Dana Edwards

Background

A long arc through governance, philosophy, and verification.

The same question runs through all of it: how do you use computation to reduce involuntary ignorance and improve the quality of governance? It starts in intelligence augmentation, moves through network states and autonomous agents, and arrives at proof-carrying systems where rules are enforced by construction, not by trust.

In 2015, I argued that cognitive bias, bounded rationality, and information asymmetry cause involuntary errors in human decision-making, and that intelligence augmentation could mediate them. In 2017, the Pangea whitepaper introduced Lucy, an autonomous agent designed to evolve into an exocortex. The thread from there to MPRD is direct: a model proposes, deterministic gates decide. The rules are the constitution, and the proof is the check. I build systems you can check, not just trust. Formal methods is one way I do that. It's not the only way.

The exocortex concept evolved from Ray Kurzweil's work on brain augmentation. I took that idea and built on it: a wisdom engine, a search engine but for decision support. The problem it was designed to solve was involuntary ignorance. For democracy to produce better governance, you need a wiser, more informed voter, a wiser lawmaker, and smarter institutions. Lucy was a prototype for what we now see with modern AI assistants, but its role was to empower each network citizen, not unlike what Sam Altman later described as "building a brain for the world" that is "extremely personalized and easy for everyone to use."

Sam Altman, "The Gentle Singularity", the parallel to Lucy, seven years later.

Influences

Two works shaped my thinking on technological unemployment and intelligence augmentation. I. J. Good's 1965 paper framed the stakes: if an ultraintelligent machine can design better machines, human intelligence is left behind. James Albus's Path to a Better World showed that automation need not produce mass poverty if the economic surplus is distributed intelligently. From Albus and Good, I developed two ideas over a decade ago: a Citizen's Income and a Citizen's Dividend, the latter modeled on the Alaska Permanent Fund. These were philosopher-level discussions in 2013; they are mainstream political discourse now. The thread from there to MPRD is the same: if automation changes who can act, governance must change how action is constrained.

"Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of such machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make."

I. J. Good, Speculations Concerning the First Ultraintelligent Machine (1965)

Writing

Tutorials, interactive labs, and one question.

What does it mean to justify a claim about software? Each tutorial starts with a concrete picture, then tightens into a model tools can manipulate. The labs turn abstract claims into something visible.

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