The Big Picture: Getting Skeptical About Global Warming Skepticism

Skeptical Science
Getting Skeptical About Global Warming Skepticism

The Big Picture

Posted on 24 September 2010 by dana1981

Oftentimes we get bogged down discussing one of the many pieces of evidence behind man-made global warming, and in the process we can't see the forest for the trees. It's important to every so often take a step back and see how all of those trees comprise the forest as a whole. Skeptical Science provides an invaluable resource for examining each individual piece of climate evidence, so let's make use of these individual pieces to see how they form the big picture.

The Earth is warming

We know the planet is warming from surface temperature stations and satellites measuring the temperature of the Earth's surface and lower atmosphere. We also have various tools which have measured the warming of the Earth's oceans. Satellites have measured an energy imbalance at the top of the Earth's atmosphere. Glaciers, sea ice, and ice sheets are all receding. Sea levels are rising. Spring is arriving sooner each year. There's simply no doubt - the planet is warming.

And yes, the warming is continuing. The 2000s were hotter than the 1990s, which were hotter than the 1980s, which were hotter than the 1970s. 2010 is on pace to be at least in the top 3 hottest calendar years on record. In fact, the 12-month running average global temperature broke the record 3 times in 2010, according to NASA GISS data. Sea levels are still rising, ice is still receding, spring is still coming earlier, there's still a planetary energy imbalance, etc. etc. Contrary to what some would like us to believe, the planet has not magically stopped warming.

Humans are causing this warming

There is overwhelming evidence that humans are the dominant cause of this warming, mainly due to our greenhouse gas emissions. Based on fundamental physics and math, we can quantify the amount of warming human activity is causing, and verify that we're responsible for essentially all of the global warming over the past 3 decades. In fact we expect human greenhouse gas emissions to cause more warming than we've thus far seen, due to the thermal inertia of the oceans (the time it takes to heat them). Human aerosol emissions are also offsetting a significant amount of the warming by causing global dimming.

There are numerous 'fingerprints' which we would expect to see from an increased greenhouse effect (i.e. more warming at night, at higher latitudes, upper atmosphere cooling) that we have indeed observed. Climate models have projected the ensuing global warming to a high level of accuracy, verifying that we have a good understanding of the fundamental physics behind climate change.

Sometimes people ask "what would it take to falsify the man-made global warming theory?". Well, basically it would require that our fundamental understanding of physics be wrong, because that's what the theory is based on. This fundamental physics has been scrutinized through scientific experiments for decades to centuries.

The warming will continue

We also know that if we continue to emit large amounts of greenhouse gases, the planet will continue to warm. We know that the climate sensitivity to a doubling of atmospheric CO₂ from the pre-industrial level of 280 parts per million by volume (ppmv) to 560 ppmv (we're currently at 390 ppmv) will cause 2–4.5°C of warming. And we're headed for 560 ppmv in the mid-to-late 21st century if we continue business-as-usual emissions.

The net result will be bad

There will be some positive results of this continued warming. For example, an open Northwest Passage, enhanced growth for some plants and improved agriculture at high latitudes (though this will require use of more fertilizers), etc. However, the negatives will almost certainly outweigh the positives, by a long shot. We're talking decreased biodiversity, water shortages, increasing heat waves (both in frequency and intensity), decreased crop yields due to these impacts, damage to infrastructure, displacement of millions of people, etc.

Arguments to the contrary are superficial

One thing I've found in reading skeptic criticisms of climate science is that they're consistently superficial. For example, the criticisms of James Hansen's 1988 global warming projections never go beyond "he was wrong", when in reality it's important to evaluate what caused the discrepancy between his projections and actual climate changes, and what we can learn from this. And those who argue that "it's the Sun" fail to comprehend that we understand the major mechanisms by which the Sun influences the global climate, and that they cannot explain the current global warming trend. And those who argue "it's just a natural cycle" can never seem to identify exactly which natural cycle can explain the current warming, nor can they explain how our understanding of the fundamental climate physics is wrong.

There are legitimate unresolved questions

Much ado is made out of the expression "the science is settled." My personal opinion is that the science is settled in terms of knowing that the planet is warming dangerously rapidly, and that humans are the dominant cause.

There are certainly unresolved issues. There's a big difference between a 2°C and a 4.5°C warming for a doubling of atmospheric CO₂, and it's an important question to resolve, because we need to know how fast the planet will warm in order to know how fast we need to reduce our greenhouse gas emissions. There are significant uncertainties in some feedbacks which play into this question. For example, will clouds act as a net positive feedback (by trapping more heat, causing more warming) or negative feedback (by reflecting more sunlight, causing a cooling effect) as the planet continues to warm?

These are the sorts of questions we should be debating, and the issues that most climate scientists are investigating. Unfortunately there is a large segment of the population which is determined to continue arguing the resolved questions for which the science has already been settled. And when climate scientists are forced to respond to the constant propagation of misinformation on these settled issues, it just detracts from our investigation of the legitimate, unresolved, important questions.

The Big Picture

The big picture is that we know the planet is warming, humans are causing it, there is a substantial risk to continuing on our current path, but we don't know exactly how large the risk is. However, uncertainty regarding the magnitude of the risk is not an excuse to ignore it. We also know that if we continue on a business-as-usual path, the risk of catastrophic consequences is very high. In fact, the larger the uncertainty, the greater the potential for the exceptionally high risk scenario to become reality. We need to continue to decrease the uncertainty, but it's also critical to acknowledge what we know and what questions have been resolved, and that taking no action is not an option.

Newcomers, Start Here

Posted on 15 August 2010 by John Cook

Skeptical Science is based on the notion that science by its very nature is skeptical. Genuine skepticism means you don't take someone's word for it but investigate for yourself. You look at all the facts before coming to a conclusion. In the case of climate science, our understanding of climate comes from considering the full body of evidence.

In contrast, climate skepticism looks at small pieces of the puzzle while neglecting the full picture. Climate skeptics vigorously attack any evidence for man-made global warming yet uncritically embrace any argument, op-ed, blog or study that refutes global warming. If you began with a position of climate skepticism then cherrypick the data that supports your view while fighting tooth and nail against any evidence that contradicts that position, I'm sorry but that's not genuine scientific skepticism.

So the approach of Skeptical Science is as follows. It looks at the many climate skeptic arguments, exposes how they focus on small pieces of the puzzle and then puts them in their proper context by presenting the full picture. The skeptic arguments are listed by popularity (eg - how often each argument appears in online articles). For the more organised mind, they're also sorted into taxonomic categories.

Good starting points for newbies

If you're new to the climate debate (or are of the mind that there's no evidence for man-made global warming), a good starting point is 10 Indicators of Global Warming which lays out the evidence that warming is happening and the follow-up article, 10 Human Fingerprints on Climate Change which lays out the evidence that humans are the cause. More detail is available in empirical evidence that humans are causing global warming. Contrary to what you may have heard, the case for man-made global warming doesn't hang on models or theory - it's built on direct measurements of many different parts of the climate, all pointing to a single, coherent answer.

