Fairness — Patterns

The Fairness pillar focuses on accessibility, AI ethics, human oversight, bias mitigation, and equitable design, so solutions serve all users fairly. These patterns turn the pillar’s design principles into concrete, reviewable practices: what to look for in a solution, what good looks like, and the anti-patterns that undermine it.

These patterns put the Fairness pillar’s design principles into practice. The principles inform architecture decisions, but they don’t produce fair outcomes on their own — read them alongside the Fairness pillar for the full guidance behind each one.

  • Design for Lightning accessibility patterns — build with SLDS and standard Lightning Web Components vetted for WCAG 2.2 AA, and validate any custom component through assistive technology testing.
  • Reduce and monitor bias with the right tools for each model type — validate model outputs for equitable outcomes before deployment and continuously in production, using the instrumentation suited to each model type.
  • Leverage Shield Platform Encryption for data protection controls — protect sensitive attributes and route Event Monitoring logs to a SIEM for tamper-evident audit trails.
  • Design review workflows for high-stakes predictions — configure approval processes and confidence thresholds so consequential predictions receive appropriate human review.
  • Apply Organization-Wide Defaults (OWD) and Field-Level Security (FLS) for non-discrimination — restrict access by default and grant only what each role needs, avoiding exposure of sensitive attributes.
  • Enable user agency through platform consent — track granular AI consent per use case and let users opt out of AI-driven features with human alternatives when possible.

Each category pairs patterns (what good looks like) with anti-patterns (what to avoid), organized so you can review a solution area by area. Start from the fairness outcome you need:

  • Making the experience usable by everyone? Use Accessibility for WCAG compliance, assistive technology support, and inclusive design.
  • Building responsible, equitable AI? Use AI Ethics for bias mitigation, fairness metrics, human oversight, non-discrimination, and consent.
  • Operating agents in production? Use Agentic Patterns for bias detection, transparent AI, and equitable agent behavior.

Patterns for WCAG compliance, assistive technology support, inclusive design, and accessible user experiences.

Fairness patterns for agentic systems including bias detection, transparent AI, and equitable agent behavior.

Patterns for ethical AI development, bias mitigation, fairness metrics, human oversight, non-discrimination, consent, and responsible AI practices.