Trying to develop a simple math model for the
most recent events in western democracies I took some findings in neurosciences
(e.g. psychology of moral) as a set of
statistical links between variables. Specifically, there is a book “The Righteous Mind: Why Good People are
Divided by Politics and Religion” (2012) written by J. Haidt, which stresses the
importance of fairness for both conservative and liberal minds (in sense of
moral prejudice). All people have own understanding of fairness, having some
core values, however. It was also found that people cooperate much better when
unfairness in cooperation is punished. When free-riders pay for the absence of
fair behavior for other participants (it is not the absence of fairness for the
free riders but rather fair-not-ness for the others). The whole ensemble of current
fairness/unfairness judgements in the entire population defines net morality in
the society. Majority is always around the net value. However, extreme
deviations from this net value can be large and such people are most interested
in shifting the equilibrium to their side (e.g., preachers, hippie, priests,
criminals, etc.). They all proved to be able to influence individuals and
groups shifting moral norms, including the understanding of personal and
universal fairness. These are examples of inherent moral influence because such
preachers do believe in their versions of fairness.
Another category of people
trying to change the net value of moral judgements at large and using the
outcome of such shifting is politicians. One can look at the map of the most recent
elections in Austria or in the USA, or any other western country, and observe
the distribution of moral predominance in big cities and the rest. It looks
like that the whole territory is covered by the same color. And this is usually
not the color of the winning party (except the USA). This is great division between conservative
and liberal moral, both are intrinsic to people (at least, it is my
interpretation of the Haidt’s book). For us, the most important is that this
division is dynamic and subject to influence of propaganda (in Bernays terms). We
suggest that such influence and dynamics are not random and can be described by
simple mathematical model based on laws stationary evolution of an ensemble
under endogenous and exogenous forces.
Now, we get back to
free riders. One part of population considers another part as free riders on
average in terms that they obtain more than deserved in a not fair way. The
outcome is simple – the absence of cooperation with the other part and
cooperation enhancement within the same moral norms group. The division has
been growing with time together with the growth in economic (and likely social)
inequality. Trump got it (as well as right-wing politicians in Europe) first
and sent to the conservative part of population a message that unfairness will
be punished (make the US great again!) This is direct message which actually
make two major effects – increasing cooperation in both liberal and
conservative cores of population and increasing deviations of the average conservative
and liberal understanding of fairness from the net value.
We develop a math model
of moral evolution, which includes the intrinsic (basic) and current
distribution of fairness understanding, the dynamic development under endogenous
(and likely exogenous in satellite countries of Western Europe) forces depending
on the evolution of economic (income) inequality observed during the past 30 to
50 years. The latter is described by the evolution of Gini ratio, the share of
labor in GDP (GDI) and the mean personal income. The sensitivity of a person to
external influence is also distributed over the population and depends on the
intensity of external influence. In other words, increasing economic inequality
made many people to feel unfairness and become more sensitive to external
propaganda which, in turn, makes people more sensitive on average.
