A (Long) Footnote about Science

In “Deduction, Induction, and Knowledge” I make a case that knowledge (as opposed to belief) can only be inductive, that is, limited to specific facts about particular phenomena. It’s true that a hypothesis or theory about a general pattern of relationships (e.g., the general theory of relativity) can be useful, and even necessary. As I say at the end of “Deduction…”, the fact that a general theory can’t be proven

doesn’t — and shouldn’t — stand in the way of acting as if we possess general knowledge. We must act as if we possess general knowledge. To do otherwise would result in stasis, or analysis-paralysis.

Which doesn’t mean that a general theory should be accepted just because it seems plausible. Some general theories — such as global climate models (or GCMs) are easily falsified. They persist only because pseudo-scientists and true believers refuse to abandon them. (There is no such thing as “settled science”.)

Neil Lock, writing at Watts Up With That?, offers this perspective on inductive vs. deductive thinking:

Bottom up thinking is like the way we build a house. Starting from the ground, we work upwards, using what we’ve done already as support for what we’re working on at the moment. Top down thinking, on the other hand, starts out from an idea that is a given. It then works downwards, seeking evidence for the idea, or to add detail to it, or to put it into practice….

The bottom up thinker seeks to build, using his senses and his mind, a picture of the reality of which he is a part. He examines, critically, the evidence of his senses. He assembles this evidence into percepts, things he perceives as true. Then he pulls them together and generalizes them into concepts. He uses logic and reason to seek understanding, and he often stops to check that he is still on the right lines. And if he finds he has made an error, he tries to correct it.

The top down thinker, on the other hand, has far less concern for logic or reason, or for correcting errors. He tends to accept new ideas only if they fit his pre-existing beliefs. And so, he finds it hard to go beyond the limitations of what he already knows or believes. [“‘Bottom Up’ versus ‘Top Down’ Thinking — On Just about Everything“, October 22, 2017]

(I urge you to read the whole thing, in which Lock applies the top down-bottom up dichotomy to a broad range of issues.)

Lock overstates the distinction between the two modes of thought. A lot of “bottom up” thinkers derive general hypotheses from their observations about particular events. But — and this is a big “but” — they are also amenable to revising their hypotheses when they encounter facts that contradict them. The best scientists are bottom-up and top-down thinkers whose beliefs are based on bottom-up thinking.

General hypotheses are indispensable guides to “everyday” living. Some of them (e.g., fire burns, gravity causes objects to fall) are such reliable guides that it’s foolish to assume their falsity. Nor does it take much research to learn, for example, that there are areas within a big city where violent crime is rampant. A prudent person — even a “liberal” one — will therefore avoid those areas.

There are also general patterns — now politically incorrect to mention — with respect to differences in physical, psychological, and intellectual traits and abilities between men and women and among races. (See this, this, and this, for example.) These patterns explain disparities in achievement, but they are ignored by true believers who would wish away the underlying causes and penalize those who are more able (in a relevant dimension) for the sake of ersatz equality. The point is that a good many people — perhaps most people — studiously ignore facts of some kind in order to preserve their cherished beliefs about themselves and the world around them.

Which brings me back to science and scientists. Scientists, for the most part, are human beings with a particular aptitude for pattern-seeking and the manipulation of abstract ideas. They can easily get lost in such pursuits and fail to notice that their abstractions have taken them a long way from reality (e.g., Einstein’s special theory of relativity).

This is certainly the case in physics, where scientists admit that the standard model of sub-atomic physics “proves” that the universe shouldn’t exist. (See Andrew Griffin, “The Universe Shouldn’t Exist, Scientists Say after Finding Bizarre Behaviour of Anti-Matter“, The Independent, October 23, 2017.) It is most certainly the case in climatology, where many pseudo-scientists have deployed hopelessly flawed models in the service of policies that would unnecessarily cripple the economy of the United States.

As I say here,

scientists are human and fallible. It is in the best tradition of science to distrust their claims and to dismiss their non-scientific utterances.

Non-scientific utterances are not only those which have nothing to do with a scientist’s field of specialization, but also include those that are based on theories which derive from preconceptions more than facts. It is scientific to admit lack of certainty. It is unscientific — anti-scientific, really — to proclaim certainty about something that is so little understood the origin of the universe or Earth’s climate.


Related posts:
Hemibel Thinking
The Limits of Science
The Thing about Science
Science in Politics, Politics in Science
Global Warming and the Liberal Agenda
Debunking “Scientific Objectivity”
Pseudo-Science in the Service of Political Correctness
Science’s Anti-Scientific Bent
“Warmism”: The Myth of Anthropogenic Global Warming
Modeling Is Not Science
Demystifying Science
Analysis for Government Decision-Making: Hemi-Science, Hemi-Demi-Science, and Sophistry
Pinker Commits Scientism
AGW: The Death Knell
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?
The “Marketplace” of Ideas
Revisiting the “Marketplace” of Ideas
The Technocratic Illusion
The Precautionary Principle and Pascal’s Wager
AGW in Austin? (II)
Is Science Self-Correcting?
“Science” vs. Science: The Case of Evolution, Race, and Intelligence
Modeling Revisited
Bayesian Irrationality
Mettenheim on Einstein’s Relativity
The Fragility of Knowledge
Global-Warming Hype
Pattern-Seeking
Hurricane Hysteria
Deduction, Induction, and Knowledge
Much Ado about the Unknown and Unkownable

Not-So-Random Thoughts (XV)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

*     *     *

Victor Davis Hanson writes:

This descent into the Dark Ages will not end well. It never has in the past. [“Building the New Dark-Age Mind,” Works and Days, June 8, 2015]

Hamson’s chronicle of political correctness and doublespeak echoes one theme of my post, “1963: The Year Zero.”

*     *     *

Timothy Taylor does the two-handed economist act:

It may be that the question of “does inequality slow down economic growth” is too broad and diffuse to be useful. Instead, those of us who care about both the rise in inequality and the slowdown in economic growth should be looking for policies to address both goals, without presuming that substantial overlap will always occur between them. [“Does Inequality Reduce Economic Growth: A Skeptical View,” The Conversible Economist, May 29, 2015]

The short answer to the question “Does inequality reduce growth?” is no. See my post “Income Inequality and Economic Growth.” Further, even if inequality does reduce growth, the idea of reducing inequality (through income redistribution, say) to foster growth is utilitarian and therefore morally egregious. (See “Utilitarianism vs. Liberty.”)

*     *     *

In “Diminishing Marginal Utility and the Redistributive Urge” I write:

[L]eftists who deign to offer an economic justification for redistribution usually fall back on the assumption of the diminishing marginal utility (DMU) of income and wealth. In doing so, they commit (at least) four errors.

The first error is the fallacy of misplaced concreteness which is found in the notion of utility. Have you ever been able to measure your own state of happiness? I mean measure it, not just say that you’re feeling happier today than you were when your pet dog died. It’s an impossible task, isn’t it? If you can’t measure your own happiness, how can you (or anyone) presume to measure and aggregate the happiness of millions or billions of individual human beings? It can’t be done.

Which brings me to the second error, which is an error of arrogance. Given the impossibility of measuring one person’s happiness, and the consequent impossibility of measuring and comparing the happiness of many persons, it is pure arrogance to insist that “society” would be better off if X amount of income or wealth were transferred from Group A to Group B….

The third error lies in the implicit assumption embedded in the idea of DMU. The assumption is that as one’s income or wealth rises one continues to consume the same goods and services, but more of them….

All of that notwithstanding, the committed believer in DMU will shrug and say that at some point DMU must set in. Which leads me to the fourth error, which is an error of introspection….  [If over the years] your real income has risen by a factor of two or three or more — and if you haven’t messed up your personal life (which is another matter) — you’re probably incalculably happier than when you were just able to pay your bills. And you’re especially happy if you put aside a good chunk of money for your retirement, the anticipation and enjoyment of which adds a degree of utility (such a prosaic word) that was probably beyond imagining when you were in your twenties, thirties, and forties.

Robert Murphy agrees:

[T]he problem comes in when people sometimes try to use the concept of DMU to justify government income redistribution. Specifically, the argument is that (say) the billionth dollar to Bill Gates has hardly any marginal utility, while the 10th dollar to a homeless man carries enormous marginal utility. So clearly–the argument goes–taking a dollar from Bill Gates and giving it to a homeless man raises “total social utility.”

There are several serious problems with this type of claim. Most obvious, even if we thought it made sense to attribute units of utility to individuals, there is no reason to suppose we could compare them across individuals. For example, even if we thought a rich man had units of utility–akin to the units of his body temperature–and that the units declined with more money, and likewise for a poor person, nonetheless we have no way of placing the two types of units on the same scale….

In any event, this is all a moot point regarding the original question of interpersonal utility comparisons. Even if we thought individuals had cardinal utilities, it wouldn’t follow that redistribution would raise total social utility.

Even if we retreat to the everyday usage of terms, it still doesn’t follow as a general rule that rich people get less happiness from a marginal dollar than a poor person. There are many people, especially in the financial sector, whose self-esteem is directly tied to their earnings. And as the photo indicates, Scrooge McDuck really seems to enjoy money. Taking gold coins from Scrooge and giving them to a poor monk would not necessarily increase happiness, even in the everyday psychological sense. [“Can We Compare People’s Utilities?,” Mises Canada, May 22, 2015]

See also David Henderson’s “Murphy on Interpersonal Utility Comparisons” (EconLog, May 22, 2015) and Henderson’s earlier posts on the subject, to which he links. Finally, see my comment on an earlier post by Henderson, in which he touches on the related issue of cost-benefit analysis.