Smart Phone Apps

For smart phone users, the rebuttals to all the skeptic arguments are also available on a number of mobile platforms. The first Skeptical Science app was an iPhone app, released in February 2010. This is updated regularly with the latest content from the website and very accessible in a beautifully designed interface by Shine Technologies. Shine Tech then went on to create a similar Android app which has some extra features missing from the iPhone version. A Nokia app was also created by Jean-François Barsoum (this was one of the 10 finalists in the Calling All Innovators competition).

As well as the list of rebuttals, Skeptical Science also has a blog where the latest research and developments are examined and discussed. Comments are welcome and the level of discussion is of a fairly high quality thanks to a fairly strict Comments Policy. You need to register a user account to post comments. One thing many regulars are not aware of is you can edit your user account details (to get to this page, click on your username in the left margin).

Keep up to date by email, RSS, Facebook or Twitter

To keep up to date on latest additions to the website, sign up to receive new blog posts by email. There's an RSS feed for blog posts and for the engaged commenter, a feed for new user comments. I recommend you follow the Skeptical Science Twitter page as I not only tweet latest blog posts but also any other interesting climate links I happen upon throughout the day. New blog posts are also added to our Facebook page.

About John Cook

Lastly, for those wondering about who runs Skeptical Science, the website is maintained by John Cook. I studied physics at the University of Queensland but currently, I'm not a professional scientist - I run this website as a layman. People sometimes wonder why I spend so much time on this site and which group backs me. No group funds me. I receive no funding other than the occasional Paypal donations. As the lack of funding limits how much time I can spend developing the site, donations are appreciated. My motivations are two-fold: as a parent, I care about the world my daughter will grow up in and as a Christian, I feel a strong obligation to the poor and vulnerable who are hardest hit by climate change. Of course these are very personal reasons - I'm sure everyone comes at this from different angles. I go more deeply into my motivations in Why I care about climate change.

The SkS Team

However, there are many more who make invaluable contributions to Skeptical Science. There are a number of authors who write blog posts and are currently in the process of writing all the rebuttals in plain English. Translators from all over the world have translated the rebuttals into 15 different languages. There have been contributors to the one-line responses to skeptic arguments, proofreaders, technical support from boffins who understand computers a lot better than myself and commenters whose feedback have helped improve and hone the website's content. Skeptical Science has evolved from a small blog into a community of intelligent, engaged people with a commitment to science and our climate.

Soft sciences are often harder than hard sciences

The University of Alabama

Soft sciences are often harder than hard sciences
Discover (1987, August) by Jared Diamond

n ''The overall correlation between frustration and instability (in 62 countries of the world) was 0.50.'' --Samuel Huntington, professor of government, Harvard

n ''This is utter nonsense. How does Huntington measure things like social frustration? Does he have a social-frustration meter? I object to the academy's certifying as science what are merely political opinions.'' -- Serge Lang, professor of mathematics, Yale

n ''What does it say about Lang's scientific standards that he would base his case on twenty-year-old gossip?'' . . . ''a bizarre vendetta'' . . . ''a madman . . .'' -- Other scholars, commenting on Lang's attack

For those who love to watch a dogfight among intellectuals supposedly above such things, it's been a fine dogfight, well publicized in Time and elsewhere. In one corner, political scientist and co-author of The Crisis of Democracy, Samuel Huntington. In the other corner, mathematician and author of Diophantine Approximation on Abelian Varieties with Complex Multiplication, Serge Lang. The issue: whether Huntington should be admitted, over Lang's opposition, to an academy of which Lang is a member. The score after two rounds: Lang 2, Huntington 0, with Huntington still out.

Lang vs. Huntington might seem like just another silly blood-letting in the back alleys of academia, hardly worth anyone's attention. But this particular dogfight is an important one. Beneath the name calling, it has to do with a central question in science: Do the so-called soft sciences, like political science and psychology, really constitute science at all, and do they deserve to stand beside ''hard sciences,'' like chemistry and physics?

The arena is the normally dignified and secretive National Academy of Sciences (NAS), an honor society of more than 1,500 leading American scientists drawn from almost every discipline. NAS's annual election of about 60 new members begins long before each year's spring meeting, with a multi- stage evaluation of every prospective candidate by members expert in the candidate's field. Challenges of candidates by the membership assembled at the annual meeting are rare, because candidates have already been so thoroughly scrutinized by the appropriate experts. In my eight years in NAS, I can recall only a couple of challenges before the Lang-Huntington episode, and not a word about those battles appeared in the press.

At first glance, Huntington's nomination in 1986 seemed a very unlikely one to be challenged. His credentials were impressive: president of the American Political Science Association; holder of a named professorship at Harvard; author of many widely read books, of which one, American Politics: The Promise of Disharmony, got an award from the Association of American Publishers as the best book in the social and behavioral sciences in 1981; and many other distinctions. His studies of developing countries, American politics, and civilian-military relationships received the highest marks from social and political scientists inside and outside NAS. Backers of Huntington's candidacy included NAS members whose qualifications to judge him were beyond question, like Nobel Prize winning computer scientist and psychologist Herbert Simon.

If Huntington seemed unlikely to be challenged, Lang was an even more unlikely person to do the challenging. He had been elected to the academy only a year before, and his own specialty of pure mathematics was as remote as possible from Huntington's specialty of comparative political development. However, as Science magazine described it, Lang had previously assumed for himself ''the role of a sheriff of scholarship, leading a posse of academics on a hunt for error,'' especially in the political and social sciences. Disturbed by what he saw as the use of ''pseudo mathematics'' by Huntington, Lang sent all NAS members several thick mailings attacking Huntington, enclosing photocopies of letters describing what scholar A said in response to scholar B's attack on scholar C, and asking members for money to help pay the postage and copying bills. Under NAS rules, a candidate challenged at an annual meeting is dropped unless his candidacy is sustained by two-thirds of the members present and voting. After bitter debates at both the 1986 and 1987 meetings, Huntington failed to achieve the necessary two-thirds support.

Much impassioned verbiage has to be stripped away from this debate to discern the underlying issue. Regrettably, a good deal of the verbiage had to do with politics. Huntington had done several things that are now anathema in U.S. academia: he received CIA support for some research; he did a study for the State Department in 1967 on political stability in South Vietnam; and he's said to have been an early supporter of the Vietnam war. None of this should have affected his candidacy. Election to NAS is supposed to be based solely on scholarly qualifications; political views are irrelevant. American academics are virtually unanimous in rushing to defend academic freedom whenever a university president or an outsider criticizes a scholar because of his politics. Lang vehemently denied that his opposition was motivated by Huntington's politics. Despite all those things, the question of Huntington's role with respect to Vietnam arose repeatedly in the NAS debates. Evidently, academic freedom means that outsiders can't raise the issue of a scholar's politics but other scholars can.

It's all the more surprising that Huntington's consulting for the CIA and other government agencies was an issue, when one recalls why NAS exists. Congress established the academy in 1863 to act as official adviser to the U.S. government on questions of science and technology. NAS in turn established the National Research Council (NRC), and NAS and NRC committees continue to provide reports about a wide range of matters, from nutrition to future army materials. As is clear from any day's newspaper, our government desperately needs professionally competent advice, particularly about unstable countries, which are one of Huntington's specialties. So Huntington's willingness to do exactly what NAS was founded to do -- advise the government -- was held against him by some NAS members. How much of a role his politics played in each member's vote will never be known, but I find it unfortunate that they played any role at all.

