One
of the cornerstones of my understanding of global population and
consumption is the mathematical relationship between happiness and
ecological footprint (our individual consumption of ecological
resources). While trying to derive real significance from the
convenient abstraction, I gained insights into how much of the
natural world we can safely use, the purpose and mechanics of the
global economy, and how people's values influence the survival of our
species. Yet still I didn't fully appreciate why it had the form it
did.
In
the mean time, I grappled with the dynamics of human behavior and how
to derive a means of successfully communicating the lessons I was
learning so they could be used to hopefully extend the lifetime of
our species, which my research showed is uncomfortably limited. One
approach was to focus on complexity and how it influences both
comprehension and the completion of basic tasks. I studied the
implications of a general relationship I had discovered in my own
experience between efficiency and the timing of progress in various
activities, including the propagation of error in product development
and messages as represented by my writing and that of others.
I
suspected that task completion might be related to the pace and
nature of global consumption and population growth. While I couldn't
find a close correlation, I did discover that our species is
attempting to use all of the Earth's resources that don't threaten
the planet's ability to meet our basic needs, and we have
historically been doing so in at least four different ways at a speed
that varies with how much we consume.
A
few weeks ago I had the latest of a string of epiphanies that has
marked my research since the beginning. I accepted the possibility
that the timing of consumption might be independent of the timing of
task completion, and sought to generalize how they might fit together
to describe how much resources are consumed during a task. In the
process, I derived
a relationship of the form found between happiness and ecological
footprint. I was then able to apply the generalization, which I came
to call the "happiness approximation" to how happiness has
changed over human history and how it could conceivably change
over a person's lifetime.
As
I studied the consequences of the happiness approximation, I homed in
on the special cases of completion and consumption that involve full
use of resources in the completion of a task, which would be optimum
where resources are limited. A simple statistical simulation showed
that optimum completion averaged out to 76%, and that general
completion had an average of 87%. Averaging those two values produced
the 82% that the happiness relationship had identified as maximum
average happiness for a population (and also happens to be close to
the 80% used as a rule of thumb for realistic completion by project
managers.
The
timing of task completion also rang a bell of familiarity. The
minimum amount of time it takes to complete a task (in the
simulation) is 19, which is close to the 20 years that is the lowest
life expectancy in my historical data (at the earliest year: 10,000
BC). If this correlation is correct, then it is the earliest point in
a person's life that they can achieve 100% happiness, which according
to the simulation only happens in 14% of cases.
I
also modeled a better match to traditional expectations of task
completion time, including something close to achievement of
historical values of happiness and life expectancy in 2015. It never
achieved total or optimum completion, and still took three units of
time to reach maximum consumption, which is what I typically use for
planning purposes (where one unit of time represents best possible
achievement). Only 2% of a general population achieves that or
better, which speaks to how selective an organization must be to
realistically promise such performance; much less than 1% could be
expected to achieve the perfect performance that an organization
might optimistically promise in one unit of time.
