Hacker News·3 min read·hard

From Evaluation to Guardrails: What We Brought to ACM FAccT 2026

R
royapakzad
From Evaluation to Guardrails: What We Brought to ACM FAccT 2026
AI Summary

Researchers at the ACM FAccT conference argued that AI guardrails require the same level of rigorous evaluation as the underlying models. They emphasized the need for context-specific and language-specific testing to ensure reliable AI deployment.

At ACM FAccT, we demonstrated why AI guardrails need the same scrutiny as models. Moving from static policies to context- and language-specific evaluations, our hands-on session proved that agentic guardrails equipped with tools like web search are vital for reliable, real-world deployment.

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From Evaluation to Guardrails: What We Brought to ACM FAccT 2026 — Headlinne — headlinne