AIArena: A Blockchain-Based Decentralized AI Training Platform

2024-12-19

arXiv.org

AI Summary

Centralized control of AI development by a few technology giants exacerbates model bias, undermines governance, limits public participation, and distorts data rights allocation. To address these challenges, this paper introduces the first blockchain-based decentralized AI training platform, built on an EVM-compatible chain (Base Sepolia). It implements an on-chain, consensus-driven mechanism for contribution evaluation and automated revenue distribution, ensuring full transparency, verifiable accountability, and equitable value redistribution across the entire training lifecycle. The platform supports heterogeneous model submissions and distributed collaborative training, and proposes a novel smart-contract-driven framework for quantifying multi-dimensional contributions—spanning compute resources, data, and model artifacts. Empirical evaluation demonstrates 98.2% fairness in reward allocation and sustained system throughput supporting over one thousand daily active nodes, establishing a verifiable infrastructure for AI democratization and value alignment.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Machine Learning: Ethics, Bias, and Fairness
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Algorithmic accountability and transparency on the web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

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.

Problem

• Centralized AI control by corporations causes bias and limits innovation.
• Lack of public involvement and governance in AI model development.
• Monopolistic data control threatens fair data usage and model integrity.

Innovation

• Blockchain-based decentralized AI training platform
• On-chain incentive mechanisms for fair rewards
• Public Base blockchain Sepolia testnet implementation