Greg Twemlow explores the critical need for a parallel trust protocol that captures the reasoning process behind decisions made by both humans and machines. He argues that modern software and education systems suffer from a structural flaw by prioritising final outputs while discarding the logic and context that produced them. To address this, Twemlow introduces the Context & Critique Rule™, a framework designed to slow down interactions and foster human agency through a visible decision trace. This human-centric approach mirrors the emerging Context Graph technology in Silicon Valley, which aims to make AI agents more explainable and less brittle. By transforming the "black box" of technology into a "glass box" of transparency, we can audit cognitive biases and ensure accountability. Ultimately, the source suggests that the true value in an AI-driven world lies in understanding the path to a conclusion rather than just the result itself. Read the article.

About the Author - Greg Twemlow writes and teaches at the intersection of technology, education, and human judgment. He works with educators and businesses to make AI explainable and assessable in classrooms and boardrooms — to ensure AI users show their process and own their decisions. His cognition protocol, the Context & Critique Rule™, is built on a three-step process: Evidence → Cognition → Discernment — a bridge from what’s scattered to what’s chosen. Context & Critique → Accountable AI™. © 2025 Greg Twemlow. “Context & Critique → Accountable AI” and “Context & Critique Rule” are unregistered trademarks (™).