I accept, however, that a more decisive issue in the debates involved perceptions of the soft sciences -- e.g., Lang's perception that Huntington used pseudo mathematics. To understand the terms soft and hard science, just ask any educated person what science is. The answer you get will probably involve several stereotypes: science is something done in a laboratory, possibly by people wearing white coats and holding test tubes; it involves making measurements with instruments, accurate to several decimal places; and it involves controlled, repeatable experiments in which you keep everything fixed except for one or a few things that you allow to vary. Areas of science that often conform well to these stereotypes include much of chemistry, physics, and molecular biology. These areas are given the flattering name of hard science, because they use the firm evidence that controlled experiments and highly accurate measurements can provide.

We often view hard science as the only type of science. But science (from the Latin scientia -- knowledge) is something much more general, which isn't defined by decimal places and controlled experiments. It means the enterprise of explaining and predicting -- gaining knowledge of -- natural phenomena, by continually testing one's theories against empirical evidence. The world is full of phenomena that are intellectually challenging and important to understand, but that can't be measured to several decimal places in labs. They constitute much of ecology, evolution, and animal behavior; much of psychology and human behavior; and all the phenomena of human societies, including cultural anthropology, economics, history, and government.

These soft sciences, as they're pejoratively termed, are more difficult to study, for obvious reasons. A lion hunt or revolution in the Third World doesn't fit inside a test tube. You can't start it and stop it whenever you choose. You can't control all the variables; perhaps you can't control any variable. You may even find it hard to decide what a variable is. You can still use empirical tests to gain knowledge, but the types of tests used in the hard sciences must be modified. Such differences between the hard and soft sciences are regularly misunderstood by hard scientists, who tend to scorn soft sciences and reserve special contempt for the social sciences. Indeed, it was only in the early 1970s that NAS, confronted with the need to offer the government competent advice about social problems, began to admit social scientists at all. Huntington had the misfortune to become a touchstone of this widespread misunderstanding and contempt.

While I know neither Lang nor Huntington, the broader debate over soft versus hard science is one that has long fascinated me, because I'm among the minority of scientists who work in both areas. I began my career at the hard pole of chemistry and physics, then took my Ph.D. in membrane physiology, at the hard end of biology. Today I divide my time equally between physiology and ecology, which lies at the soft end of biology. My wife, Marie Cohen, works in yet a softer field, clinical psychology. Hence I find myself forced every day to confront the differences between hard and soft science. Although I don't agree with some of Lang's conclusions, I feel he has correctly identified a key problem in soft science when he asks, ''How does Huntington measure things like social frustration? Does he have a social-frustration meter?'' Indeed, unless one has thought seriously about research in the social sciences, the idea that anyone could measure social frustration seems completely absurd.

The issue that Lang raises is central to any science, hard or soft. It may be termed the problem of how to ''operationalize'' a concept. (Normally I hate such neologistic jargon, but it's a suitable term in this case.) To compare evidence with theory requires that you measure the ingredients of your theory. For ingredients like weight or speed it's clear what to measure, but what would you measure if you wanted to understand political instability? Somehow, you would have to design a series of actual operations that yield a suitable measurement -- i.e., you must operationalize the ingredients of theory.

Scientists do this all the time, whether or not they think about it. I shall illustrate operationalizing with four examples from my and Marie's research, progressing from hard science to softer science.

Let's start with mathematics, often described as the queen of the sciences. I'd guess that mathematics arose long ago when two cave women couldn't operationalize their intuitive concept of ''many.'' One cave woman said, ''Let's pick this tree over here, because it has many bananas.'' The other cave woman argued, ''No, let's pick that tree over there, because it has more bananas.'' Without a number system to operationalize their concept of ''many,'' the two cave women could never prove to each other which tree offered better pickings.

There are still tribes today with number systems too rudimentary to settle the argument. For example, some Gimi villagers with whom I worked in New Guinea have only two root numbers, iya = 1 and rarido = 2, which they combine to operationalize somewhat larger numbers: 4 = rarido-rarido, 7 = rarido-rarido-rarido-iya, etc. You can imagine what it would be like to hear two Gimi women arguing about whether to climb a tree with 27 bananas or one with 18 bananas.

Now let's move to chemistry, less queenly and more difficult to operationalize than mathematics but still a hard science. Ancient philosophers speculated about the ingredients of matter, but not until the eighteenth century did the first modern chemists figure out how to measure these ingredients. Analytical chemistry now proceeds by identifying some property of a substance of interest, or of a related substance into which the first can be converted. The property must be one that can be measured, like weight, or the light the substance absorbs, or the amount of neutralizing agent it consumes.

For example, when my colleagues and I were studying the physiology of hummingbirds, we knew that the little guys liked to drink sweet nectar, but we would have argued indefinitely about how sweet sweet was if we hadn't operationalized the concept by measuring sugar concentrations. The method we used was to treat a glucose solution with an enzyme that liberates hydrogen peroxide, which reacts (with the help of another enzyme) with another substance called dianisidine to make it turn brown, whereupon we measured the brown color's intensity with an instrument called a spectrophotometer. A pointer's deflection on the spectrophotometer dial let us read off a number that provided an operational definition of sweet. Chemists use that sort of indirect reasoning all the time, without anyone considering it absurd.

My next-to-last example is from ecology, one of the softer of the biological sciences, and certainly more difficult to operationalize than chemistry. As a bird watcher, I'm accustomed to finding more species of birds in a rain forest than in a marsh. I suspect intuitively that this has something to do with a marsh being a simply structured habitat, while a rain forest has a complex structure that includes shrubs, lianas, trees of all heights, and crowns of big trees. More complexity means more niches for different types of birds. But how do I operationalize the idea of habitat complexity, so that I can measure it and test my intuition?

Obviously, nothing I do will yield as exact an answer as in the case where I read sugar concentrations off a spectrophotometer dial. However, a pretty good approximation was devised by one of my teachers, the ecologist Robert MacArthur, who measured how far a board at a certain height above the ground had to be moved in a random direction away from an observer standing in the forest (or marsh) before it became half obscured by the foliage. That distance is inversely proportional to the density of the foliage at that height. By repeating the measurement at different heights, MacArthur could calculate how the foliage was distributed over various heights.

In a marsh all the foliage is concentrated within a few feet of the ground, whereas in a rain forest it's spread fairly equally from the ground to the canopy. Thus the intuitive idea of habitat complexity is operationalized as what's called a foliage height diversity index, a single number. MacArthur's simple operationalization of these foliage differences among habitats, which at first seemed to resist having a number put on them, proved to explain a big part of the habitats' differences in numbers of bird species. It was a significant advance in ecology.

For the last example let's take one of the softest sciences, one that physicists love to deride: clinical psychology. Marie works with cancer patients and their families. Anyone with personal experience of cancer knows the terror that a diagnosis of cancer brings. Some doctors are more frank with their patients than others, and doctors appear to withhold more information from some patients than from others. Why?

Marie guessed that these differences might be related to differences in doctors' attitudes toward things like death, cancer, and medical treatment. But how on earth was she to operationalize and measure such attitudes, convert them to numbers, and test her guesses? I can imagine Lang sneering ''Does she have a cancer-attitude meter?''

