Transparency & Documentation
Model and system cards, datasheets, disclosure of evaluations, and documentation that survives an audit.
7concepts
74flashcards
52minutes of reading
- 01 Datasheets for Datasets The questions a dataset's documentation has to answer for someone deciding whether to use it, why the composition and collection sections carry the weight, and what happens when a dataset outlives the answers.
- 02 Disclosure Without Overclaiming What honest capability communication looks like, why published evaluation numbers mislead by default, and the specific claims that most often outrun their evidence.
- 03 Counterfactual Explanations and Algorithmic Recourse How a counterfactual explanation is computed as a constrained optimisation, why the nearest counterfactual is often the wrong advice once features cause one another, and how recourse breaks when constraints are missing, the model is retrained, or the explanation is gamed.
- 04 Documentation That Survives an Audit The properties that separate documentation an assessor accepts from documentation they discount, why generated beats written, and how to structure a technical file so it stays true as the system changes.
- 05 Explaining a Decision to the Person Affected Why feature attributions are not explanations for a subject, what a counterfactual explanation provides instead, and the gap between technical interpretability and the account a person is owed.
- 06 Local Explanations: LIME, SHAP and Their Limits How the two dominant model-agnostic explainers turn one prediction into feature weights, the axioms that make Shapley values attractive and the sampling that makes KernelSHAP an approximation, and the evidence that both can be unstable, contradictory and deliberately fooled.
- 07 System Cards and Documenting the Whole Pipeline Why documenting a model is insufficient when behaviour is produced by a pipeline, what a system card adds, and how to keep documentation current when the system changes weekly.