本文通过一所顶尖研究型大学与一家跨国企业的案例研究合作，探究了全球去中心化组织中负责任AI（Responsible AI, RAI）治理工作的评估挑战。尽管已有诸多RAI框架被提出，但它们在决策权分散的复杂组织场景中的应用仍未得到充分研究。我们跨多个业务单元和AI用例开展的RAI评估揭示了影响RAI落地的四大关键模式：（1）集团层面指引与本地解读之间的复杂相互作用；（2）抽象原则向操作实践转化的挑战；（3）落地方法的地区与职能差异；（4）风险监督中问责机制不一致。基于这些发现，我们提出自适应RAI治理（Adaptive RAI Governance, ARGO）框架，该框架通过三个相互依存的层级平衡中央协调与本地自主权：共享基础标准、中央咨询资源、情境化本地落地。我们贡献了来自产学研合作的RAI评估洞见，强调了模块化治理方法的重要性——这类方法既能适配组织复杂性，又能保持与负责任AI原则的一致性。这些经验为去中心化结构下的组织推进RAI从原则走向操作实践提供了实用指导。
英文摘要：
This paper examines the assessment challenges of Responsible AI (RAI) governance efforts in globally decentralized organizations through a case study collaboration between a leading research university and a multinational enterprise. While there are many proposed frameworks for RAI, their application in complex organizational settings with distributed decision-making authority remains underexplored. Our RAI assessment, conducted across multiple business units and AI use cases, reveals four key patterns that shape RAI implementation: (1) complex interplay between group-level guidance and local interpretation, (2) challenges translating abstract principles into operational practices, (3) regional and functional variation in implementation approaches, and (4) inconsistent accountability in risk oversight. Based on these findings, we propose an Adaptive RAI Governance (ARGO) Framework that balances central coordination with local autonomy through three interdependent layers: shared foundation standards, central advisory resources, and contextual local implementation. We contribute insights from academic-industry collaboration for RAI assessments, highlighting the importance of modular governance approaches that accommodate organizational complexity while maintaining alignment with responsible AI principles. These lessons offer practical guidance for organizations navigating the transition from RAI principles to operational practice within decentralized structures.
The organizational use of artificial intelligence (AI) has rapidly spread across various sectors. Alongside the awareness of the benefits brought by AI, there is a growing consensus on the necessity of tackling the risks and potential harms, such as bias and discrimination, brought about by advanced AI technologies. A multitude of AI ethics principles have been proposed to tackle these risks, but the outlines of organizational processes and practices for ensuring socially responsible AI development are in a nascent state. To address the paucity of comprehensive governance models, we present an…
Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry
Oxford Internet Institute, University of Oxford（牛津大学牛津互联网研究院）；Center for Information Technology Policy, Princeton University（普林斯顿大学信息技术政策中心）；AstraZeneca（阿斯利康）；University of Bologna（博洛尼亚大学）
Organizations of all sizes, across all industries and domains are leveraging artificial intelligence (AI) technologies to solve some of their biggest challenges around operations, customer experience, and much more. However, due to the probabilistic nature of AI, the risks associated with it are far greater than traditional technologies. Research has shown that these risks can range anywhere from regulatory, compliance, reputational, and user trust, to financial and even societal risks. Depending on the nature and size of the organization, AI technologies can pose a significant risk, if not us…
When Should Algorithms Resign? A Proposal for AI Governance
Center for Data Science, New York University（纽约大学数据科学中心）；The Alan Turing Institute（艾伦·图灵研究所）；Faculty of Law, University of Cambridge（剑桥大学法学院）；Berkman Klein Center for Internet & Society（伯克曼 Klein 互联网与社会中心）
We empirically study the state of three prominent DAO governance systems on the Ethereum blockchain: Compound, Uniswap and ENS. In particular, we examine how the voting power is distributed in these systems. Using a comprehensive dataset of all governance token holders, delegates, proposals and votes, we analyze who holds the voting rights and how they are used to influence governance decisions.
