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On the Government and the Theory of Democracy

With Republicans opposed to modern government, it’s worth understanding the basic mechanism of democracy.

Before elected government, there were still governments. In many places it was by the wealthy, by the church, by divine right and that was the only right. There, law was based on status—blood and force and prophecy of who could pull a sword from a stone.

And then came the idea of natural rights, that everyone should be treated with a certain respect because we are alive and that is enough status by itself.

When we speak of democracy, we’re talking about a sophisticated cycle:

  1. People choose their government.
  2. The government performs for a time.
  3. People reevaluate and repeat step 1.

This kernel of scientific government is essential to progress and to maintaining a functioning society. It attempts to strike a balance between unfettered change and conserving the old. It sets a cadence, it gives a ritual, it provides a path forward.

Those who stand in opposition to democracy are standing opposed to the basic educational loop by which we can improve society. They propose something like:

  1. People don’t choose their government. The government is whoever can grab the reins and kick everyone else off.
  2. The government does whatever the fuck it wants. (To be fair, it could be good, but if it isn’t there’s no recourse.)
  3. Ashes, ashes. We all fall down.

Then, maybe, the survivors build something out of those ashes.

But the tried-and-true loop of democratic government is superior, adaptable, dependable. Only it has a flaw. Its flaw is that we have to give up our power and we have to trust that the people will make good decisions over time. Not every time, but that on average the decisions will be better than a dictator’s, better than a business’, and better than any minority interest of any kind, religious, ethnic, whatever.

And that requires the people have a say. But there are those who are afraid of what we have to say to each other. On both sides.

Many fear the racism, the batshit conspiracy, the anti-religious zealotry of so-called Christians. Others fear the cancel culture, the spectre of communism arising from greater social welfare programs, and culture that’s not aligned with their values or tastes.

But that’s society, and that’s what we have to work with. Fear. That we might fuck it all up, and ruin it all, and be left with ashes. But, for all the resistance to Donald John Trump, the conservatives of this country have not admitted that America trusted and allowed for such a grave mistake. We afforded this ruin, including thousands upon thousands who have given up their lives to a virus that this supposed leader did not prepare to act against and that he has largely neglected to manage.

We know our lives may be lost to blunders of impetuosity by our fellow citizens, but we still believe in the cause that over time, on average, we will do better by voting, by choosing. That the flaw that allowed Donald John Trump to exist as a candidate, and then as an elected president, is the same flaw that makes our system work at all. That yes, we can fuck it all up. But no, we do not want to fuck it up, and we will strive to learn the lessons and avoid the mistakes and purge the corruption and right the ship and sail into the bloody sunset!

Anyhoo. The election is in ten short weeks.

How High Should Taxes Be?

We should adjust tax rates over time to dial them in.

70% on the ten-million-and-first dollar? A wealth tax? How high should we tax the wealthy?

First, why do we tax at all? The theory of taxation is that, contrary to those who call it theft, taxation is payment of debt. By virtue of the services rendered, the tax is how the services are paid for. Larger earners, conducting more commercial activity, using more of the legal system, shipping inspection, and so forth, are to pay a higher percentage due to their higher rewards and higher use.

Economists get into the effects of tax more than the reasons for it, or the fairness of it. Things like the Laffer Curve are drawn up, to theorize that taxation matters a lot and that government revenue can be equal at very different places along the curve, while private spending and overall economy can be very different. Politically-embedded economists thus focus on an apolitical, theoretical system to make a political argument.

But the woman waiting for a bus to take her to her minimum-wage job isn’t rewarded by such abstractions. She knows that the nominal rate and the effective rate are about the same for her, while they are a Grand Canyon apart for those who can afford a team of accountants. She knows that she could pay 100% of her whole life’s wages and never pay as much as some of the wealthiest should in a single year.

None of which answers the question of how high taxes should be. The ultimate answer to that query is that nobody knows, and unfortunately, we’re not planning to find out. The answer to how high taxes should be is that we should adjust them continuously, and find out based on the experimentation. That we have the knowledge and ability to do so, we lack only the political will.

For example, we could start with the current tax rates, and make half-point adjustments to all brackets, or add new brackets and adjust those too. As long as the timing is regular and the adjustments are gradual, we can account for a lot of the noise. As long as we are willing to tweak the rates based on current conditions, lowering taxes in recessionary times, raising them in times of health, the slow and methodical march of the tax rates could yield us with something better than arguing will.

The interest rate already works this way. Is it not time for the tax rate to join it?

Pruitt’s Data Rule and Deep Learning

(Soon-to-be former?) head of the EPA Pruitt has proposed a public data rule (RIN 2080-AA14). This could be a good rule, but it really depends on the implementation. This post focuses, briefly, on the implication for deep learning science in such a rule.

Briefly, deep learning takes normalized, record-based data and creates a mapping from input data to some per-record output determination.

Think of a phone book (the data) with individual listings (the records) and then some determination you want to do on those records. It could be something very simple (last name has n vowels) or something complicated.

The data itself may be public, but depending on the implementation of the proposed rule, making this secondary data public in any meaningful sense may be very difficult.

There are several challenges. One is simply the amount of records that may be used. Another is the trained network may be proprietary or non-portable or even dependent on custom hardware. There may also be situations where several neural networks act in tandem, each derived from a bulk of training data (some of which may itself be output from other networks), which would further complicate the data access requirements.

But there is also the question of whether the output would be public, even if published. Normally data is public when the individual measurements are available and the methodology behind those measurements is known. But there is a reasonable and inevitable blindness to the internal workings of deep learning. Trying to explain the exact function the machine has derived is increasingly difficult as complexity increases, and even if all the inputs and outputs are public, the transition function may be obscure.

Which isn’t to say that data, methods, and findings should not be replicated, peer reviewed, and subject to introspection. The EPA should, for example, draw a stricter line against carbon fuel companies and other chemical companies, requiring that more of their filings be public.

In the case of deep learning, not for the EPA’s sake, but for the sake of science itself, better rules for how to replicate and make available data and findings are needed.

Others have already pointed out the difficulty of studies predicated on sensitive personal data like medical records. But there is a general need to solve that problem as well, as the inability to examine such information may block important findings from surfacing.

This is similar to the fight over minors buying e-cigarettes online: opponents of e-cigarettes act as though there is a particular, nefarious plot by vendors, but we do not have anything close to a universal age verification system. Better to develop one for all the tasks that require it.

And so it is with the EPA rule: Congress should draft a law that allows all scientific data used by the government to be as public as is possible.