I
am returning to a business concept I have been working on for many months, and
which I have provisionally labelled ‘Energy Ponds’. All that thinking
about new economic solutions for a world haunted by insidious pathogens – no,
not selfie sticks, I am talking about the other one, COVID-19 – pushed me to
revisit fundamentally the concept of Energy Ponds, and you, my readers, you are
my rubber duck.
The
rubber duck (Latin: anas flexilis), also known as bath duck (anas
balneum) is a special semi-aquatic avian species, whose valour I know from
my son, IT engineer by profession. Every now and then, he says, on the phone: ‘Dad,
focus, you are going to be my rubber duck’. The rubber duck is an imaginary
animal. It feeds on discursive waters. You talk to it in order to get your own
thoughts straight. When I am my son’s rubber duck, he explains me some
programming problems and solutions, he checks if I understand what he says, and
when I test positive, it means that he can get the message across to any
moderately educated hominid.
I
am going to proceed along the path of discursive equilibrium, in a cycle made
of three steps. First, I will try to describe my idea in 1 – 2 sentences, in a
simple and intelligible way. Then, I develop on that short description, with
technical details. In the third step, I look for gaps and holes in the
so-presented concept, and then I go again: short description, development,
critical look etc. I think I will repeat the cycle until I reach the Subjective
Feeling of Having Exhausted the Matter. Nelson Goodman and John Rawls proposed
something slightly similar (Goodman
1955[1];
Rawls
1999[2]):
when I talk long enough to myself, and to an imaginary audience, my concepts
sharpen.
Here
I go. First attempt. I synthesize. The concept of ‘Energy Ponds’ consists in
ram-pumping water from rivers into retentive, semi-natural wetlands, so as to
maximize the retention of water, and, in the same time, in using the elevation
created through ram-pumping so as to generate hydroelectricity. At the present
stage of conceptual development, ‘Energy Ponds’ require optimization at two
levels, namely that of adequately choosing and using the exact geographical
location, and that of making the technology of ram-pumping economically viable.
I
develop. We are increasingly exposed to hydrological effects of climate change,
namely to recurrent floods and droughts, and it starts being a real pain in the
ass. We need to figure out new ways of water management, so as to retain a
maximum of rainwater, whilst possibly alleviating occasional flood-flows. Thus,
we need to figure out good ways of capturing rainwater, and of retaining it.
Rivers are the drainpipes of surrounding lands, whence the concept of draining
basin: this is the expanse of land, adjacent to a river, where said river
collects (drains) water from. That water comes from atmospheric precipitations.
When we collect water from rivers, we collect rainwater, which fell on the
ground, trickled underground, and then, under the irresistible force of grandpa
Newton, flew towards the lowest point in the whereabouts, that lowest point
being the river.
Thus,
when we collect water from the river, we collect rainwater, just drained
through land. We can collect it in big artificial reservoirs, which has been
done for decades. An alternative solution is to retain water in wetlands. This
is something that nature has been doing for millions of years. We have sort of
a ready-made recipe from. Wetlands are like sponges covered with towels. A
layer of spongy ground, allowing substantial accumulation of water, is covered
with a dense, yet not very thick layer of shallowly rooted vegetation. That
cover layer prevents the evaporation of water.
Now,
I go into somehow novel a form of expression, i.e. novel for me. The age I am,
52, I have that slightly old school attachment to writing, and for the last 4
years, I have been mostly writing on my blog. Still, as a university professor,
I work with young people – students – and those young people end up, every now
and then, by teaching me something. I go more visual in my expression, which this
whole written passage can be considered as an introduction to. Under the two
links below, you will find:
That
would be all in this update. Just as with my other ideas, in the times we have,
i.e. with the necessity to figure out new s**t in the presence of pathogens,
you are welcome to contact me with any intellectual contribution you feel like supplying.
I
noticed it is one month that I did not post anything on my blog. Well, been
doing things, you know. Been writing, and thinking by the same occasion. I am
forming a BIG question in my mind, a question I want to answer: how are we
going to respond to climate change? Among all the possible scenarios of such
response, which are we the most likely to follow? When I have a look, every now
and then, at Greta Thunberg’s astonishingly quick social ascent, I wonder why are
we so divided about something apparently so simple? I am very clear: this is
not a rhetorical question from my part. Maybe I should claim something like: ‘We
just need to get all together, hold our hands and do X, Y, Z…’. Yes, in a
perfect world we would do that. Still, in the world we actually live in, we don’t.
