The Trust Crisis in AI: Why Citations Are the Only Currency That Matters

Generative AI has a lying problem. And for government, that's not just a bug—it's a liability.

Recent trials in the public sector have exposed the dangers of "black box" models. When a chatbot hallucinates a policy that doesn't exist, it erodes decades of public trust in seconds. We are in the middle of a trust crisis.

The "Black Box" Problem

Standard LLMs are probabilistic engines. They predict the next word, not the truth. Without a grounding mechanism, they are prone to confident fabrication. For a policy researcher writing a brief for a Minister, a 99% accurate answer is still a 100% failure if the 1% error misrepresents legislation.

Provenance as the New Standard

The solution isn't "better prompting"; it's verified provenance. This is why cited answers AI is becoming the non-negotiable standard for professional knowledge work.

True Verified AI operates on a simple principle: If it's not in the source text, it doesn't exist.

When Answerable generates a response, it doesn't just invent text. It retrieves specific chunks of your verified reports, synthesizes them, and footnotes every single claim. It allows you to audit the machine. If the AI claims "housing targets have increased by 15%," you can click the citation and see the exact table in your 2024 Housing Strategy report.

In high-stakes environments, trust is binary. You either have it, or you don't. Citations are the bridge back to reality.