Data-driven and distributed governance of building facilities management using decentralized autonomous organization, digital twin, and large language models
School of Technology, Eastern Illinois University（东伊利诺伊大学技术学院）；Myers-Lawson School of Construction, Virginia Polytechnic Institute and State University（弗吉尼亚理工学院和州立大学迈尔斯-劳森建设学院）
Algorithmic Decision Making (ADM) has permeated all aspects of society. Government organizations are also affected by this trend. However, the use of ADM has been getting negative attention from the public, media, and interest groups. There is little to no actionable guidelines for government organizations to create positive impact through ADM. In this case study, we examined eight municipal organizations in the Netherlands regarding their actual and intended use of ADM. We interviewed key personnel and decision makers. Our results show that municipalities mostly use ADM in an ad hoc manner, a…
Decentralized autonomous organizations (DAOs) are a recent innovation in organizational structures, which are already widely used in the blockchain ecosystem. We empirically study the on-chain governance systems of 21 DAOs and open source the live dataset. The DAOs we study are of various size and activity, and govern a wide range of protocols and services, such as decentralized exchanges, lending protocols, infrastructure projects and common goods funding. Our analysis unveils a high concentration of voting rights, a significant hidden monetary costs of on-chain governance systems, as well as…
Utrecht University（乌得勒支大学）；University of Amsterdam（阿姆斯特丹大学）；Lappeenranta University of Technology（拉彭兰塔理工大学）
Decentralized autonomous organizations as a new form of online governance arecollections of smart contracts deployed on a blockchain platform that intercede groupsof people. A growing number of Decentralized Autonomous Organization Platforms,such as Aragon and Colony, have been introduced in the market to facilitate thedevelopment process of such organizations. Selecting the best fitting platform ischallenging for the organizations, as a significant number of decision criteria, such aspopularity, developer availability, governance issues, and consistent documentation ofsuch platforms, should b…
Oversight Structures for Agentic AI in Public-Sector Organizations
Centre for Digital Governance, Hertie School（数字治理中心，赫尔姆斯学校）；Oxford Internet Institute, University of Oxford（牛津互联网研究所，牛津大学）；Weizenbaum Institute Berlin, Germany（贝伦贝格Weizenbaum研究所）；Technical University Munich, Germany（慕尼黑技术大学）
A Technical Policy Blueprint for Trustworthy Decentralized AI
MLCommons；Sage Bionetworks；Google（谷歌）；Inria（法国国家计算机科学研究所）；Intel（英特尔）；Flower；Apheris；University of Notre Dame（圣母大学）；NVIDIA（英伟达）；Factored；Florida International University（佛罗里达国际大学）
Voting Biases in Decentralized Autonomous Organization (DAO) Governance
Private Sector（私营部门）；IMT School for Advanced Studies Lucca（卢卡高等研究学院）；Complexity Science Hub Vienna（维也纳复杂科学中心）；University of Mannheim（曼海姆大学）；GESIS - Leibniz Institute for the Social Sciences（GESIS - 莱布尼茨社会科学研究所）
Decentralized autonomous organization and blockchain-based incentivization framework for community-based facilities management
School of Technology, Eastern Illinois University（东伊利诺伊大学技术学院）；Myers-Lawson School of Construction, Virginia Polytechnic Institute and State University（弗吉尼亚理工学院和州立大学梅斯-劳森建筑学院）
Spending on cybersecurity products and services is expected to top 123 billion U.S. dollars for 2020, more than double the 55 billion U.S. dollars spent in 2011.1 In that same period, cyber breaches quadrupled. Organizations globally face increasing liabilities, while boards of directors grapple with a seemingly Sisyphean challenge. Cyber Crossroads was born out of these alarming trends and a realization that the world cannot go on funneling finite resources into an indefinite, intractable problem. Cyber Crossroads brings together expertise from across the world, spanning aspects of the cyber …
Toward Responsible and Beneficial AI: Comparing Regulatory and Guidance-Based Approaches -A Comprehensive Comparative Analysis of Artificial Intelligence Governance Frameworks across the European Union, United States, China, and IEEE
Digital health transformation in Quebec: assessment of interoperability and governance strategies
École de santé publique de l’Université de Montréal（蒙特利尔大学公共卫生学院）；Centre intégré universitaire de santé et de services sociaux du Centre-Sud-de-l'Île-de-Montréal（蒙特利尔岛中南地区综合大学卫生与社会服务服务中心）；Centre interuniversitaire de recherche en analyse des organisations（组织分析研究跨大学中心）
Disaster and emergency management are under the responsibility of many organizations and there are serious coordination problems in post-disaster crisis management. This paper proposes a decentralized non-governmental organization resource management system for disasters (NGO-RMSD / STK-AKYS). This system is based on blockchain technology and it will enable the non-governmental organizations (NGO) and public institutions to manage and coordinate the resources in a trusted environment in the case of disasters. A proof of concept implementation is developed by using the Quorum blockchain framewo…