*     *     *

Here’s a slice of what Robert Tracinski has to say about “reform conservatism”:

The key premise of this non-reforming “reform conservatism” is the idea that it’s impossible to really touch the welfare state. We might be able to alter its incentives and improve its clanking machinery, but only if we loudly assure everyone that we love it and want to keep it forever.

And there’s the problem. Not only is this defeatist at its core, abandoning the cause of small government at the outset, but it fails to address the most important problem facing the country.

“Reform conservatism” is an answer to the question: how can we promote the goal of freedom and small government—without posing any outright challenge to the welfare state? The answer: you can’t. All you can do is tinker around the edges of Leviathan. And ultimately, it won’t make much difference, because it will all be overwelmed in the coming disaster. [“Reform Conservatism Is an Answer to the Wrong Question,” The Federalist, May 22, 2015]

Further, as I observe in “How to Eradicate the Welfare State, and How Not to Do It,” the offerings of “reform conservatives”

may seem like reasonable compromises with the left’s radical positions. But they are reasonable compromises only if you believe that the left wouldn’t strive vigorously to undo them and continue the nation’s march toward full-blown state socialism. That’s the way leftists work. They take what they’re given and then come back for more, lying and worse all the way.

See also Arnold Kling’s “Reason Roundtable on Reform Conservatism” (askblog, May 22, 2015) and follow the links therein.

*     *     *

I’ll end this installment with a look at science and the anti-scientific belief in catastrophic anthropogenic global warming.

Here’s Philip Ball in “The Trouble With Scientists“:

It’s likely that some researchers are consciously cherry-picking data to get their work published. And some of the problems surely lie with journal publication policies. But the problems of false findings often begin with researchers unwittingly fooling themselves: they fall prey to cognitive biases, common modes of thinking that lure us toward wrong but convenient or attractive conclusions. “Seeing the reproducibility rates in psychology and other empirical science, we can safely say that something is not working out the way it should,” says Susann Fiedler, a behavioral economist at the Max Planck Institute for Research on Collective Goods in Bonn, Germany. “Cognitive biases might be one reason for that.”

Psychologist Brian Nosek of the University of Virginia says that the most common and problematic bias in science is “motivated reasoning”: We interpret observations to fit a particular idea. Psychologists have shown that “most of our reasoning is in fact rationalization,” he says. In other words, we have already made the decision about what to do or to think, and our “explanation” of our reasoning is really a justification for doing what we wanted to do—or to believe—anyway. Science is of course meant to be more objective and skeptical than everyday thought—but how much is it, really?

Whereas the falsification model of the scientific method championed by philosopher Karl Popper posits that the scientist looks for ways to test and falsify her theories—to ask “How am I wrong?”—Nosek says that scientists usually ask instead “How am I right?” (or equally, to ask “How are you wrong?”). When facts come up that suggest we might, in fact, not be right after all, we are inclined to dismiss them as irrelevant, if not indeed mistaken….

Given that science has uncovered a dizzying variety of cognitive biases, the relative neglect of their consequences within science itself is peculiar. “I was aware of biases in humans at large,” says [Chris] Hartgerink [of Tilburg University in the Netherlands], “but when I first ‘learned’ that they also apply to scientists, I was somewhat amazed, even though it is so obvious.”…

One of the reasons the science literature gets skewed is that journals are much more likely to publish positive than negative results: It’s easier to say something is true than to say it’s wrong. Journal referees might be inclined to reject negative results as too boring, and researchers currently get little credit or status, from funders or departments, from such findings. “If you do 20 experiments, one of them is likely to have a publishable result,” [Ivan] Oransky and [Adam] Marcus [who run the service Retraction Watch] write. “But only publishing that result doesn’t make your findings valid. In fact it’s quite the opposite.”9 [Nautilus, May 14, 2015]

Zoom to AGW. Robert Tracinski assesses the most recent bit of confirmation bias:

A lot of us having been pointing out one of the big problems with the global warming theory: a long plateau in global temperatures since about 1998. Most significantly, this leveling off was not predicted by the theory, and observed temperatures have been below the lowest end of the range predicted by all of the computerized climate models….

Why, change the data, of course!

Hence a blockbuster new report: a new analysis of temperature data since 1998 “adjusts” the numbers and magically finds that there was no plateau after all. The warming just continued….

How convenient.

It’s so convenient that they’re signaling for everyone else to get on board….

This is going to be the new party line. “Hiatus”? What hiatus? Who are you going to believe, our adjustments or your lying thermometers?…

The new adjustments are suspiciously convenient, of course. Anyone who is touting a theory that isn’t being borne out by the evidence and suddenly tells you he’s analyzed the data and by golly, what do you know, suddenly it does support his theory—well, he should be met with more than a little skepticism.

If we look, we find some big problems. The most important data adjustments by far are in ocean temperature measurements. But anyone who has been following this debate will notice something about the time period for which the adjustments were made. This is a time in which the measurement of ocean temperatures has vastly improved in coverage and accuracy as a whole new set of scientific buoys has come online. So why would this data need such drastic “correcting”?

As climatologist Judith Curry puts it:

The greatest changes in the new NOAA surface temperature analysis is to the ocean temperatures since 1998. This seems rather ironic, since this is the period where there is the greatest coverage of data with the highest quality of measurements–ARGO buoys and satellites don’t show a warming trend. Nevertheless, the NOAA team finds a substantial increase in the ocean surface temperature anomaly trend since 1998.

….

I realize the warmists are desperate, but they might not have thought through the overall effect of this new “adjustment” push. We’ve been told to take very, very seriously the objective data showing global warming is real and is happening—and then they announce that the data has been totally changed post hoc. This is meant to shore up the theory, but it actually calls the data into question….

All of this fits into a wider pattern: the global warming theory has been awful at making predictions about the data ahead of time. But it has been great at going backward, retroactively reinterpreting the data and retrofitting the theory to mesh with it. A line I saw from one commenter, I can’t remember where, has been rattling around in my head: “once again, the theory that predicts nothing explains everything.” [“Global Warming: The Theory That Predicts Nothing and Explains Everything,” The Federalist, June 8, 2015]

Howard Hyde also weighs in with “Climate Change: Where Is the Science?” (American Thinker, June 11, 2015).

Bill Nye, the so-called Science Guy, seems to epitomize the influence of ideology on “scientific knowledge.”  I defer to John Derbyshire:

Bill Nye the Science Guy gave a commencement speech at Rutgers on Sunday. Reading the speech left me thinking that if this is America’s designated Science Guy, I can be the nation’s designated swimsuit model….

What did the Science Guy have to say to the Rutgers graduates? Well, he warned them of the horrors of climate change, which he linked to global inequality.

We’re going to find a means to enable poor people to advance in their societies in countries around the world. Otherwise, the imbalance of wealth will lead to conflict and inefficiency in energy production, which will lead to more carbon pollution and a no-way-out overheated globe.

Uh, given that advanced countries use far more energy per capita than backward ones—the U.S.A. figure is thirty-four times Bangladesh’s—wouldn’t a better strategy be to keep poor countries poor? We could, for example, encourage all their smartest and most entrepreneurial people to emigrate to the First World … Oh, wait: we already do that.

The whole climate change business is now a zone of hysteria, generating far more noise—mostly of a shrieking kind—than its importance justifies. Opinions about climate change are, as Greg Cochran said, “a mark of tribal membership.” It is also the case, as Greg also said, that “the world is never going to do much about in any event, regardless of the facts.”…

When Ma Nature means business, stuff happens on a stupendously colossal scale.  And Bill Nye the Science Guy wants Rutgers graduates to worry about a 0.4ºC warming over thirty years? Feugh.

The Science Guy then passed on from the dubiously alarmist to the batshit barmy.

There really is no such thing as race. We are one species … We all come from Africa.

Where does one start with that? Perhaps by asserting that: “There is no such thing as states. We are one country.”

The climatological equivalent of saying there is no such thing as race would be saying that there is no such thing as weather. Of course there is such a thing as race. We can perceive race with at least three of our five senses, and read it off from the genome. We tick boxes for it on government forms: I ticked such a box for the ATF just this morning when buying a gun.

This is the Science Guy? The foundational text of modern biology bears the title On the Origin of Species by Means of Natural Selection, or the Preservation of Favored Races in the Struggle for Life. Is biology not a science?

Darwin said that populations of a species long separated from each other will diverge in their biological characteristics, forming races. If the separation goes on long enough, any surviving races will diverge all the way to separate species. Was Ol’ Chuck wrong about that, Mr. Science Guy?

“We are one species”? Rottweilers and toy poodles are races within one species, a species much newer than ours; yet they differ mightily, not only in appearance but also—gasp!—in behavior, intelligence, and personality. [“Nye Lied, I Sighed,” Taki’s Magazine, May 21, 2015]

This has gone on long enough. Instead of quoting myself, I merely refer you to several related posts:

Demystifying Science
AGW: The Death Knell
Evolution and Race
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?

Signature

“Settled Science” and the Monty Hall Problem

The so-called 97-percent consensus among climate scientists about anthropogenic global warming (AGW) isn’t evidence of anything but the fact that scientists are only human. Even if there were such a consensus, it certainly wouldn’t prove the inchoate theory of AGW, any more than the early consensus against Einstein’s special theory of relativity disproved that theory.

