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The Next Paradigm Is User-Centric Agent, Not Platform-Centric Service

Luankang Zhang, Hang Lv, Qiushi Pan, Kefen Wang, Yonghao Huang, Xinrui Miao, Yin Xu, Wei Guo, Yong Liu, Hao Wang, Enhong Chen

TL;DR

This paper argues that the future of digital services should shift from a platform-centric to a user-centric agent, and presents a practical device-cloud pipeline for its implementation, and discusses the necessary governance and ecosystem structures for its adoption.

Abstract

Modern digital services have evolved into indispensable tools, driving the present large-scale information systems. Yet, the prevailing platform-centric model, where services are optimized for platform-driven metrics such as engagement and conversion, often fails to align with users' true needs. While platform technologies have advanced significantly-especially with the integration of large language models (LLMs)-we argue that improvements in platform service quality do not necessarily translate to genuine user benefit. Instead, platform-centric services prioritize provider objectives over user welfare, resulting in conflicts against user interests. This paper argues that the future of digital services should shift from a platform-centric to a user-centric agent. These user-centric agents prioritize privacy, align with user-defined goals, and grant users control over their preferences and actions. With advancements in LLMs and on-device intelligence, the realization of this vision is now feasible. This paper explores the opportunities and challenges in transitioning to user-centric intelligence, presents a practical device-cloud pipeline for its implementation, and discusses the necessary governance and ecosystem structures for its adoption.

The Next Paradigm Is User-Centric Agent, Not Platform-Centric Service

TL;DR

This paper argues that the future of digital services should shift from a platform-centric to a user-centric agent, and presents a practical device-cloud pipeline for its implementation, and discusses the necessary governance and ecosystem structures for its adoption.

Abstract

Modern digital services have evolved into indispensable tools, driving the present large-scale information systems. Yet, the prevailing platform-centric model, where services are optimized for platform-driven metrics such as engagement and conversion, often fails to align with users' true needs. While platform technologies have advanced significantly-especially with the integration of large language models (LLMs)-we argue that improvements in platform service quality do not necessarily translate to genuine user benefit. Instead, platform-centric services prioritize provider objectives over user welfare, resulting in conflicts against user interests. This paper argues that the future of digital services should shift from a platform-centric to a user-centric agent. These user-centric agents prioritize privacy, align with user-defined goals, and grant users control over their preferences and actions. With advancements in LLMs and on-device intelligence, the realization of this vision is now feasible. This paper explores the opportunities and challenges in transitioning to user-centric intelligence, presents a practical device-cloud pipeline for its implementation, and discusses the necessary governance and ecosystem structures for its adoption.
Paper Structure (19 sections, 3 figures)

This paper contains 19 sections, 3 figures.

Figures (3)

  • Figure 1: Conflict of Interest: The platform-centric optimization objective fundamentally diverges from the user's goal.
  • Figure 2: Organization of Our Paper
  • Figure 3: An Edge-Cloud Collaborative Pipeline for User-Centric Agent