The color of chemical compounds can often serve as an intuitive device for predicting their properties (Image: MarineBio)

Recently I read a comment by a leading chemist in which he said that in chemistry, intuition is much more important than in physics. This is a curious comment since intuition is one of those things which is hard to define but which most people who play the game appreciate when they see it. It is undoubtedly important in any scientific discipline and certainly so in physics; Einstein for instance was regarded as the outstanding intuitionist of his age, a man whose grasp of physical reality unaided by mathematical analysis was unmatched. Yet it seems to me that “chemical intuition” is a phrase which you hear much more than “physical intuition”. When it comes to intuition, chemists seem to be more in the league of financial traders, geopolitical experts and psychologists than physicists.

Why is this the case? The simple reason is that in chemistry, unlike physics, armchair mathematical manipulation and theorizing can take you only so far. While armchair speculation and order-of-magnitude calculations can certainly be very valuable, no chemist can design a zeolite, predict the ultimate product of a complex polymer synthesis or list the biological properties that a potential drug can have by simply working through the math. As the great organic chemist R B Woodward once said of his decision to pursue chemistry rather than math, in chemistry, ideas have to answer to reality. Chemistry much more than physics is an experimental science built on a foundation of rigorous and empirical models, and as the statistican George Box once memorably quipped, all models are wrong, but some are useful. It is chemical intuition that can separate the good models from the bad ones.

How then, to acquire chemical intuition? All chemists crave intuition, few have it. It’s hard to define it, but I think a good definition would be that of a quality that lets one skip a lot of the details and get to the essential result, often one that is counter intuitive. That definition reminds me of a recent book by the philosopher Daniel Dennett in which he describes an intellectual device called an “intuition pump“. An “intuition pump” is essentially a shortcut – anything from a linguistic trick to a thought experiment – that allows one to skirt the usual process of rigorous and methodical analysis and get to the point. A lot of chemical thinking involves the fine art of manipulating intuition pumps. It is the art of asking the simple, decisive question that gets to the heart of the matter. As in a novel mathematical proof, a moment of chemical intuition commands an element of surprise. And as with a truly ingenious mathematical derivation, it should ideally lead us to smack our foreheads and ask why we could not think of something so simple before.

Ultimately when it comes to harnessing intuition, there can be no substitute for experience. Yet the masters of the art in the last fifty years have imparted valuable lessons on how to acquire it. Here are three that I have noticed, and I would think they would apply as much to other disciplines as to chemistry.

1. Don’t ignore the obvious: One of the most striking features of chemistry as a science is that very palpable properties like color, smell, taste and elemental state are directly connected to molecular structure. For instance There is an unforgettably direct connection between the smell of a simple molecule called cis-3-hexenol and that of freshly cut grass. Once you smell both separately it is virtually impossible to forget the connection. Chemists who are known for their intuition never lose sight of these simple molecular properties, and they use them as disarming filters that can cut through the complex calculations and the multimillion dollar chemical analysis.

I remember an anecdote about the Caltech chemist Harry Gray (an expert among other things on colored chemical compounds) who once deflated the predictions of some sophisticated quantum mechanics calculation by simply asking what the color of the proposed compound was; apparently there was no way the calculations could have been right if the compound had a particular color. As you immerse yourself in laborious compound characterization, computational modeling and statistical significance, don’t forget what you can taste, touch, smell and see. As Pink Floyd said, this is all that your world will ever be.

2. Get a feel for energetics: The essence of chemistry can be boiled down to a fight unto death of countless factors that rally either for or against the amount of useful energy - technically called the free energy - that a system can provide. In one sense all of chemistry is one big multivariable optimization problem. When you are designing molecules as anticancer agents, for hydrogen storage or solar energy conversion or as enzyme mimics, ultimately what decides whether they will work or not is energetics, how well they can stabilize and be stabilized and ultimately lower the free energy of the system. Intimate familiarity with numbers can help in these cases. Get a feel for the rough contributions made by hydrogen bonds, electrostatics, steric interactions and solvent influences, essentially all the important forces between molecules that dictate the fate of chemical systems. This is especially important for chemists working at the interface of chemistry and biology; remember, life is a game played within a 3 kcal/mol window and any insight that allows you to nail down numbers within this window can only help. The same goes for other parameters like Van der Waals radii and bond lengths. Linus Pauling was lying in bed with a cold when he managed to build accurate models of protein structure, largely based on his unmatched feel for such numbers. And every chemist can learn from the incomparable intuition of Enrico Fermi who tossed pieces of paper in the air when the first atomic bomb went off, and used the distance at which they fell to calculate a crude estimate of the yield.

A striking case of insights acquired through thinking about energetics is illustrated by a story that the Nobel Prize winning chemist Roald Hoffmann narrates in a recent issue of “American Scientist”. Hoffmann was theoretically investigating the conversion of graphene to graphane, which is the saturated counterpart of graphene (one in which all double bonds have been converted to single ones), under high pressure. After having done some high-level calculations, his student came into his office and communicated a very counter-intuitive result; apparently graphane was more stable than the equivalent number of benzenes. This was highly counterintuitive since every chemistry student learns that so-called aromatic compounds with alternating double bonds are more stable that their single-bond analogs because of the ubiquitous phenomenon of resonance. Hoffmann could not believe the result and his first reaction was to suspect that something must be wrong with the calculation.

Then, as he himself recalls, he leaned back in his chair, closed his eyes and brought half a century’s store of chemical intuition to bear on the problem. Ultimately after all the book-keeping had been done, it turned out that the result was a simple consequence of energetics; the energy gained in the formation of strong carbon-carbon bonds more than offset that incurred due to the loss of aromaticity. The fact that it took a Nobel Laureate some time to work out the result is not in any way a criticism but a resounding validation of thinking in terms of simple energetics. Chemistry is full of surprises- even for Roald Hoffmann- and that’s what makes it endlessly exciting.

3. Stay in touch with the basics, and learn from other fields: This is a lesson that is often iterated but seldom practiced. An old professor of mine used to recommend flipping open an elementary chemistry textbook every day to a random page and reading ten pages from it. Sometimes our research becomes so specialized and we become so enamored of our little corner of the chemical world that we forget the big picture. Part of the lessons cited above simply involves not missing the forest for the trees and always thinking of basic principles of structure and reactivity in the bigger sense.

This also involves keeping in touch with other fields of chemistry since an organic chemist never knows when a basic fact from his college inorganic chemistry textbook will come in handy. Most great chemists who were masters of chemical intuition could seamlessly transition their thoughts between different subfields of their science. This lesson is especially important in today’s age when specialization has become so intense that it can sometimes lead to condescension toward fields other than your own. A corollary of learning from other fields is collaboration; what you don’t have you can at least partially borrow. As Oppenheimer used to say about afternoon tea when he was director of the Institute for Advanced Study, “Tea is where we explain to each other what we don’t understand”. Chemists and scientists in general need to learn to have tea more often.

Ultimately if we want to develop chemical intuition, it is worth remembering that all our favorite molecules, whether solar energy catalysts, cancer drugs or fertilizers, are all part of the same chemical universe, obeying the same rules even if in diverse contexts. Ultimately, no matter what kind of molecule we are interrogating, Wir sind alle chemikers, every single one of us.

This is a revised and updated version of a post on The Curious Wavefunction.

Genetic sequencing may provide easy data but the truly useful missing data might lie at the level of protein signaling pathways (Image: Yaffe, Science Signaling, 2013, doi: 10.1126/scisignal.2003684)

In his new book “To Save Everything, Click Here: The Folly of Technological Solutionism”, the philosopher of technology Evgeny Morozov develops the concept of “technological solutionism”, the tendency to define problems primarily or purely based on whether or not a certain technology can address them. This is a concerning trend since it foreshadows a future where problems are no longer prioritized by their social or political importance but instead by how easily they would succumb under the blade of well-defined and easily available technological solutions. Morozov’s solutionism is a more sophisticated version of the adage about everything looking like a nail when you have a hammer. But it’s all too real in this age of accelerated technological development, when technology advances much faster than we can catch up with its implications. It’s a problem that only threatens to grow.

One soaring example of this gap between the ease of application of technology and the value of the results obtained from this easy application is genomics. Moore’s Law is even truer for genetic sequencing than it is for transistors, and scientists are applying sequencing to both basic biological and applied medical problems with furious abandon. Sequencing will continue to get cheaper and easier, perhaps culminating in the availability of a desktop sequencer for every household in a few decades. The social implications of this personalized access to sequencing are undoubtedly going to be momentous and uncertain, but the kind of drawbacks they will bring with them even in a technical sense are already apparent, most prominently in current efforts to sequence genomes and discover new cures for cancer.

