Using Process to restore integrity to the system.
There are two main forms of reasoning. Inductive reasoning and deductive reasoning. To use them well they need to be incorporated into processes, formalized into institutions and then employed.
What is a Deductive Reasoning
At the risk of oversimplifying, deductive processes use deductive reasoning:
"Deductive reasoning is a logical process in which a conclusion is based on the concordance of multiple premises that are generally assumed to be true."
What are the risks of Deductive Reasoning?
Deductive reasoning frequently results in formal fallacies (due to misapplication of logic) and in fallacies due to faulty premises. Thus for deductive reasoning to be refined and validated the premises of the deduction have to be tested.
Deductive Process
Thus a Deductive Process needs to things, one is that it's formal logic be defined (and modeled) to identify "formal fallacies" and avoid conclusions that don't follow their premises and faulty premises. Then even if the logic seems to be unassailable the premises still have to be examined. Deductive process works through an iterative process of detailing from abstract theory.
Inductive reasoning and Inductive process
Inductive reasoning:
" Inductive reasoning makes broad generalizations from specific observations."
This article explains it better than most:
"Inductive reasoning works the other way, moving from specific observations to broader generalizations and theories. Informally, we sometimes call this a "bottom up" approach (please note that it's "bottom up" and not "bottoms up" which is the kind of thing the bartender says to customers when he's trying to close for the night!). In inductive reasoning, we begin with specific observations and measures, begin to detect patterns and regularities, formulate some tentative hypotheses that we can explore, and finally end up developing some general conclusions or theories." [http://www.socialresearchmethods.net/kb/dedind.php]
Induction and Deduction must be used together
Some people like to pit inductive reasoning against deductive reasoning as if one method were superior to the other. But both are necessary to process success. And both kinds of reasonings have risks. Abstract theories are generalized from observations, experimentation and sometimes inspiration based on those. There is no deduction without induction. One can come up with faulty theories even if the theory seems to explain the observations. There is no science without verification, validation and refinement processes
Scientists of the Euro-American Gold age got around the dangers of logical trap fallacies by using extensive experimentation and testing to verify, refine and validate hypothesii. As we've moved into a more gilded age, even some of the process improvement people have forgotten about the role of "refining" models. There is a rush to get them to the market as fast as possible, that just doesn't work. Even as hucksters continue to talk about Verification and Validation, while the feedback loop is still drawn, it's not in their minds. In the rush to move science to production the role of experimentation in refining efforts gets forgotten. Experimentation isn't just for verification and validation. It is also for refining the requirements for functionality, and refining one's understanding of what one is looking at. A lot has been dumped in the privateering rush to privatize science and try to make riches. Good process has been one of them. The reason that practical engineers did extensive testing is that science is built on failure. And it's not right to test concepts with train wrecks using live Guinea Pigs. That was a lesson learned through many train wrecks in the early days of train building.
Deductive reasoning has to be tested through inductive processes. And inductive processes are the source for general principles and lessons needed to make progress. The moment a new idea comes along, if the idea contradicts some established theory it tends to get rejected unless there is testing and validation and some "bottom up" means to bring the idea to the attention of the theoreticians.
Governing as the use of Inductive and Deductive processes in Concert.
In requirements we talk about "Bottom up" and "top down." Good requirements has both bottom up inductive processes and top down deductive processes. Requirements have to be fleshed out using engineering principles and iterative experimentation. I want a vehicle for getting from one continent to another. How do I do it? I can do it over the ocean in a boat. But there are constraints on the speed of a boat. The concept may be top down, but now we have a process of discovery. It took 400+ years of failure and experimentation to get boats that could travel at top speeds greater than 10 knots. At 10 knots Europe ruled the world, But ships have never been good at mastering more than 30 knots safely.
