Dark data is for governing a simulation
My previous post outlines the ideas I have about a fantasy government of data and urgency as it relates to the COVID19 situation. Here, I want to contrast different approaches to governing.
COVID19: eventually there will only be survivors
The current government’s obsession over the absolute numbers ignores the fact that when this is over, these casualties will only be numbers. In the future, our government will have to contend with the remaining survivors. At that time, the survivors will judge the government’s wisdom in prioritizing dark data over the observations available to it.
Darkening data to please the government
The dark data observations are actually assertions that the present world obeys the expectations for how the world operates according to very small number of people’s (often just one) understanding. This presents the opportunity for those same individuals to force the simulated world to the way that best conforms to their wishes. No one else will know whether the tests are for actual science or for some agenda.
Urgency is foundational
I believe our ancestors approach science-guidance very differently. I believe this came from there being a culture that encouraged everyone to participate in the practice of science and collect of new evidence that undermines old science. This older culture is similar to the automated government of data and urgency. The automated approach emphasizes data representing recent observations from reliable sensors of objects that are not biased by rules based on preconceptions.
Common sense referees science
The science for how to deal with COVID19 is clear, and it clearly goes against all common sense. This may be a time when the best response to scientific recommendation is to dismiss it as ridiculous.
Dark data betrays bright data
The current democratic government is run by politicians, bureaucrats, and electorate who all are gaslighted into distrusting their own observations that disprove the original explanations and projections. We need to ignore what we are seeing and continue on the original plan because it was based on infallible science, science we know is proven because we can replicate the experiments that prove it.
Holding dark data accountable
The biggest failing of science in the current COVID situation is its inability to react to new evidence that its original conclusions were wrongly decided, and the assurances to governments were incompetent. We implicitly accept that any initial science-based decisions attains some law-like status that is automatically presumed to be true until there is overwhelming evidence that it is wrong. In particular, such decision making does not permit a simple apology for making a mistake following new data that clearly disproves the original science.
The risk of remembering the past
For COVID19 crisis, remembering the relevant past includes remembering the lessons of the 1918 pandemic. What exactly are we supposed to learn from this past? A lot of people lost their lives prematurely due to lack of government shutdown of local commerce. A decade of widespread enjoyment of good living occurred because the government did not interfere with the economy in its response to the pandemic.
Pandemic of Dark Data
Perhaps the real agent behind this pandemic is science itself. Given a sufficiently dire circumstance, science can shut down our natural defenses of critically thinking about observations we can clearly see. Science tells us that if this is the disease it warned us would come, then we have no choice but place all trust on science at the expense of paying attention to what we are seeing.
COVID19: Optimal New Case Rate
The difference between my fantasy government and the current governments is that my fantasy government reassesses the urgency after the first month of lock down. The population likely will be not as alarmed by the condition especially when they see that the system is not being as overwhelmed as first feared. The government by data and urgency may find that there is no longer an urgency among the population. This is how it arrives at the conclusion that the current levels of new cases (far from zero) are tolerable for the time being.
Hypothesis Discovery 