Part of Marie's solution was to use a questionnaire that other scientists had developed by extracting statements from sources like tape-recorded doctors' meetings and then asking other doctors to express their degree of agreement with each statement. It turned out that each doctor's responses tended to cluster in several groups, in such a way that his responses to one statement in a cluster were correlated with his responses to other statements in the same cluster. One cluster proved to consist of expressions of attitudes toward death, a second cluster consisted of expressions of attitudes toward treatment and diagnosis, and a third cluster consisted of statements about patients' ability to cope with cancer. The responses were then employed to define attitude scales, which were further validated in other ways, like testing the scales on doctors at different stages in their careers (hence likely to have different attitudes). By thus operationalizing doctors' attitudes, Marie discovered (among other things) that doctors most convinced about the value of early diagnosis and aggressive treatment of cancer are the ones most likely to be frank with their patients.

In short, all scientists, from mathematicians to social scientists, have to solve the task of operationalizing their intuitive concepts. The book by Huntington that provoked Lang's wrath discussed such operationalized concepts as economic well-being, political instability, and social and economic modernization. Physicists have to resort to very indirect (albeit accurate) operationalizing in order to ''measure'' electrons. But the task of operationalizing is inevitably more difficult and less exact in the soft sciences, because there are so many uncontrolled variables. In the four examples I've given, number of bananas and concentration of sugar can be measured to more decimal places than can habitat complexity and attitudes toward cancer.

Unfortunately, operationalizing lends itself to ridicule in the social sciences, because the concepts being studied tend to be familiar ones that all of us fancy we're experts on. Anybody, scientist or no, feels entitled to spout forth on politics or psychology, and to heap scorn on what scholars in those fields write. In contrast, consider the opening sentences of Lang's paper Diophantine Approximation on Abelian Varieties with Complex Multiplication: ''Let A be an abelian variety defined over a number field K. We suppose that A is embedded in projective space. Let AK be the group of points on A rational over K.'' How many people feel entitled to ridicule these statements while touting their own opinions about abelian varieties?

No political scientist at NAS has challenged a mathematical candidate by asking ''How does he measure things like 'many'? Does he have a many-meter?'' Such questions would bring gales of laughter over the questioner's utter ignorance of mathematics. It seems to me that Lang's question ''How does Huntington measure things like social frustration?'' betrays an equal ignorance of how the social sciences make measurements.

The ingrained labels ''soft science'' and ''hard science'' could be replaced by hard (i.e., difficult) science and easy science, respectively. Ecology and psychology and the social sciences are much more difficult and, to some of us, intellectually more challenging than mathematics and chemistry. Even if NAS were just an honorary society, the intellectual challenge of the soft sciences would by itself make them central to NAS.

But NAS is more than an honorary society; it's a conduit for advice to our government. As to the relative importance of soft and hard science for humanity's future, there can be no comparison. It matters little whether we progress with understanding the diophantine approximation. Our survival depends on whether we progress with understanding how people behave, why some societies become frustrated, whether their governments tend to become unstable, and how political leaders make decisions like whether to press a red button. Our National Academy of Sciences will cut itself out of intellectually challenging areas of science, and out of the areas where NAS can provide the most needed scientific advice, if it continues to judge social scientists from a posture of ignorance.

COPYRIGHT 1987 Discover
COPYRIGHT 2004 Gale Group

Hard Science vs. Soft Science

Hard Science vs. Soft Science

It is customary to divide sciences into two categories, hard and soft sciences - examples of hard sciences are physics and astronomy, while ecology and psychology are often classified as soft sciences.

One group of sciences is also distinguished by strict and rigorous scientific standards, and close attention to formal standards for hypothesis formulation and testing. The other sciences take a much more informal approach, basically taking the view that if it works, use it.

The strict school is of course the one corresponding to, and responsible for, the soft sciences. Physicists and their ilk tend to be guided by the observation of Albert Einstein that Nature is subtle but not malicious ("Raffiniert is der Herrgott, aber boshaft ist er nicht"), so they feel justified in using anything they can come up with to unravel the subtleties and ferret out Nature's secrets (Stephen Hawking on the other hand said that "Not only does God play dice with the universe, but sometimes he throws them where they cannot be seen," which justifies even more devious methods of scientific investigation). The strict school will have none of this - what matters is being scientific, not doing science. That is how they keep the soft sciences soft. By setting absurd standards that discourage creative thinking they inhibit our ability to understand the natural world, and thus maintain a sterile respectability.

Speculation is part of science. Research that is not guided by hypothesis testing is the only way to make serendipitous discoveries. For example, who would have dared to hypothesize the existence of deep-sea vent communities fuelled by sulpher-eating bacteria, or funded the research to test such a radical and speculative hypothesis?

Fortunately many scientists pay only lip service to the formal approach, and focus on knowledge, which is the real meaning of "science" (from the Latin root for knowing - in other languages the usage is the same, as with the German "Wissenschaft"). I once attended a lecture by a very severe Professor who had his students analyse 400 papers in the scientific literature, finding that only two of them followed "correct" scientific procedure. This is good news, since it means that 99.5% of scientists (398/400) disagree with him.

Even so, the followers of Karl Popper have an impact and their ability to impede the progress of science should not be underestimated. Whenever a potentially useful principle raises its head in the soft sciences there will be those ready to smack it into the ground, as criticisms of the Competitive Exclusion Principle show.

Developed and maintained by William Silvert.

A Common Sense Way to Protect Public Health and the Environment

THE PRECAUTIONARY PRINCIPLE

A Common Sense Way to Protect Public Health and the Environment

Prepared by The Science and Environmental Health Network Jan2000

What is the precautionary principle?

A comprehensive definition of the precautionary principle was spelled out in a January 1998 meeting of scientists, lawyers, policy makers and environmentalists at Wingspread, headquarters of the Johnson Foundation in Racine, Wisconsin. The Wingspread Statement on the Precautionary Principle, which is included in full at the end of this fact sheet, summarizes the principle this way:

"When an activity raises threats of harm to the environment or human health, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically."

Key elements of the principle include taking precaution in the face of scientific uncertainty; exploring alternatives to possibly harmful actions; placing the burden of proof on proponents of an activity rather than on victims or potential victims of the activity; and using democratic processes to carry out and enforce the principle-including the public right to informed consent.

Is there some special meaning for "precaution"?

It's the common sense idea behind many adages: "Be careful." "Better safe than sorry." "Look before you leap." "First do no harm."

What about "scientific uncertainty"? Why should we take action before science tells us what is harmful or what is causing harm?

Sometimes if we wait for proof it is too late. Scientific standards for demonstrating cause and effect are very high. For example, smoking was strongly suspected of causing lung cancer long before the link was demonstrated conclusively that is, to the satisfaction of scientific standards of cause and effect. By then, many smokers had died of lung cancer. But many other people had already quit smoking because of the growing evidence that smoking was linked to lung cancer. These people were wisely exercising precaution despite some scientific uncertainty.

Often a problem-such as a cluster of cancer cases or global warming-is too large, its causes too diverse, or the effects too long term to be sorted out with scientific experiments that would prove cause and effect. It's hard to take these problems into the laboratory. Instead, we have to rely on observations, case studies or predictions based on current knowledge.

