<p>数字资产领域正在经历由生成性人工智能（GenAI）驱动的重大变革。区块链和人工智能技术的融合正在彻底改变各个行业，并改变组织的运作方式。随着公司采用 GenAI，它们必须应对隐私、安全和知识产权保护等复杂问题，以避免法律陷阱，同时最大化人工智能平台的变革潜力。</p>
<p>去中心化人工智能（deAI）的出现为快速扩展的人工智能生态系统的治理和参与增加了另一层复杂性。去中心化平台由人工智能加密代币驱动，带来了新的挑战和机遇，使治理框架比以往任何时候都更加重要。deAI 将人工智能的力量与区块链技术结合在一起，通常依赖于人工智能加密代币来促进其生态系统内的交易。这些代币扮演多重角色：授予访问预测建模等人工智能驱动服务的权限，激励参与协作网络，并通过允许代币持有者参与决策过程来促进治理。</p>
<p>根据使用案例，deAI 生态系统可以提供相对于集中式 GenAI 平台的显著优势。这些优势包括透明性、去中心化控制和包容性。值得注意的 deAI 项目包括 SingularityNET，旨在加速 deAI 的发展，以及 Fetch.ai，提供自主人工智能代理的市场。随着这些平台的发展，理解它们的优势和挑战，尤其是与集中式人工智能相比，对于寻求利用人工智能和区块链技术的企业至关重要。</p>
<p>除了许多好处，deAI 还为人工智能治理引入了独特的考虑，特别是在知识产权（IP）和数据所有权方面。最近涉及集中式人工智能模型的版权争议突显了公司利用用于训练人工智能算法的大量数据集与数据提供者之间的紧张关系。这些争议导致了具有先例的诉讼，创作者声称他们的作品被用于以侵犯版权和其他法律的方式训练 GenAI 模型。由人工智能加密代币驱动的 deAI 平台显示出作为限制或完全避免这些知识产权和数据所有权争议的手段的潜力，通过使用优先考虑用户控制并有意义地补偿数据贡献者的区块链技术。</p>
<p>deAI 项目承诺在人工智能生命周期内提供透明性，并能够缓解数据权利的法律紧张关系。通过使用区块链技术去中心化控制，支持者认为 deAI 将在创建更具包容性的人工智能生态系统方面发挥重要作用，帮助弥合人工智能&#34;拥有者&#34;和&#34;没有者&#34;之间的经济鸿沟。然而，deAI 也面临着重大的治理挑战，特别是在应对监管合规和处理去中心化管理固有风险方面。与在集中控制下运作的传统人工智能平台不同，deAI 平台往往处于监管灰色地带。目前大多数法律假设存在一个可以对数据保护和合规负责的集中实体。由共识协议而非单一控制实体治理的去中心化生态系统可能会挑战这一框架。在没有明确的&#34;控制者&#34;的情况下，去中心化平台可能难以与主要针对集中系统设计的相对成熟的法律标准保持一致。</p>
<p>除了适用不当的法律和监管标准外，技术和操作挑战也可能阻碍 deAI 的采用。可扩展性仍然是一个重大障碍，因为去中心化平台的基础区块链基础设施往往难以高效处理大规模人工智能应用。加上管理去中心化生态系统的复杂性，这些限制可能会减缓 deAI 模型相对于其集中对手的采用。问题在于 deAI 是否能够克服这些障碍，以与当前集中式 GenAI 平台的主导地位竞争。通过解决这些治理和可扩展性问题，deAI 项目有潜力重新定义人工智能领域，但实现这一愿景将需要创新解决方案和对监管环境的谨慎导航。</p>
<p>生成性人工智能与区块链技术的融合带来了巨大的潜力和一定程度的未知风险。为了成功利用 deAI 的好处，组织必须采用专门设计的治理框架，以应对去中心化人工智能平台和技术的法律、伦理和实际挑战。deAI 正在重塑所有权和协作的观念，尽管其与集中平台竞争的能力仍不确定。现在，优先考虑透明性、问责制和主动规划对于负责任地应对这一不断发展的环境至关重要。</p>
<p><img src="https://imageproxy.pbkrs.com/https://lh-prod-oper-pub-opercenter.s3.amazonaws.com/discovery-image/compress-1a61c2bc74938002.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="" original-src="https://imageproxy.pbkrs.com/https://lh-prod-oper-pub-opercenter.s3.amazonaws.com/discovery-image/compress-1a61c2bc74938002.png"/></p>