Actually, in the case of AGW, the so-called consensus is far from a consensus about the extent of warming, its causes, and its implications. (See, for example, this post and this one.) But it’s undeniable that a lot of climate scientists believe in a “strong” version of AGW, and in its supposedly dire consequences for humanity.

Why is that? Well, in a field as inchoate as climate science, it’s easy to let one’s prejudices drive one’s research agenda and findings, even if only subconsciously. And isn’t it more comfortable and financially rewarding to be with the crowd and where the money is than to stand athwart the conventional wisdom? (Lennart Bengtsson certainly found that to be the case.) Moreover, there was, in the temperature records of the late 20th century, a circumstantial case for AGW, which led to the development of theories and models that purport to describe a strong relationship between temperature and CO2. That the theories and models are deeply flawed and lacking in predictive value seems not to matter to the 97 percent (or whatever the number is).

In other words, a lot of climate scientists have abandoned the scientific method, which demands skepticism, in order to be on the “winning” side of the AGW issue. How did it come to be thought of as the “winning” side? Credit vocal so-called scientists who were and are (at least) guilty of making up models to fit their preconceptions, and ignoring evidence that human-generated CO2 is a minor determinant of atmospheric temperature. Credit influential non-scientists (e.g., Al Gore) and various branches of the federal government that have spread the gospel of AGW and bestowed grants on those who can furnish evidence of it. Above all, credit the media, which for the past two decades has pumped out volumes of biased, half-baked stories about AGW, in the service of the “liberal” agenda: greater control of the lives and livelihoods of Americans.

Does this mean that the scientists who are on the AGW bandwagon don’t believe in the correctness of AGW theory? I’m sure that most of them do believe in it — to some degree. They believe it at least to the same extent as a religious convert who zealously proclaims his new religion to prove (mainly to himself) his deep commitment to that religion.

What does all of this have to do with the Monty Hall problem? This:

Making progress in the sciences requires that we reach agreement about answers to questions, and then move on. Endless debate (think of global warming) is fruitless debate. In the Monty Hall case, this social process has actually worked quite well. A consensus has indeed been reached; the mathematical community at large has made up its mind and considers the matter settled. But consensus is not the same as unanimity, and dissenters should not be stifled. The fact is, when it comes to matters like Monty Hall, I’m not sufficiently skeptical. I know what answer I’m supposed to get, and I allow that to bias my thinking. It should be welcome news that a few others are willing to think for themselves and challenge the received doctrine. Even though they’re wrong. (Brian Hayes, “Monty Hall Redux” (a book review), American Scientist, September-October 2008)

The admirable part of Hayes’s statement is its candor: Hayes admits that he may have adopted the “consensus” answer because he wants to go with the crowd.

The dismaying part of Hayes’s statement is his smug admonition to accept “consensus” and move on. As it turns out the “consensus” about the Monty Hall problem isn’t what it’s cracked up to be. A lot of very bright people have solved a tricky probability puzzle, but not the Monty Hall problem. (For the details, see my post, “The Compleat Monty Hall Problem.”)

And the “consensus” about AGW is very far from being the last word, despite the claims of true believers. (See, for example, the relatively short list of recent articles, posts, and presentations given at the end of this post.)

Going with the crowd isn’t the way to do science. It’s certainly not the way to ascertain the contribution of human-generated CO2 to atmospheric warming, or to determine whether the effects of any such warming are dire or beneficial. And it’s most certainly not the way to decide whether AGW theory implies the adoption of policies that would stifle economic growth and hamper the economic betterment of millions of Americans and billions of other human beings — most of whom would love to live as well as the poorest of Americans.

Given the dismal track record of global climate models, with their evident overstatement of the effects of CO2 on temperatures, there should be a lot of doubt as to the causes of rising temperatures in the last quarter of the 20th century, and as to the implications for government action. And even if it could be shown conclusively that human activity will temperatures to resume the rising trend of the late 1900s, several important questions remain:

  • To what extent would the temperature rise be harmful and to what extent would it be beneficial?
  • To what extent would mitigation of the harmful effects negate the beneficial effects?
  • What would be the costs of mitigation, and who would bear those costs, both directly and indirectly (e.g., the effects of slower economic growth on the poorer citizens of thw world)?
  • If warming does resume gradually, as before, why should government dictate precipitous actions — and perhaps technologically dubious and economically damaging actions — instead of letting households and businesses adapt over time by taking advantage of new technologies that are unavailable today?

Those are not issues to be decided by scientists, politicians, and media outlets that have jumped on the AGW bandwagon because it represents a “consensus.” Those are issues to be decided by free, self-reliant, responsible persons acting cooperatively for their mutual benefit through the mechanism of free markets.

*     *     *

Recent Related Reading:
Roy Spencer, “95% of Climate Models Agree: The Observations Must Be Wrong,” Roy Spencer, Ph.D., February 7, 2014
Roy Spencer, “Top Ten Good Skeptical Arguments,” Roy Spencer, Ph.D., May 1, 2014
Ross McKittrick, “The ‘Pause’ in Global Warming: Climate Policy Implications,” presentation to the Friends of Science, May 13, 2014 (video here)
Patrick Brennan, “Abuse from Climate Scientists Forces One of Their Own to Resign from Skeptic Group after Week: ‘Reminds Me of McCarthy’,” National Review Online, May 14, 2014
Anthony Watts, “In Climate Science, the More Things Change, the More They Stay the Same,” Watts Up With That?, May 17, 2014
Christopher Monckton of Brenchley, “Pseudoscientists’ Eight Climate Claims Debunked,” Watts Up With That?, May 17, 2014
John Hinderaker, “Why Global Warming Alarmism Isn’t Science,” PowerLine, May 17, 2014
Tom Sheahan, “The Specialized Meaning of Words in the “Antarctic Ice Shelf Collapse’ and Other Climate Alarm Stories,” Watts Up With That?, May 21, 2014
Anthony Watts, “Unsettled Science: New Study Challenges the Consensus on CO2 Regulation — Modeled CO2 Projections Exaggerated,” Watts Up With That?, May 22, 2014
Daniel B. Botkin, “Written Testimony to the House Subcommittee on Science, Space, and Technology,” May 29, 2014

Related posts:
The Limits of Science
The Thing about Science
Debunking “Scientific Objectivity”
Modeling Is Not Science
The Left and Its Delusions
Demystifying Science
AGW: The Death Knell
Modern Liberalism as Wishful Thinking
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”

Pinker Commits Scientism

Steven Pinker, who seems determined to outdo Bryan Caplan in wrongheadedness, devotes “Science Is Not Your Enemy” (The New Republic,  August 6, 2013), to the defense of scientism. Actually, Pinker doesn’t overtly defend scientism, which is indefensible; he just redefines it to mean science:

The term “scientism” is anything but clear, more of a boo-word than a label for any coherent doctrine. Sometimes it is equated with lunatic positions, such as that “science is all that matters” or that “scientists should be entrusted to solve all problems.” Sometimes it is clarified with adjectives like “simplistic,” “naïve,” and “vulgar.” The definitional vacuum allows me to replicate gay activists’ flaunting of “queer” and appropriate the pejorative for a position I am prepared to defend.

Scientism, in this good sense, is not the belief that members of the occupational guild called “science” are particularly wise or noble. On the contrary, the defining practices of science, including open debate, peer review, and double-blind methods, are explicitly designed to circumvent the errors and sins to which scientists, being human, are vulnerable.

After that slippery performance, it’s all smooth sailing — or so Pinker thinks — because all he has to do is point out all the good things about science. And if scientism=science, then scientism is good, right?

Wrong. Scientism remains indefensible, and there’s a lot of scientism in what passes for science. You don’t need to take my word for it; Pinker’s own words tell the tale.

But, first, let’s get clear about the meaning and fallaciousness of scientism. The various writers cited by Pinker describe it well, but Hayek probably offers the most thorough indictment of it; for example:

[W]e shall, wherever we are concerned … with slavish imitation of the method and language of Science, speak of “scientism” or the “scientistic” prejudice…. It should be noted that, in the sense in which we shall use these terms, they describe, of course, an attitude which is decidedly unscientific in the true sense of the word, since it involves a mechanical and uncritical application of habits of thought to fields different from those in which they have been formed. The scientistic as distinguished from the scientific view is not an unprejudiced but a very prejudiced approach which, before it has considered its subject, claims to know what is the most appropriate way of investigating it…..

The blind transfer of the striving for quantitative measurements to a field in which the specific conditions are not present which give it its basic importance in the natural sciences, is the result of an entirely unfounded prejudice. It is probably responsible for the worst aberrations and absurdities produced by scientism in the social sciences. It not only leads frequently to the selection for study of the most irrelevant aspects of the phenomena because they happen to be measurable, but also to “measurements” and assignments of numerical values which are absolutely meaningless. What a distinguished philosopher recently wrote about psychology is at least equally true of the social sciences, namely that it is only too easy “to rush off to measure something without considering what it is we are measuring, or what measurement means. In this respect some recent measurements are of the same logical type as Plato’s determination that a just ruler is 729 times as happy as an unjust one.”…

Closely connected with the “objectivism” of the scientistic approach is its methodological collectivism, its tendency to treat “wholes” like “society” or the “economy,” “capitalism” (as a given historical “phase”) or a particular “industry” or “class” or “country” as definitely given objects about which we can discover laws by observing their behavior as wholes. While the specific subjectivist approach of the social sciences starts … from our knowledge of the inside of these social complexes, the knowledge of the individual attitudes which form the elements of their structure, the objectivism of the natural sciences tries to view them from the outside ; it treats social phenomena not as something of which the human mind is a part and the principles of whose organization we can reconstruct from the familiar parts, but as if they were objects directly perceived by us as wholes….

