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世界经济论坛&amp凯捷:2025已付实践的AI智能体:评估与治理基础白皮书(中译版)(34页).pdf

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1、AI Agents in Action:Foundations for Evaluation and GovernanceW H I T E P A P E RN O V E M B E R 2 0 2 5In collaboration with Capgemini Images:Adobe StockDisclaimer This document is published by the World Economic Forum as a contribution to a project,insight area or interaction.The findings,interpret

2、ations and conclusions expressed herein are a result of a collaborative process facilitated and endorsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum,nor the entirety of its Members,Partners or other stakeholders.2025 World Economic

3、 Forum.All rights reserved.No part of this publication may be reproduced or transmitted in any form or by any means,including photocopying and recording,or by any information storage and retrieval system.ContentsForeword 4Executive summary 5Introduction 61 Evolving technical foundations of AI agents

4、 81.1 The software architecture of an AI agent 81.2 Communication protocols and interoperability 101.3 Cybersecurity considerations 122 Foundations for AI agent evaluation and governance 132.1 Classification 142.2 Evaluation 192.3 Risk assessment 222.4 Governance considerations for AI agents:a progr

5、essive approach 253 Looking ahead:multi-agent ecosystems 29Conclusion 30Contributors 31Endnotes 34AI Agents in Action:Foundations for Evaluation and Governance2ForewordIn recent years,organizations have moved beyond predictive models and chat interfaces to experiment with artificial intelligence(AI)

6、in more transformative ways.AI agents are now emerging as integrated collaborators in business,public services and everyday life.The adoption of AI agents could bring significant gains in efficiency,altered kinds of human-machine interaction and the advent of novel digital ecosystems.This transition

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根据《AI Agents in Action: Foundations for Evaluation and Governance》报告,以下是全文关键点: 1. **AI代理兴起**:AI代理正逐渐融入更多任务和工作流程,预计未来几年内广泛采用。 2. **技术基础**:AI代理采用经典软件、神经网络、基础模型和自主控制等技术,具有多层架构。 3. **分类**:根据功能、角色、可预测性、自主性和环境,对AI代理进行分类。 4. **评估**:通过基准测试和实际部署评估AI代理的性能和限制。 5. **风险评估**:识别和分析潜在风险,包括网络安全、安全、操作、法律和利益相关者影响。 6. **治理**:采用渐进式治理方法,根据代理的自主性、权威性和复杂性调整监督和保障措施。 7. **案例研究**:通过机器人吸尘器、编码协同助手和自动驾驶汽车等案例,展示了上述概念的应用。
安全部署指南" 从评估到监管" 风险与机遇"
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