In an insightful commentary in the journal Science Signaling, MIT professor Michael Yaffe alerts us to the pitfalls of somewhat mindlessly applying genomic sequencing to discovering the basis and cure for cancer. One of the great medical breakthroughs of the twentieth century was the finding that cancer is in its heart and soul a genetic disease. This finding was greatly bolstered by the discovery of specific genes (oncogenes and tumor suppressor genes) which when mutated greatly increase the probability and progress of the disease. The availability of cheap sequencing techniques in the latter half of the century gave scientists and doctors what seemed to be a revolutionary tool for getting to the root of the genetic basis of cancer. Starting with the great success of the human genome project, it became increasingly easier to sequence entire genomes of cancer patients to discover the mutations that cause the disease. Scientists have been hopeful since then that sequencing cancer cells from hundreds of patients would enable them to discover new mutations which in turn would point to new potential therapies.

But as Yaffe points out, this approach has often ended up relegating true insights into cancer to the application of one specific technology – that of genomics – to probe the complexities of the diseases. And as he says, this is exactly like the drunk looking under the lamppost, not because that’s where his keys really are but that’s where the light is. In this case the real basis for cancer therapy constitutes the keys, sequencing is the light. During the last few years there have been several significant studies on major cancers like breast, colorectal and ovarian cancer which have sought to sequence cancer cells from hundreds of patients. This information has been incorporated into The Cancer Genome Atlas, an ambitious effort to chart and catalog all the significant mutations that every important cancer can possibly accrue.

But these efforts have largely ended up finding more of the same. The Cancer Genome Atlas is a very significant repository, but it may end up accumulating data that’s irrelevant for actually understanding or curing cancer. Yaffe acknowledges this fact and expresses thoughtful concerns about the further expenditure of funds and effort on massive cancer genome sequencing at the expense of other potentially valuable projects.

So far, the results have been pretty disappointing. Various studies on common human tumors, many under the auspices of The Cancer Genome Atlas (TCGA), have demonstrated that essentially all, or nearly all, of the mutated genes and key pathways that are altered in cancer were already known…Despite the U.S. National Institutes of Health (NIH) spending over a quarter of a billion dollars (and all of the R01 grants that are consequently not funded to pay for this) and the massive data collection efforts, so far we have learned little regarding cancer treatment that we did not already know. Now, NIH plans to spend millions of dollars to massively sequence huge numbers of mouse tumors!

It’s pretty clear that while there has been valuable data gathered from sequencing these patients, almost none of it has led to novel insights. Why, then, do the NIH and researchers continue to focus on raw, naked sequencing? Enter the data junkie and the lamppost:

I believe the answer is quite simple: We biomedical scientists are addicted to data, like alcoholics are addicted to cheap booze. As in the old joke about the drunk looking under the lamppost for his lost wallet, biomedical scientists tend to look under the sequencing lamppost where the “light is brightest”—that is, where the most data can be obtained as quickly as possible. Like data junkies, we continue to look to genome sequencing when the really clinically useful information may lie someplace else.

The term “data junkie” conjures up images of the quintessential chronically starved, slightly bug-eyed nerd hungry for data who does not quite realize the implications or the wisdom of simply churning information out from his fancy sequencing machines and computer algorithms. The analogy would have more than a shred of truth to it since it speaks to something all of us are in danger of becoming; data enthusiasts who generate information simply because they can. This would be technological solutionism writ large; turn every cancer research and therapeutics problem into a sequencing problem because that’s what we can do cheaply and easily.

Clearly this is not a feasible approach if we want to generate real insights into cancer behavior. Sequencing will undoubtedly continue to be an indispensable tool but as Yaffe points out, the real action takes place at the level of proteins, in the intricacies of the signaling pathways involving hundreds of protein hubs whose perturbation is key to a cancer cell’s survival. When drugs kill cancer cells they don’t target genes, they directly target proteins. Yaffe mentions several recent therapeutic discoveries which were found not by sequencing but by looking at the chemical reactions taking place in cancer cells and targeting their sources and products; essentially by adopting a protein-centric approach instead of a gene-centric one. Perhaps we should re-route some of those resources which we are using for sequencing into studying these signaling proteins and their interdependencies:

These therapeutic successes may have come even faster, and the drugs may be more effectively used in the future, if cancer research focuses on network-wide signaling analysis in human tumors (20), particularly when coupled with insights that the TCGA sequencing data now provide Currently, signaling measurements are hard, not particularly suited for high-throughput methods, and not yet optimized for use in clinical samples. Why not invest in developing and using technologies for these signaling directed studies?

In other words, why not ask the drunk to buy a lamp and install it in another part of town where his keys are more likely to located? It’s a cogent recommendation. But it’s important not to lose sight of the larger implications of Yaffe’s appeal to explore alternative paradigms for finding effective cures for cancers. In one sense he is directly speaking to the love affair with data and new technology that seems to be increasingly infecting the minds and hearts of the new generation. Whether it’s cancer researchers hoping that sequencing will lead to breakthroughs or political commentators hoping that Twitter and Facebook will help bring democracy in the Arab world, we are all in danger of being sucked into the torrent of technological solutionism. Of this we must be eternally vigilant.

Harmonia axyridis, a colorful beetle that is turning into an invasive species (Image: Wikipedia Commons)

When the Europeans discovered the “New World”, they infamously brought with them diseases which that world had never before encountered. Infectious agents like smallpox, typhus and cholera were generously shared with the local population – often deliberately so – and were responsible for significantly decimating the natives’ numbers. It’s a common theme; a species colonizes an ecosystem occupied by another and whether by accident or design, spreads invasive pathogens which quickly overwhelm the untrained immune system of the native species. Whether it’s humans or ladybugs, invasive pathogens have always been a reliable weapon to bring about genocide.

And speaking of ladybugs, something similar is being observed with the colorful species named Harmonia axyridis. Everyone likes beetles – I regularly caught them and observed their life cycle as a teenager – but it seems they don’t necessarily like everyone. At the beginning of the twentieth century, a species of ladybug named Harmonia was introduced from Russia and Central Europe into parts of Europe and the United States as a pest control agent. Farmers relished its ability to destroy aphids and other scale insects which fed on valuable crops. Thought to have disappeared in the 1920s, Harmonia reemerged in Louisiana in the late 80 and was encouraged to spread elsewhere. Not surprisingly, since then the Law of Unintended Consequences has taken over and assured collateral damage. While the ladybugs are taking care of invasive aphids, they have turned invasive themselves, killing off several other species of ladybugs and insects and especially a dominant species named Cocinella which is an important part of ecosystems.

In order to find out what was killing the native species, researchers from the University of Giessen took samples of the clear fluid called hemolymph that is secreted from the bugs’ legs. Chemical separation and analysis revealed the presence of a molecule which was named harmonine. Harmonine is a simple compound; chemists would recognize it as a diamine. It seemed the puzzle was solved; not only was harmonine thought to kill off Cocinella, but it most intriguingly proved fatal to the tuberculosis bacterium and the malarial parasite. In a theme that has been gratifyingly repeated throughout history, a chemical weapon from an insect’s armamentarium gave rise to a promising lead against human disease.

Except for one glitch. While the hemolymph itself did kill the Cocinella ladybugs, pure, synthetic harmonine made in a laboratory did nothing to them. The implication was clear; there must be something else in the hemolymph besides harmonine that was destroying Harmonia’s competitors. In a recent report in Science the same group has found the culprit. An obligate fungus – technically called a microsporidium – proliferates throughout the hemolymph. The fungal spores cause no harm to Harmonia probably because through time Harmonia has acquired resistance to them. In fact Harmonia seems to have made its peace with the fungus so well that the researchers located it in both the eggs and larvae of the beetle.

The fungus is catastrophic to Cocinella, however. Harmonia’s  eggs and larvae kill Cocinella competitors when they hungrily snack on them. Injection of fungal spores into the rival beetle causes death within two weeks. This time the authors were careful to eliminate other factors; injection of hemolymph in which the microsporidia was eliminated caused no ill effects, confirming the causal role of the fungus. In addition the researchers found the dying Cocinella beetles swarming with fungal spores (poor bastards).

The study shows that over the ages Harmonia has started to wield a pathogenic fungus like a finely honed biological weapon. One interesting aspect which the researchers don’t explore in this study is whether the co-evolution of the beetle and fungus began when it was introduced widely as a pest control agent or whether the two have been friends from early on in Harmonia’s evolutionary history. But whatever the history between these two symbionts, it’s clear that nature has been using biological weapons since much before we ever thought of putting anthrax spores in an envelope.

Reference: Invasive Harlequin Ladybird Carries Biological Weapons Against Native Competitors, Vilcinskas et al. Science, 2013, 340, 862.

Josiah Willard Gibbs, who would be my personal pick for "greatest American physicist in history" (Image: Wikipedia Commons).