The belief that human history, which is the result of the interaction of innumerable human minds, must yet be subject to simple laws accessible to human minds is now so widely held that few people are at all aware what an astonishing claim it really implies. Instead of working patiently at the humble task of rebuilding from the directly known elements the complex and unique structures which we find in the world, and of tracing from the changes in the relations between the elements the changes in the wholes, the authors of these pseudo-theories of history pretend to be able to arrive by a kind of mental short cut at a direct insight into the laws of succession of the immediately apprehended wholes. However doubtful their status, these theories of development have achieved a hold on public imagination much greater than any of the results of genuine systematic study. “Philosophies” or “theories” of history (or “historical theories”) have indeed become the characteristic feature, the “darling vice” of the 19th century. From Hegel and Comte, and particularly Marx, down to Sombart and Spengler these spurious theories came to be regarded as representative results of social science; and through the belief that one kind of “system” must as a matter of historical necessity be superseded by a new and different “system,” they have even exercised a profound influence on social evolution. This they achieved mainly because they looked like the kind of laws which the natural sciences produced; and in an age when these sciences set the standard by which all intellectual effort was measured, the claim of these theories of history to be able to predict future developments was regarded as evidence of their pre-eminently scientific character. Though merely one among many characteristic 19th century products of this kind, Marxism more than any of the others has become the vehicle through which this result of scientism has gained so wide an influence that many of the opponents of Marxism equally with its adherents are thinking in its terms. (Friedrich A. Hayek, The Counter Revolution Of Science [Kindle Locations 120-1180], The Free Press.)

After a barrage like that (and this), what’s a defender of scientism to do? Pinker’s tactic is to stop using “scientism” and start using “science.” This makes it seem as if he really isn’t defending scientism, but rather trying to show how science can shed light onto subjects that are usually not in the province of science. In reality, Pinker preaches scientism by calling it science.

For example:

The new sciences of the mind are reexamining the connections between politics and human nature, which were avidly discussed in Madison’s time but submerged during a long interlude in which humans were assumed to be blank slates or rational actors. Humans, we are increasingly appreciating, are moralistic actors, guided by norms and taboos about authority, tribe, and purity, and driven by conflicting inclinations toward revenge and reconciliation.

There is nothing new in this, as Pinker admits by adverting to Madison. Nor was the understanding of human nature “submerged” except in the writings of scientistic social “scientists.” We ordinary mortals were never fooled. Moreover, Pinker’s idea of scientific political science seems to be data-dredging:

With the advent of data science—the analysis of large, open-access data sets of numbers or text—signals can be extracted from the noise and debates in history and political science resolved more objectively.

As explained here, data-dredging is about as scientistic as it gets:

When enough hypotheses are tested, it is virtually certain that some falsely appear statistically significant, since every data set with any degree of randomness contains some spurious correlations. Researchers using data mining techniques if they are not careful can be easily misled by these apparently significant results, even though they are mere artifacts of random variation.

Turning to the humanities, Pinker writes:

[T]here can be no replacement for the varieties of close reading, thick description, and deep immersion that erudite scholars can apply to individual works. But must these be the only paths to understanding? A consilience with science offers the humanities countless possibilities for innovation in understanding. Art, culture, and society are products of human brains. They originate in our faculties of perception, thought, and emotion, and they cumulate [sic] and spread through the epidemiological dynamics by which one person affects others. Shouldn’t we be curious to understand these connections? Both sides would win. The humanities would enjoy more of the explanatory depth of the sciences, to say nothing of the kind of a progressive agenda that appeals to deans and donors. The sciences could challenge their theories with the natural experiments and ecologically valid phenomena that have been so richly characterized by humanists.

What on earth is Pinker talking about? This is over-the-top bafflegab worthy of Professor Irwin Corey. But because it comes from the keyboard of a noted (self-promoting) academic, we are meant to take it seriously.

Yes, art, culture, and society are products of human brains. So what? Poker is, too, and it’s a lot more amenable to explication by the mathematical tools of science. But the successful application of those tools depends on traits that are more art than science (bluffing, spotting “tells,” avoiding “tells,” for example).

More “explanatory depth” in the humanities means a deeper pile of B.S. Great art, literature, and music aren’t concocted formulaically. If they could be, modernism and postmodernism wouldn’t have yielded mountains of trash.

Oh, I know: It will be different next time. As if the tools of science are immune to misuse by obscurantists, relativists, and practitioners of political correctness. Tell it to those climatologists who dare to challenge the conventional wisdom about anthropogenic global warming. Tell it to the “sub-human” victims of the Third Reich’s medical experiments and gas chambers.

Pinker anticipates this kind of objection:

At a 2011 conference, [a] colleague summed up what she thought was the mixed legacy of science: the eradication of smallpox on the one hand; the Tuskegee syphilis study on the other. (In that study, another bloody shirt in the standard narrative about the evils of science, public-health researchers beginning in 1932 tracked the progression of untreated, latent syphilis in a sample of impoverished African Americans.) The comparison is obtuse. It assumes that the study was the unavoidable dark side of scientific progress as opposed to a universally deplored breach, and it compares a one-time failure to prevent harm to a few dozen people with the prevention of hundreds of millions of deaths per century, in perpetuity.

But the Tuskegee study was only a one-time failure in the sense that it was the only Tuskegee study. As a type of failure — the misuse of science (witting and unwitting) — it goes hand-in-hand with the advance of scientific knowledge. Should science be abandoned because of that? Of course not. But the hard fact is that science, qua science, is powerless against human nature, which defies scientific control.

Pinker plods on by describing ways in which science can contribute to the visual arts, music, and literary scholarship:

The visual arts could avail themselves of the explosion of knowledge in vision science, including the perception of color, shape, texture, and lighting, and the evolutionary aesthetics of faces and landscapes. Music scholars have much to discuss with the scientists who study the perception of speech and the brain’s analysis of the auditory world.

As for literary scholarship, where to begin? John Dryden wrote that a work of fiction is “a just and lively image of human nature, representing its passions and humours, and the changes of fortune to which it is subject, for the delight and instruction of mankind.” Linguistics can illuminate the resources of grammar and discourse that allow authors to manipulate a reader’s imaginary experience. Cognitive psychology can provide insight about readers’ ability to reconcile their own consciousness with those of the author and characters. Behavioral genetics can update folk theories of parental influence with discoveries about the effects of genes, peers, and chance, which have profound implications for the interpretation of biography and memoir—an endeavor that also has much to learn from the cognitive psychology of memory and the social psychology of self-presentation. Evolutionary psychologists can distinguish the obsessions that are universal from those that are exaggerated by a particular culture and can lay out the inherent conflicts and confluences of interest within families, couples, friendships, and rivalries that are the drivers of plot.

I wonder how Rembrandt and the Impressionists (among other pre-moderns) managed to create visual art of such evident excellence without relying on the kinds of scientific mechanisms invoked by Pinker. I wonder what music scholars would learn about excellence in composition that isn’t already evident in the general loathing of audiences for most “serious” modern and contemporary music.

As for literature, great writers know instinctively and through self-criticism how to tell stories that realistically depict character, social psychology, culture, conflict, and all the rest. Scholars (and critics), at best, can acknowledge what rings true and has dramatic or comedic merit. Scientistic pretensions in scholarship (and criticism) may result in promotions and raises for the pretentious, but they do not add to the sum of human enjoyment — which is the real aim of literature.

Pinker inveighs against critics of scientism (science, in Pinker’s vocabulary) who cry “reductionism” and “simplification.” With respect to the former, Pinker writes:

Demonizers of scientism often confuse intelligibility with a sin called reductionism. But to explain a complex happening in terms of deeper principles is not to discard its richness. No sane thinker would try to explain World War I in the language of physics, chemistry, and biology as opposed to the more perspicuous language of the perceptions and goals of leaders in 1914 Europe. At the same time, a curious person can legitimately ask why human minds are apt to have such perceptions and goals, including the tribalism, overconfidence, and sense of honor that fell into a deadly combination at that historical moment.

It is reductionist to explain a complex happening in terms of a deeper principle when that principle fails to account for the complex happening. Pinker obscures that essential point by offering a silly and irrelevant example about World War I. This bit of misdirection is unsurprising, given Pinker’s foray into reductionism, The Better Angels of Our Nature: Why Violence Has Declined, which I examine here.

As for simplification, Pinker says:

The complaint about simplification is misbegotten. To explain something is to subsume it under more general principles, which always entails a degree of simplification. Yet to simplify is not to be simplistic.

Pinker again dodges the issue. Simplification is simplistic when the “general principles” fail to account adequately for the phenomenon in question.

If Pinker is right about anything, it is when he says that “the intrusion of science into the territories of the humanities has been deeply resented.” The resentment, though some of it may be wrongly motivated, is fully justified.

