EXTERNAL RESOURCES
Useful work,
read in context.
Standards, frameworks, and research referenced across our writing, with a short note on what each source contributes.
FACT-CHECKING / PRACTICE
IFCN Code of Principles
A public standard for transparency, fairness, sourcing, funding, and corrections.
VERIFICATION / FIELD GUIDE
First Draft verification guide
Practical methods for checking where information came from and what context it may be missing.
MEASUREMENT / EXPLAINER
Precision and recall
Two useful measures for understanding what a classifier includes and what it misses.
RESEARCH / CONFIDENCE
On calibration of modern neural networks
A widely cited paper on the gap between a model’s confidence and its observed correctness.
PROVENANCE / STANDARD
C2PA specification
The technical standard behind signed assertions about the origin and editing history of digital content.
GOVERNANCE / FRAMEWORK
NIST AI Risk Management Framework
A practical framework for governing, mapping, measuring, and managing AI risk.
POLICY / PRINCIPLES
OECD AI Principles
International principles for AI that is transparent, robust, accountable, and centered on people.