According to the precautionary principle, when reasonable scientific evidence of any kind gives us good reason to believe that an activity, technology or substance may be harmful, we should act to prevent harm. If we always wait for scientific certainty, people may suffer and die, and damage to the natural world may be irreversible.

Why do we need the precautionary principle now?

Those who issued the Wingspread Statement and many others believe that the effects of careless and harmful activities have accumulated over the years. They believe that humans and the rest of the natural world have a limited capacity to absorb and overcome this harm and that we must be much more careful than we have been in the past.

There are plenty of warning signs that suggest we should proceed with caution. Some are in human beings themselves-such as increased rates of learning disabilities, asthma and certain types of cancer. Other warning signs are the dying off of plant and animal species, the depletion of stratospheric ozone, and the likelihood of global warming. It is hard to pin these effects to clear or simple causes-just as it is difficult to predict exactly what many effects will be. But good sense and plenty of scientific evidence tell us we must take care, and that all our actions have consequences.

We have lots of environmental regulations. Aren't we already exercising precaution?

In some cases, to some extent, yes. When federal money is to be used in a major project, such as building a road on forested land or developing federal waste programs, the planners must produce an "environmental impact statement" to show how it will affect the surroundings. Then the public has a right to help determine whether the study has been thorough and all the alternatives considered. That is a precautionary action.

But most environmental regulations, such as the Clean Air Act, the Clean Water Act and the Superfund Law, are aimed at cleaning up pollution and controlling the amount of it released into the environment. They regulate toxic substances as they are emitted rather than limiting their use or production in the first place.

These laws have served an important purpose they have given us cleaner air, water and land.

But they are based on the assumption that humans and ecosystems can absorb a certain amount of contamination without being harmed. We are now learning how difficult it is to now what levels of contamination, if any, are safe.

Many of our food and drug laws and practices are more precautionary. Before a drug is introduced into the marketplace, the manufacturer must demonstrate that it is safe and effective. Then people must be told about risks and side effects before they use it .

But there are some major loopholes in our regulations and the way they are applied. If the precautionary principle were universally applied, many toxic substances, contaminants, and unsafe practices would not be produced or used in the first place. The precautionary principle concentrates on prevention rather than cure.

What are the loopholes in current regulations?

One is the use of "scientific certainty" as a standard, as discussed above. Often we assume that if something can't be proved scientifically, it isn't true. The lack of certainty is used to justify continuing to use a potentially harmful substance or technology.

Another is the use of "risk assessment" to determine whether a substance or practice should be regulated. One problem is that the range of risks considered is very narrow-usually death, and usually from cancer. Another is that those who will assume the risk are not informed or consulted. For example, people who live near a factory that emits a toxic substance are rarely told about the risks or asked whether they accept them.

A related, third loophole is "cost-benefit analysis" -determining whether the costs of a regulation are worth the benefits it will bring. Usually the short-term costs of regulation receive more consideration than the long-term costs of possible harm-and the public is left to deal with the damages. Also, many believe it is virtually impossible to quantify the costs of harm to a population or the benefits of a healthy environment. The effect of these loopholes is to give the benefit of the doubt to new and existing products and technologies and to all economic activities, even those that eventually prove harmful. Enterprises, projects, technologies and substances are, in effect, "innocent until proven guilty." Meanwhile, people and the environment assume the risks and often become the victims.

How would the precautionary principle change all that without bringing the economy to a halt?

It would encourage the exploration of alternatives --better, safer, cheaper ways to do things -- and the development of "cleaner' products and technologies. Sometimes simply slowing down in order to learn more about potential harm -- or doing nothing -- is the best alternative. The principle would serve as a "speed bump" in the development of technologies and enterprises.

It would shift the burden of proof from the public to proponents of a technology. The principle would ensure that the public knows about and has a say in the deployment of technologies that may be hazardous. Proponents would have to demonstrate through an open process that a technology was safe or necessary and that no better alternatives were available. The public would have a say in this determination.

Is this a new idea?

The precautionary principle was introduced in Europe in the 1980s and became the basis for the 1987 treaty that bans dumping of persistent toxic substances in the North Sea. It figures in the Convention on Biodiversity. A growing number of Swedish and German environmental laws are based on the precautionary principle. International conferences on persistent toxic substances and ozone depletion have been forums for the promotion and discussion of the precautionary principle.

Interpretations of the principle vary, but the Wingspread Statement is the first to define its major components and explain the rationale behind it.

Will the countries that adopt the precautionary principle become less competitive on the world marketplace?

The idea is to progress more carefully than we have done before. Some technologies may be brought onto the marketplace more slowly. Others may be stopped or phased out. On the other hand, there will be many incentives to create new technologies that will make it unnecessary to produce and use harmful substances and processes. These new technologies will bring economic benefits in the long run.

Countries on the forefront of stronger, more comprehensive environmental laws, such as Germany and Sweden, have developed new, cleaner technologies despite temporary higher costs. They are now able to export these technologies. Other countries risk being left behind, with outdated facilities and technologies that pollute to an extent that the people will soon recognize as intolerable. There are signs that this is already happening.

How can we possibly prevent all bad side effects from technological progress?

Hazards are a part of life. But it is important for people to press for less harmful alternatives, to exercise their rights to a clean, life-sustaining environment and, when they could be exposed to hazards, to know what those hazards are and to have a part in deciding whether to accept them.

How will the precautionary principle be implemented?

The precautionary principle should become the basis for reforming environmental laws and regulations and for creating new regulations. It is essentially an approach, a way of thinking. In coming years, precaution should be exercised, argued and promoted on many levels-in regulations, industrial practices, science, consumer choices, education, communities, and schools.

Wingspread Statement on the Precautionary Principle

The release and use of toxic substances, the exploitation of resources, and physical alterations of the environment have had substantial unintended consequences affecting human health and the environment. Some of these concerns are high rates of learning deficiencies, asthma, cancer, birth defects and species extinctions; along with global climate change, stratospheric ozone depletion and worldwide contamination with toxic substances and nuclear materials.

We believe existing environmental regulations and other decisions, particularly those based on risk assessment, have failed to protect adequately human health and the environment the larger system of which humans are but a part.

We believe there is compelling evidence that damage to humans and the worldwide environment is of such magnitude and seriousness that new-principles for conducting human activities are necessary.

While we realize that human activities may involve hazards, people must proceed more carefully than has been the case in recent history. Corporations, government entities, organizations, communities, scientists and other individuals must adopt a precautionary approach to all human endeavors.

Therefore, it is necessary to implement the Precautionary Principle: When an activity raises threats of harm to human health or the environment, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically.

In this context the proponent of an activity, rather than the public, should bear the burden of proof.

The process of applying the Precautionary Principle must be open, informed and democratic and must include potentially affected parties. It must also involve an examination of the full range of alternatives, including no action.

Wingspread Participants:

(Affiliations are noted for identification purposes only.)

• Dr. Nicholas Ashford' Massachusetts Inst. Of Technology,

• Katherine Barrett, Univ. of British Columbia

• Anita Bernstein, Chicago-Kent College of Law

• Dr. Robert Costanza, University of Maryland

• Pat Costner, Greenpeace

• Dr. Carl Cranor, Univ. of California, Riverside

• Dr. Peter deFur, Virginia Commonwealth Univ.