Related reading (added 08/10/13 and 09/06/13):
Bill Vallicella, “Steven Pinker on Scientism, Part One,” Maverick Philosopher, August 10, 2013
Leon Wieseltier, “Crimes Against Humanities,” The New Republic, September 3, 2013 (gated)

Related posts about Pinker:
Nonsense about Presidents, IQ, and War
The Fallacy of Human Progress

Related posts about modernism:
Speaking of Modern Art
Making Sense about Classical Music
An Addendum about Classical Music
My Views on Classical Music, Vindicated
But It’s Not Music
A Quick Note about Music
Modernism in the Arts and Politics
Taste and Art
Modernism and the Arts

Related posts about science:
Science’s Anti-Scientific Bent
Modeling Is Not Science
Physics Envy
We, the Children of the Enlightenment
Demystifying Science
Analysis for Government Decision-Making: Hemi-Science, Hemi-Demi-Science, and Sophistry
Scientism, Evolution, and the Meaning of Life
The Candle Problem: Balderdash Masquerading as Science
Mysteries: Sacred and Profane
The Glory of the Human Mind

Pseudoscience, “Moneyball,” and Luck

Orin Kerr of The Volokh Conspiracy endorses the following clap-trap, uttered by Michael Lewis (author of Liar’s Poker and Moneyball) in the course of a commencement speech at Princeton University:

A few years ago, just a few blocks from my home, a pair of researchers in the Cal psychology department staged an experiment. They began by grabbing students, as lab rats. Then they broke the students into teams, segregated by sex. Three men, or three women, per team. Then they put these teams of three into a room, and arbitrarily assigned one of the three to act as leader. Then they gave them some complicated moral problem to solve: say what should be done about academic cheating, or how to regulate drinking on campus.

Exactly 30 minutes into the problem-solving the researchers interrupted each group. They entered the room bearing a plate of cookies. Four cookies. The team consisted of three people, but there were these four cookies. Every team member obviously got one cookie, but that left a fourth cookie, just sitting there. It should have been awkward. But it wasn’t. With incredible consistency the person arbitrarily appointed leader of the group grabbed the fourth cookie, and ate it. Not only ate it, but ate it with gusto: lips smacking, mouth open, drool at the corners of their mouths. In the end all that was left of the extra cookie were crumbs on the leader’s shirt.

This leader had performed no special task. He had no special virtue. He’d been chosen at random, 30 minutes earlier. His status was nothing but luck. But it still left him with the sense that the cookie should be his.

So far, sort of okay. But then:

This experiment helps to explain Wall Street bonuses and CEO pay, and I’m sure lots of other human behavior. But it also is relevant to new graduates of Princeton University. In a general sort of way you have been appointed the leader of the group. Your appointment may not be entirely arbitrary. But you must sense its arbitrary aspect: you are the lucky few. Lucky in your parents, lucky in your country, lucky that a place like Princeton exists that can take in lucky people, introduce them to other lucky people, and increase their chances of becoming even luckier. Lucky that you live in the richest society the world has ever seen, in a time when no one actually expects you to sacrifice your interests to anything.

All of you have been faced with the extra cookie. All of you will be faced with many more of them. In time you will find it easy to assume that you deserve the extra cookie. For all I know, you may. But you’ll be happier, and the world will be better off, if you at least pretend that you don’t.

Never forget: In the nation’s service. In the service of all nations.

Thank you.

And good luck.

I am unsurprised by Kerr’s endorsement of Lewis’s loose logic, given Kerr’s rather lackadaisical attitude toward the Constitution (e.g., this post).

Well, what could be wrong with the experiment or Lewis’s interpretation of it? The cookie experiment does not mean what Lewis thinks it means. It is like the Candle Problem in that Lewis  draws conclusions that are unwarranted by the particular conditions of the experiment. And those conditions are so artificial as to be inapplicable to real situations. Thus:

1. The  teams and their leaders were chosen randomly. Businesses, governments, universities, and other voluntary organizations do not operate that way. Members choose themselves. Leaders (in business, at least) are either self-chosen (if they are owners) or chosen by higher-ups on the basis of past performance and what it says (imperfectly) about future performance.

2. Because managers of businesses are not arbitrarily chosen, there is no analogy to the team leaders in the experiment, who were arbitrarily chosen and who arbitrarily consumed the fourth cookie. For one thing, if a manager reaps a greater reward than his employees, that is because the higher-ups value the manager’s contributions more than those of his employees. That is an unsurprising relationship, when you think about it, but it bears no resemblance to the case of a randomly chosen team with a randomly chosen leader.

3. Being the beneficiary of some amount of luck in one’s genetic and environmental inheritance does not negate the fact that one must do something with that luck to reap material rewards. The “extra cookie,” as I have said, is generally produced and earned, not simply put on a plate to be gobbled. If a person earns more cookies because he is more productive, and if he is more productive (in part) because of his genetic and environmental inheritance, that person’s great earning power (over the long haul) is based on the value of what he produces. He does not take from others (as Lewis implies), nor does he owe to others a share of what he earns (as Lewis implies).

Just to drive home the point about Lewis’s cluelessness, I will address his book Moneyball, from which a popular film of the same name was derived. This is Amazon.com‘s review of the book:

Billy Beane, general manager of MLB’s Oakland A’s and protagonist of Michael Lewis’s Moneyball, had a problem: how to win in the Major Leagues with a budget that’s smaller than that of nearly every other team. Conventional wisdom long held that big name, highly athletic hitters and young pitchers with rocket arms were the ticket to success. But Beane and his staff, buoyed by massive amounts of carefully interpreted statistical data, believed that wins could be had by more affordable methods such as hitters with high on-base percentage and pitchers who get lots of ground outs. Given this information and a tight budget, Beane defied tradition and his own scouting department to build winning teams of young affordable players and inexpensive castoff veterans.

Lewis was in the room with the A’s top management as they spent the summer of 2002 adding and subtracting players and he provides outstanding play-by-play…. Lewis, one of the top nonfiction writers of his era (Liar’s Poker, The New New Thing), offers highly accessible explanations of baseball stats and his roadmap of Beane’s economic approach makes Moneyball an appealing reading experience for business people and sports fans alike.

The only problems with Moneyball are (a) its essential inaccuracy and (b) its incompleteness as an analysis of success in baseball.

On the first point, “moneyball” did not start with Billy Beane and the Oakland A’s, and it is not what it is made out to be. Enter Eric Walker, the subject and author of “The Forgotten Man of Moneyball, Part 1,” and “The Forgotten Man of Moneyball, Part 2,” published October 7, 2009, on a site at deadspin.com. (On the site’s home page, the title bar displays the following: Deadspin, Sports News without Access, Favor, or Discretion.) Walker’s recollections merit extensive quotation:

…[W]ho am I, and why would I be considered some sort of expert on moneyball? Perhaps you recognized my name; more likely, though, you didn’t. Though it is hard to say this without an appearance of personal petulance, I find it sad that the popular history of what can only be called a revolution in the game leaves out quite a few of the people, the outsiders, who actually drove that revolution.

Anyway, the short-form answer to the question is that I am the fellow who first taught Billy Beane the principles that Lewis later dubbed “moneyball.” For the long-form answer, we ripple-dissolve back in time …

. . . to San Francisco in 1975, where the news media are reporting, often and at length, on the supposed near-certainty that the Giants will be sold and moved. There sit I, a man no longer young but not yet middle-aged, a man who has not been to a baseball game — or followed the sport — for probably over two decades….

With my lady, also a baseball fan of old, I go to a game. We have a great time; we go to more games, have more great times. I am becoming enthused. But I am considering and wondering — wondering about the mechanisms of run scoring, things like the relative value of average versus power…. I go to the San Francisco main library, looking for books that in some way actually analyze baseball. I find one. One. But what a one.

If this were instead Reader’s Digest, my opening of that book would be “The Moment That Changed My Life!” The book was Percentage Baseball, by one Earnshaw Cook, a Johns Hopkins professor who had consulted on the development of the atomic bomb….

…Bill James and some others, who were in high school when Cook was conceiving the many sorts of formulae they would later get famous publicizing in their own works, have had harsh things to say about Cook and his work. James, for example, wrote in 1981, “Cook knew everything about statistics and nothing at all about baseball — and for that reason, all of his answers are wrong, all of his methods useless.” That is breathtakingly wrong, and arrogant. Bill James has done an awful lot for analysis, both in promoting the concepts and in original work (most notably a methodology for converting minor-league stats to major-league equivalents). But, as Chili Davis once remarked about Nolan Ryan, “He ain’t God, man.” A modicum of humility and respect is in order…. Cook’s further work, using computer simulations of games to test theory (recorded in his second book, Percentage Baseball and the Computer), was ground-breaking, and it came long before anyone thought to describe what Cook was up to as “sabermetrics” and longer still before anyone emulated it.

…I wanted to get a lot closer to the game than box seats. I had, some years before, been a radio newscaster and telephone-talk host, and I decided to trade on that background. But in a market like the Bay Area, one does not just walk into a major radio station and ask for a job if it has been years since one’s last position; so, I walked into a minor radio station, a little off-the-wall FM outfit, and instantly became their “sports reporter”; unsalaried, but eligible for press credentials from the Giants….

Meanwhile, however, I was constantly working on expanding Cook’s work in various ways, trying to develop more-practical methods of applying his, and in time my, ideas….

When I felt I had my principles in a practical, usable condition, I started nagging the Giants about their using the techniques. At first, it was a very tough slog; in those days — this would be 1979 or so, well before Bill James’ Abstracts were more than a few hundred mimeographed copies -– even the basic concepts were unknown, and, to old baseball men, they were very, very weird ideas….

In early 1981, as a demonstration, I gave the Giants an extensive analysis of their organization; taking a great risk, I included predictions for the coming season. I have that very document beside me now as I type…. I was, despite the relative crudeness of the methodology in those days, a winner: 440 runs projected, 427 scored; ERA projected, 3.35, ERA achieved, 3.28; errors projected, 103, actual errors committed, 102; and, bottom line, projected wins, 57, actual wins 56….

