There comes times when the situation is outside of the navigator’s experience and training. In those times, the old navigator may be incapable of opening his mind to fully pay attention to what is actually happening. Some times call for a younger mind that is learning in real time, absorbing the recent observations with youthful wonderment. Those are usually times of the most severe crises.
This distinction of chores versus tasks has a corrupting influence on work. It is form of the corrupting influence of money because we tie compensation or continued employment to the progress made during tasks. This is different because money is not a factor. Greed is not the cause of the corruption. Instead, it is the corruption of having to justify one’s position. It is the corruption of being gainfully employed. To justify employment, we need to show the gain. Our work has to be important in some larger sense.
The government must quit. Certainly there will be new cases, and new deaths. The rate will fluctuate over time, location, and demographic. The important information is whether the population is tolerating this, and whether they are adapting. To get this information, the government needs to stand down and watch.
I envision a distant time when a dedomenocracy has been operating for multiple generations so it has good data about human responses to crises. That data should tell the algorithm that humans are prone to fear reactions. It will also tell the algorithm that an over protected population lacks the experience of handing real fears.
A dedomenocracy fears nothing while a democracy fears everything. In this context, everything refers to the collective library of scientific knowledge. Nothing refers to the empty space that may harbor plans that we will can only learn by paying close attention to the present, allowing observations to contradict theories we accepted in the past.
There is a benefit to opening our processes to the possibility that the reality may be changing, where the changing is from an evolving intelligence or even from a plethora of competing intelligences that have transitions of power much like our political systems. Admitting dark data into our algorithms blinds us to this possibility, especially when we allow dark data to have priority over observations.
A government by data could consider the observations of iatrogenic complications and deaths. The public’s fear of a virus could grant this government permission to impose some new authoritarian policy that would do something, but that something would exploit the opportunity to improve the future prospects based on all observations of the current world. Such a government would be free to decide to tackle the problem of iatrogenesis instead of the problem of the virus. Fixing the overextension of medicine may ultimately benefit more people than overreacting to a virus that is not as threatening as the population perceived.
In a democracy, the declaration of an emergency is a declaration to freeze science, particularly in those areas that tend to predict the most pessimistic results if nothing is done. I suspect this is inevitable because a democracy selects specific individuals to be leaders, and human leadership demands steadfast determination to see a policy to completion and the install confidence of the population. Given the recent experience, this particular property of democracy raises doubts about a democracy’s ability to handle a new emergency that is inconsistent with established theories and the operational plans based on those theories.
The failure of the modern democratic governments is that none of these fundamental perspectives of the population were debated democratically. The irony is that the democratic government of elected officials presiding over unelected bureaucrats imposed these answers on the population. Instead of assessing the population’s sentiments on these questions, the democratic government cajoled the population into following the science, and to listen to the doctors. The science may be correct, and the doctors may be wise, but they might be answering the wrong questions.
All government funded scientists, whether through salary, contract, or grant, have a conflict of interest when it comes to providing science to support government policies. The strong bias is toward supporting those policies and avoiding any challenge to those policies.