Technical Footnotes/Explanation on Sustainability:
Nuclear Safety: The main safety concern here is the availability of
nuclear materials and technology to erratic subnational groups of all kinds;
however, there is also a possibility of larger than expected damage from
accidents which could occur under third world safety regimes, when there is
pressure to hold down costs. These concerns really are a matter of sheer
survival. Plausible scenarios for what might happen in the wake of certain
events are not reassuring.
Stuck in a Nash Equilibrium: When each player acts to maximize personal advantage, without considering the bigger picture, all players may suffer. “Prisoner’s dilemma” is the classic example. In economics, people commonly say “A Nash solution is often not a Pareto optimum.” That means that there is a “win-win” possibility, an outcome which would benefit all players, if we could figure out a way to get there. Some old politicians used to say: “If it’s a bigger pie, everyone can have a bigger slice.”
In
the specific case of energy, for example, I try hard to explain how a more
forward-looking, sustainable strategy can be tuned to ensure benefits to all
major players, oil users and suppliers both – but in practical situations this
can be difficult. When time is limited, oil consumers may want to hear about their
part of the story. And there are those
who think their job depends on shooting or projecting a false image and asking
questions later if ever.
Von
Neumann, the father of game theory, would probably have viewed the work of
Thomas Schelling and of Howard Raiffa as really essential in creating the kinds
of insights needed to get us to a Pareto optimum. More formal mathematical
theories of dynamic games vary in their ability to do justice to such insights;
many in game theory now believe that one must pay more central attention to the
role of learning, for which we now have much
more powerful tools. The specialist might note that most of the tools
developed to approximate the Bellman equation carry over easily to the Isaacs
equation – but the real challenge concerns
visions, designs and strategies for interaction which get beyond the
Nash equilibrium to something more like a global optimum.
In
the world of society and economics, as in the world of neural networks, change is
much easier when an incremental path can be found. Incremental adaptation
schemes based on derivative or value signals propagated through a large system
are essential to even the mouse level of intelligence, I would claim. But it is also important
at times to have a more global “imagination” system (to provide coherent
analysis of global scenarios not yet experienced in past history) and a
“creativity” system (to escape from “local minimum” or “nonconvexity” problems,
related to what Soros calls “reflexivity” in economic systems).
Checking Atomic Elements: Could Any of Them Run Out? Though I am not an expert on that topic, I have asked
a colleague for a few quick words to be a starting point for those who wish to
look further. He writes, informally:
“The work by Graedel is probably the most complete in the
area of metal cycles and the overall consumption of metals by various
regions. I attach the papers on Copper, Zinc and Silver, which are all
thought to be a possibility for scarcity.
Also a really good source for minerals is the usgs, for example their 2006
surveys are linked below, and there are others. I include the platinum
and palladium metal group also which they survey. You can find historical
data going back on these which you could use to assess the accuracy of their
earlier projections versus the current data.
http://minerals.usgs.gov/minerals/pubs/commodity/copper/coppemcs06.pdf
http://minerals.usgs.gov/minerals/pubs/commodity/silver/silvemcs06.pdf
http://minerals.usgs.gov/minerals/pubs/commodity/zinc/zinc_mcs06.pdf
http://minerals.usgs.gov/minerals/pubs/commodity/platinum/platimcs06.pdf
Personally I am not so worried about metals, they are readily fungible, the
more difficult one is water which is not and which tends to cross borders with
an unreasonable abandon, and which we have figured out remarkable engineering
feats to stop doing so, with enormous potential political consequences.”
Fiscal and Political Sustainability: This is a
large topic which I hope to post more on in the future. For the moment, I
should note that my Harvard PhD thesis was not just about backpropagation (as
discussed in the page on neural networks).
It was really four pieces in one – a piece on backpropagation or reverse
differentiation; a small piece just for me (chapter 5); a piece on new ways to
fit causal models better to time-series data, to get better forecasts and
better understanding than with classical statistical methods; and – most of all
– the use of these methods to create an operational version of a model
of “war and peace” developed by my thesis adviser, Prof. Karl W. Deutsch. (The
thesis has been reprinted in its entirety as part of the book The Roots of
Backpropagation: From Ordered Derivatives to Neural Networks and Political
Forecasting, by me, Wiley, 1994.) Deutsch was a fascinating person, with a
very visible and powerful intuition which he used every day of his life – even
though he fervently disbelieved in the very idea! I don’t think he even knew
what a neural network was, but his book, the Nerves of Government,
provides a fascinating account of how one might try to understand political and
social phenomena as a kind of neural network – but he also warned that we
shouldn’t take the idea of collective intelligence in the wrong way, and he
recommended that we also read Janis’s book Groupthink. He saw my thesis
as the final vindication of the ideas he presented in his book Nationalism
and Social Communications. He was at that time president of the
International Political Science Association, and one of the key thinkers behind
the creation and strengthening of the European Union.
For the time being, I will post just one of my papers
related to these themes:
P.
Werbos & J. Titus (1978) An
empirical test of new forecasting methods derived from a theory of
intelligence: The prediction of conflict in Latin America, IEEE Trans SMC, September.
This work taught me many, many
lessons. One was that a lot of earlier empirical work on conflict – at the
level of macro data – was grossly misleading, because it was dominated by two
data points (typically World War I and World War II). Some variables can be
predicted relatively robustly, like some of the key determinants of conflict.
But conflict itself is much harder. Certain kinds of data on content in communications
network data might do much better, but no one on earth has been working the
combination of methods and disciplines that would be necessary to do so. For
the past many years, I have relied more on other approaches to understand these
things – as in chapter 5 of the thesis, and in applying the kind of conceptual
understanding that other partsof this web page provide.