By this time, I had taken a big step up as a broadcaster, moving from that inconsequential little station to KQED, the NPR outlet in San Francisco, whence I would eventually be syndicated by satellite to 20 NPR affiliates across the country, about half in major markets.

As a first consequence of that move, a book editor who had heard the daily module while driving to work and thought it interesting approached me with a proposal that I write a book in the general style of my broadcasts. I began work in the fall of 1981, and the book, The Sinister First Baseman and Other Observations, was published in 1982, to excellent reviews and nearly no sales. Frank Robinson, then the Giants’ manager and a man I had come to know tolerably well, was kind enough to provide the Foreword for the book, which was a diverse collection of baseball essays….

At any rate, there I was, finally on contract with a major-league ball club, the Giants, but in a dubious situation…. I did persuade them to trade Gary Lavelle to the Blue Jays, but instead of names like John Cerutti and Jimmy Key, whom I had suggested, Haller got Jim Gott, who gave the Giants one good year as a starter and two forgettable years in the pen, plus two guys who never made the majors. But deals for Ken Oberkfell and especially for John Tudor, which I lobbied for intensely, didn’t get made (Haller called 20 minutes too late to get Oberkfell). I still remember then-Giants owner Bob Lurie, when I was actually admitted to the Brain Trust sanctum on trade-deadline day, saying around his cigar, “What’s all this about John Tudor?” (Tudor, then openly available, had a high AL ERA because he was a lefty in Fenway — this was well before “splits” and “park effects” were commonplace concepts — and I tried to explain all that, but no dice; Tudor went on to an NL ERA of 2.66 over seven seasons.)

When Robinson was fired by the Giants, I knew that owing to guilt by association (remember, Robby wrote the Foreword to my book) I would soon be gone, and so I was. My term as a consultant with the Giants was about half a season. In that brief term, I had had some input into a few decisions, but most of what I advocated, while listened to, was never acted on.

But having once crossed the major-league threshold, I was not about to sink back into oblivion. Across the Bay was an organization with a famously more forward-looking front office, with which I had already had contact. I asked, they answered, and so my career with the A’s began.

Modern analysis has shown a whole treasure chest of interesting and often useful performance metrics, but it remains so that the bedrock principle of classic analysis is simple: out-making controls scoring. What I call “classic” analysis is the principles that I presented to the Oakland Athletics in the early 1980s, which governed their thinking through 20 or so successful seasons, and which were dubbed “moneyball” by Michael Lewis in his book of that title. Because of that book, there has arisen a belief that whatever the A’s do is, by definition, “moneyball”; with the decline in their fortunes in recent years has come a corresponding belief that “moneyball” is in decline — dead, some would say [1] — because the A’s and moneyball are seen as essentially one thing.

That is simply wrong…. “Moneyball,” as the name says, is about seeking undervalued commodities [emphasis added]. In my day, what I regard as the crucial aspects of run-generation, notably on-base percentage, were seriously undervalued, so “moneyball” consisted in finding batters with those skills.

A team that today sustains one of the lowest on-base percentages in baseball, and actively acquires players with drastically low career on-base numbers, is very obviously practicing a different “moneyball” than that for which it became famed. Today’s A’s, it seems, see the undervalued commodities as “defense and athletic players drafted out of high school” (as a recent article on the organization put it). These are not your father’s A’s. What success their new tack will have remains to be seen (their present fortunes are a transition state); but “moneyball” as practiced today by the A’s seems no longer to have at its core the same analytic principles that then-GM Sandy Alderson and I worked with a quarter-century ago, and that I presented to Billy Beane in that now semi-famous paper [“Winning Baseball”]….

In 1994, Sandy promoted Billy Beane to assistant GM. At the same time, he asked me to prepare an overview of the general principles of analysis for Billy, so that Billy could get in one sitting an idea of the way the organization was looking at talent. In the end, I delivered a report titled “Winning Baseball,” with the subtitle: “An objective, numerical, analytic analysis of the principles and practices involved in the design of a winning baseball team.” The report was 66 pages long; I still grit my teeth whenever I remember that Michael Lewis described it as a “pamphlet [on page 58 of this edition of Moneyball].”…

My goal in that report, which I seem to have met, was to put the ideas — not the detailed principles, just the ideas — forward in simple, clear language and logical order, so that they would be comprehensible by and reasonable to a working front-office executive. Sandy Alderson didn’t need a document like this, then or at the outset, but he was a Harvard-trained attorney; I considered myself to be writing not just to Billy Beane but to any veteran baseball man (which, as it turned out, was just as well)….

Lewis not only demotes “Winning Baseball” to a pamphlet, but also demotes Walker to passing mention on three pages of Moneyball: 58, 62, and 63 (in the paperback edition linked above). Why would Lewis slight and distort Walker’s contributions to “moneyball”? Remember that Lewis is not a scientist, mathematician, or statistician. He is a journalist with a B.A. in art history who happened to work at Salomon Brothers for a few years. I have read his first book, Liar’s Poker. It is obviously the work of a young man with a grievance and a flair for dramatization. Moneyball is obviously the work of a somewhat older man who has honed his flair for dramatization. Do not mistake it for a rigorous analysis of the origins and effectiveness of “moneyball.”

Just how effective was “moneyball,” as it was practiced by the Oakland Athletics? There is evidence to suggest that it was quite effective. For example:


Sources and notes: Team won-lost records are from Baseball-Reference.com. Estimates of team payrolls are from USA Today’s database of salaries for professional sports teams, which begins in 1988 for major-league baseball (here). The payroll index measures the ratio of each team’s payroll in a given year to the major-league average for the same year.

The more that a team spends on player salaries, the better the team’s record. But payroll accounts for only about 18 percent of the variation in the records of major-league teams during the period 1988-2011. Which means that other factors, taken together, largely determine a team’s record. Among those factors is “moneyball” — the ability to identify, obtain, effectively use, and retain players who are “underpriced” relative to their potential. But the contribution of “moneyball” cannot be teased out of the data because, for one thing, it would be impossible to quantify the extent to which a team actually practices “moneyball.” That said, it is evident that during 1988-2011 the A’s did better than the average team, by the measure of wins per dollar of payroll: Compare the dark green regression line, representing the A’s, with the black regression line, representing all teams.

That is all well and good, but the purpose of a baseball team is not to win a high number of games per dollar of payroll; it is to win — period. By that measure, the A’s of the Alderson-Beane “moneyball” era have been successful, at times, but not uniquely so:


Source: Derived from Baseball-Reference.com.

The sometimes brilliant record of the Athletics franchise during 1901-1950 is owed to one man: Cornelius McGillicuddy (1862-1956). And the often dismal record of the franchise during 1901-1950 is owed to one man: the same Cornelius McGillicuddy. True fans of baseball (and collectors of trivia) know Cornelius McGillicuddy as Connie Mack, or more commonly as Mr. Mack. The latter is an honorific bestowed on Mack because of his dignified mien and distinguished career in baseball: catcher from 1886 to 1896; manager of the Pittsburgh Pirates from 1894 to 1896; manager of the Philadelphia Athletics from 1901 to 1950; part owner and then sole owner of the Athletics from 1901 to 1954.  (He is also an ancestor of two political figures who bear his real name and alias: Connie Mack III and Connie Mack IV.)

Mack’s long leadership and ownership of the A’s is important because it points to the reasons for the A’s successes and failures during the fifty years that he led the team from the bench. Here, from Wikipedia, is a story that is familiar to persons who know their baseball history:

[Mack] was widely praised in the newspapers for his intelligent and innovative managing, which earned him the nickname “the Tall Tactician”. He valued intelligence and “baseball smarts”, always looking for educated players. (He traded away Shoeless Joe Jackson despite his talent because of his bad attitude and unintelligent play.[9]) “Better than any other manager, Mack understood and promoted intelligence as an element of excellence.”[10] He wanted men who were self-directed, self-disciplined and self-motivated; his ideal player was Eddie Collins.[11]

“Mack looked for seven things in a young player: physical ability, intelligence, courage, disposition, will power, general alertness and personal habits.”[12]

He also looked for players with quiet and disciplined personal lives, having seen many players destroy themselves and their teams through heavy drinking in his playing days. Mack himself never drank; before the 1910 World Series he asked all his players to “take the pledge” not to drink during the Series. When Topsy Hartsel told Mack he needed a drink the night before the final game, Mack told him to do what he thought best, but in these circumstances “if it was me, I’d die before I took a drink.”[13]

In any event, his managerial style was not tyrannical but easygoing.[14] He never imposed curfews or bed checks, and made the best of what he had; Rube Waddell was the best pitcher and biggest gate attraction of his first decade as A’s manager, so he put up with his drinking and general unreliability for years until it began to bring the team down and the other players asked Mack to get rid of him.[15]

Mack’s strength as a manager was finding the best players, teaching them well and letting them play. “He did not believe that baseball revolved around managerial strategy.”[10] He was “one of the first managers to work on repositioning his fielders” during the game, often directing the outfielders to move left or right, play shallow or deep, by waving his rolled-up scorecard from the bench.[12] After he became well known for doing this, he often passed his instructions to the fielders by way of other players, and simply waved his scorecard as a feint.[16]

*   *   *

Mack saw baseball as a business, and recognized that economic necessity drove the game. He explained to his cousin, Art Dempsey, that “The best thing for a team financially is to be in the running and finish second. If you win, the players all expect raises.” This was one reason he was constantly collecting players, signing almost anyone to a ten-day contract to assess his talent; he was looking ahead to future seasons when his veterans would either retire or hold out for bigger salaries than Mack could give them.