A photo of an impish Richard Feynman playing the bongos appears in Ray Monk’s biography of Oppenheimer. It is accompanied by the caption “Richard Feynman, Julian Schwinger’s main rival for the title of greatest American physicist in history”. That got me thinking; who is the greatest American physicist in history? What would your choice be?

The question is interesting because it’s not as simple as asking who’s the “greatest physicist in history”. The answer to that question tends to usually settle on Isaac Newton or Albert Einstein; in fact few American physicists if any would show up on the top ten list of greatest physicists ever. But limit the question to American physicists and the matter becomes more complicated. Contrast this to asking who’s the greatest American chemist in history; there the answer – Linus Pauling – appears much more unambiguous and widely agreed upon.

Any discussion of “greatest scientist” is always harder than it sounds. By what measure do you judge greatness?: A single, monumental discovery? Contributions to diverse fields? Theory or experiment? Creation of an influential school of physics? Or by looking at lifetime achievement which, rather than focusing on one fundamental discovery, involves many important ones? There are contenders for “greatest American physicist” who encompass all these metrics of achievement.

Here’s what’s concerning: Even a generous, expansive list of contenders for “greatest American physicist” in history is embarrassingly thin compared to a comparable list of European physicists. For instance, let’s consider the last three hundred years or so and think up a selection which includes both Nobel Laureates and non-Nobel Laureates. The condition is to only include American-born physicists, otherwise the list will start becoming absurd.

Here’s my personal list for the title of greatest American physicist in history, in no particular order: Joseph Henry, J. Willard Gibbs, Albert Michelson, Robert Millikan, Robert Oppenheimer, Richard Feynman, Murray Gell-Mann, Julian Schwinger, Ernest Lawrence, Edward Witten, John Bardeen, John Slater, John Wheeler and Steven Weinberg. I am sure I am leaving someone out but I suspect other lists would be similar in length. It’s pretty obvious that this list pales in comparison with an equivalent list of European physicists which would include names like Einstein, Dirac, Rutherford, Bohr, Pauli and Heisenberg; and this is just if we include twentieth-century physicists. Not only are the European physicists greater in number but their ideas are also more foundational; as brilliant as the American physicists are, almost none of them made a contribution comparable in importance to the exclusion principle or general relativity.

Note that I said “almost none”. If you ask who’s my personal favorite for “greatest American physicist in history”, it would not be Feynman or Schwinger or Witten; instead it would be Josiah Willard Gibbs, a man who seems destined to remain one of the most underappreciated scientists of all time but who Einstein called “the greatest mind in American history”. Feynman and Schwinger may have invented quantum electrodynamics, but Gibbs invented the foundations of thermodynamics and statistical mechanics, a truly seminal contribution that was key to the development of both physics and chemistry. It’s hard to overestimate the importance of concepts like free energy, chemical potential, enthalpy and the phase rule for physics, chemistry, biology, engineering and everything in between. In fact, so influential was Gibbs’s work that it inspired that of Paul Samuelson, who unlike physicists, is actually agreed upon as the greatest American economist in history. If you really want to throw around lists of great American physicists (or even scientists in general), you simply cannot exclude Gibbs. In my dictionary Gibbs’s contributions are comparable to that of any famous relativist or atomic physicist.

More importantly though, the sparse list of great homegrown American physicists makes two things clear. Firstly, that America is truly a land of immigrants; it’s only by including foreign-born physicists like Fermi, Bethe, Einstein, Chandrasekhar, Wigner, Yang and Ulam can the list of American physicists even start to compete with the European list. Secondly and even more importantly, the selection demonstrates that even in 2013, physics in America is a very young science compared to European physics. Consider that even into the 1920s or so, the Physical Review which is now regarded as the top physics journal in the world was considered a backwater publication, if not a joke in Europe (Rhodes, 1987). Until the 1930s American physicists had to go to Cambridge, Gottingen and Copenhagen to study at the frontiers of physics. It was only in the 30s that, partly due to heavy investment in science by both private foundations and the government and partly due to the immigration of European physicists from totalitarian countries, American physics started on the road to the preeminence that it enjoys today. Thus as far as cutting-edge physics goes, America is not even a hundred years old. The Europeans had a head start of three hundred years; no wonder their physicists feature in top ten lists. And considering the very short time that this country has enjoyed at the forefront of science, we have to admit that America has done pretty well.

The embarrassingly thin list of famous American physicists is good news. It means that the greatest American physicist is yet to be born. Now that’s an event we can all look forward to.

The ocean acts as a large heat sink (Image: Wikipedia Commons)

When I was in graduate school I once came across a computer program that’s used to predict the activities of as yet unsynthesized drug molecules. The program is “trained” on a set of existing drug molecules with known activities (the “training set”) and is then used to predict those of an unknown set (the “test set”). In order to make learning the ropes of the program more interesting, my graduate advisor set up a friendly contest between me and a friend in the lab. We were each given a week to train the program on an existing set and find out how well we could do on the unknowns.

After a week we turned in our results. I actually did better than my friend on the existing set, but my friend did better on the test set. From a practical perspective his model had predictive value, a key property of any successful model. On the other hand my model was one that still needed some work. Being able to “predict” already existing data is not prediction, it’s explanation. Explanation is important, but a model such as mine that merely explained what was already known is an incomplete model since the value and purpose of a truly robust model is prediction. In addition, a model that merely explains can be made to fit the data by tweaking its parameters with the known experimental numbers.

These are the thoughts that went through my mind as I read a recent paper from Nature Climate Change in which climate change modelers “predicted” the last ten years of global temperature stagnation. The lack of global warming since about 2000 does not disprove everything we know about climate change; the discovery of global warming is based on much more than just computer models (Weart, 2008). But models are still an integral tool for predicting future changes, and the fact that the current stagnation was not accurately encompassed by the models did pose an inconvenient truth for climate change scientists. In the latest paper scientists from Spain and France seem to have located the reason for the failure; it seems that the models were underestimating the contribution of the oceans in acting as a sink for the heat. Heat absorption by the ocean is a long established mechanism for the cessation or slowing down of atmospheric warming but it seems that the models were not accounting for this natural variability well enough. What happens is that when human induced global warming and ocean absorption reinforce each other you get a net warming signal. However when they oppose each other then the ocean sink puts a brake on the warming, which is what we see during recent years. From what I can tell, once they bumped up the value of the parameters dealing with ocean absorption of heat they could use one particular model to reproduce the observed stagnation of temperatures.

That’s fair enough. This kind of retrospective calculation is a standard part of model building. But let’s not call it a “prediction”, it’s actually a “postdiction”. The present study indicates that models used for predicting temperature changes need some more work, especially when dealing with tightly coupled complex systems such as ocean sinks. In addition you cannot simply make these models work by tweaking the parameters; the problem with this approach is that it risks condemning the models to a narrow window of applicability beyond which they will lack the flexibility to take sudden changes into account. A robust model is one with a minimal number of parameters which does not need to be constantly tweaked to explain what has already happened and which is as general as possible. Current climate models are not useless, but in my opinion the fact that they could not prospectively predict the temperature stagnation implies that they lack robustness. They should really be seen as “work in progress”.

I can also see how such a study will negatively affect the public image of global warming. People are usually not happy with prediction after the fact, and there is little doubt that skeptics and deniers will play up the futility of climate change models based on this study to varying degrees. But this is really a problem with any models that are designed to make predictions about complex systems. The right thing to do is to honestly own up to the failures of your models and suggest modifications, and it’s only through such constant feedback that the models can be improved. The next assessment of the IPCC should clearly state this discrepancy. Georgia Tech professor Judith Curry puts the issue in context:

“The flawed assumption behind the orthodoxy was that natural variability is merely ‘noise’ superimposed on the long term trend.  The natural variability has been shown over the past two decades to have a magnitude that dominates the greenhouse warming signal.  It is becoming increasingly apparent that our attribution of warming since 1980 and future projections of climate change needs to consider natural internal variability as a factor of fundamental importance.  I sincerely hope that the (IPCC) AR5 provides an assessment of what we know and what we don’t know and areas of disagreement, rather than trying to manufacture a consensus.”

Unfortunately this standard process of introspection and improvement is subverted when a topic like climate change becomes highly politicized. Proponents are often wary of publicizing limitations as part of a healthy process of scientific give and take for fear of retribution by denialists. The politicization of science harms both proponents and honest skeptics and we are all worse off for it.

"Inside the Center" by Ray Monk, Jonathan Cape Publishers (Image: Amazon)

Why are we drawn to tragic heroes much more then to conventional ones? Perhaps because tragic heroes, because of the flaws and ambiguity inherent in their nature, continue to intrigue us long after we have finished admiring the essentially simple and good character of conventional heroes. Hamlet catches hold of our imagination much more than Antonio, Severus Snape more than Albus Dumbledore. So it is with Robert Oppenheimer, a man who continues to beguile and fascinate us long after his death. When news came of this new biography of Oppenheimer, fans like me were naturally inclined to ask what could possibly be new about it. In the past decade or so there have been several portraits and biographies of the father of the atomic bomb, with the culmination of these efforts being Kai Bird and Martin Sherwin’s Pulitzer Prize-winning volume “American Prometheus”. With so many around, do we need another biography?

