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世界经济论坛:2026数据与智能赋能集体优势:终结全球供应链中的强迫劳动白皮书(中译版)(28页).pdf

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1、Harnessing Data and Intelligence for Collective Advantage:Ending Forced Labour in Global Supply ChainsW H I T E P A P E RJ A N U A R Y 2 0 2 6Images:Adobe StockDisclaimer This document is published by the World Economic Forum as a contribution to a project,insight area or interaction.The findings,in

2、terpretations 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.2026 World E

3、conomic 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 3Executive summary 41 The problem:The vicious cycle of forced labour and

4、 data fragmentation 51.1 Persistence amid progress:The enduring nature offorced labour 51.2 The structural roots of fragmentation:Data,incentives,trust 6 and governance gaps1.3 Breaking the vicious cycle 92 The solution:The Global Data Partnership Against Forced Labour 10 as a new model for collecti

5、ve impact2.1 A system-level response to a systemic challenge 102.2 The theory of change 112.3 Why federated data and agentic AI are gamechangers 132.4 Proof of Concept in Thailand 152.5 Stakeholder value and collective advantage 182.6 Summary of the solution 193 The future:From proof to global impac

6、t 203.1 Minimum viable product:Scaling beyond the 20 Proof of Concept3.2 Trust by design:Governance,risks and enabling 21 conditions for scale3.3 Building global momentum and vision for 2030 22Conclusion 23Contributors 24Endnotes 26Harnessing Data and Intelligence for Collective Advantage:Ending For

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1. **问题现状**:全球强迫劳动问题持续存在,近2800万人被困(ILO 2022年数据),因数据碎片化、激励错位和信任缺失,导致预防与问责不足。 2. **解决方案**:推出“全球反强迫劳动数据伙伴关系”,采用联邦数据模型和智能AI,连接政府、企业、公民社会数据,无需集中或共享原始数据,保障主权与隐私。 3. **核心价值**: - 政府:提升执法精准度与政策响应; - 企业:降低合规成本,增强供应链韧性; - 公民社会:放大工人声音,推动系统性解决方案; - 投资者:获取可靠数据优化资源分配。 4. **进展与愿景**:泰国试点验证技术可行性,2026年扩展至全球,目标2030年将强迫劳动转化为“可预防风险”。
数据如何破局? 联盟有何价值? 技术如何赋能?
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