Superplatforms Have to Attack AI Agents

Fuente: arXiv
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Autori principali: Lin, Jianghao, Zhu, Jiachen, Zhou, Zheli, Xi, Yunjia, Liu, Weiwen, Yu, Yong, Zhang, Weinan
Natura: Preprint
Pubblicazione: 2025
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author Lin, Jianghao
Zhu, Jiachen
Zhou, Zheli
Xi, Yunjia
Liu, Weiwen
Yu, Yong
Zhang, Weinan
author_facet Lin, Jianghao
Zhu, Jiachen
Zhou, Zheli
Xi, Yunjia
Liu, Weiwen
Yu, Yong
Zhang, Weinan
contents Over the past decades, superplatforms, digital companies that integrate a vast range of third-party services and applications into a single, unified ecosystem, have built their fortunes on monopolizing user attention through targeted advertising and algorithmic content curation. Yet the emergence of AI agents driven by large language models (LLMs) threatens to upend this business model. Agents can not only free user attention with autonomy across diverse platforms and therefore bypass the user-attention-based monetization, but might also become the new entrance for digital traffic. Hence, we argue that superplatforms have to attack AI agents to defend their centralized control of digital traffic entrance. Specifically, we analyze the fundamental conflict between user-attention-based monetization and agent-driven autonomy through the lens of our gatekeeping theory. We show how AI agents can disintermediate superplatforms and potentially become the next dominant gatekeepers, thereby forming the urgent necessity for superplatforms to proactively constrain and attack AI agents. Moreover, we go through the potential technologies for superplatform-initiated attacks, covering a brand-new, unexplored technical area with unique challenges. We have to emphasize that, despite our position, this paper does not advocate for adversarial attacks by superplatforms on AI agents, but rather offers an envisioned trend to highlight the emerging tensions between superplatforms and AI agents. Our aim is to raise awareness and encourage critical discussion for collaborative solutions, prioritizing user interests and perserving the openness of digital ecosystems in the age of AI agents.
format Preprint
id arxiv_https___arxiv_org_abs_2505_17861
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Superplatforms Have to Attack AI Agents
Lin, Jianghao
Zhu, Jiachen
Zhou, Zheli
Xi, Yunjia
Liu, Weiwen
Yu, Yong
Zhang, Weinan
Artificial Intelligence
Computers and Society
Information Retrieval
Over the past decades, superplatforms, digital companies that integrate a vast range of third-party services and applications into a single, unified ecosystem, have built their fortunes on monopolizing user attention through targeted advertising and algorithmic content curation. Yet the emergence of AI agents driven by large language models (LLMs) threatens to upend this business model. Agents can not only free user attention with autonomy across diverse platforms and therefore bypass the user-attention-based monetization, but might also become the new entrance for digital traffic. Hence, we argue that superplatforms have to attack AI agents to defend their centralized control of digital traffic entrance. Specifically, we analyze the fundamental conflict between user-attention-based monetization and agent-driven autonomy through the lens of our gatekeeping theory. We show how AI agents can disintermediate superplatforms and potentially become the next dominant gatekeepers, thereby forming the urgent necessity for superplatforms to proactively constrain and attack AI agents. Moreover, we go through the potential technologies for superplatform-initiated attacks, covering a brand-new, unexplored technical area with unique challenges. We have to emphasize that, despite our position, this paper does not advocate for adversarial attacks by superplatforms on AI agents, but rather offers an envisioned trend to highlight the emerging tensions between superplatforms and AI agents. Our aim is to raise awareness and encourage critical discussion for collaborative solutions, prioritizing user interests and perserving the openness of digital ecosystems in the age of AI agents.
title Superplatforms Have to Attack AI Agents
topic Artificial Intelligence
Computers and Society
Information Retrieval
url https://arxiv.org/abs/2505.17861