Data Leverage Digital Garden

Why the AI evaluation crisis could force a reckoning on dataset provenance, attribution, and consent.

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

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?

Back to the basics of data leverage.

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

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

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

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.

A short argument that model outputs and training-data priors can improve rough approximations of data attribution.

A short argument that "augment, do not replace" is about data control.

A short argument that AI systems pool diffuse human work into privately governed, public-good-like model weights.

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

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

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

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.

A rough map of my current local Markdown to Leaflet, Substack, and social-post workflow.