How Web 3 Can Address the Unfairness of AI Language Models

🤖AI language models are built by training on vast amounts of internet data, including text scraped from websites.

💻The current training process for large language models lacks permission and compensation for content contributors.

🌐Web 3 proposes a decentralized approach to AI, where contributors receive tokens as a form of ownership.

💰In a decentralized AI model, contributors can be compensated with tokens based on the amount of content they contribute.

🔑Token ownership can be required for accessing and using AI networks and products, creating a Commons-based ownership model.

How are AI language models built?

—AI language models are built by training on a massive amount of internet data, including text scraped from websites without explicit permission.

Do content contributors get compensated for their contributions?

—Currently, most contributors to AI language models do not receive any compensation for their content contributions.

What is Web 3?

—Web 3 refers to a decentralized internet infrastructure that aims to give more control and ownership to users and content creators.

How does Web 3 address the unfairness of AI language models?

—Web 3 proposes a system where contributors are rewarded with tokens, providing financial compensation and ownership rights.

Can token ownership be used to access AI networks and products?

—Yes, requiring token ownership can create a Commons-based ownership model where users need tokens to use AI networks and products.

00:00Large language models built on AI training scrape internet content, raising concerns of unfairness and potential copyright violations.

00:40Web 3 offers a decentralized solution where contributors to AI models are rewarded with tokens as compensation.

01:03Token ownership can be required to access and use AI networks and products, creating a commons-based ownership model.