<p>去中心化人工智能（deAI）平台的兴起，受到生成式人工智能和区块链技术的推动，为人工智能生态系统的治理和参与带来了机遇和挑战。deAI 提供了透明性和去中心化控制等优势，但在合规性和可扩展性方面面临障碍。知识产权和数据所有权相关的问题至关重要，因为最近的争议突显了数据提供者与公司之间的紧张关系。为了有效利用 deAI，组织必须制定治理框架，以应对这些平台所带来的独特法律和伦理挑战，同时负责任地应对不断变化的环境</p>

<p>The digital assets space is undergoing a significant transformation driven by generative AI (GenAI). The convergence of blockchain and AI technologies is revolutionizing industries and altering how organizations operate. As companies adopt GenAI, they must navigate complex issues such as privacy, security, and intellectual property protection to avoid legal pitfalls while maximizing the transformative potential of AI platforms.</p>
<div class="lb-trans"><p>数字资产领域正在经历由生成性人工智能（GenAI）驱动的重大变革。区块链和人工智能技术的融合正在彻底改变各个行业，并改变组织的运作方式。随着公司采用 GenAI，它们必须应对隐私、安全和知识产权保护等复杂问题，以避免法律陷阱，同时最大化人工智能平台的变革潜力。</p>
</div><p>The emergence of decentralized AI (deAI) adds another layer of complexity to AI governance and participation in the rapidly expanding AI ecosystem. Powered by AI crypto tokens, deai platforms introduce new challenges and opportunities, making governance frameworks more critical than ever. DeAI combines the power of AI with blockchain technology, often relying on AI crypto tokens to enable transactions within its ecosystems. These tokens serve multiple roles: granting access to AI-driven services like predictive modeling, incentivizing participation in collaborative networks, and facilitating governance by allowing token holders to engage in decision-making processes.</p>
<div class="lb-trans"><p>去中心化人工智能（deAI）的出现为快速扩展的人工智能生态系统的治理和参与增加了另一层复杂性。去中心化平台由人工智能加密代币驱动，带来了新的挑战和机遇，使治理框架比以往任何时候都更加重要。deAI 将人工智能的力量与区块链技术结合在一起，通常依赖于人工智能加密代币来促进其生态系统内的交易。这些代币扮演多重角色：授予访问预测建模等人工智能驱动服务的权限，激励参与协作网络，并通过允许代币持有者参与决策过程来促进治理。</p>
</div><p>Depending on the use case, deAI ecosystems can offer significant advantages over centralized GenAI platforms. These advantages include transparency, decentralized control, and inclusivity. Notable deAI projects include SingularityNET, which aims to accelerate the advancement of deAI, and Fetch.ai, which provides a marketplace for autonomous AI agents. As these platforms grow, understanding their benefits and challenges, especially compared to centralized AI, is essential for businesses seeking to leverage AI and blockchain technologies.</p>
<div class="lb-trans"><p>根据使用案例，deAI 生态系统可以提供相对于集中式 GenAI 平台的显著优势。这些优势包括透明性、去中心化控制和包容性。值得注意的 deAI 项目包括 SingularityNET，旨在加速 deAI 的发展，以及 Fetch.ai，提供自主人工智能代理的市场。随着这些平台的发展，理解它们的优势和挑战，尤其是与集中式人工智能相比，对于寻求利用人工智能和区块链技术的企业至关重要。</p>
</div><p>Along with its many benefits, deAI introduces unique considerations to AI governance, especially regarding intellectual property (IP) and data ownership. Recent copyright disputes involving centralized AI models highlight the tensions between companies benefiting from vast datasets used to train AI algorithms and the data providers. These disputes have led to precedential lawsuits, with creators alleging that their works were used to train GenAI models in ways that infringe copyright and other laws. DeAI platforms, powered by AI crypto tokens, are showing promise as means of limiting or altogether avoiding these IP and data ownership disputes, through the use of blockchain technologies that prioritize user control and meaningfully compensate data contributors.</p>
<div class="lb-trans"><p>除了许多好处，deAI 还为人工智能治理引入了独特的考虑，特别是在知识产权（IP）和数据所有权方面。最近涉及集中式人工智能模型的版权争议突显了公司利用用于训练人工智能算法的大量数据集与数据提供者之间的紧张关系。这些争议导致了具有先例的诉讼，创作者声称他们的作品被用于以侵犯版权和其他法律的方式训练 GenAI 模型。由人工智能加密代币驱动的 deAI 平台显示出作为限制或完全避免这些知识产权和数据所有权争议的手段的潜力，通过使用优先考虑用户控制并有意义地补偿数据贡献者的区块链技术。</p>
