# Decentralized & Collaborative AI on Blockchain

## TL;DR

This paper introduces a decentralized framework for collaborative AI development on blockchain, enabling shared, continuously updated models with incentivized data contribution, promoting open and up-to-date AI models.

## Contribution

It proposes a novel blockchain-based system for collaborative dataset building and model updating with incentive mechanisms, enhancing transparency and accessibility.

## Key findings

- Framework enables collaborative dataset creation.
- Smart contracts facilitate continuous model updates.
- Incentive structures motivate high-quality data contributions.

## Abstract

Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can quickly become out of date without effort to acquire more data and re-train them. We propose a framework for participants to collaboratively build a dataset and use smart contracts to host a continuously updated model. This model will be shared publicly on a blockchain where it can be free to use for inference. Ideal learning problems include scenarios where a model is used many times for similar input such as personal assistants, playing games, recommender systems, etc. In order to maintain the model's accuracy with respect to some test set we propose both financial and non-financial (gamified) incentive structures for providing good data. A free and open source implementation for the Ethereum blockchain is provided at https://github.com/microsoft/0xDeCA10B.