• Gordon Durnil, attorney

• Dr. Kenneth Geiser, Toxics Use Reduction Inst., Univ. of Mass., Lowell

• Dr. Andrew Jordan, Centre for Social and Economic Research on the Global Environment, Univ. Of East

• Anglia, United Kingdom

• Andrew King, United Steelworkers of America,

• Canadian Office, Toronto, Canada

• Dr. Frederick Kirschenmann, farmer

• Stephen Lester, Center for Health, Environment and Justice

• Sue Maret, Union Inst.

• Dr. Michael M'Gonigle, University of Victoria, British Columbia, Canada

• Dr. Peter Montague, Environmental Research Foundation

• Dr. John Peterson Myers, W. Alton Jones Foundation

• Dr. Mary O'Brien, environmental consultant

• Dr. David Ozonoff, Boston Univ.

• Carolyn Raffensperger, Science and Environmental Health Network

• Dr. Philip Regal, Univ. of Minnesota

• Hon. Pamela Resor, Massachusetts House of Rep.

• Florence Robinson, Louisiana Environmental Network

• Dr. Ted Schettler, Physicians for Social Responsibility

• Ted Smith, Silicon Valley Toxics Coalition

• Dr. Klaus-Richard Sperling, Alfred-Wegener- Institut, Hamburg, Germany

• Dr. Sandra Steingraber, author

• Diane Takvorian, Environmental Health Coalition

• Joel Tickner, University of Mass., Lowell

• Dr. Konrad von Moltke, Dartmouth College

• Dr. Bo Wahlstrom, KEMI (National Chemical Inspectorate), Sweden

• Jackie Warledo, Indigenous Environmental Network

Science and Environmental Health Network
Rt. 1 Box 73
Windsor North Dakota 58424
701-763-6286
E-mail: 75114.1164@compuserve.com

THE PRECAUTIONARY PRINCIPLE IN THE REAL WORLD

Environmental Research Foundation

January 21, 2008

THE PRECAUTIONARY PRINCIPLE IN THE REAL WORLD

By Peter Montague

The Wingspread Statement's definition of the precautionary principle is now widely quoted:

"When an activity raises threats of harm to human health or the environment, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically.

"In this context the proponent of an activity, rather than the public, should bear the burden of proof.

"The process of applying the Precautionary Principle must be open, informed and democratic and must include potentially affected parties. It must also involve an examination of the full range of alternatives, including no action."

The Essence of Precaution:

Critics say that the precautionary principle is not well-defined. However, the Science and Environmental Health Network (SEHN) points out that, in all formulations of the precautionary principle, we find three elements:

1) When we have a reasonable suspicion of harm, and

2) scientific uncertainty about cause and effect, then

3) we have a duty to take action to prevent harm.

The precautionary principle does not tell us what action to take. However, proponents of a precautionary approach have suggested a series of actions:

(1) Set goals;

(2) Examine all reasonable ways of achieving the goals, intending to adopt the least-harmful way;

(3) Assume that all projects or activities will be harmful, and therefore seek the least-harmful alternative. Shift the burden of proof -- when consequences are uncertain, give the benefit of the

doubt to nature, public health and community well-being. Expect responsible parties (not governments or the public) to bear the burden of producing needed information. Expect reasonable assurances of safety for products before they can be marketed -- just as the Food

and Drug Administration expects reasonable assurances of safety before new pharmaceutical products can be marketed.

(4) Throughout the decision-making process, honor the knowledge of "say" in the outcome. This approach naturally allows issues of ethics, right-and-wrong, history, cultural appropriateness, and justice to become important in the decision.

(5) Assume that humans will make mistakes and that decisions will sometimes turn out badly. Therefore, monitor results, heed early warnings, and be prepared to make mid-course corrections as needed; this implies that we will avoid irreversible decisions and irretrievable commitments.

Instead of asking the basic risk-assessment question -- "How much harm is allowable?" -- the precautionary approach asks, "How little harm is possible?"

In sum: Faced with reasonable suspicion of harm, the precautionary approach urges a full evaluation of available alternatives for the purpose of preventing or minimizing harm.

==============

Further reading:

In the U.S., the leading proponent of the precautionary approach is the Science and Environmental Health Network (SEHN). Their web site is a gold mine of information.

Here are some suggested readings:

Precautionary principle -- overviews

-- By Schettler, Barrett and Raffensperger (2002)

-- By Nancy Myers (2002)

-- The Wingspread Statement (1998)

-- By Jared Blumenfeld (2003)

-- Peter Montague, Opportunity of a Lifetime

Precautionary principle in the workplace:

-- By Eileen Senn (2003)

-- By Frank Ackerman and Rachel Massey (2002)

-- By The American Public Health Association (1996)

-- By Eileen Senn Tarlau (1990)

-- By Anne Stikjel and Lucas Reijnders (1995)

Precautionary principle and environmental justice:

-- By the California Environmental Protection Agency (2003)

-- By Peter Montague (Environmental Justice and Precaution, July, 2003)

-- By Peter Montague: Environmental Justice Requires the Precautionary Principle (Feb., 2003)

Precautionary principle and municipal/county government:

-- The San Francisco Precaution Ordinance (2002)

-- The San Francisco White Paper on Precaution (2002)

Precautionary principle and environmental science:

-- By David Kriebel and others in Environmental Health Perspectives (2001)

Precautionary principle and children's health:

--By The American Public Health Association (2000)

Precautionary principle and public health:

-- By Tickner, Kriebel, and Wright (2003)

Precautionary Principle and Risk Assessment

Peter Montague, "Getting Beyond Risk Assessment"

Precaution and the Law

Joe Guth, Transforming American Law to Promote Preservation of the Earth

Joe Guth, A model "little NEPA" law

Those who claim to know empirical truth cannot be talking about scientific knowledge.

science*

Science is first and foremost a set of logical and empirical methods which provide for the systematic observation of empirical phenomena in order to understand them. We think we understand empirical phenomena when we have a satisfactory theory which explains how the phenomena work, what regular patterns they follow, or why they appear to us as they do. Scientific explanations are in terms of natural phenomena rather than supernatural phenomena, although science itself requires neither the acceptance nor the rejection of the supernatural.

Science is also the organized body of knowledge about the empirical world which issues from the application of the abovementioned set of logical and empirical methods.

Science consists of several specific sciences, such as biology, physics, chemistry, geology, and astronomy, which are defined by the type and range of empirical phenomena they investigate.

Finally, science is also the application of scientific knowledge, as in the altering of rice with daffodil and bacteria genes to boost the vitamin A content of rice.

the logical and empirical methods of science

There is no single scientific method. Some of the methods of science involve logic, e.g., drawing inferences or deductions from hypotheses, or thinking out the logical implications of causal relationships in terms of necessary or sufficient conditions. Some of the methods are empirical, such as making observations, designing controlled experiments, or designing instruments to use in collecting data.

