What controls help prevent AI bias?

Controls to prevent AI bias include diverse and representative training data, pre-deployment bias testing across demographic groups, ongoing output monitoring for statistical disparities, documented model cards describing training data and known limitations, human-in-the-loop review for high-stakes decisions, and third-party audits for high-risk AI applications. The SCF AI governance domain includes bias monitoring and fairness controls aligned to the NIST AI RMF.