I’ve been maniacally busy with an impossible assignment the last few weeks. An hour-long lecture to young scientists dedicated to machine learning (ML), artificial intelligence (AI) and big data (BD) about complexity.
I zoom in on five different forces that together form a social climate (veracity, loyalty, money, coercion and fitness) and try to show that different configurations lead to different climate configurations.
Climate configurations are interpretations of the conditions in which decisions are made. I distinguish individual and collective interpretations. Individual decisions are made against the background of what the decision maker as an individual can do best (in terms of veracity, loyalty, money, coercion and fitness) to survive individually. Collective decisions are made against the background of what the collective (or institution) can do best (in terms of veracity, loyalty, money, coercion and fitness) to survive as a collective.
Een ABCM stramien
I enlist the help of the grid in Fig. 1 to support ABCM-based interpretations of FIG. 2 and FIG. 2a.
It concerns the usual Petri net notation with circles for state of affairs and rectangles for processes or functions. The idea of fig. 1 is that the environment (world/domain) generates situations (SITUATION) that can prompt rationalizing actors to make a plan of action (plan). This process is fed by the decision-maker’s DNA (his subconscious character if it is an individual and its climate if it is a collective) and the valuations (VERACITY, LOYALTY, COERCION/SECURITY, MONEY, FITNESS) that this decision-maker is employing at that moment for making an action plan (PLAN). This can be done in thought (imagine), but also in practice (behave). The result (RESULT) flows back into the environment, which turns it into a situation or a story (STORY) that in turn leads to making plans, etc., etc.
Application to the last year of COVID-19 in China
If these forms of climate play a role, they must be reflected in the ways in which the different forms of policy regarding COVID-19 have emerged. I choose the last year of COVID-19 in the PRC (Fig. 2) as the first target for the application of the grid from Fig. 1.
1.4 billion people live in China. By July 2020, the pandemic was under control and society was open again. For the first 10 months of the past year, fewer than 250 people a day were infected with COVID-19 and less than five died from it. Two months ago there was an uptick in the number of infections and shortly afterwards in the number of deaths. Measures were taken locally and the numbers are back under control. Wikipedia says today:
Relative to other countries, China’s COVID infections and deaths are very low. China is similar to countries such as Taiwan, Australia, New Zealand, and Singapore that have also been very successful in controlling the virus. China’s response involved extensive testing, mask wearing, temperature checks, ventilation, contact tracing, quarantines, isolation of infected people, and heavy restrictions in response to local outbreaks.
I assume the quote is a good representation of what the policy has been in the PRC. So I will use that as a description of the collective decisions in China during that period.
VERACITY then plays a role in the shared realization that COVID-19 is a contagious disease that spreads exponentially without measures and that in many cases leads to unbearable suffering and life-threatening conditions. That’s what the first six months of the pandemic in and around Wuhan have shown, including the lock-down of a metropolis and the construction (and cleaning up shortly after) of sizable emergency hospitals and nursing homes. See FIG. 2a (with a correction in April) for the numbers from that period. Incidentally, veracity is not always a decisive value in the PRC. There are situations (I am thinking of the treatment of medically trained COVID-19 whistleblowers) in which LOYALTY to the ruling party is decisive, in a way that invokes coercion-protected security values, whether or not hypothetical (SECURITY-COERCION). The other measures mentioned in Wikipedia are also considered appropriate in China in terms of the prevailing value climate. China has been able to reopen its society and also its economy in mid-2020 (MONEY) while maintaining a high level of alertness and effective measures against local outbreaks, which often appear to be caused by international passenger traffic. Minimal obstacles to the movement of people and goods and the associated data are necessary conditions for survival in the current world (FITNESS) and require adequate infrastructures and bearable osmotic processes at the borders.
There is a big difference in scale between the numbers in the first and last months in China. In China, the pandemic appears to be under control. There, the policies have not only proven to be effective, they also appear to have been adopted as acceptable (or tolerable).
Elsewhere, I look at the US in a similar way.