Scientific methods are impersonal. Thus, whatever one scientist is able to do qua scientist, any other scientist should be able to duplicate. When a person claims to measure or observe something by some purely subjective method, which others cannot duplicate, that person is not doing science. When scientists cannot duplicate the work of another scientist that is a clear sign that the scientist has erred either in design, methodology, observation, calculation, or calibration.

scientific facts and theories

Science does not assume it knows the truth about the empirical world a priori. Science assumes it must discover its knowledge. Those who claim to know empirical truth a priori (such as so-called scientific creationists) cannot be talking about scientific knowledge. Science presupposes a regular order to nature and assumes there are underlying principles according to which natural phenomena work. It assumes that these principles or laws are relatively constant. But it does not assume that it can know a priori either what these principles are or what the actual order of any set of empirical phenomena is.

A scientific theory is a unified set of principles, knowledge, and methods for explaining the behavior of some specified range of empirical phenomena. Scientific theories attempt to understand the world of observation and sense experience. They attempt to explain how the natural world works.

A scientific theory must have some logical consequences we can test against empirical facts by making predictions based on the theory. The exact nature of the relationship of a scientific theory making predictions and being tested is something about which philosophers widely disagree, however (Kourany 1997).

It is true that some scientific theories, when they are first developed and proposed, are often little more than guesses based on limited information. On the other hand, mature and well-developed scientific theories systematically organize knowledge and allow us to explain and predict wide ranges of empirical events. In either case, however, one characteristic must be present for the theory to be scientific. The distinguishing feature of scientific theories is that they are "capable of being tested by experience" (Popper, 40).

To be able to test a theory by experience means to be able to predict certain observable or measurable consequences from the theory. For example, from a theory about how physical bodies move in relation to one another, one predicts that a pendulum ought to follow a certain pattern of behavior. One then sets up a pendulum and tests the hypothesis that pendulums behave in the way predicted by the theory. If they do, then the theory is confirmed. If pendulums do not behave in the way predicted by the theory, then the theory is falsified. (This assumes that the predicted behavior for the pendulum was correctly deduced from your theory and that your experiment was conducted properly.)

The fact that a theory passed an empirical test does not prove the theory, however. The greater the number of severe tests a theory has passed, the greater its degree of confirmation and the more reasonable it is to accept it. However, to confirm is not the same as to prove logically or mathematically. No scientific theory can be proved with absolute certainty.

Furthermore, the more tests which can be made of the theory, the greater its empirical content (Popper, 112, 267). A theory from which very few empirical predictions can be made will be difficult to test and generally will not be very useful. A useful theory is rich or fecund, i.e., many empirical predictions can be generated from it, each one serving as another test of the theory. Useful scientific theories lead to new lines of investigation and new models of understanding phenomena that heretofore have seemed unrelated (Kitcher). This feature of fecundity is probably the main difference between the theory of natural selection and the theory of special creation. The theory of special creation has not led to new discoveries, better understanding, or increased understanding of the relatedness of areas within the field of biology or between such fields as biology and psychology. As such, the theory of special creation is nearly useless. And, since the theory is put forth as dogma, it is the antithesis of a scientific theory.

However, even if a theory is very rich and even if it passes many severe tests, it is always possible that it will fail the next test or some other theory will be proposed that explains things even better. Logically speaking, a currently accepted scientific theory could even fail the same tests it has passed many times in the past. Karl Popper calls this characteristic of scientific theories, "falsifiability."

the fallibility of science

A necessary consequence of scientific claims being falsifiable is that they are also fallible. For example, Einstein's special theory of relativity is accepted as "correct" in the sense that "its necessary inclusion in calculations leads to excellent agreement with experiments" (Friedlander 1972, 41). This does not mean the theory is infallibly certain. Scientific facts, like scientific theories, are not infallible certainties. Facts involve not only easily testable perceptual elements; they also involve interpretation.

Noted paleoanthropologist and science writer Stephen Jay Gould reminds us that in science 'fact' can only mean "confirmed to such a degree that it would be perverse to withhold provisional assent" (Gould 1983, 254). However, facts and theories are different things, notes Gould, "not rungs in a hierarchy of increasing certainty. Facts are the world's data. Theories are structures of ideas that explain and interpret facts." In Popper's words: "Theories are nets cast to catch what we call 'the world': to rationalize, to explain, and to master it. We endeavor to make the mesh ever finer and finer."

To the uninformed public, facts contrast with theories. Non-scientists commonly use the term 'theory' to refer to a speculation or guess based on limited information or knowledge. However, when we refer to a scientific theory, we are not referring to a speculation or guess, but to a systematic explanation of some range of empirical phenomena. Nevertheless, scientific theories vary in degree of certainty from the highly improbable to the highly probable. That is, there are varying degrees of evidence and support for different theories, i.e., some are more reasonable to accept than others.

There are, of course, many more facts than theories, and once something has been established as a scientific fact (e.g., that the earth goes around the sun) it is not likely to be replaced by a "better" fact in the future. Whereas, the history of science clearly shows that scientific theories do not remain forever unchanged. The history of science is, among other things, the history of theorizing, testing, arguing, refining, rejecting, replacing, more theorizing, more testing, etc. It is the history of theories working well for a while, anomalies occurring (i.e., new facts being discovered which do not fit with established theories) and new theories being proposed and eventually replacing the old ones partially or completely (Kuhn). It is the history of rare geniuses--such as a Newton, a Darwin or an Einstein--finding new and better ways of explaining natural phenomena.

We should remember that science, as Jacob Bronowski put it, "is a very human form of knowledge....Every judgment in science stands on the edge of error.... Science is a tribute to what we can know although we are fallible" (Bronowski, 374). "One aim of the physical sciences," he said, "has been to give an exact picture of the material world. One achievement of physics in the twentieth century has been to prove that aim is unattainable" (353).

scientific knowledge

Scientific knowledge is human knowledge and scientists are human beings. They are not gods, and science is not infallible. Yet, the general public often thinks of scientific claims as absolutely certain truths. They think that if something is not certain, it is not scientific and if it is not scientific, then any other non-scientific view is its equal. This misconception seems to be, at least in part, behind the general lack of understanding about the nature of scientific theories.

Another common misconception is that since scientific theories are based on human perception, they are necessarily relative and therefore do not really tell us anything about the real world. Science, according to certain "postmodernists" cannot claim to give us a true picture of what the empirical world is really like; it can only tell us how it appears to scientists. There is no such thing as scientific truth. All scientific theories are mere fictions. However, just because there is no one, true, final, godlike way to view reality, does not mean that every viewpoint is as good as every other. Just because science can only give us a human perspective, does not mean that there is no such thing as scientific truth. When the first atomic bomb went off as some scientists had predicted it would, another bit of truth about the empirical world was revealed. Bit by bit we are discovering what is true and what is false by empirically testing scientific theories. To claim that those theories which make it possible to explore space are "just relative" and "represent just one perspective" of reality, is to profoundly misunderstand the nature of science and scientific knowledge.

science as a candle in the dark

Science is, as Carl Sagan put it, a candle in the dark. It shines a light on the world around us and allows us to see beyond our superstitions and fears, beyond our ignorance and delusions, and beyond the magical thinking of our ancestors, who rightfully fought for their survival by fearing and trying to master occult and supernatural powers.

Jacob Bronowski put it all in perspective in one scene from his televised version of the Ascent of Man. I'm referring to the episode on "Knowledge and Certainty" where he went to Auschwitz, walked into a pond where the ashes were dumped, bent down and scooped up a handful of muck.

