Equitable Data-Value Exchange (EDVEX)

Gold definitionUpdated Apr 2, 2026

Definition

Equitable Data-Value Exchange (EDVEX) is a framework proposed to address economic inequality in the machine learning value chain. It aims to create a minimal market where data generators receive fair economic equity, counteracting the current system where value disproportionately accrues to data aggregators.

At a glance

Executive summary

Equitable Data-Value Exchange (EDVEX) is a proposed framework to fix the unfair economics in how data is used for AI. It aims to ensure that people who create data get a fair share of its value, rather than most of the profit going to big data companies. This is important for making AI development sustainable and ethical in the long run.

TL;DR

EDVEX is a plan to make sure data creators get paid fairly when their data is used for AI, fixing the current system where most of the money goes to big tech companies.

Key points

Proposes a 'minimal market' framework to ensure equitable economic benefits for all participants in the ML data value chain.
Solves the problem of economic data processing inequality and structural unsustainability of the current ML value chain, where data generators receive little to no value.
Used by researchers and ML engineers focused on data ethics, fair compensation, and sustainable AI development.
Contrasts with the current opaque, aggregator-dominated data economy characterized by missing provenance, asymmetric bargaining power, and non-dynamic pricing.
Part of a growing trend towards ethical AI, data governance, and fair economic models for data in the age of AI.

Use cases

Fair Compensation for User Data: Platforms implementing EDVEX principles could automatically compensate users for their data contributions, e.g., social media users receiving micro-payments for content used in training generative AI.
Transparent Data Marketplaces: Development of marketplaces where data provenance is clear, and dynamic pricing models ensure fair value exchange between data providers and ML developers.
Ethical AI Development: Companies adopting EDVEX to ensure their AI models are trained on ethically sourced and compensated data, enhancing trust and regulatory compliance.
Data Cooperatives: Empowering groups of data generators (e.g., farmers, medical patients) to collectively bargain for better data deals and share in the value generated by their aggregated data.

Also known as

EDVEX