机科学
能见度
自然实验
数字内容
质量(理念)
不平等
人机交互
认知建筑学
创造力
用户生成的内容
认知
多媒体
自然(考古学)
内容创建
数字鸿沟
数字化学习
数字艺术
社会学习
信息处理
知识管理
用户体验设计
数字媒体
投资(军事)
微分效应
差速器(机械装置)
通信设计
数字革命
创意产业
数字经济
营销
数据科学
作者
Hongpeng Wang,Jia Zhang,Zhen Yan,Yi Luo
标识
DOI:10.1108/intr-10-2025-1682
摘要
Purpose The widespread adoption of Artificial Intelligence-Generated Summary (AIGS) is reshaping how the user accesses and evaluates digital content. By automatically condensing information, AIGS enhances efficiency and facilitates user decision-making, but raises concerns about digital inequality among content creators. This study examines how AIGS affects such inequality between macro and micro creators. Design/methodology/approach Using a natural experiment on BiliBili, we analyze data from 1,590 creators and 79,909 videos posted before and after the introduction of AIGS. Combining machine learning with a difference-in-differences framework, we quantify the impact of AIGS on creators' rewards and creative effort across both verbal and visual dimensions. Findings Results show that AIGS mitigates digital inequality. While macro creators experience faster growth in viewership, micro creators gain more in engagement metrics–completion rate, follower growth, and bullet-screen comments. AIGS also stimulates greater creative investment among micro creators, reflected in enhanced verbal and visual novelty. Thus, AIGS promotes fairness by aligning user recognition with intrinsic content quality rather than social cues. Originality/value This study advances understanding of how AI-generated tools reshape digital ecosystems by examining the differential effects of AIGS across creator tiers. It conceptualizes AIGS not merely as a content creator but also as a cognitive aid that alleviates users' mental load and guides their evaluation. By revealing how AIGS influences information processing and redistributes visibility and rewards, this study identifies a cognitive pathway through which AI can mitigate digital inequality. Methodologically, it integrates machine learning with multimodal data to measure creative effort, demonstrating how AI-mediated information design can promote fairness and inclusivity in digital platforms.
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