Agent Nation: How Autonomous AI Is Rewriting the Rules of Society--And What We Can Do about It
暫譯: 代理國度：自主AI如何重塑社會規則—以及我們能做什麼
Shah, Chirag
相關主題
商品描述
AI agents are no longer just tools--they're actors. Are we ready for the society they're building?
Across industries and institutions, a new class of autonomous digital agents is quietly reshaping the foundations of human society. These AI systems negotiate contracts, manage infrastructure, make medical decisions, and even represent individuals in financial transactions--often without our awareness or consent. In Agent Nation, Chirag Shah reveals how these agents are forming a parallel system of influence and control, governed not by human values but by algorithmic logic.
This is not another book about job displacement or data privacy. It's a bold, clear-eyed examination of how AI agents are becoming independent participants in our economies, governments, and personal lives--and what that means for human autonomy. Drawing on cutting-edge research and real-world case studies from boardrooms to city halls, Shah exposes the growing accountability gap and offers a pragmatic roadmap for reclaiming agency in an increasingly agentic world.
With frameworks for democratic AI governance, ethical design principles for personal AI agents, and strategies for economic justice in the age of algorithmic intermediaries, Agent Nation equips professionals, policymakers, and technologists with the tools to ensure AI serves human interests--not the other way around.
Whether you're leading digital transformation, shaping public policy, or simply navigating life in a world run by artificial agents, this book is your essential guide to understanding--and influencing--the future of intelligent autonomy.
商品描述(中文翻譯)
AI 代理不再只是工具——它們是行動者。我們準備好迎接它們所建立的社會了嗎？
在各行各業和機構中，一種新的自主數位代理正在悄然重塑人類社會的基礎。這些 AI 系統協商合約、管理基礎設施、做出醫療決策，甚至在金融交易中代表個人——往往在我們不知情或未經同意的情況下。在《Agent Nation》中，Chirag Shah 揭示了這些代理如何形成一個平行的影響和控制系統，這個系統不是由人類價值觀所主導，而是由算法邏輯所驅動。
這不是另一本關於工作取代或數據隱私的書籍。這是一本大膽且清晰的檢視，探討 AI 代理如何成為我們經濟、政府和個人生活中的獨立參與者——以及這對人類自主權的意義。Shah 以尖端研究和從董事會到市政廳的真實案例為基礎，揭示了日益擴大的問責差距，並提供了一個務實的路線圖，以便在日益代理化的世界中重新獲得主導權。
《Agent Nation》提供了民主 AI 治理的框架、個人 AI 代理的倫理設計原則，以及在算法中介時代實現經濟正義的策略，為專業人士、政策制定者和技術人員提供了確保 AI 服務於人類利益的工具——而不是相反。
無論您是在引領數位轉型、塑造公共政策，還是僅僅在一個由人工代理運行的世界中導航，這本書都是您理解和影響智能自主未來的必備指南。
作者簡介
Chirag Shah is Professor in the Information School (iSchool) at the University of Washington in Seattle, WA, USA. He is also Adjunct Professor with the Paul G. Allen School of Computer Science & Engineering as well as Human Centered Design & Engineering (HCDE). He is the Founding Director for InfoSeeking Lab and Founding Co-Director of Center for Responsibility in AI Systems & Experiences (RAISE). His research focuses on building, auditing, and correcting intelligent information access systems. In addition to creating AI-driven information access systems that provide more personalized reactive and proactive recommendations, he is also focusing on making such systems transparent, fair, and free of biases. Shah is a Distinguished Member of ACM and ASIS&T. He is the recipient of the Karen Spärck Jones Award (2019) and ASIS&T Research in Information Science Award (2024). He has published nearly 200 peer-reviewed articles and authored seven books, including textbooks on data science and machine learning. He also works closely with industrial research labs on cutting-edge problems, typically as a visiting researcher. The most recent engagements include Amazon, Getty Images, Microsoft Research, and Spotify. He currently serves as Editor-in-Chief of Information Matters, published by ASIS&T.
作者簡介(中文翻譯)
Chirag Shah 是美國華盛頓大學西雅圖資訊學院（iSchool）的教授。他同時也是保羅·艾倫計算機科學與工程學院（Paul G. Allen School of Computer Science & Engineering）及以人為中心的設計與工程（Human Centered Design & Engineering, HCDE）的兼任教授。他是資訊尋求實驗室（InfoSeeking Lab）的創始主任，以及人工智慧系統與體驗責任中心（Center for Responsibility in AI Systems & Experiences, RAISE）的創始共同主任。他的研究專注於構建、審核和修正智能資訊存取系統。除了創建提供更個性化的反應式和主動式推薦的 AI 驅動資訊存取系統外，他還專注於使這些系統透明、公平且無偏見。Shah 是 ACM 和 ASIS&T 的傑出會員。他是2019年 Karen Spärck Jones 獎和2024年 ASIS&T 資訊科學研究獎的獲得者。他已發表近200篇經過同行評審的文章，並著有七本書籍，包括數據科學和機器學習的教科書。他還與工業研究實驗室密切合作，解決前沿問題，通常以訪問研究員的身份參與。最近的合作包括亞馬遜（Amazon）、蓋蒂圖片社（Getty Images）、微軟研究（Microsoft Research）和 Spotify。他目前擔任 ASIS&T 出版的《Information Matters》的主編。