Does it mean we are collectively stupid, like baseline, and just some enlightened
individuals can sometimes see the truly rational path of moving ahead? Might
be. Yet, another view is possible. We might be doing apparently dumb things
locally, and those apparent local flops could sum up to something quite
sensible at the aggregate scale.
There
is some science behind that intuition, and some very provisional observations. I
finally (and hopefully) nailed down the revision of the
article on energy efficiency. I have already started
developing on this one in my last update, entitled ‘Knowledge
and Skills’, and now, it is done. I have just revised the
article, quite deeply, and by the same occasion, I hatched a methodological
paper, which I submitted to MethodsX.
As I want to develop a broader discussion on these two papers, without
repeating their contents, I invite my readers to get acquainted with their PDF,
via the archives of my blog. Thus, by clicking the title Energy
Efficiency as Manifestation of Collective Intelligence in Human Societies,
you can access the subject matter paper on energy efficiency, and clicking on Neural
Networks As Representation of Collective Intelligence
will take you to the methodological article.
I
think I know how to represent, plausibly, collective intelligence with
artificial intelligence. I am showing the essential concept in the picture
below. Thus, I start with a set of empirical data, describing a society. Well
in the lines of what I have been writing, on this blog, since early spring this
year, I assume that quantitative variables in my dataset, e.g. GDP per capita,
schooling indicators, the probability for an average person to become a mad
scientist etc. What is the meaning of those variables? Most of all, they exist
and change together. Banal, but true. In other words, all that stuff represents
the cumulative outcome of past, collective action and decision-making.
I
decided to use the intellectual momentum, and I used the same method with a
different dataset, and a different set of social phenomena. I took Penn Tables
9.1 (Feenstra et al. 2015[1]), thus a well-known base
of macroeconomic data, and I followed the path sketched in the picture below.
Long
story short, I have two big surprises. When I look upon energy efficiency and
its determinants, turns out energy efficiency is not really the chief outcome
pursued by the 59 societies studied: they care much more about the local, temporary
proportions between capital immobilised in fixed assets, and the number of
resident patent applications. More specifically, they seem to be principally
optimizing the coefficient of fixed assets per 1 patent application. That is
quite surprising. It sends me back to my peregrinations through the land of
evolutionary theory (see for example: My
most fundamental piece of theory).
When
I take a look at the collective intelligence (possibly) embodied in Penn Tables
9.1, I can see this particular collective wit aiming at optimizing the share of
labour in the proceeds from selling real output in the first place. Then,
almost immediately after, comes the average number of hours worked per person
per year. You can click on
this link and read the full manuscript I have just submitted with
the Quarterly Journal of Economics.
Wrapping
it (provisionally) up, as I did some social science with the assumption of
collective intelligence in human societies taken at the level of methodology, and
I got truly surprising results. That
thing about energy efficiency – i.e. the fact that when in presence of some
capital in fixed assets, and some R&D embodied in patentable inventions, we
seem caring about energy efficiency only secondarily – is really mind-blowing. I
had already done some research on energy as factor of social change, and,
whilst I have never been really optimistic about our collective capacity to
save energy, I assumed that we orient ourselves, collectively, on some kind of
energy balance. Apparently, we do only when we have nothing else to pay
attention to. On the other hand, the
collective focus on macroeconomic variables pertinent to labour, rather
than prices and quantities, is just as gob-smacking. All economic education,
when you start with Adam Smith and take it from there, assumes that economic
equilibriums, i.e. those special states of society when we are sort of in balance
among many forces at work, are built around prices and quantities. Still, in that
research I have just completed, the only kind of price my neural network can build
a plausibly acceptable learning around, is the average price level in international
trade, i.e. in exports, and in imports. All the prices, which I have been
taught, and which I taught are the cornerstones of economic equilibrium, like
prices in consumption or prices in investment, when I peg them as output
variables of my perceptron, the incriminated perceptron goes dumb like hell and
yields negative economic aggregates. Yes, babe: when I make my neural network
pay attention to price level in investment goods, it comes to the conclusion
that the best idea is to have negative national income, and negative population.
