We are a company built on the conviction that understanding is the most valuable, and least measured, capability of the next century.

A note from Manny.

We are living at the start of what is likely the most important scientific and technological moment in human history. The full scope of the transformative possibility of artificial intelligence is beyond our comprehension. So are many of the potential risks.

Whether we benefit from the possibilities, or fall victim to the risks, depends on how we use the tools we are now building. Will we use them to elevate, educate, and enlighten ourselves? Or instead use them to pacify, overwhelm, invalidate, and ultimately replace ourselves?

It's hard to say whether these statements are overly-dramatic, or not nearly alarmist enough.

What I can confidently say is that the work we are doing at ELEMENT is being pursued in service of a vision of the future in which the rise of the machines will be synonymous with the rise of the people.

As AI takes on more of the work that matters, the ability to evaluate, critique, direct, and inform AI systems is quickly becoming the single most important skill a person can have. ELEMENT's mission is to accurately measure how deeply a person understands any given topic. That depth of understanding is the very thing that determines whether someone can work alongside AI systems in a way that elevates both the human and the AI.

On a personal note, ELEMENT's mission is a convergence of three threads I have spent the majority of my adult intellectual life pulling on. During my time as a graduate student of mathematical logic, I became preoccupied with the question of what understanding actually is, and whether it could be given a formal account. As a young professor I experienced first-hand that the most reliable instrument for measuring understanding is a careful conversation, and that no traditional test has ever come close. As a writer and producer of science media, I spent years working to make complex ideas digestible to broad audiences, which was its own training in the difference between knowledge that can be recited, and knowledge that has been integrated so deeply that it transforms the mind it inhabits.

For most of two decades these threads ran in parallel without me recognizing where they were headed, or how they might converge. The arrival of large language models is what brought them together. Here, finally, was a technology capable of conducting careful conversation at scale. A bridge between rigorous formality and dynamic adaptability. A tool that made it possible to take the oldest method of inquiry humanity has, the Socratic dialogue, and reimagine it as an AI-powered analytical tool. ELEMENT is what comes of that synthesis: a system for measuring understanding by conversing and listening, conducted by AI that has been carefully calibrated to know what to listen for.

A tool that can accurately measure expertise in an individual is a very useful thing, but the long-term ambition for our work at ELEMENT is something much grander. Imagine an atlas of human comprehension; an ever-evolving cosmos of interconnected constellations of expertise which can be tapped into for insights, ideas, guidance, critiques, and real-time solutions.

Such a mapping would allow for individuals' skill-sets, knowledge-bases, and unique ways of thinking to be called upon for the tasks, roles, and projects where they can provide the most help. Such a mapping would transform how we approach not just hiring or enterprise, but also education, scientific research, creative collaboration, and any field or endeavor that involves leveraging the skills and know-how of a group.

The future we are working toward is not only closer to a true meritocracy, but also one in which artificial intelligence does not replace or diminish us, but instead helps us better understand ourselves.

If any of this resonates, or if you have spent serious time working on related ideas (toward a theory of understanding, on new modes of assessment, or on conceptual mappings of knowledge and expertise across populations), I would like to hear from you.