art with code

2016-12-07

Decision making, part N

(Warning: kooky stuff ahead)

Continuing on the "what's a good decision making system"-thread, here's a vague and incomplete idea that I've been turning over. A system of governance finds a problem to solve, generates a solution to it and implements it. To find a problem, it needs to know about it, which requires information about the state of the governed system and the ability to filter the information to recognize problems. To generate a solution, it needs to generate and evolve several different solutions and pick the best one. To implement the solution, it needs traction in the governed system.

In abstract: sensory information -> problem filter -> problem broadcast -> solution generation -> solution filter -> implementation plan -> implementation broadcast -> implementation.

Gathering sensory information is a [streaming] parallel map pass. The problem filter is a pattern recognizer, maybe a reduction tree of some sort. The problem broadcast make the problem known to solution generators. The solution generation is another parallel map pass, and the solution filter is a tournament. The implementation plan generation is similarly map-reduce, followed by the broadcast to implementers who then get to work.

It's not quite as simple though, as each step requires continuous feedback loops to optimize the implementation. Some parts of the problem are only found out at implementation time and the solution and plan need to evolve with the problem.

One anecdote from AI is that the quality of your algorithm is secondary to the amount of data you have. So you want the map passes gather as much data as possible and have a reduction network on top to do the filtering. The quality of a working reduction network is less important than the width of the gather pass. And I guess the reduction network functions the better the larger part of the population it involves.

In sports the best results are within an order of magnitude from average results. Maybe the same is true for intellectual pursuits: the world's best dictator may work as well or better than a parallelized council of ten average ministers, but a lot worse than a couple hundred average ministers, never mind a few dozen million.

Traction. For an implementation to actually get done, there needs to be buy-in among the implementers. For that the implementers need to be involved in figuring out the problem, solution and the implementation plan. To fix a problem, you need to know what problem you are fixing, otherwise you're just doing random pointless things and can't evolve the solution. Implementation is yet another of those things that benefits a lot from parallelization.

What do reduction networks and voting have to do with each other? Each filtering step needs a decision to be made, decisions need to be informed and informed decisions need a wide base of decision makers to provide the information. So, uh, grab a big part of the population, run the selection by them, go with the majority? Or is there a better way to get the information from the population, get the things that really matter and use that to do the selection?

The problem with small governments is that the smaller a government, the easier it is to bias. Bribery, threats, cronyism, nepotism, lobbying, you name it. Heck, just paying the decision makers an above-average salary is enough to bias the decisions. The problem with large governments is that you're sampling a much noisier pool. Uninformed people are easier to sway with negotiation skill? How does that differ from swaying a small amount of a bit differently uninformed people (i.e. MPs)? The republic battle-cry is "against mob rule!", but is it just a smaller mob that rules in a republic? Does a system that uses a small amount of elected lawyers do a better job at solving problems than a system that uses the whole population?

How do you filter out flagrantly anti-minority decisions? What's the threshold in the ratio between majority advantage and minority disadvantage. How do the current systems guard against that? Make the decision making body small enough to be outnumbered by the relevant minorities? But they also have guards and all this force boosting going on... demonstrations by thousands seem to have very little effect even on single parties, much less the whole government.

(Yes, there is a threshold in majority:minority-decisions: murder is outlawed, no? Much to the chagrin of the murder society. More controversial are decisions such as not providing street signs in every language of the world. It would be good to have that, and it is making the life more difficult for a significant part of the population, but currently the benefit is too low compared to the cost. So we compromise by having English signs at the airports, Swedish signs at most places in the south and west, Russian signs at shops in border towns, Japanese signs at Helsinki design shops and so on.)

The anti-democracy strawman usually goes like this: Suppose you have a vote that devolves into a nasty argument. In the next session, the winners of the previous vote propose hanging the losers of the previous vote. Continue until you have only two people left. Now, why don't we see that in parliaments? Surely the ruling party votes to have the opposition parties and their supporters shot. All the way until you have two MPs left, one stabs the other and declares himself emperor. .. Oh wait, that does actually happen. How do you avoid this kind of thing?

How do governments go wrong? By wrong here I mean something like "does not implement policies in the interest of the population". In other words, the governmental idea of good policy diverges from the population's idea of good policy. Or is it from the population's benefit? Does good policy do good or is it merely something seen to be good. How do you pass "bitter pill"-policies if everyone making the decision will take a short-term loss for a long-term gain. Same way as we do now?

The goal of a system of governance is to implement policies that are beneficial to the population. When a system benefits a sub-group disproportionally, the system is biased. When a system is generating policies worse than best known, it is uninformed. When a system can't implement the generated policies effectively, it lacks traction. A system of governance should strive to be unbiased, informed and popular.

To be unbiased, the system should be unbiased from the start and the cost of biasing the system should be high enough to be prohibitive. For the system to be unbiased, the individual actors in the system need to be close to an unmodified representative sample of the population. For the cost of biasing to be prohibitive, the number of individual actors in the system times the average cost of biasing an actor should be as high as possible.

To be informed, the system needs information. The more relevant information the system has, the better decisions it can make. Find fixable problems, find good solutions, find good implementation plans, refine through attempts at implementation. Each step requires a lot of sensory data and processing. To maximize the sensory input of the system, you need to maximize the number of sensors times the power of the sensor. Similarly, the processing power of the system is the number of processors times the power of each processor.
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