How To Build Effective Technical Guardrails for AI Applications

Technical guardrails provide control and security for AI applications by implementing checks at the data, model, and output layers. At the data layer, essential guardrails include input validation and sanitization, protecting PII data through methods like hashing, and detecting bias by analyzing data distribution. Other data-level checks ensure data timeliness and integrity to prevent hallucinations and maintain model accuracy. Within the model layer, guardrails involve using role-based access control to prevent unauthorized changes and conducting continuous bias audits to correct issues like model overfitting.