The Evolution of Science, Society, and Policy Engineering
A big problem with data is that it takes time, energy, and resources to accumulate and acquire. This is easier to do in the “hard” sciences where things are done in laboratory conditions over relatively short periods of time. In the social sciences, data collection can take years or decades and has to be done in the fuzzy conditions of the real world or in a simplified world that may or may not be accurate in a computer program.
The first step to making our government operate more effectively and efficiently is to make a conscientious and sustained effort to ethically and effectively collect data. The next step is to synthesize and analyze the data to tell a story about how things work in our human societies. The third step, and I think, the most difficult step, is to actually use the data to achieve better results in our human societies and across human societies. To do this, we must sacrifice our old notions of how things are and how things ought to work in an endless stream of refinement and bias smashing until we recognize the universe, ourselves, and our places in it for what they really are.
We were at this same place once before, way back in the Renaissance when Western civilization rediscovered, refined, enhanced, and built upon the awareness and knowledge of medicine. We can infer causal relations amongst aspects of the social system, just as we learned about the human body. However complex and interconnected societies and parts of society may be, it is incorrect to say that it is impossible to figure the age old problems of societies, economies, and environments, even if we may not presently have the statistical techniques or software to do so at the present time. We can either invest in this new research now and implement what we can ethically implement at this time to help ourselves, or we can wallow in the willful ignorance of the past, consuming planet and society in the pursuit of wealth and relative power that is not real and is not being used well anyway.
Policy making is a science; politicking is an art. The former serves as the root for the latter, even though the former is effectively impotent without the latter. Politicking without grounding in the science of policy engineering and compassionate care will always only backfire on those who are exercising their technical abilities to politick. Policy engineering, however, needs to be wrapped in the garments of effective and appealing politicking in order to be preserved, implemented, and expanded.
Tags: big data, change, choice, civilization, complexity, complexity science, computer program, conflict, culture, Data, econometrics, economics, economy, environment, Environmental science, governing, hard science, Medicine, policy, policy engineering, renaissance, Research, science, Social science, society, statistics, stats, technology
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