Sustainable data ecosystems

What Humanity Needs To Flourish In The Next Decade

We are headed toward a world of productivity without prosperity, execution without verification and capacity without constraint. But this outcome is not inevitable.

A Collectivist, Economic Perspective on AI

Information technology is in the midst of a revolution in which omnipresent data collection and machine learning are impacting the human world as never before. The word ``intelligence'' is being...

Built on Shared Knowledge: What the World Wants from AI Wealth

AI labs and policymakers are focusing on AI dividends to address economic insecurity. We asked 1,041 people across 64 countries what they actually want from AI wealth.

Attestation across the AI Supply Chain - Data Leverage

A proposal for interoperable attestation objects that connect training data, evaluation labor, and AI-generated outputs across the AI supply chain.

Control content use for AI training with Cloudflare’s managed robots.txt and blocking for monetized content

Cloudflare is making it easier for publishers and content creators of all sizes to prevent their content from being scraped for AI training by managing robots.txt on their behalf, and allowing targeted blocking of AI crawling on sites that serve ads.

The Paradox of Reuse in 2026: A Case of Quasi-Enclosure, or "Subsidized Club Goods that Sort of Look Like Public Goods"

How we can understand, and react to, the complicated impacts of AI systems on online communities and knowledge commons

A Human-Centric Framework for Data Attribution in Large Language Models

In the current Large Language Model (LLM) ecosystem, creators have little agency over how their data is used, and LLM users may find themselves unknowingly plagiarizing existing sources. Attribution of LLM-generated text to LLM input data could help with these challenges, but so far we have more questions than answers: what elements of LLM outputs require attribution, what goals should it serve, how should it be implemented? We contribute a human-centric data attribution framework, which situates the attribution problem within the broader data economy. Specific use cases for attribution, such as creative writing assistance or fact-checking, can be specified via a set of parameters (including stakeholder objectives and implementation criteria). These criteria are up for negotiation by the relevant stakeholder groups: creators, LLM users, and their intermediaries (publishers, platforms, AI companies). The outcome of domain-specific negotiations can be implemented and tested for whether the stakeholder goals are achieved. The proposed approach provides a bridge between methodological NLP work on data attribution, governance work on policy interventions, and economic analysis of creator incentives for a sustainable equilibrium in the data economy.

Abundance vs. Scarcity: Who Controls the Internet After AI?

AI is straining the open web, forcing a choice between abundance with redistribution and scarcity built on paywalls, writes Paul Keller.

Unlocking a Million Times More Data for AI | IFP

How a new ARPANET-style program could solve the data accessibility problem

Project Liberty Institute Launches Landmark Recommendations of its Fair Data Economy Task Force - Project Liberty

“The digital revolution promised opportunity for all. Instead, we’ve witnessed the unprecedented concentration of our data and power in the hands of a few. At Project Liberty, we believe it’s time to start building the digital future we all deserve,” said Frank McCourt, Founder of Project Liberty. “This report is a call to action. Our […]

Collective Bargaining in the Information Economy Can Address...

This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as journalists,...

Attribution-Based Control (ABC) for Safe AI

ABC enables data owners to control AI usage while users verify sources. Solving hallucinations, privacy & trust at scale.

Cloudflare's Matthew Prince has a plan to get Google and the AI oliigarchs to pay for your content even though many are used to getting it for free. He might have enough leverage to make them.

AI chatbots are blowing up the 30-year economic relationship publishers have had with search engines. Many think this will kill the web if not addressed. Google needs to change first. It's resisting. Cloudflare's Matthew Prince is going to try and make them.