But now I want my trip to be fast. For faster speeds you need something that can move over oceans through the air. That is called flying. How do you make something fly? Observation suggested we could do it with wings like birds. It took 1400 years before anyone could figure out how to do that successfully and demonstrate it. It took 50 years before flying was safe. Years of failure and experimentation. My Grandfather perished in 1938 while flying a PB-Y. He was a Pilot, so between the inherent dangers of flying an immature technology and the looming Great War, his odds were 50/50 of making it 5 years after he graduated the Academy. For space shuttle pilots the odds were a little better. That they only had two catastrophic failures showed that they took risk seriously. Risk is part of life. The purpose of science is to use tools that can keep one eye open when humans/sentient beings are walking the cliffs and valleys that make it up.
Process models understand this. They build Deductive process models and Inductive process models, and they use both. These models are useful for trying to understand and predict behaviors. Scientists are trying to use create artificial intelligence using deductive and inductive models. I'd like to see them used for improving the natural intelligence of our governing processes and society. Seeking artificial intelligence is kind of useless unless it is part of improving our own intelligence. Some people are so frustrated with the messy, poor processes they live with they concentrate on building AIs in ivory towers. We fear "Skynet" because we know there is something wrong with our use of intelligence.
We need to use Deductive Processes and Inductive Processes to systematically govern ourselves as societies and a world.
Good Government as acknowledging the value of and employing both Inductive and Deductive Processes.
It hit me a long time ago (before 2010) that the value of Enlightened ideas is is in enlightened processes and enlightened requirements and constraints. If the AI and process people could design an ideal government Democracy probably wouldn't come to mind first, but if they were tasked to apply the principles of Inductive reasoning and deductive reasoning to a business process model for governing a society using these principles -- they'd come up with a Democratic system. This is because top down processes are faulty without verification, validation and refining processes -- Inductive process. And Bottom up processes are faulty without generalization, standardization and requirements. Which are deductive processes.
Democratic representation is (or should be) an inductive process. Local Direct Democracy is in your general assemblies, in accepting feedback from workers. In letting them choose representatives. Workers are your best testers and validators for concept. Oppressive and tyrannical process is also bad and dysfunctional process. Good representation hears all voices because the best way to avoid conflict is to find out what issues are and solve them, rather than exploiting them for pyramid games. The point is that a functional Representative Republic is also good governing process that employs inductive and deductive products to feedback for success.
Boss types want to believe their general theories are valid "a priori" but in real life most governing theory rests on shifting sand. What works strategically at one moment may fail as conditions react to that strategy. Thus good government requires continual feedback, and sometimes a changing of the guard. But for now:
More to come
Further Reading
Article:
I'm not citing the dictionary as I used several and forgot which I quoted from.
http://onlinelibrary.wiley.com/doi/10.1111/j.1756-8765.2009.01050.x/epdf
Modeling Design Processes: [http://www.aaai.org/ojs/index.php/aimagazine/article/view/855/773]
Inductive Reasoning
http://www.livescience.com/21569-deduction-vs-induction.html
This article is just as fallacious:
http://www.iep.utm.edu/ded-ind/
Deduction and induction were defined thousands of years ago, and they try to invent new definitions and claim the old ones are somehow invalid because they invented new ones. Mathematical induction is the definition of inductive reasoning.
Very Good:
http://www.socialresearchmethods.net/kb/dedind.php
Notes
Process improvement people have been looking at the processes of management for some time. And it hit me during a very boring (because I was being lectured on a subject I'd already studied ad nauseum) training session on process improvement that I hadn't seen much of that applied to governing. So I started looking at the subject, all the while hoping that I'd find some thinker who'd already covered parts of it so I wouldn't have to reinvent the wheel. By looking at the process of government as a system with a series of processes that need to be systematized. One can apply the process improvement ideas of the Golden Age of Euro-American Science to Government. For example, when looking at the Federalist Papers and the Anti-Federalist papers, and other philosophical writings of the 18th century and early 19th century the philosophers and "social-scientists" were grasping at engineering models that would use tools not that different from the process diagrams used to describe requirements, or airplane acquisition, etc... Consequently I've been consciously and subconsciously at work on this since 2010. But the first step was to re-read the writings with that in mind. I found some of the concepts I was looking for in Artificial Intelligence thinking, which is mostly the product of engineers trying to architect the ideas of some brilliant science fiction writers and scientists, so it shouldn't be surprising.
