Predicting Nothing


From American Thinker, Anthropogenic Global Warming and the Scientific Method by Betsy Gorisch


Science is about ruling things out. Any good scientific hypothesis will make predictions about the natural world — ideally, it will predict at least one natural effect whose existence cannot be caused by anything other than the hypothesis being tested. Observations are then made to acquire evidence, and the evidence is evaluated against the hypothesis’s predictions. Evidence can either rule the hypothesis out or not; if the evidence differs from the hypothesis’s predicted effects, then the hypothesis is wrong and is considered to be ruled out, or falsified. That which has not been ruled out by evidence remains possible. If enough confirmatory evidence is accumulated, the hypothesis is elevated to the status of a theory. Scientific Method is, conceptually, no more complicated than that.

Karl Popper, the great philosopher of science, used a simple observational experiment to illustrate the scientific method’s requirement of falsifiability — the requirement that a hypothesis be stated in such a way as to allow its testing against evidence with a view towards ruling it out. He noted that most people had once assumed that all swans are white. This assumption was based on the observation, over time, of uncounted numbers of white swans — and each such observation was taken as evidence supporting the assumption. However, there came a time when a black swan was found in Australia, and its discovery served to disprove the assumption that all swans are white. In generalizing from this discovery, Popper understood that you would not test the hypothesis that all swans are white by undertaking a search for white swans — because no matter how many white swans you found, you would neither have proven, nor even properly tested, the hypothesis. Instead, you must mount an intensive search for a single non-white swan.  If you found even one of those, you would have ruled the hypothesis out. Alternatively, and without finding a non-white swan, it remained viable — but because there remained the possibility of a single undetected non-white swan, it could not be regarded as proven.

The AGW hypothesis that so many people claim accounts for what is essentially pretend global warming has never been treated this way. Initially, its proponents engaged in a search for supporting evidence: Elevated average annual temperatures, local glacial retreats, elevated-temperature indicators in proxy systems such as tree-ring records, measurable coincident increases in atmospheric CO2 concentration, and so on — a search for white swans. But these efforts ignored, and failed even to seek, either any alternative explanations or evidence that would have ruled the hypothesis out. AGW has failed the predictions test again and again; any true scientific hypothesis with so poor an evidence-based evaluation record would have been scrapped by now. Instead, its proponents elevated it to the status of a theory and, ignoring the fact that climate changes continually, renamed it “climate change.”

Models are essentially used as predictive tools, so they are only as good as the information upon which they are constructed. If there are any unknown components in the modeled system, then the model’s predictions will, almost by definition, be unreliable.  In the case of a system both as complex and incompletely understood as Earth’s atmosphere, the model’s construction will essentially be required to include untested, incomplete, and/or unproven function assumptions and data. In such a case, the problems and pitfalls of using these models to construct governing policies quickly become self-evident: People trying to rely on the models essentially cannot know what they are doing.  When, for example, their model does not predict their real-world observations, they tweak it until it does — which introduces errors-by-expectation into both output and the policies based upon it. These errors increase in magnitude, and therefore in effect, in a non-linear fashion directly proportional both to the size of the system and to the modeled outputs.

AGW’s predictions are not being reliably confirmed by observations. When stasis and/or cooling occur rather than warming — as has been the case over the last decade-and-a-half — atmospheric scientists fudge interpretations by saying that if it is cool, well, that is just weather; if it is warm, though, that is climate.  Alternatively, they claim AGW predicts the cooling — as, for example, with the recent polar-vortex outbreaks.  However, a theory that predicts everything predicts nothing — because a theory that predicts everything cannot be falsified through testing; nothing will serve to rule it out.

Read more: http://www.americanthinker.com/articles/2014/11/anthropogenic_global_warming_and_the_scientific_method.html#ixzz3K5Y6CxXN
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All Inequality is not Equal

From my article in American Thinker, Everything that Counts


While Piketty reviews a history of inequality, we should realize that the inequality of the feudal society of the middle ages, where force kept the poor in a lifetime of poverty, is vastly different from the inequality from a system where innovations spur spectacular success, while benefiting large proportions of other people.  Does anybody with an iPhone hold a grudge against Steve Jobs and his billions of dollars of wealth, or the wealth of Sergi Brin of Google?

All inequality is not equal.

The Hands that Prosper

From my article in American Thinker, Everything that Counts


When Piketty suggests that we tax the wealth of the richest, exactly what does he think will happen to it?  The government will spend it – but on what?  Does he think that some politically motivated bureaucrat will allocate that capital to a more socially useful purpose than Warren Buffett would?  In which hands would that capital seek growth and job creation?  In which hands will it most likely pay farmers not to grow, and workers not to work?