It is said that science will dehumanize people and turn them into numbers. That is false, tragically false. Look for yourself. This is the concentration camp and crematorium at Auschwitz. This is where people were turned into numbers. Into this pond were flushed the ashes of some four million people. And that was not done by gas. It was done by ignorance. When people believe that they have absolute knowledge, with no test in reality, this is how they behave. This is what men do when they aspire to the knowledge of gods (374).

The trick is to know how to develop tests in reality that avoid confirmation bias, wishful thinking, self-deception, selective thinking, subjective validation, being seduced by communal reinforcement or persuaded by ad hoc hypotheses and post hoc reasoning, as well as having a healthy skepticism and an ability to apply Occam's razor when needed.

See also alternative science, naturalism, pseudoscience, and those listed in the Logic/Perception & Science/Philosophy Topical Index and those listed in Junk Science and Pseudoscience.

---

*This material is adapted from my Becoming a Critical Thinker, ch. 9, "Science and Pseudoscience." I am aware that 'science' can also refer to any systematic body of knowledge about some object of study and that mathematics and even theology are sometimes referred to as sciences. This entry is obviously not an attempt to define every possible use of the term 'science.' In some quarters, the science I am concerned with here is called natural science. I do not intend to issue any debate as to what is and what is not a 'real' science by this entry, nor do I intend to get into any "borderline" issues as to whether some discipline or activity is or is not science.

further reading

books and articles

Beveridge, W. I. B. The Art of Scientific Investigation (New York: Vintage Books, 1957).

Bronowski, Jacob. The Ascent of Man (Boston: Little, Brown and Company, 1973).

Copi, Irving M. Introduction to Logic 10th ed. (Prentice Hall, 1998).

Dawkins, Richard (2004). A Devil's Chaplain : Reflections on Hope, Lies, Science, and Love. Mariner Books.

Friedlander, Michael W. The Conduct of Science (New Jersey: Prentice-Hall, 1972).

Gardner, Martin. Science: Good, Bad and Bogus (Buffalo, N.Y.: Prometheus Books, 1981).

Giere, Ronald. Understanding Scientific Reasoning, 4th ed. (New York, Holt Rinehart, Winston: 1998).

Gould, Stephen Jay. "Evolution as Fact and Theory," in Hen's Teeth and Horse's Toes (New York: W.W. Norton & Company, 1983).

Gould, Stephen Jay. "Piltdown Revisited," in The Panda's Thumb (New York: W.W Norton and Company, 1982).

Gould, Stephen Jay. Ever Since Darwin (New York: W.W. Norton & Company, 1979).

Kitcher, Phillip. Abusing Science: the Case Against Creationism (MIT Press, 1983).

Koertge, Noretta. (Editor) A House Built on Sand : Exposing Postmodernist Myths About Science (Oxford University Press, 1998).

Kourany, Janet A. Scientific Knowledge: Basic Issues in the Philosophy of Science,2nd ed. (Belmont: Wadsworth Publishing Co., 1997).

Kuhn, Thomas S. The Structure of Scientific Revolutions 3rd ed. (University of Chicago, 1996).

Mooney, Chris. (2005). The Republican War on Science. Basic Books.

Moti, Ben-Ari. (2005). Just a Theory - Exploring the Nature of Science. Prometheus.

Popper, Karl R. The Logic of Scientific Discovery (New York: Harper Torchbooks, 1959).

Sagan, Carl. Broca's Brain (New York: Random House, 1979).

Sagan, Carl. The Demon-Haunted World: Science as a Candle in the Dark (New York:Random House, 1995).

Sokal, Alan and Jean Bricmont. Fashionable Nonsense: Postmodern Intellectuals' Abuse of Science (St. Martin's Press, 1998).

Timmer, John. 2009. Examining science on the fringes: vital, but generally wrong. "By necessity, the majority of heretical ideas will be wrong, and most of them won't ever be useful in their failure. If the scientific community reacts as if new ideas are probably wrong, it's because they are."

websites

American Association for the Advancement of Science on the Nature of Science

Some Notes on the Nature of Science Joe Schwartz, Ph.D. Stephen Barrett, M.D.

The Academy of Natural Sciences

National Science Foundation

American Physical Society

American Chemical Society

American Institute of Biological Sciences

Evolution and the Nature of Science

Science and Religion - The Freethought Zone

news stories

Sarah Palin's War on Science - The GOP ticket's appalling contempt for knowledge and learning. By Christopher Hitchens

Science is my savior by Michael Shermer

Who's Getting It Right and Who's Getting It Wrong in the Debate About Science Literacy? by Matthew Nisbet, June 9, 2003

blogs

The Truth Wears Off: Is there something wrong with the scientific method? by Jonah Lehrer December 13, 2010 The answer is "no," but the way the author introduces the issue of what he calls "the decline effect" in science can mislead the careless reader. Well, the answer is "no" if we're talking about chemistry, physics, and math, but there really does seem to be something wrong with those sciences that study subjects with so many variables it is impossible to know what's relevant and should be controlled for. Think of how complex the human body is and how many variable there are that can affect the effectiveness of a drug. Yet, it is common for scientists to do small studies with minimum controls; they find something "statistically significant" and voila!: they get published. Maybe there should be a ban on publication of the results of small studies that use human subjects.

"Before the effectiveness of a drug can be confirmed, it must be tested again and again. The test of replicability, as it’s known, is the foundation of modern research. It’s a safeguard for the creep of subjectivity. But now all sorts of well-established, multiply confirmed findings have started to look increasingly uncertain. It’s as if our facts are losing their truth. This phenomenon doesn’t yet have an official name, but it’s occurring across a wide range of fields, from psychology to ecology."

Lehrer then compares what occurs in a wide range of fields to what has been called "the decline effect" in parapsychology. Participants in ESP experiments who do well in the first trials, do poorly as time goes on. Lehrer notes, correctly in my opinion, that this is probably due to regression to the mean.

"In the late nineteen-nineties, neuroscientist John Crabbe investigated the impact of unknown chance events on the test of replicability. The disturbing implication of his study is that a lot of extraordinary scientific data is nothing but noise. This suggests that the decline effect is actually a decline of illusion. Many scientific theories continue to be considered true even after failing numerous experimental tests. The decline effect is troubling because it reminds us how difficult it is to prove anything."

It is easy to stretch what Lehrer is talking about into a profound skepticism about science. To do so would be a mistake, however. That correlations become less robust when larger samples and better controls are applied, often the case when replications are attempted in medicine or the social sciences, is not a scoop. That refinements of tests in physics should bring about differences from the first observations or studies is not a scoop, either. Good theories in science are rarely, if ever, overthrown by anomalies. A theory will be tweaked, refined, expanded, revised, rather than dumped if it is truly useful. To connect these productive refinements that are the natural order of science to publication bias and other kinds of biases in science isn't a service either to those who are doing good science or to stopping those who are not.

Two science bloggers have addressed Lehrer's article in depth and I recommend both: David Gorski of Science-Based Medicine has posted what he admits is an example of logorrhea (excessive wordiness), but is worth the read if you've got the time: The “decline effect”: Is it a real decline or just science correcting itself?

Steven Novella, who blogs in several places, has posted a response to Lehrer on his Neurologica blog: The Decline Effect.

Last updated 12/16/10