Returning
to the issue of climate change and our collective response to it, I am trying
to connect my essential dots. I have just served some like well-cooked science,
and not it is time to bite into some raw one. I am biting into facts which I
cannot explain yet, like not at all. Did you know, for example, that there are
more and more adult people dying in high-income countries, like per 1000, since
2014? You can consult the data available with World Bank, as regards the
mortality of men and that
in women. Infant mortality is generally falling, just as adult mortality in
low, and middle-income countries. It is just about adult people in wealthy
societies categorized as ‘high income’: there are more and more of them dying per
1000. Well, I should maybe say ‘more of us’, as I am 51, and relatively
well-off, thank you. Anyway, all the way up through 2014, adult mortality in high-income
countries had been consistently subsiding, reaching its minimum in 2014 at 57,5
per 1000 in women, and 103,8 in men. In 2016, it went up to 60,5 per 1000 in
women, and 107,5 in men. It seems counter-intuitive. High-income countries are
the place where adults are technically exposed to the least fatal hazards. We
have virtually no wars around high income, we have food in abundance, we enjoy reasonably
good healthcare systems, so WTF? As regards low-income countries, we could
claim that adults who die are relatively the least fit for survival ones, but what
do you want to be fit for in high-income places? Driving a Mercedes around? Why
it started to revert since 2014?
Intriguingly,
high income countries are also those, where the difference in adult mortality
between men and women is the most pronounced, in men almost the double of what
is observable in women. Once again, it is something counter-intuitive. In low-income
countries, men are more exposed to death in battle, or to extreme conditions,
like work in mines. Still, in high-income countries, such hazards are remote.
Once again, WTF? Someone could say: it is about natural selection, about
eliminating the weak genetics. Could be, and yet not quite. Elimination of weak
genetics takes place mostly through infant mortality. Once we make it like through
the first 5 years of our existence, the riskiest part is over. Adult mortality
is mostly about recycling used organic material (i.e. our bodies). Are human
societies in high-income countries increasing the pace of that recycling? Why
since 2015? Is it more urgent to recycle used men than used women?
There
is one thing about 2015, precisely connected to climate change. As I browsed some
literature about droughts in Europe and their possible impact on agriculture (see
for example All
hope is not lost: the countryside is still exposed), it turned out that
2015 was precisely the year when we started to sort of officially admitting
that we have a problem with agricultural droughts on our continent. Even more
interestingly, 2014 and 2015 seem to have been the turning point when aggregate
damages from floods, in Europe, started to curb down after something like two
decades of progressive increase. We swapped one calamity for another one, and
starting from then, we started to recycle used adults at more rapid a pace. Of
course, most of Europe belongs to the category of high-income countries.
See?
That’s what I call raw science about collective intelligence. Observation with
a lot of questions and very remote idea as for the method of answering them. Something
is apparently happening, maybe we are collectively intelligent in the process, and
yet we don’t know how exactly (are we collectively intelligent). It is possible
that we are not. Warmer climate is associated with greater prevalence of
infectious diseases in adults (Amuakwa-Mensah
et al. 2017[1]),
for example, and yet it does not explain why is greater adult mortality happening
in high-income countries. Intuitively, infections attack where people are
poorly shielded against them, thus in countries with frequent incidence of
malnutrition and poor sanitation, thus in the low-income ones.
I
am consistently delivering good, almost new science to my readers, and love
doing it, and I am working on crowdfunding this activity of mine. You can
communicate with me directly, via the mailbox of this blog: goodscience@discoversocialsciences.com.
As we talk business plans, I remind you that you can download, from the library
of my blog, the business
plan I prepared for my semi-scientific project Befund (and you can access
the French version as well). You can also get a free e-copy of my book ‘Capitalism
and Political Power’ You can support my research by donating directly,
any amount you consider appropriate, to my PayPal account.
You can also consider going to my Patreon
page and become my patron. If you decide so, I will be
grateful for suggesting me two things that Patreon suggests me to suggest you.
Firstly, what kind of reward would you expect in exchange of supporting me?
Secondly, what kind of phases would you like to see in the development of my
research, and of the corresponding educational tools?
[1] Amuakwa-Mensah, F., Marbuah,
G., & Mubanga, M. (2017). Climate variability and infectious diseases
nexus: Evidence from Sweden. Infectious Disease Modelling, 2(2),
203-217.
[1] Feenstra, Robert C., Robert Inklaar
and Marcel P. Timmer (2015), “The Next Generation of the Penn World Table”
American Economic Review, 105(10), 3150-3182, available for download at www.ggdc.net/pwt
