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Just as the Malthusians ignored the crucial role of innovation, the singularity enthusiasts ignore the crucial role of the entire socioeconomic dynamic of the planet, which in fact is the prime driver of the impending singularity.
The resulting sequence of singularities, each of which threatens stagnation and collapse, will continue to pile up, leading to what mathematicians call an essential singularity—a sort of mother of all singularities.
Until recent times, the time between major innovations far exceeded the productive life span of a human being.
a typical human being now lives significantly longer than the time between major innovations,
One of the great ongoing scientific challenges that has dominated modern physics is the search for a grand unified theory of the elementary particles and their interactions,
Measured by almost any metric this ongoing quest, which is still far from its ultimate goal, has been enormously successful, leading, for example, to the discovery of quarks as the fundamental building blocks of matter, the Higgs particle as the origin of mass in the universe, and to black holes and the Big Bang
Unlike the Newtonian paradigm upon which the Theory of Everything is based, the complete dynamics and structure of complex adaptive systems cannot be encoded in a small number of equations.
scaling theory provides a powerful tool for forging a middle ground in which a quantitative framework can be developed for understanding and predicting the coarse-grained behavior of many broad aspects of such systems.
the most surprising consequence of a visionary Theory of Everything is that it implies that on the grand scale the universe, including its origins and evolution, though extremely complicated, is not complex but in fact is surprisingly simple
Consequently, in parallel with the quest for the Theory of Everything, we need to embark on a similar quest for a grand unified theory of complexity.
The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all
From a Wired article. West disagrees.
The Fourth Paradigm: Data-Intensive Scientific Discovery. It was inspired by Jim Gray, a computer scientist at Microsoft
He identified the first three as (1) empirical observation (pre-Galileo), (2) theory based on models and mathematics (post-Newtonian), and (3) computation and simulation.
Gray viewed this fourth paradigm as an integration of the previous three, namely as a unification of theory, experiment, and simulation, but with an added emphasis on data gathering and analysis.
But there is a new kid on the block that many feel promises more and, like Anderson, potentially subverts the need for the traditional scientific method. This invokes techniques and strategies with names like machine learning, artificial intelligence, and data analytics.
They all rely on iterative procedures for finding and building upon correlations in data without concern for why such relationships exist and implicitly presume that “correlation supersedes causation.”
The discovery of the Higgs particle is a fascinating example of how Big Data can lead to important scientific discovery when integrated with traditional scientific methodology.
The lesson is clear: neither science nor data are democratic. Science is meritocratic and not all data are equal. Depending on what you are looking for or investigating, theory resulting from the traditional methodology of scientific investigation, whether highly developed and quantitative as in the case of fundamental physics, or relatively undeveloped and qualitative as in the case of much of social science, is an essential guide.
