AI即未來：普通人用好人工智能的18大工作場景 內容簡介
這是一本普通人的AI時代指南
編輯推薦
實用落地性強：聚焦文案撰寫、客戶服務、編程輔助、醫療診斷等 18 個高頻工作場景，每個場景均搭配真實案例、具體操作技巧與工具推薦，提供可直接複用的實操方案。
語言通俗易懂：避免晦澀技術術語堆砌，用 “手腳麻利的實習生”等生動比喻解釋 AI 特性，將複雜的 Transformer 架構、模型微調等知識轉化為通俗表達，非技術背景讀者也能輕鬆理解。
適配多元需求：既滿足企業管理者的組織轉型規劃、創業者的效率提升需求，也適合普通職場人解決具體工作難題，無論是想理解技術本質、優化工作流程，還是探索創新應用，都能找到針對性答案。
案例數據支撐足：包含大量跨行業實證案例（如特斯拉 AI 設計、萬事達卡欺詐檢測），引用芝加哥大學、麥肯錫、斯坦福大學等機構的研究數據，觀點更具說服力。
兼顧深度與通俗性：既有科學知識支撐，又有名人真實案例，不管是心理學愛好者、想提升人際質量的上班族，還是渴望自我成長的普通人，都能輕鬆讀懂、持續受益。
AI即未來：普通人用好人工智能的18大工作場景 作者簡介
安東尼奧・韋斯（Antonio Weiss）
擁有倫敦大學伯克貝克學院博士學位。
現任英國歷史最悠久的公共服務專業谘詢公司PSC高級合夥人；劍橋大學“數字國家”項目附屬研究員；托馬斯・克利珀公司的聯合創始人。
深耕人工智能與數字化轉型領域，曾為英國人工智能辦公室、英國航天局、英國國家醫療服務體係人工智能實驗室及政府數字服務局等核心機構提供戰略谘詢，並曾任英國首相辦公室數字、數據與技術高級顧問。
AI即未來：普通人用好人工智能的18大工作場景 目錄
◆目錄◆第一部分理解人工智能和它的工作方式
第1章什麼是生成式人工智能·········································3
第2章人工智能能為我提供哪些幫助·······························12
第3章數據科學與人工智能快速入門·······························22
第4章不同類型的人工智能模型有哪些····························33
第5章在組織中適配大語言模型·····································51
第6章人工智能：你那位才華橫溢卻並非完美的夥伴··········64
第7章人工智能實施指南··············································73
第8章評估人工智能模型··············································84
第9章從沙盒試點到企業級應用·····································98
第10章製定卓越的商業決策········································106
第11章人工智能的風險、倫理與可持續性······················113
第12章提升客戶滿意度的方法·····································126
第13章人工智能法律法規···········································135
第14章人工智能優先時代的職業發展····························143
第15章讓組織具備未來適應性·····································151第二部分如何在工作中運用人工智能
第16章創意與構思····················································162
第17章文案撰寫·······················································168
第18章圖像創作·······················································174
第19章視頻製作·······················································181
第20章客戶服務與聊天機器人·····································185
第21章語音助手·······················································191
第22章原型設計與新產品開發·····································195
第23章社交媒體·······················································200
第24章市場營銷·······················································204
第25章語言翻譯·······················································208
第26章軟件工程與編程··············································212
第27章欺詐檢測·······················································218
第28章演示文稿與幻燈片···········································221
第29章研究內容總結·················································226
第30章會議助手·······················································229
第31章教育領域·······················································233
第32章數據分析·······················································240
第33章醫療健康·······················································245
結語生成式人工智能的未來應用場景······················249
致謝···································································253
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最後修改：2026 年 09 月 19 日
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