Data Leverage

On healthy data flow in the AI age

Attestation across the AI Supply Chain

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

April 08, 2026

"People First" Policy Ideas that Complement Each Other (through better data flow)

Reacting to a wide-ranging set of policy ideas from OpenAI.

April 05, 2026

AI is driving the cost of polish down; some musings on fancy versus terse artifacts

AI progress means the "polish" of a figure or website no longer proxies for quality. Can we try to turn this into a good thing for curation, attention allocation, and even AI progress itself?

March 31, 2026

Two natural allies of a "Data Transparency" agenda: capabilities forecasters and social simulators

Making an "if you like X, you might want to support Y" argument for data-focused policy

March 08, 2026

A Short Guide to Data Strikes and Conscious Data Contribution in the Context of 2026 Frontier AI

Back to the basics of data leverage.

March 02, 2026

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

February 16, 2026

The Coding Agent Data Deal

On user data control, coding agents as retrievers, and the value of your coding transcripts

January 11, 2026

Coding agents are (1) a big deal, (2) very relevant to data leverage, and (3) able to help build tools that support data leverage!

Sharing an early reaction to recent coding agent discourse and two relevant projects

January 04, 2026

How collective bargaining for information, public AI, and HCI research all fit together

Another recap post for the Data Leverage newsletter! (and a test of using Leaflet for blogging

December 23, 2025

Almost Everybody -- Including Both Data Creators and AI Companies -- Stands to Benefit from Clearer "Data Rules".

In fact, anyone who doesn't think they will be a "big winner" long term benefits from clear rules, even if it means training data costs more in the short term.

November 25, 2025

How collective bargaining for information, public AI, and HCI research all fit together

Another recap post for the Data Leverage newsletter!

October 10, 2025

Which datasets should we assume are "in all the AI models"?

New model releases keep (re)sparking discussions about training data. What can we assume is upstream in the data river, and what do we want to see happen?

September 23, 2025

Algorithmic Collective Action With Two Collectives [crosspost]

This post was written by Aditya Karan, with support from Nick Vincent and Karrie Karahalios to accompany a FAccT 2025 paper. It was originally published on Jun 19, 2025 via the Crowd Dynamics Lab blog.

June 19, 2025

On AI-driven Job Apocalypses and Collective Bargaining for Information

Reacting to a fresh wave of discussion about AI's impact on the economy and power concentration, and reiterating the potential role of collective bargaining.

June 04, 2025

How do we know our AI output is good? Double checks, bar charts, vibes, and training data.

Connecting evaluation and dataset documentation via the lens of "AI as ranking".

May 29, 2025

Each Instance of "AI Utility" Stems from Some Human Act(s) of Information Recording and Ranking

It's ranking information all the way down.

May 27, 2025

Google and TikTok rank bundles of information; ChatGPT ranks grains.

Google and others solve our attentional problem by ranking discrete bundles of information, whereas ChatGPT ranks more granular chunks. This lens can help us reason about AI policy.

May 26, 2025

[microblog] One book is worth "0.06%" benchmark points to AI; is "no different from noise". What gives?

Commenting on recent coverage of, and discussion about, Meta's arguments about training data value quantification.

April 20, 2025

Public AI, Data Appraisal, and Data Debates

A consortium of Public AI labs can substantially improve data pricing, which may also help to concretize debates about the ethics and legality of training practices.

April 02, 2025

Evaluation Data Leverage: Advances like "Deep Research" Highlight a Looming Opportunity for Bargaining Power

Research agents and increasingly general reasoning models open the door for immense "evaluation data leverage".

March 01, 2025

Tipping Points for Content Ecosystems

Our AI design choices in 2024 could preclude "Powerful AI" in 2030.

February 11, 2025

AI Labs Should Open Source Data Protection Technologies

There's still incredible tension in the current data paradigm, but sharing "data protection" technologies, like those used by OpenAI to accuse DeepSeek of model theft, can help cut a path forward.

January 30, 2025

Live by the free-content-for-training sword, die by the free-content-for-training sword

There's deep tension in the current ask-for-forgiveness-free-for-all approach to acquiring data for model training. Will "open" models cause this tension to reach a breaking point?

January 27, 2025

Selling AGI like AG1: Will Consumers Push Back Against Proprietary Blends of Herbs and of Data?

The race to produce premiere AI products with high price tags might change the standards around data disclosure.

December 11, 2024

Perplexity CEO's Interaction with Striking New York Times Workers Does Not Reflect Well on the AI Industry

The idea that data-dependent AI systems are ready and willing to crush any leverage from knowledge workers is unlikely to make the AI industry look good to the public.

November 08, 2024

Is Zuckerberg right to say that your specific creative work has no value to AI?

Examining the Meta CEO's claim that the "individual work of most creators isn’t valuable enough for it to matter" in the context of AI training.

September 27, 2024

"Many Models" and "Track Changes" for AI: Some Thoughts on LLM Interfaces

Interacting with many models and harnessing the power of `diff`

August 07, 2024

Building a Data Pipeworks for Democratic AI: From Human Knowledge to Records to AI Systems

Focusing on feedback loops -- connecting modern AI to early cybernetics-style thinking -- could help solve looming challenges and support democratic inputs to AI.

November 12, 2023

Will the New York Times Data Strike Have a Large Impact on ChatGPT?

How can we start thinking about how opt-out decisions by content-producing organizations will affect LLMs?

September 27, 2023

A Harbinger of the Future of Content? The New York Times Starts a Data Strike

The New York Times is trying to remove its content from OpenAI models, surfacing tensions around copyright, economic harms, privacy, and the distribution of AI benefits.

August 24, 2023

The WGA Strike is a Canary in the Coal Mine for AI Labor Concerns

Could Upcoming Data Legislation Enable a "Right to Data Strike"?

May 04, 2023

Reddit, StackOverflow, and Europe: All Trending Towards Data Dignity

Once again, we’ve had an eventful few weeks in the space of data-dependent computing!

April 30, 2023

Data Leverage Recap: December 2022 - April 2023

The Last Three Months in Review: What's New and What's Next

April 17, 2023

Bing Rewards for the AI Age

The plants in the Gardens by the Bay evoke a sense of flourishing-by-design; photo by Victor from Unsplash.

March 29, 2023

Plural AI Data Alignment

Measuring the Alignment of AI Systems Based on their Data Pipelines

March 01, 2023

AI Technologies are System Maps, and You are a Cartographer

Much of my work is in pursuit of “data dignity”, an idea that stems in part from scholars arguing that we should sometimes think of “data as labor”.

February 02, 2023

AI Artist or AI Art Thief? Innovation, Public Mandates, and the Case for Talking in Terms of Leverage

The public debate over AI has seriously heated up in the wake of new advances in the design and deployment of large generative AI models.

December 15, 2022

ChatGPT is Awesome and Scary: You Deserve Credit for the Good Parts (and Might Help Fix the Bad Parts)

More on why you're an expert language model trainer

December 03, 2022

The Paradox of Reuse, Language Models Edition

Background

December 01, 2022

Don’t give OpenAI all the credit for GPT-3: You might have helped create the latest “astonishing” advance in AI too

The much-celebrated GPT-3 that can answer questions, write poems, and more wouldn’t be possible without content written by millions of people around the world. Shouldn’t they get some credit?

September 21, 2020