Bias Testing and Fairness Audits for AI Systems: A Practical Guide
Bias testing is no longer optional. Learn the three types of AI bias, proven fairness metrics, when to audit, and what documentation regulators expect.
Practical guidance on data governance, AI governance, software architecture, and the future of agentic AI development. Written by Joshua Garza.
Bias testing is no longer optional. Learn the three types of AI bias, proven fairness metrics, when to audit, and what documentation regulators expect.
You cannot govern what you have not inventoried. Learn how to build a defensible AI system inventory, classify risk tiers aligned with the EU AI Act, and maintain the registry as a living governance document.
Maturity assessments, policy development, stewardship, data quality culture
EU AI Act, NIST AI RMF, AI system inventory, bias testing, compliance
Technical debt, modernization, microservices, API design, cloud migration
Dark factory principles, scenario-based validation, autonomous agents, Digital Twin environments
Data quality rules, observability, monitoring, SLAs, tools and frameworks
Fractional CTO, data strategy, technology leadership, team building
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