The rapid advancement of AI has underscored critical challenges in its development and implementation, largely due to centralized control by a few major corporations. This concentration of power intensifies biases within AI models, resulting from inadequate governance and oversight mechanisms. Additionally, it limits public involvement and heightens concerns about the integrity of model generation. Such monopolistic control over data and AI outputs threatens both innovation and fair data usage, as users inadvertently contribute data that primarily benefits these corporations. In this work, we propose AIArena, a blockchain-based decentralized AI training platform designed to democratize AI development and alignment through on-chain incentive mechanisms. AIArena fosters an open and collaborative environment where participants can contribute models and computing resources. Its on-chain consensus mechanism ensures fair rewards for participants based on their contributions. We instantiate and implement AIArena on the public Base blockchain Sepolia testnet, and the evaluation results demonstrate the feasibility of AIArena in real-world applications.

翻译：人工智能的快速发展凸显了其开发与实施过程中的关键挑战，这主要源于少数大型企业的集中控制。这种权力集中加剧了人工智能模型内部的偏见，其根源在于治理与监督机制的不足。此外，它限制了公众参与，并加剧了人们对模型生成完整性的担忧。这种对数据和人工智能输出的垄断性控制，既威胁着创新，也威胁着数据的公平使用，因为用户无意中贡献的数据主要使这些企业受益。在本工作中，我们提出了AIArena，一个基于区块链的去中心化人工智能训练平台，旨在通过链上激励机制实现人工智能开发与对齐的民主化。AIArena培育了一个开放协作的环境，参与者可以贡献模型和计算资源。其链上共识机制确保了参与者能根据其贡献获得公平的奖励。我们在公共的Base区块链Sepolia测试网上实例化并实现了AIArena，评估结果证明了AIArena在实际应用中的可行性。