In this case the answer is a qualified yes. Monk who is the acclaimed biographer of Wittgenstein and Russell has produced a thoughtful and insightful portrait that covers a lot of the same ground as other books but also sheds much clearer insights into Oppenheimer’s character and a handful of key events from his life. To his credit Monk carefully acknowledges existing biographies of Oppenheimer and points out gaps which he intends to fill with his own efforts. The UK edition of the book is titled “Inside the Center”, both as a reference to Oppenheimer’s wish to be at the center of science and policy, as well as an allusion to his own lack of a unifying center. The book is very well written and presents a judicious balance of detail and broader discussion. The writing is clear and crisp, although not particularly eloquent, and delivers a solid, authoritative account of the subject matter.

Monk’s main goal is to illuminate the central dilemma of Oppenheimer’s life; that of identity. His second goal is to pay attention to those aspects of Oppenheimer’s science which have been glossed over by other biographers. Oppenheimer was a brilliant, complex individual who excelled at a variety of things, an astonishingly quick thinker and wide-ranging intellectual who was as much at home with Sanskrit and French literature as with theoretical physics. Yet he was a man who kept on searching for a core identity that would hold it all together and who throughout his life harbored self-doubt. Monk looks for the root of this crisis in Oppenheimer’s rejection of his German-Jewish background. Oppenheimer sought to distance himself from his father’s identity as a wealthy, highly successful, self-made Jewish textile importer from New York City. It’s not clear why he did this, but it’s at least partly because of a self-hatred engendered by anti-Semitism in America. Later on he turned toward Hinduism, and the Bhagavad Gita in particular, as a sort of partial replacement for his Jewish faith. While the Bhagavad Gita is a book of great beauty and wisdom, it places too much emphasis on detachment and the labors themselves rather than on the fruits of those labors. Monk believes that it was partly Oppenheimer’s fondness for this philosophy that prevented him from achieving things which men with lesser gifts achieved. A privileged and sheltered childhood combined with his extraordinary intelligence also left him with rather poorly developed social skills.

Oppenheimer’s ambiguous attitude toward achievement and his capacity for self-doubt was particularly visible during his time at Harvard University, a time which Monk is especially deft at describing. At Harvard Oppenheimer excelled academically, graduating in only three years, but made few friends. His letters from this period provide extremely valuable insights into his core qualities. In them Oppenheimer appears in turn erudite, pitiful, accomplished, insecure and pretentious. They showcase his great gifts as an actor who could project a larger-than-life image and who could mold himself to suit the task and please his audience. These qualities were responsible for both his later successes and downfall. From Harvard Oppenheimer went first to Cambridge where he initially floundered in experimental physics and evidenced serious psychological problems. It was only at the University of Gottingen where he flourished and came into his own as a physicist.

These were great times for physics. Quantum mechanics was revolutionizing our understanding of the natural world and Cambridge and Gottingen were at the center of these developments. Monk describes Oppenheimer’s early contributions to the applications of quantum theory and his friendship with many of its pioneers including Bohr, Born and Dirac. He quickly established himself as one of the most promising physicists of his generation. Other qualities which were to cause him problems later – his impatience, conceit and arrogance – emerged during his time in Europe. With his quick mind and somewhat underdeveloped social skills Oppenheimer could hurt people as well as intrigue them. But Europe was clearly where he became a confident young scientist out to transform the teaching and practice of physics.

Oppenheimer returned to America with a mandate to establish an American school of theoretical physics that was second to none, and by any measure he succeeded. Over the next decade, at Berkeley and Caltech, he mesmerized a group of students who went on to make major contributions to American physics. During the first half of the decade Oppenheimer read widely but was consumed mainly by his science. Monk is very good at explaining some of Oppenheimer’s key contributions during this period that have been neglected by other biographers, especially his research on quantum electrodynamics, cosmic rays and mesons. Ironically, his most lasting contribution to physics was the early description of what we call black holes, but somewhat characteristically he was indifferent to this accomplishment in his later years. Monk discusses why Oppenheimer never managed to do work of the highest caliber, and locates the reason partly in the diversity of his interests which kept him from focusing on one thing for too long, partly in his somewhat mysterious view of the frontiers of physics that kept him from confidently pushing ahead, and partly again in his interest in the Bhagavad Gita which emphasizes detachment and a studied indifference to the fruits of one’s labors. During the latter half of the 1930s Oppenheimer also became interested in left-wing organizations and activities. This was a common political reaction during those times when fascism seemed to be taking over the world. Oppenheimer’s interest was also engendered by a tumultuous relationship with a left-wing medical student named Jean Tatlock. But Monk also makes it evident that while contributing to a variety of left-wing causes, Oppenheimer’s heart was never really in it. While Monk has a sure understanding of Oppenheimer’s life during this period, Bird and Sherwin’s book provides a more detailed description of his political activities.

Monk’s account of Oppenheimer’s time as director of Los Alamos as well as the technical and political challenges connected with the bomb is quite readable, although this material has been covered to death in other sources, most notably in Richard Rhodes’s seminal book “The Making of the Atomic Bomb”. It was astonishing how quickly Oppenheimer transformed himself from being a rarefied intellectual who had not even led a university department to one of the best directors of a vast scientific and engineering enterprise that anyone had ever seen. He was regarded as being intellectually superior to others, even in the midst of the most exalted concentration of intellect the twentieth century had seen until then. He was personally acquainted with thousands of personnel – from Nobel Laureates to janitors – and made them all feel special. He had an almost preternatural ability to masterfully summarize a complex discussion in a few sentences; in his presence other scientists felt smarter and more insightful. Even those who later became his detractors acknowledged his indispensable role in the success of the Manhattan Project. His quick grasp of every issue – from social concerns to the most hands-on engineering problems – and his charm and persuasive powers were on full display here.

The one thing that stands out from Monk’s narrative is a concise account of Oppenheimer’s fateful security problems, the clearest that I have found in any source. The basic story is now clear: Oppenheimer was approached by his friend Haakon Chevalier on behalf of a communist with a proposal to ferry atomic information to the Soviet Union. Oppenheimer refused right away, but did not report this approach to security officials. While this may have been justified (since no information had been communicated), Oppenheimer then made up a story in which Chevalier had approached three individuals and not one. He further declined to give the army Chevalier’s name until much later and confused them even more by telling at least one person that the person approached had been his brother Frank. His evasion and equivocation engendered a deep sense of suspicion in the military establishment. The account makes it clear that while Oppenheimer was a remarkably quick study, he was also incredibly naive and completely underestimated how seriously the security officials would take his story and to what lengths they would go to investigate its perceived implications. In an effort to ingratiate himself to the military establishment he dug himself deeper, and this behavior would haunt him for the rest of his life. The story also sheds light on an ugly part of Oppenheimer’s personality, his willingness to implicate his former students and colleagues to save himself.

After the war Oppenheimer was the most famous scientist in the world, a highly sought after government consultant and policy advisor. He stopped doing active work in physics, but still served as an outstanding critic and synthesizer of facts. He was always in touch with the latest research, and as a series of important post-war physics conferences demonstrated, was still considered the leader of the theoretical physics community in America who others looked up to as an incisive and wise teacher. This was especially evident in his selection as director of the prestigious Institute for Advanced Study in Princeton.

However Oppenheimer got seduced by power. The same charm and persuasion that made him such an effective leader at Berkeley and Los Alamos also made him powerful enemies in the military and the government, most notably Edward Teller and Lewis Strauss. His opposition to the hydrogen bomb, which was ambiguous in any case, was construed by his enemies as evidence of disloyalty or a lapse of judgment at the very least; it did not matter that many other prominent scientists opposed the hydrogen bomb on sound principles, and it also did not matter that Oppenheimer was a proponent of tactical nuclear weapons. On one hand his enemies were simply jealous since they did not have the kind of influence that he had, but they were certainly helped by his arrogance and lack of diplomacy and compromise, not to mention the inconsistencies in the story he had told security officials at Los Alamos. Oppenheimer also refused to see what direction the winds were blowing and was too enamored of his position in Washington to consider retiring from policy matters, leading Einstein to wisely point out that “Oppenheimer’s problem is that he loves a woman who does not love him; the United States Government”.

