As AI technology advances rapidly, concerns over the risks of bigness in
digital markets are also growing. The EU's Digital Markets Act (DMA) aims to
address these risks. Still, the current framework may not adequately cover
generative AI systems that could become gateways for AI-based services. This
paper argues for integrating certain AI software as core platform services and
classifying certain developers as gatekeepers under the DMA. We also propose an
assessment of gatekeeper obligations to ensure they cover generative AI
services. As the EU considers generative AI-specific rules and possible DMA
amendments, this paper provides insights towards diversity and openness in
generative AI services.

AI 技术快速发展的同时，对数字市场巨头风险的关注也在增加。欧盟的数字市场法案 (DMA) 旨在应对这些风险，但目前的框架可能还不足以覆盖可能成为 AI 服务入口的生成式 AI 系统。本文主张将某些 AI 软件作为核心平台服务集成，并将某些开发者归为 DMA 下的守门人。我们还提出对守门人义务的评估，以确保其覆盖生成式 AI 服务。随着欧盟考虑生成式 AI 特定规则和 DMA 可能的修正案，本文为生成式 AI 服务的多样性和开放性提供了深入洞察。

AI 和欧盟数字市场法案：应对生成式人工智能的规模问题

AI and the EU Digital Markets Act: Addressing the Risks of Bigness in  Generative AI

Echo chambers, i.e., situations where one is exposed only to opinions that
agree with their own, are an increasing concern for the political discourse in
many democratic countries. This paper studies the phenomenon of political echo
chambers on social media. We identify the two components in the phenomenon: the
opinion that is shared ('echo'), and the place that allows its exposure
('chamber' --- the social network), and examine closely at how these two
components interact. We define a production and consumption measure for
social-media users, which captures the political leaning of the content shared
and received by them. By comparing the two, we find that Twitter users are, to
a large degree, exposed to political opinions that agree with their own. We
also find that users who try to bridge the echo chambers, by sharing content
with diverse leaning, have to pay a 'price of bipartisanship' in terms of their
network centrality and content appreciation. In addition, we study the role of
'gatekeepers', users who consume content with diverse leaning but produce
partisan content (with a single-sided leaning), in the formation of echo
chambers. Finally, we apply these findings to the task of predicting partisans
and gatekeepers from social and content features. While partisan users turn out
relatively easy to identify, gatekeepers prove to be more challenging.

本文研究了社交媒体上的政见共鸣箱现象，通过比较社交媒体用户分享和接收内容的政治倾向度量，发现 Twitter 用户往往暴露于认同自己政见的政治观点之中，并探讨了试图打破共鸣箱的网络中介者的困境与关键色彩，同时研究了消费多元观点但产出片面政治观点的 “关键人物” 在共鸣箱形成中的作用，并应用了这些发现来预测社交媒体上的分裂者和关键人物。