Unlike most baseball owners, Mack had almost no income apart from the A’s, so he was often in financial difficulties. Money problems – the escalation of his best players’ salaries (due both to their success and to competition from the new, well-financed Federal League), combined with a steep drop in attendance due to World War I — led to the gradual dispersal of his second championship team, the 19101914 team, who [sic] he sold, traded, or released over the years 1915–1917. The war hurt the team badly, leaving Mack without the resources to sign valuable players….

All told, the A’s finished dead last in the AL seven years in a row from 1915 to 1921, and would not reach .500 again until 1926. The rebuilt team won back-to-back championships in 1929–1930 over the Cubs and Cardinals, and then lost a rematch with the latter in 1931. As it turned out, these were the last WS titles and pennants the Athletics would win in Philadelphia or for another four decades.

With the onset of the Great Depression, Mack struggled financially again, and was forced to sell the best players from his second great championship team, such as Lefty Grove and Jimmie Foxx, to stay in business. Although Mack wanted to rebuild again and win more championships, he was never able to do so owing to a lack of funds.

Had an earlier Michael Lewis written Moneyball in the 1950s, as a retrospective on Mack’s career as a manager-owner, that Lewis would have said (correctly) that the A’s successes and failures were directly related to (a) the amount of money spent on the team’s payroll, (b) Connie Mack’s character-based criteria for selecting players, and (c) his particular approach to managing players.  That is quite a different story than the one conveyed by the Moneyball written by the real Lewis.

Which version of Moneyball is correct? No one can say for sure. But the powerful evidence of Connie Mack’s long tenure suggests that it takes a combination of the two versions of Moneyball to be truly successful, that is, to post a winning record year after year. It seems that Lewis (inadvertently) jumped to a conclusion about what makes for a successful baseball team — probably because he was struck by the A’s then-recent success and did not look to the A’s history.

In any event, success through luck is not the moral of Moneyball; the moral is success through deliberate effort. But Michael Lewis ignored the moral of his own “masterwork” when he stood before an audience of Princeton graduates and told them that they are merely (or mainly) lucky. How does one graduate from Princeton merely (or mainly) by being lucky? Does it not require the application of one’s genetic talents? Did not most of the graduates of Princeton arrive there, in the first place, because they had applied their genetic talents well during their years in high school or prep school (and even before that)? Is one’s genetic inheritance merely a matter of luck, or is it the somewhat predictable result of the mating of two persons who were not thrown together randomly, but who had a lot in common — including (most likely) high intelligence?

Just as the cookie experiment invoked by Lewis is a load of pseudoscientific hogwash, the left-wing habit of finding luck at the bottom of every achievement is a load of politically correct hogwash. Worse, it is an excuse for punishing success.

Lewis’s peroration on luck is just a variation on a common left-wing theme: Success is merely a matter of luck, so it is the state’s right and duty to redistribute the spoils of luck.

Related posts:
Moral Luck
The Residue of Choice
Can Money Buy Excellence in Baseball?
Inventing “Liberalism”
Randomness Is Over-Rated
Fooled by Non-Randomness
Accountants of the Soul
Rawls Meets Bentham
Social Justice
Positive Liberty vs. Liberty
More Social Justice
Luck-Egalitarianism and Moral Luck
Nature Is Unfair
Elizabeth Warren Is All Wet
Luck and Baseball, One More Time
The Candle Problem: Balderdash Masquerading as Science
More about Luck and Baseball
Barack Channels Princess SummerFall WinterSpring
Obama’s Big Lie

The Candle Problem: Balderdash Masquerading as Science

UPDATED 04/12/12

The hot new item in management “science” appears to be the Candle Problem. Graham Morehead discusses the problem and its broader, “scientifically” supported conclusions:

The Candle Problem was first presented by Karl Duncker. Published posthumously in 1945, “On problem solving” describes how Duncker provided subjects with a candle, some matches, and a box of tacks. He told each subject to affix the candle to a cork board wall in such a way that when lit, the candle won’t drip wax on the table below (see figure at right). Can you think of the answer?

The only answer that really works is this: 1.Dump the tacks out of the box, 2.Tack the box to the wall, 3.Light the candle and affix it atop the box as if it were a candle-holder. Incidentally, the problem was much easier to solve if the tacks weren’t in the box at the beginning. When the tacks were in the box the participant saw it only as a tack-box, not something they could use to solve the problem. This phenomenon is called “Functional fixedness.”

Sam Glucksberg added a fascinating twist to this finding in his 1962 paper, “Influece of strength of drive on functional fixedness and perceptual recognition.” (Journal of Experimental Psychology 1962. Vol. 63, No. 1, 36-41). He studied the effect of financial incentives on solving the candle problem. To one group he offered no money. To the other group he offered an amount of money for solving the problem fast.

Remember, there are two candle problems. Let the “Simple Candle Problem” be the one where the tacks are outside the box — no functional fixedness. The solution is straightforward. Here are the results for those who solved it:

Simple Candle Problem Mean Times :

  • WITHOUT a financial incentive : 4.99 min
  • WITH a financial incentive : 3.67 min

Nothing unexpected here. This is a classical incentivization effect anybody would intuitively expect.

Now, let “In-Box Candle Problem” refer to the original description where the tacks start off in the box.

In-Box Candle Problem Mean Times :

  • WITHOUT a financial incentive : 7:41 min
  • WITH a financial incentive : 11:08 min

How could this be? The financial incentive made people slower? It gets worse — the slowness increases with the incentive. The higher the monetary reward, the worse the performance! This result has been repeated many times since the original experiment.

Glucksberg and others have shown this result to be highly robust. Daniel Pink calls it a legally provable “fact.” How should we interpret the above results?

When your employees have to do something straightforward, like pressing a button or manning one stage in an assembly line, financial incentives work. It’s a small effect, but they do work. Simple jobs are like the simple candle problem.

However, if your people must do something that requires any creative or critical thinking, financial incentives hurt. The In-Box Candle Problem is the stereotypical problem that requires you to think “Out of the Box,” (you knew that was coming, didn’t you?). Whenever people must think out of the box, offering them a monetary carrot will keep them in that box.

A monetary reward will help your employees focus. That’s the point. When you’re focused you are less able to think laterally. You become dumber. This is not the kind of thing we want if we expect to solve the problems that face us in the 21st century.

All of this is found in a video (to which Morehead links), wherein Daniel Pink (an author and journalist whose actual knowledge of science and business appears to be close to zero) expounds the lessons of the Candle Problem. Pink displays his (no-doubt-profitable) conviction that the Candle Problem and related “science” reveals (a) the utter bankruptcy of capitalism and (b) the need to replace managers with touchy-feely gurus (like himself, I suppose). That Pink has worked for two of the country’s leading anti-capitalist airheads — Al Gore and Robert Reich — should tell you all that you need to know about Pink’s real agenda.

Here are my reasons for sneering at Pink and his ilk:

1. I have been there and done that. That is to say, as a manager, I lived through (and briefly bought into) the touchy-feely fads of the ’80s and ’90s. Think In Search of Excellence, The One Minute Manager, The Seven Habits of Highly Effective People, and so on. What did anyone really learn from those books and the lectures and workshops based on them? A perceptive person would have learned that it is easy to make up plausible stories about the elements of success, and having done so, it is possible to make a lot of money peddling those stories. But the stories are flawed because (a) they are based on exceptional cases; (b) they attribute success to qualitative assessments of behaviors that seem to be present in those exceptional cases; and (c) they do not properly account for the surrounding (and critical) circumstances that really led to success, among which are luck and rare combinations of personal qualities (e.g., high intelligence, perseverance, people-reading skills). In short, Pink and his predecessors are guilty of reductionism and the post hoc ergo propter hoc fallacy.

2. Also at work is an undue generalization about the implications of the Candle Problem. It may be true that workers will perform better — at certain kinds of tasks (very loosely specified) — if they are not distracted by incentives that are related to the performance of those specific tasks. But what does that have to do with incentives in general? Not much, because the Candle Problem is unlike any work situation that I can think of. Tasks requiring creativity are not performed under deadlines of a few minutes; tasks requiring creativity are (usually) assigned to persons who have demonstrated a creative flair, not to randomly picked subjects; most work, even in this day, involves the routine application of protocols and tools that were designed to produce a uniform result of acceptable quality; it is the design of protocols and tools that requires creativity, and that kind of work is not done under the kind of artificial constraints found in the Candle Problem.