Ultimately what Oppenheimer’s adversaries did was inexcusable, but he made it easier for them. Monk crafts a careful and clear narrative of world events and Oppenheimer’s own actions that led to his shameful security hearing in 1954. The trial was rigged against Oppenheimer from the start and the decision to oust him from power had already been made; it turned out to be the kind of show trial prevalent in the same Soviet Union which its architects so ostensibly detested. Many aspects of the hearing were blatantly unconstitutional, from illegal wiretaps on Oppenheimer’s phone to the withholding of key relevant documents used in court from him and his attorney under the guise of national security. It is painful to read through the proceedings, and the whole episode will always be a blot on the political history of this country. The most perverse irony in all this is that time after time, ever since his days as a student in Europe, through both words and actions, Oppenheimer had displayed genuine love and admiration for his country and had proven his allegiance to America. In the end it’s best to remember Edward Murrow’s statement that “disagreement should never be equated with disloyalty”.

Oppenheimer and Einstein at the Institute for Advanced Study (Image: Atomic-Annihilation, Life Magazine)

After his hearing Oppenheimer’s political influence effectively ended. However he still continued to be the director of the Institute for Advanced Study until 1967, a position that gave him access to some of the world’s greatest thinkers. In this capacity he brought together leading intellectuals from both the natural and the social sciences. He also remained a highly sought after speaker and writer, regarded as an authoritative voice on the relationship between science and society. His mastery of the English language is especially evident in his transcribed speeches. In the 1960s, as a gesture of political rehabilitation he was awarded the Atomic Energy Commission’s Enrico Fermi award, and he also lived long enough to see Teller and Strauss being shamed and ostracized by the scientific and political communities. Oppenheimer died of throat cancer in 1967, still a famous man, but still striving to be at the center of things.

Monk has written a fine biography of this complex, brilliant and flawed man, one of the most important individuals of the twentieth century. For those not familiar with Oppenheimer, it’s as good a starting point as any other. For the rest, it’s still a valuable resource that very clearly illuminates key aspects of Oppenheimer’s life and times, some better than in any other biography. Ultimately though, Robert Oppenheimer will always remain intriguing and mysterious because of his lack of a defining center. Perhaps we will have to resign ourselves to the fact that, just like his beloved electron, the location of Oppenheimer’s core identity will remain indeterminate.

Note: This is a revised version of a review of the book on Amazon.com.

Free market evangelists need to take a closer look at the fundamentals of their approach (Image: Gutter Magazine)

If we were omniscient and had infinitely fast and perfect computers, perhaps we could use quantum mechanics to explain chemistry, biology, economics and psychology. In reality, no amount of quantum mechanical theorizing can explain how molecular aggregates coalesce to give rise to self-replicating assemblies, let alone how these assemblies acquire the capacity for consciousness, introspection and purposeful action.

Now imagine someone who has started out with the honest and admirable goal of trying to apply quantum mechanics to understand the behavior of a “simple” biological system like a protein. He knows for a fact that quantum mechanics can account for (not explain) all of chemistry- the great physicist Paul Dirac himself said that. He has complete confidence that quantum mechanics is really the best way to get the most accurate estimates of thermodynamic free energy, solubility, molecular charges and a variety of other important chemical properties for his favorite protein.

But as our brave protagonist actually starts working out the equations, he starts struggling. After all the Schrodinger equation can be solved exactly only for the hydrogen atom. Even a simple protein constitutes a system that is infinitely more complex. The complexity forces our embattled savant to make cruel approximations at every stage. At some point, not only is he forced to commit the blasphemy of using classical mechanics for simulating the motion of the protein, but he also has to stoop to using empirical data for parameterizing many of his models. At one point he finds himself fighting against the Uncertainty Principle itself!

In the end our hero is chagrined. He started out with the lofty dream of using quantum mechanics to create an atomic-level description of his favorite protein. He ended up instead with a set of approximations, parameters from experiments, and classical mechanics-derived quantities which were required simply for explaining the features of the system. Prediction was not even an option at this point.

But his colleagues were delighted; long experience had taught them that in most cases the best you can hope for are useful models and not accurate theories. The patchwork model actually gave fairly useful answers. Like most models in chemistry, it had some explanatory and predictive value. Even though the model was imperfect and they did not completely understand why it worked, it worked well enough to spit out useful numbers. But this modest degree of success held no sway for our bright young scientist. He stubbornly insisted that if only we had an infinitely fast computer and an unlimited amount of time, quantum mechanics would no doubt have been spectacularly successful at predicting every property of his system with one hundred percent accuracy. Maybe next time he should just wait until he gets a perfectly accurate computer and has an infinite amount of time.

I state this parable to illustrate what I think is a rather unwarranted swathe of criticism that you occasionally hear from libertarians about the financial crisis during the last few years. The reasons for the financial crisis are many, probably more complex than the laws of quantum mechanics, and society will surely keep on debating them for years. But one of the most common reasons cited by libertarians (usually in the form of a complaint) for the failure of the economy is that we should not blame the free market for what happened because we didn’t actually have a free market. If only we had a chance to have a perfect free market (or at least freer than what it is), things would take care of themselves. Not surprisingly, this line of argument quickly leads to the case for less instead of more regulation.

Notwithstanding the fact that this argument inches uncomfortably close to arguments made by the most vocal proponents of socialism during the twentieth century (“There was nothing wrong with the system per se, only with the way it was implemented”), I think the argument is fundamentally misleading. Yes, maybe a perfect free market wouldn’t have led to the crisis, but that’s like our young chemist saying that infinitely accurate computers and approximation-free quantum mechanics would not have led to the kind of imperfect models that he ended up with. The problem is that there are so many obstacles in the application of quantum mechanics to a real-life chemical system that we are simply forced to abandon the dream of using it for describing and predicting such systems with speed and efficiency. Unless we come up with a practical prescription for how quantum mechanics is going to address all the obstacles in a real-world system without making approximations, it seems futile to argue that it can really take us to the nirvana of sixteen decimal places.

To me it seems that libertarians are ignoring similar obstacles in pursuit of their dream of a perfect free market. What are these obstacles? Most of them are actually well known: There’s imperfect competition because of the existence of inherent inequalities, leading to monopolies. There’s all that special interest lobbying, encouraged by politicians, which discourages true competition and allows monopolies to get a head start. There’s dispassionate cost/benefit analysis by corporations that often leads them to pollute the environment to their heart’s content. There’s information asymmetry, which simply keeps people from knowing all the facts.

But all these problems are really part of a great stumbling block- human nature itself. All the obstacles described above are basically the consequence of ingrained, rather unseemly human qualities- greed and the lust for power, the temptation to deceive, and a relentless focus on short-term goals at long-term expense. In reality, many obstacles in the way of a truly free market are put there not by zealous government regulators but by the inconvenient inequalities and stresses endemic in any complex system. I don’t see these qualities disappearing from our world anytime soon.

Now of course, I do agree that the free market was invented to curb some of the worst excesses of these inequities, and it has worked remarkably well in this regard. But the approach has limitations. Maybe libertarians need to understand that the last vestiges of the dark side of humanity can never be exorcised since they are an indelible part of what makes us human. So unless we come up with practical solutions to the problem of human nature itself – a difficult goal, to put it mildly – it’s rather futile to keep on chanting that all our problems would be solved if only we could somehow make these inherently human qualities disappear.

The final argument that libertarians usually make is this: Just because there are obstacles in the way of a goal that may seem insurmountable, it does not mean we should not even try to achieve perfection. Now that’s a perfectly laudable attitude, but the problem is that unless you come up with a practical solution for all the problems that you face on the way, your goal is just going to remain an abstract and unworkable ideal, not exactly the kind of solution that’s desirable in the practical arenas of politics and economics. Politics especially is the art of the possible, an endeavor where imperfect solutions which all sides can agree upon are far more preferable to abstract, idealized solutions on which it’s impossible to have consensus (just witness our current political gridlock). More importantly, sometimes a relentless drive toward one goal at the expense of everything else creates problems of other kinds; the science analogy in our previous example would be unimaginably expensive calculations, scientists laid-off because of the lack of results, overheating of the computers leading to fires etc. In case of economics we have all seen these problems.

Personally my main problem with “strong” libertarianism is that it often fails to consider the other aspects of the system, instead looking at every problem exclusively through the lens of lower taxes and greater market freedom, as if resolving these variables will take care of everything else. But that’s not the case. There’s the well-known problem of externalities and unintended consequences, there’s the problem of unregulated firms getting ‘too big to fail’ and there’s the persistent problem of growing income inequality; all these problems will still exist to varying extents in a libertarian’s perfect world because they are built into human nature and the workings of complex systems. Surely we have to admit that these are real issues too.