Our safety net succeeds in eliminating the crushing poverty known by the third world.  Our challenge is to avoid replacement of the soul-deprivation of numbing poverty with the soul-deprivation of dependency.  Our biggest problem with the health of the poor in America is not starvation, but obesity.  As Paul Ryan framed it, we do not want to turn the safety net into a hammock.

Wealth more often dissipates in a few generations and moves to stronger hands.  Dynasties are rare; most fortunes are lost in a few generations.  We do not really need centrally planned redistribution; this problem generally takes care of itself when capital deployment is subject to competition and human frailties.  Inequality is a natural outcome of the competitive allocation of capital, and we are all better-served when capital is in strong hands and deployed wisely.  Rarely are those hands attached to the long arms of the government.

Inequality vs Mobility

From my article in American Thinker, Everything that Counts:

Vast inequalities may harbor the potential for social unrest, but that is muted by social mobility.  Oprah and Andre Young (Dr. Dre) may have been born in poverty, but that has not kept them from rising to the top one tenth of one percent.  Here is a defining question: did the dramatic rise in the fortunes of Dr. Dre and Oprah increase or decrease inequality as a whole?

Here is the central problem with Piketty’s task: the data on inequality measures categories, not individuals.

Individuals rise and fall among categories, often taking leaps as luck and talent unfold.  Oprah’s success increases inequality, but her success also demonstrates an increase in mobility.  Individuals may buy a lottery ticket knowing that the odds are against them if they know that their opportunity is equal to other lottery ticket buyers.  They will be less likely to buy a ticket if they think the game is rigged (i.e., crony capitalism).  For many, the mobility and the equality of opportunity are most important.  We hold no grudge against the winner, because we understand that the winner could be we.

While Piketty reviews a history of inequality, we should realize that the inequality of the feudal society of the middle ages, where force kept the poor in a lifetime of poverty, is vastly different from the inequality from a system where innovations spur spectacular success, while benefiting large proportions of other people.  Does anybody with an iPhone hold a grudge against Steve Jobs and his billions of dollars of wealth, or the wealth of Sergi Brin of Google?

All inequality is not equal.

Detroit’s Suicide


There are many who blame the woes of Detroit on the decline in the auto industry, but the auto industry did not decline- it just moved.  Paul Krugman passes the decline off to the normal creative destruction of capitalist progress.  Bullshit, again.  A small businessman who used to be in Detroit explains the decline very clearly.

Don Wilkie writes in American Thinker, How Detroit Almost Killed My Business.


As mentioned earlier, when I left Detroit I had 20 employees.  But, 10 years earlier I had 5 employees.  As the business grew I had to hire more people.  As it turned out, to get one good employee, I had to hire about 8.  So to get an additional 15 people, I had to hire over ten years approximately 120 people.  This is when doing business in Detroit really started to get expensive.

When an employee left my employ, whether by quitting or being fired, they immediately went to the Unemployment Office where they were given unemployment payments.  Employers such as me went to great lengths to make sure that if someone was fired it was for a good documentable reason, in an effort to avoid having to pay for unemployment.  In practice, that didn’t matter too much.  The likelihood that the State would grant benefits was extremely high, maybe 80%.  If you protested you had to appear before a state “referee,” who was, unsurprisingly, very biased in favor of the claimant.

But as bad as unemployment costs got, they were nothing compared to Workman’s Compensation.  Here is the way the game was played:  If you were on unemployment it was understood that you were “ready, willing and able” to work. If you were on Workman’s Compensation it meant you were injured and could not work.  So, an employee always went for Unemployment benefits first and when they ran out, suddenly discovered that he was injured, usually with a bad back.  In Detroit, an employer almost never won a Comp case.

After a period of time, my insurance company put me in what was called the “Assigned Risk” pool.  What that meant in practice was that my Workman’s Compensation insurance costs doubled overnight.  Every new employee hired became a huge financial burden not in terms of wages but in terms of Unemployment and Workman’s Comp costs.

But perhaps the scariest thing that could happen to an employer was being summoned in front of the Civil Rights Commission, to face charges of “Wrongful Discharge.” Here you had to prove a negative, that you did not violate someone’s rights.  This happened to me three times.  If the Commission determined you were guilty, which were two out of three for me, the remedy was to pay all of an employee’s wages from the time he was separated from your employ to the time of the Commission’s finding.  Since the system moved very slowly, an employer could be faced with paying as much as two years’ salary.

Read more: http://www.americanthinker.com/2013/07/how_detroit_almost_killed_my_business.html#ixzz2a3KdulYK
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One does not have to travel far to find these similar problems in many other locations.  It is having a chilling effect on business start ups and employment nationwide.  Detroit just took it to a slightly more ludicrous extreme and it has been going on longer than other locations.  It is a test tube of disastrous progressive policies, economic naivete, political corruption, and the subjugation of any accountability to fears of being called racist.