3. The Candle Problem, with its anti-incentive “lesson,” is therefore inapplicable to the real world, where incentives play a crucial and positive role:

  • The profit incentive leads firms to invest resources in the development and/or production of things that consumers are willing to buy because those things satisfy wants at the right price.
  • Firms acquire resources to develop and produce things by bidding for those resources, that is, by offering monetary incentives to attract the resources required to make the things that consumers are willing to buy.
  • The incentives (compensation) offered to workers of various kinds (from scientists with doctorates to burger-flippers) are generally commensurate with the contributions made by those workers to the production of things of value to consumers, and to the value placed on those things by consumers.
  • Workers agree to the terms and conditions of employment (including compensation) before taking a job. The incentive for most workers is to keep a job by performing adequately over a sustained period — not by demonstrating creativity in a few minutes. Some workers (but not a large fraction of them) are striving for performance-based commissions, bonuses, and profit-sharing distributions. But those distributions are based on performance over a sustained period, during which the striving workers have plenty of time to think about how they can perform better.
  • Truly creative work is done, for the most part, by persons who are hired for such work on the basis of their credentials (education, prior employment, test results). Their compensation is based on their credentials, initially, and then on their performance over a sustained period. If they are creative, they have plenty of psychological space in which to exercise and demonstrate their creativity.
  • On-the-job creativity — the improvement of protocols and tools by workers using them — does not occur under conditions of the kind assumed in the Candle Problem. Rather, on-the-job creativity flows from actual work and insights about how to do the work better. It happens when it happens, and has nothing to do with artificial time constraints and monetary incentives to be “creative” within those constraints.
  • Pink’s essential pitch is that incentives can be replaced by offering jobs that yield autonomy (self-direction), mastery (the satisfaction of doing difficult things well), and purpose (that satisfaction of contributing to the accomplishment of something important). Well, good luck with that, but I (and millions of other consumers) want what we want, and if workers want to make a living they will just have to provide what we want, not what turns them on. Yes, there is a lot to be said for autonomy, mastery, and purpose, but there is also a lot to be said for getting a paycheck. And, contrary to Pink’s implication, getting a paycheck does not rule out autonomy, mastery, and purpose — where those happen to go with the job.

Pink and company’s “insights” about incentives and creativity are 180 degrees off-target. McDonald’s could use the Candle Problem to select creative burger-flippers who will perform well under tight deadlines because their compensation is unrelated to the creativity of their burger-flipping. McDonald’s customers should be glad that McDonald’s has taken creativity out of the picture by reducing burger-flipping to the routine application of protocols and tools.

UPDATE:

In an e-mail to a friend, I put it this way:

The Candle Problem is an interesting experiment, and probably valid with respect to the performance of specific tasks against tight deadlines. I think the results apply whether the stakes are money or any other kind of prize. The experiment illustrates the “choke” factor, and nothing more profound than that.

I question whether the experiment applies to the usual kind of incentive (e.g., a commissions or bonus), where the “incentee” has ample time (months, years) for reflection and research that will enable him to improve his performance and attain a bigger commission or bonus (which usually isn’t an all-or-nothing arrangement).

There’s also the dissimilarity of the Candle Problem — which involves more-or-less randomly chosen subjects, working against an artificial deadline — and actual creative thinking — usually involving persons who are experts (even if the expertise is as mundane as ditch-digging), working against looser deadlines or none at all.

Demystifying Science

“Science” is an unnecessarily daunting concept to the uninitiated, which is to say, almost everyone. Because scientific illiteracy is rampant, advocates of policy positions — scientists and non-scientists alike — often are able to invoke “science” wantonly, thus lending unwarranted authority to their positions.

WHAT IS SCIENCE?

Science is knowledge, but not all knowledge is science. A scientific body of knowledge is systematic; that is, the granular facts or phenomena which comprise the body of knowledge are connected in patterned ways. Moreover, the facts or phenomena represent reality; they are not mere concepts, which may be tools of science but are not science. Beyond that, science — unless it is a purely descriptive body of knowledge — is predictive about the characteristics of as-yet unobserved phenomena. These may be things that exist but have not yet been measured (in terms of the applicable science), or things that are yet to be (as in the effects of new drug on a disease).

Above all, science is not a matter of “consensus” — AGW zealots to the contrary notwithstanding. Science is a matter of rigorously testing theories against facts, and doing it openly. Imagine the state of physics today if Galileo had been unable to question Aristotle’s theory of gravitation, if Newton had been unable to extend and generalize Galileo’s work, and if Einstein had deferred to Newton. The effort to “deny” a prevailing or popular theory is as old as science. There have been “deniers’ in the thousands, each of them responsible for advancing some aspect of knowledge. Not all “deniers” have been as prominent as Einstein (consider Dan Schectman, for example), but each is potentially as important as Einstein.

It is hard for scientists to rise above their human impulses. Einstein, for example, so much wanted quantum physics to be deterministic rather than probabilistic that he said “God does not play dice with the universe.” To which Nils Bohr replied, “Einstein, stop telling God what to do.” But the human urge to be “right” or to be on the “right side” of an issue does not excuse anti-scientific behavior, such as that of so-called scientists who have become invested in AGW.

There are many so-called scientists who subscribe to AGW without having done relevant research. Why? Because AGW is the “in” thing, and they do not wish to be left out. This is the stuff of which “scientific consensus” is made. If you would not buy a make of automobile just because it is endorsed by a celebrity who knows nothing about automotive engineering, why would you “buy” AGW just because it is endorsed by a herd of so-called scientists who have never done research that bears directly on it?

There are two lessons to take from this. The first is  that no theory is ever proven. (A theory may, if it is well and openly tested, be useful guide to action in certain rigorous disciplines, such as engineering and medicine.) Any theory — to be a truly scientific one — must be capable of being tested, even by (and especially by) others who are skeptical of the theory. Those others must be able to verify the facts upon which the theory is predicated, and to replicate the tests and calculations that seem to validate the theory. So-called scientists who restrict access to their data and methods are properly thought of as cultists with a political agenda, not scientists. Their theories are not to be believed — and certainly are not to be taken as guides to action.

The second lesson is that scientists are human and fallible. It is in the best tradition of science to distrust their claims and to dismiss their non-scientific utterances.

THE ROLE OF MATHEMATICS AND STATISTICS IN SCIENCE

Mathematics and statistics are not sciences, despite their vast and organized complexity. They offer ways of thinking about and expressing knowledge, but they are not knowledge. They are languages that enable scientists to converse with each other and outsiders who are fluent in the same languages.

Expressing a theory in mathematical terms may lend the theory a scientific aura. But a theory couched in mathematics (or its verbal equivalent) is not a scientific one unless (a) it can be tested against observable facts by rigorous statistical methods, (b) it is found, consistently, to accord with those facts, and (c) the introduction of new facts does not require adjustment or outright rejection of the theory. If the introduction of new facts requires the adjustment of a theory, then it is a new theory, which must be tested against new facts, and so on.

This “inconvenient fact” — that an adjusted theory is a new theory —  is ignored routinely, especially in the application of regression analysis to a data set for the purpose of quantifying relationships among variables. If a “model” thus derived does a poor job when applied to data outside the original set, it is not an uncommon practice to combine the original and new data and derive a new “model” based on the combined set. This practice (sometimes called data-mining) does not yield scientific theories with predictive power; it yields information (of dubious value) about the the data employed in the regression analysis. As a critic of regression models once put it: Regression is a way of predicting the past with great certainty.

A science may be descriptive rather than mathematical. In a descriptive science (e.g., plant taxonomy), particular phenomena sometimes are described numerically (e.g., the number of leaves on the stem of a species), but the relations among various phenomena are not reducible to mathematics. Nevertheless, a predominantly descriptive discipline will be scientific if the phenomena within its compass are connected in patterned ways.

NON-SCIENCE, SCIENCE, AND PSEUDO-SCIENCE

Non-scientific disciplines can be useful, whereas some purportedly scientific disciplines verge on charlatanism. Thus, for example:

  • History, by my reckoning, is not a science. But a knowledge of history is valuable, nevertheless, for the insights it offers into the influence of human nature on the outcomes of economic and political processes. I call the lessons of history “insights,” not scientific relationships, because history is influenced by so many factors that it does not allow for the rigorous testing of hypotheses.
  • Physics is a science in most of its sub-disciplines, but there are some (e.g., cosmology and certain interpretations of quantum mechanics) where it descends into the realm of speculation. Informed, fascinating speculation to be sure, but speculation all the same. It avoids being pseudo-scientific only because it might give rise to testable hypotheses.
  • Economics is a science only to the extent that it yields valid, statistical insights about specific microeconomic issues (e.g., the effects of laws and regulations on the prices and outputs of goods and services). The postulates of macroeconomics, except to the extent that they are truisms, have no demonstrable validity. (See, for example, my treatment of the Keynesian multiplier.) Macroeconomics is a pseudo-science.

CONCLUSION

There is no such thing as “science,” writ large; that is, no one may appeal, legitimately, to “science” in the abstract. A particular discipline may be a science, but it is a science only to the extent that it comprises a factual body of knowledge and testable theories. Further, its data and methods must be open to verification and testing. And only a particular theory — one that has been put to the proper tests — can be called a scientific one.

For the reasons adduced in this post, scientists who claim to “know” that there is no God are not practicing science when they make that claim. They are practicing the religion that is known as atheism. The existence or non-existence of God is beyond testing, at least by any means yet known to man.

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Words of Caution for Scientific Dogmatists
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Debunking “Scientific Objectivity”
Pseudo-Science in the Service of Political Correctness
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The Universe . . . Four Possibilities
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Re: Climate “Science”
More Evidence against Anthropogenic Global Warming
Yet More Evidence against Anthropogenic Global Warming
A Non-Believer Defends Religion
Evolution as God?
Modeling Is Not Science
Anthropogenic Global Warming Is Dead, Just Not Buried Yet
Beware the Rare Event
Landsburg Is Half-Right
Physics Envy
The Unreality of Objectivism
What Is Truth?
Evolution, Human Nature, and “Natural Rights”
More Thoughts about Evolutionary Teleology
A Digression about Probability and Existence
More about Probability and Existence
Existence and Creation
We, the Children of the Enlightenment
Probability, Existence, and Creation
The Atheism of the Gaps
Probability, Existence, and Creation: A Footnote