So what should libertarians do? Well, didn’t our intrepid quantum mechanic grudgingly accept the intervention of approximations and parameterization in his pursuit of the perfect theory of protein function? These approximations seemed ugly but he had to use them to circumvent the intrinsic limitations of quantum mechanics. Similarly, perhaps free marketers could realize that at least in some cases government intervention, no matter how ugly it may seem, may be the only way to reach a workable goal. It may not be the best of all worlds, but it could be the least of all evils. What would have happened if our bright young scientist had kept on insisting that he wouldn’t budge an inch if he were forced to use anything other than approximation-free quantum mechanics? He would have ended up with nothing. And in economics even more than in chemistry, a model that partly works is better than a model that does not exist. As Churchill put it, “Sometimes it’s not enough to do our best; we need to do what’s necessary”. It’s an adage that free marketers need to ponder.

This is a modified and updated version of a post I previously wrote on The Curious Wavefunction blog.

Image: Zmie Science

Since we were discussing the differences between climate change “skeptics” and “deniers” (or “denialists”, whatever you want to call them) the other day this piece is timely. The Wall Street Journal is not exactly known for reasoned discussion of climate change, but this Op-Ed piece may set a new standard even for its own naysayers and skeptics. It’s a piece by William Happer and Harrison Schmitt that’s so one-sided, sparse on detail, misleading and ultimately pointless that I am wondering if it’s a spoof.

Happer and Schmitt’s thesis can be summed up in one line: More CO2 in the atmosphere is a good thing because it’s good for one particular type of crop plant. That’s basically it. No discussion of the downsides, not even a pretense of a balanced perspective. Unfortunately it’s not hard to classify their piece as a denialist article because it conforms to some of the classic features of denial; it’s entirely one sided, it’s very short on detail, it does a poor job even with the little details that it does present and it simply ignores the massive amount of research done on the topic. In short it’s grossly misleading.

First of all Happer and Schmitt simply dismiss any connection that might exist between CO2 levels and rising temperatures, in the process consigning a fair amount of basic physics and chemistry to the dustbin. There are no references and no actual discussion of why they don’t believe there’s a connection. That’s a shoddy start to put it mildly; you would expect a legitimate skeptic to start with some actual evidence and references. Most of the article after that consists of a discussion of the differences between so-called C3 plants (like rice) and C4 plants (like corn and sugarcane). This is standard stuff found in college biochemistry textbooks, nothing revealing here. But Happer and Schmitt leverage a fundamental difference between the two – the fact that C4 plants can utilize CO2 more efficiently than C3 plants under certain conditions – into an argument for increasing CO2 levels in the atmosphere.

This of course completely ignores all the other potentially catastrophic effects that CO2 could have on agriculture, climate, biodiversity etc. You don’t even have to be a big believer in climate change to realize that focusing on only a single effect of a parameter on a complicated system is just bad science. Happer and Schmitt’s argument is akin to the argument that everyone should get themselves addicted to meth because one of meth’s effects is euphoria. So ramping up meth consumption will make everyone feel happier, right?

But even if you consider that extremely narrowly defined effect of CO2 on C3 and C4 plants, there’s still a problem. What’s interesting is that the argument has been countered by Matt Ridley in the pages of this very publication:

But it is not quite that simple. Surprisingly, the C4 strategy first became common in the repeated ice ages that began about four million years ago. This was because the ice ages were a very dry time in the tropics and carbon-dioxide levels were very low—about half today’s levels. C4 plants are better at scavenging carbon dioxide (the source of carbon for sugars) from the air and waste much less water doing so. In each glacial cold spell, forests gave way to seasonal grasslands on a huge scale. Only about 4% of plant species use C4, but nearly half of all grasses do, and grasses are among the newest kids on the ecological block.

So whereas rising temperatures benefit C4, rising carbon-dioxide levels do not. In fact, C3 plants get a greater boost from high carbon dioxide levels than C4. Nearly 500 separate experiments confirm that if carbon-dioxide levels roughly double from preindustrial levels, rice and wheat yields will be on average 36% and 33% higher, while corn yields will increase by only 24%.

So no, the situation is more subtle than the authors think. In fact I am surprised that, given that C4 plants actually do grow better at higher temperatures, Happer and Schmitt missed an opportunity for making the case for a warmer planet. In any case, there’s a big difference between improving yields of C4 plants under controlled greenhouse conditions and expecting these yields to improve without affecting other components of the ecosystem by doing a giant planetary experiment.

There’s other howlers in that piece, including the well-known chestnut that we shouldn’t worry about increasing CO2 levels because those levels have been higher in the past.

The current levels of carbon dioxide in the earth’s atmosphere, approaching 400 parts per million, are low by the standards of geological and plant evolutionary history. Levels were 3,000 ppm, or more, until the Paleogene period (beginning about 65 million years ago). For most plants, and for the animals and humans that use them, more carbon dioxide, far from being a “pollutant” in need of reduction, would be a benefit.

Right, so we are talking about a period when temperatures and sea levels were higher, giant exotic creatures ruled the land and seas, the world was as different from now as we can imagine and – and this is kind of crucial – human beings didn’t exist. If I had a time machine I am not sure that’s the period I would pick for a pleasant stroll in the park. Plus the rate at which CO2 levels increased then was much lower than that at which they are rising right now, so I am assuming life got a bit more time to adapt. Now I have no problem if Happer and Schmitt are making the argument that we should go back to what it was like 65 million years ago and all possibly die a collective death while the flora and fauna around us thrives. But I don’t think that’s what they are trying to say.

Making the argument that increased CO2 levels are ok because certain varieties of plants would thrive is at best a narrow and one-sided point of view suitable for a personal blog. But having this point of view pitched as an argument in the WSJ? These folks are giving climate change deniers a bad name.

People who believe in conspiracy theories display the classic symptoms of patternicity and agenticity (Image: Caffeinated Thoughts)

Why do people believe in God, ghosts, goblins, spirits, the afterlife and conspiracy theories? Two common threads running through these belief systems are what skeptic Michael Shermer in his insightful book “The Believing Brain” calls “patternicity” and “agenticity”. As the names indicate, patternicity refers to seeing meaningful patterns in meaningless noise. Agenticity refers to seeing mysterious but palpable causal ‘agents’, puppet masters who pull the strings and bring about unexplained phenomena. God is probably the perfect example of an agent.

Patternicity and agenticity can both be seen as primitive evolutionary features of our brain that have been molded into instinctive behaviors. They were important in a paleolithic environment where decisions often had to be made quickly and based on instinct. In a simple example cited by Shermer, consider an early hominid sauntering along somewhere in the African Savannah. He hears a rustle in the grass. Is it a predator or is it just the wind? If he assumes the former and it turns out to be the latter, no harm is done. But if he assumes it’s just the wind and lets down his guard and it turns out to be a predator, that’s it; he’s lunch and just got weeded out of the gene pool. The first mistake is what’s called a ‘Type 1’ or false-positive error; the second one is a ‘Type 2’ or a false-negative error. Humans seem more prone to committing false positive errors because the cost of (literally) living with those errors is often less than the cost of (literally) dying from the false negatives. Agenticity is in some sense subsumed by patternicity; in the case of the hominid, he might end up ascribing the noise in the grass to a predator (an ‘agent’) even if none exists. The important thing to realize is that we are largely the descendants of humans who made false-positive errors; natural selection ensured this perpetuation.

Before we move on it’s worth noting that assuring yourself a place in the genetic pool by committing a false positive error is not as failsafe as it sounds. Sometimes people can actually cause harm by erring on the side of caution; this is the kind of behavior that is enshrined in the Law of Unintended Consequences. For instance after 9/11, about a thousand people died because they thought it safer to drive across the country rather than fly. 9/11 did almost nothing to tarnish the safety record of flying, but those who feared airplane terrorism (the ‘pattern’) reacted with their gut and ended up doing their competitors’ gene pools a favor.

Yet for all this criticism of pattern detection, it goes without saying that patternicity and agenticity have been immensely useful in human development. In fact the hallmark of science is pattern detection in noise. Patternicity is also key for things like solving crimes and predicting where the economy is going. However scientists, detectives and economists are all well aware of how many times the pattern detection machine in their heads misfires or backfires. When it comes to non-scientific predictions the machine’s even worse. The ugly side of patternicity and agenticity is revealed in people’s belief in conspiracy theories. Those who think there was a giant conspiracy between the CIA, the FBI, the Mob, Castro and the executive branch of the government are confronted with the same facts that others are. Yet they connect the dots differently and elevate certain individuals and groups (‘agents’) to great significance. Patternicity connects the dots, agenticity sows belief. The tendency to connect dots and put certain agents on a pedestal is seen everywhere, from believing that vaccines cause autism to being convinced that climate change is a giant hoax orchestrated by thousands of scientists around the world.

Notwithstanding these all too common pathologies of the pattern detection machine, it’s satisfying to find a common, elegant evolutionary mechanism in our primitive brain that would be consistent with generally favoring false positives over false negatives. What I find interesting is that this behavior even seems to exist at the level of molecules.