</div><p>DeAI projects promise transparency and the ability to ease legal tensions over data rights throughout the AI lifecycle. By decentralizing control through the use of blockchain technology, proponents argue that deAI will be instrumental in creating more inclusive AI ecosystems, serving to bridge the economic divide between AI &#34;haves&#34; and &#34;have-nots.&#34; However, deAI also faces significant governance challenges, particularly in navigating regulatory compliance and addressing the inherent risks of decentralized management. Unlike traditional AI platforms, which operate under centralized control, deAI platforms often fall into regulatory gray zones. Most current laws assume the existence of a centralized entity that can be held responsible for data protection and compliance. Decentralized ecosystems, governed by consensus protocols rather than a single controlling entity, can challenge this framework. Without a clear &#34;controller,&#34; decentralized platforms may struggle to align with the relatively mature legal standards that have been designed largely with centralized systems in mind.</p>
<div class="lb-trans"><p>deAI 项目承诺在人工智能生命周期内提供透明性，并能够缓解数据权利的法律紧张关系。通过使用区块链技术去中心化控制，支持者认为 deAI 将在创建更具包容性的人工智能生态系统方面发挥重要作用，帮助弥合人工智能&#34;拥有者&#34;和&#34;没有者&#34;之间的经济鸿沟。然而，deAI 也面临着重大的治理挑战，特别是在应对监管合规和处理去中心化管理固有风险方面。与在集中控制下运作的传统人工智能平台不同，deAI 平台往往处于监管灰色地带。目前大多数法律假设存在一个可以对数据保护和合规负责的集中实体。由共识协议而非单一控制实体治理的去中心化生态系统可能会挑战这一框架。在没有明确的&#34;控制者&#34;的情况下，去中心化平台可能难以与主要针对集中系统设计的相对成熟的法律标准保持一致。</p>
</div><p>Beyond the application of arguably inapt legal and regulatory standards, technical and operational challenges may likewise hinder deAI adoption. Scalability remains a significant hurdle, as the underlying blockchain infrastructure of decentralized platforms often struggles to process large-scale AI applications efficiently. Coupled with the complexities of managing decentralized ecosystems, these limitations could slow the adoption of deAI models compared to their centralized counterparts. The question remains whether deAI can overcome these obstacles to rival the current dominance of centralized GenAI platforms. By addressing these governance and scalability issues, deAI projects have the potential to redefine the AI landscape, but achieving this vision will require innovative solutions and careful navigation of the regulatory environment.</p>
<div class="lb-trans"><p>除了适用不当的法律和监管标准外，技术和操作挑战也可能阻碍 deAI 的采用。可扩展性仍然是一个重大障碍，因为去中心化平台的基础区块链基础设施往往难以高效处理大规模人工智能应用。加上管理去中心化生态系统的复杂性，这些限制可能会减缓 deAI 模型相对于其集中对手的采用。问题在于 deAI 是否能够克服这些障碍，以与当前集中式 GenAI 平台的主导地位竞争。通过解决这些治理和可扩展性问题，deAI 项目有潜力重新定义人工智能领域，但实现这一愿景将需要创新解决方案和对监管环境的谨慎导航。</p>
</div><p>The fusion of GenAI and blockchain technology brings both significant potential and a certain amount of uncharted risk. To successfully leverage the benefits of deAI, organizations must adopt governance frameworks designed specifically to address the legal, ethical, and practical challenges of decentralized AI platforms and technologies. DeAI is reshaping ideas of ownership and collaboration, though its ability to rival centralized platforms remains uncertain. For now, prioritizing transparency, accountability, and proactive planning is essential to navigating this evolving landscape responsibly.</p>
<div class="lb-trans"><p>生成性人工智能与区块链技术的融合带来了巨大的潜力和一定程度的未知风险。为了成功利用 deAI 的好处，组织必须采用专门设计的治理框架，以应对去中心化人工智能平台和技术的法律、伦理和实际挑战。deAI 正在重塑所有权和协作的观念，尽管其与集中平台竞争的能力仍不确定。现在，优先考虑透明性、问责制和主动规划对于负责任地应对这一不断发展的环境至关重要。</p>
</div><p><img src="https://imageproxy.pbkrs.com/https://lh-prod-oper-pub-opercenter.s3.amazonaws.com/discovery-image/compress-1a61c2bc74938002.png" alt="" original-src="https://lh-prod-oper-pub-opercenter.s3.amazonaws.com/discovery-image/compress-1a61c2bc74938002.png"/></p>

Decentralized AI Platforms Offer Transparency, Governance Challenges

- 数字资产领域正因生成性人工智能（GenAI）而发生重大变革。  
- 去中心化人工智能（deAI）平台引入新挑战与机遇，强调治理框架的重要性。  
- deAI 项目承诺透明性，但面临合规性和可扩展性等治理挑战。  

去中心化的 AI 平台提供透明度，但也带来了治理挑战