examples-audit

Analyzing mock data for cultural bias involves evaluating test datasets and documentation to reveal hidden patterns that privilege a default user group. This surfaces inclusivity gaps related to holidays, food, family, and payment cues.

Inclusive design analysis for seed data evaluates cultural assumptions across product examples to ensure diverse representation. It generates a structured report highlighting exclusions and recommending improvements for broader accessibility.

Analyzing documentation for inclusivity gaps involves reviewing seed data and examples to detect default user patterns. This yields a structured diversity report detailing cultural assumptions and providing recommendations for more inclusive content.

Yes, you can use an optional inclusion configuration file to guide cultural bias audits on project data. The analysis requires access to project data and reads configuration settings to output a structured diversity report.

Auditing examples for diversity evaluates specific cultural cues like holidays, food, locations, payment methods, and family structures across data samples. This identifies patterns reflecting a default user and highlights inclusivity gaps.