I realized this when I was recently studying some proteins whose exclusive job is to metabolize and detoxify foreign molecules. These proteins can be seen as the gatekeepers of the cell. Throughout evolution we have been bathed in a sea of useful, useless and toxic chemicals. Our bodies need some mechanism for distinguishing the good molecules from the bad. To enable this living organisms have evolved several proteins which bind to these molecules and in most cases change their structure or simply eject them from the cell. The most important of these are called cytochrome P450 and P-Glycoprotein. Cytochrome P450 metabolizes drugs, nutrients, hormones, poisons; basically any molecular entities that living organisms encounter in a changing environment. P-Glycoprotein is a kind of vacuum cleaner that first sucks up molecules and then throws them out.

A molecular model of cytochrome P450, a protein that metabolizes and detoxifies foreign molecules such as toxins (Image: ESRF)

Cytochrome P450 and P-Glycoprotein are crucial for detoxifying our body and letting only ‘good’ molecules pass through. But like our early hominid they are imperfect and seem to often err on the side of caution, making false positive errors. This problem is routinely confronted by drug developers who are consternated to find molecules that may perform perfectly in killing cancer cells in test tubes, but that are immediately modified or ejected out of the cells by cytochrome P450 and P-Glycoprotein when administered to test subjects like rats or human beings. Finding a putative drug compound that will not be modified or rejected by cytochrome P450, P-Glycoprotein or any number of other gatekeeper proteins is one of the biggest challenges in early stage drug development.

And yet if we think about it, both cytochrome P450 and humans are doing the bidding of patternicity and agenticity. For a human as well as for a protein, generally speaking it’s much safer to make a false positive error than a false negative one. In case of cytochrome P450, it might be ok if it discards a useful nutrient or two along with dozens of toxic chemicals. But if it lets even two or three deadly compounds from, say, snail toxin or snake venom in, those might be the last compounds it encounters during the painfully short lifetime of its human owner. Now of course, at the beginning when cytochrome P450 was in the process of evolving it probably existed in many more forms than what it does today. Some of these forms committed false positive mistakes and others committed false negatives. But it’s clear from the ongoing discussion that just like the human hearing the rustle in the grass and mistaking it for the wind, proteins which committed false negative errors were declared persona non grata by natural selection and weeded out. Those making false positive mistakes lived another day to see another molecule ejected.

To me the observation of patternicity and agenticity at the level of human brains as well as individual proteins is a testament to the enormous power and elegance of evolution in molding living organisms across an incredible hierarchy of molecules, cells, organs, individuals and societies through common mechanisms. It occurs to me that if evolution had to pick favorite lines from poems, one of them would probably be “Two roads diverged on the way to life, and I took the one which made me commit a false positive error”.

"Angry hot planet" (Image: Green Party)

This post is really a question. Over the past few years, ever since the climate change debate, well, heated up, the words “skeptic” and “denier” have been thrown around on countless websites and blogs, usually accompanied by much frothing at the mouth. This has left me wondering; is there anything bordering on a consensus among the climaterati that recognizes a difference between the two?

Now I understand of course that the words lie on an often too slippery continuum. I also realize that true deniers often conveniently cloak themselves with a veneer of polite skepticism. But it strikes me that my own perception of both groups is akin to Potter Stewart’s famous take on pornography; I can’t (and won’t) always define them, but I can usually recognize bonafide cases, at least extreme ones. So for instance, in my dictionary Senator James Inhofe  is squarely in the “denier” camp but Freeman Dyson is squarely in the “skeptic” camp.

In addition I firmly believe that being a skeptic is not just a good thing but a great thing; skepticism is what all of science is founded on after all. So I respect true skeptics as much as I detest true deniers. I am still undecided on someone like Bjorn Lomborg who seems to have started out as a firm denier but gradually gravitated toward the skeptic camp. There’s the additional problem that people like Lomborg sometimes pitch a mix of denial and bonafide skepticism and it can be hard to distinguish between the two.

I also seem to have developed my own rough, somewhat well-defined compass for recognizing members of each group. As far as I can tell there are three central premises of the science of climate change, stated in my opinion in increasing order of uncertainty:

1. The climate is warming.

2. This warming is unprecedented and is almost certainly because of human influence.

3. This unprecedented warming is going to do some very bad (or at least unpredictable) things.

To me it appears that almost nobody except the most rabid fundamentalist denier would have a problem with the first point. Personally I would also call someone who disagrees with the second point as at least leaning toward being a denier; to me there’s really no other good explanation for the warming that we have seen except human activity.

The third point is where it gets more interesting. There are people who agree that humans are warming the planet, but then wonder about the exact details of the effects: How much will it exactly warm? Will it warm equally everywhere? And most importantly – and this is something Bjorn Lomborg has often asked – would the favorable effects of the warming outweigh the unfavorable ones? Many of these questions involve prediction and they ask if the science and art of climate change is predictive enough. I have to say that in most cases I place people who ask these kinds of questions in the “skeptic” camp, although there are sometimes exceptions. It’s also not escaped my notice that the difference between denial and skepticism sometimes simply comes down to whether someone is just throwing around opinions or actually sweating the details.

But that’s enough of what I think. What do readers think? Who in your opinion is a “skeptic” and who is a “denier”? And let’s also involve the other side, the one which thinks that the whole thing is a giant communist scam or misguided science or whatever. What kinds of terms do you have for the moderate and extreme varieties in your sworn enemies and how do you define them?

Friendly housekeeping note: More than for other posts I am going to have the comments on this post on a tight leash since I don’t want the comments section to morph into a mudfest. Strong disagreement and criticism are fine, strenuous arguments are ok, interpretive dance videos are especially welcome; unhinged rants are not. What we are looking for is a spectrum of opinion on definitions. Maybe something approaching a consensus will emerge from the comments or maybe opinion will be as diverse as species of beetles. In either case with enough commenters it should be interesting.

Political ideology - tracking from liberal to conservative from left to right - can influence the purchase of a bulb with (green) and without (gray) an environmental label (Image: Gromet et al. PNAS, 2013, doi: 10.1073/pnas.1218453110)

Energy efficiency sounds like a good idea on multiple fronts; mitigating global warming, reducing dependence on foreign oil and saving money. Conservatives and liberals may disagree about the first reason, but you would expect both of them to enthusiastically embrace energy efficiency based on the other two reasons. Yet we find attitudes toward energy efficiency split along politically ideological lines in this country. Why? A new study suggests one simple potential reason: the liberal environmental messaging associated with energy efficiency may discourage conservatives from using such technologies.

That is the conclusion of a study done by researchers from Duke University and the University of Pennsylvania which was published last week in the Proceedings of the National Academy of Sciences. The United States with its two-party system and the traditional split among liberals and conservatives in matters of environmentalism is a good test case for this kind of project. The researchers’ goal was two-fold; firstly, to investigate how people’s political inclination tracks with their attitudes about energy efficiency, and secondly how that attitude is influenced by the individual reasons typically enunciated by proponents of energy efficiency.

To examine these factors the researchers carried out two studies, Study 1 and Study 2. Study 1 looked at a sample of about 700 individuals aged 19-81. They were provided information about the benefits of energy efficiency and then asked what psychological value they placed on energy efficiency itself and on the three benefits of energy efficiency: reducing carbon emissions, dependence on foreign oil and cost. The study found out that political leaning tracks well not just with general attitudes about energy efficiency but also with the individual benefits. Not surprisingly, conservatives placed the least value on reducing carbon emissions; what was surprising was that reducing cost and foreign oil dependence didn’t rank high on their priorities either. There was also a split along gender lines. The paper summarizes the findings of Study 1:

As expected, the more conservative participants were, the less they favored investing in energy-efficient technology. With regard to individuals’ psychological valuation of the environment, energy independence, and energy costs, all three judgments were associated with participants’ political ideology: The more conservative participants were, the less psychological value they placed on all these concerns. However, the ideological divide was greatest for reduction of carbon emissions, indicating the polarizing nature of environmental concerns (and the relatively broader appeal of energy independence and cost concerns across ideological lines). In additional analyses, we also included a sex × ideology interaction term, because conservative males tend to express the greatest denial of climate change. This interaction was a significant predictor for the valuation of carbon emission reductions but did not predict investment in energy efficiency or ratings for the other values.

This is an intriguing result but I have two thoughts about it. Firstly, the differences in attitude did not differ dramatically between conservatives and liberals although they reached statistical significance. Secondly, I think it would have been quite interesting to run a few more experiments in which participants were blinded to one or more of the three benefits of energy efficiency. For instance, what would conservatives say if they were told that the primary goal of energy efficiency is to reduce long-term cost? Psychological research has demonstrated the influence of prior information on consequent decision making and it would have been valuable to examine this influence in the present study.

Study 2 was smaller but much more interesting. In it participants were given $2 to buy either a standard incandescent light bulb or a fluorescent CFL light bulb. The CFL cost $1.50 and was more expensive than the standard $0.50 bulb. They could keep the change. Both liberals and conservatives were then provided information about the advantages of the CFL bulb, including its longer life and the significant long-term savings from it. Now comes the interesting part. The study was split into two sub-studies. In one case there was an environmental label (for instance one saying “Protect the Environment”) on the CFL bulb. In the other case there was no label.

What the researchers found out was that there was a marked difference between the choices of conservatives in the two cases. In the first case the label put them off in spite of the cost savings; seeing a connection with the environment closed their mind to the other benefits. In the second case without the label, the benefits of the CFL swayed their minds. The trends also held for moderate conservatives. The implications are clear; environmental messaging can actually discourage conservatives even from trying out technology that promises other clear benefits.

Here are some other interesting observations. When the prices of the bulbs were the same, then the label did not matter; all participants picked the CFL bulb, reflecting the dominance of both short-term and long-term economic concerns over others. In addition liberals always picked the CFL bulb, irrespective of its price.

Summarizing the results of Study 2, the researchers say that:

These findings indicate that connecting energy-efficient products to environmental concerns can negatively affect the demand for these products, specifically among persons in the United States who are more politically conservative. Although the majority of participants, regardless of ideology, selected the more expensive energy-efficient light bulb when it was unlabeled, the more moderate and conservative participants were less likely to purchase this option when an environmental label was attached to it.

The study (with all the usual caveats including sample size and nature) says something that both liberals and conservatives need to understand. Firstly, it’s clear that economic benefits often trump environmental ones for conservatives; at the same time, the fact that the environmental message blinded conservatives to the long-term saving says that ideology can also trump self-interest. From a practical standpoint though, this means that environmentally friendly technologies advocated by liberals are likely to be embraced by conservatives if they become cheap enough, irrespective of their attitudes toward liberal environmentalism.

More importantly, the study shows that the message matters. It tells us that liberals should perhaps tone down their big environmental message if they want to convince conservatives to adopt their products. This would be somewhat counterintuitive to the belief that a greater emphasis on environmentalism is the right way to win conservatives over to your cause. To conservatives the message is also clear; if the economics makes sense, try to ignore the political message. And the most important conclusion of this study cannot be ignored: if you really want to work together, leave ideology aside and focus on what you have in common. That’s the way to move forward.

Nuclear reactors (Image: Fast Company)

Over the last two days I had a pleasant exchange with a 7th grader from California who wanted to know more about nuclear energy for a school project. He asked me about a dozen questions on nuclear power and I answered them. It was instructive to realize how I needed to formulate my own words to make sure my responses were simple, brief and intelligible to an intelligent middle schooler. Although a few big words have inevitably crept in I think I have kept the majority of answers simple and straightforward; it was certainly a fun thing to do.

One thing that struck me was how cogent and clear the questions are. They are certainly a testament to the thoughtful consideration which my correspondent and his parents have given to the topic. But it also struck me that they are exactly the kinds of questions which curious laymen who know little about nuclear power may ask (another one of those instances where an intelligent 7th grader is quite a match for an intelligent adult layman). So I added a few of my own and answered them too. I think cases like these where you are constrained to give short and simple answers to scientific questions are not only a good exercise in improving your own understanding of topics but are also a good resource for public education. As Niels Bohr used to say, whatever you want to explain you should be able to explain using plain language.

I do hope that more middle schoolers consider science and engineering careers in energy in general and nuclear energy in particular; responsible future citizens who tackle the energy crisis head on are crucial to this country’s development . Here are the questions and answers, in no particular order.

What are reasons that prove nuclear energy is not the best alternative to replace fossil fuel?

A: Nuclear energy is actually a pretty good replacement for fossil fuels. It emits very little CO2 and other pollutants and provides a lot of energy from a very small amount of fuel. It also generates a very small amount of waste. Compared to this, coal and oil produce a lot of air pollution and waste and you also need a lot of them to generate electricity.

Despite the low cost of running a nuclear power plant, will the expensive cost of making the nuclear power plants make people think about not funding for the nuclear power plants? Why?

A: The expensive cost of nuclear power plants comes from the very long time that is needed to build them; one reason they take so much time to build is because you want to ensure that they are safe, which is a good thing. However there are new power plant designs which promise to shorten this time and reduce the expense. There is especially a new and exciting reactor called the “small modular reactor” which is small and quickly built. In addition you have to balance the cost of power plants against the cost of electricity from them (which is quite low), the small amount of pollution that they cause and the other benefits which they provide over fossil fuels.

Are there any other alternatives of energy instead of nuclear energy?

A: Yes, some other alternatives to nuclear energy include geothermal energy (energy derived from heat inside the earth), solar and wind energy. All these sources are promising but since the sun does not shine all day long and the wind does not blow all the time, they cannot provide as reliable and powerful a source of electricity as nuclear energy. In addition the technology to use these alternatives on a large scale is still not highly developed. Also, natural gas is a somewhat better alternative than coal and oil since it releases fewer greenhouse gases.

Why might there be a risk of dangers when using nuclear energy?

A: The risk of using nuclear energy comes from the possibility that radioactive elements might be released into the environment. However nuclear power plants are very carefully built to prevent such releases. Nuclear energy has a very good safety record and hundreds of nuclear power plants all over the world have operated for more than fifty years without any serious accidents. Even the two worst nuclear accidents in history (Chernobyl and Fukushima) have harmed very few people compared to the pollution from fossil fuels. In fact there are people and animals living around Chernobyl who are in excellent health.

Can nuclear reactors in nuclear power plants have a harmful affect on humanity if ever any mistakes happen? Why? Does the radiation coming from the nuclear power plants be a major down side of using nuclear energy? Explain.

A: Yes, a release of radiation from a nuclear reaction can have some harmful effects on the health of human beings. Depending on the circumstances of the accident, the radiation can affect cell division and can potentially lead to diseases like cancer. However nuclear reactors have been constructed to a very high safety standard. Only two nuclear reactors out of several hundred (Chernobyl and Fukushima) have had serious accidents, and all the research done until now tells us that the radiation released from them has harmed very few people compared to pollution from fossil fuel plants and other accidents such as mining and automobile accidents. Thus nuclear power has had very little harmful effects on humanity until now.

How can the unsolved problem of nuclear waste disposal affect the use of nuclear energy?

A: The problem of nuclear waste disposal is challenging but it is not unsolved. For starters, the total amount of nuclear waste from all reactors is extremely small and can be placed in a 3 meter pile on a single football field. In addition only a small part of that waste is long-lived. Thus we can separate that part from the short-lived waste which will disappear soon. We can also use some of the waste in generating more electricity from nuclear reactors.

Is nuclear energy the best replacement to fossil fuel? Why or why not?

A: Nuclear energy is certainly one of the best replacements for fossil fuels. It generates a lot of energy from a very small amount of fuel, emits very little CO2 and other harmful pollutants and has a very good safety record. In fact it has saved a lot of lives in the past which may have been lost had we built fossil fuel plants instead of nuclear reactors. The problem of radioactive waste is challenging but can be solved if we separate and re-use the waste.

Will the high amount of security needed at nuclear power plants play a role on the dangers of producing nuclear energy? Why?

A: Nuclear power plants don’t need as much security as you would imagine. The fuel used in nuclear reactors is not easily accessible if someone wants to steal it. In addition the fuel is highly radioactive so anyone who tries to steal it runs the risk of being greatly harmed by the radiation. Thus security at nuclear power plants by itself will not pose a problem in using nuclear energy.

Will there ever be a safe way to produce and use nuclear energy? Why or why not?

A: Yes. The nuclear energy that has been produced in the last fifty years has been very safely produced and used. There is also a lot of new research going on into reactors that are even more powerful, smaller and safer. We will always have to make sure that we don’t accidentally release radiation from a nuclear reactor, but until now we have been very successful in preventing a deadly radiation release so there is little reason to believe that things will be different in the future.

Why are some people afraid of nuclear power?

A: People are generally afraid of things they can’t see and touch, such as radiation. In addition you hear a lot about the rare nuclear accident in the papers compared to the more frequent car accident or shooting because of which many more people die. In addition many people are not very familiar with the advantages of nuclear power and thus are suspicious of it. Also, some folks think of nuclear bombs when they think of nuclear reactors although the two are completely different; a nuclear reactor can never explode like a bomb.

How does a nuclear reactor work?

A: A nuclear reactor is basically a machine for generating heat. The heat comes from the splitting of the nuclei of atoms in two elements: uranium or plutonium. The heat is carried away by a coolant like water which is used to drive a turbine that generates electricity.

How are nuclear reactors made safe?

A: Many factors contribute to a safety of a nuclear reactor. The nuclear material itself is very well shielded and the reactor is covered with a huge dome that will not allow radioactive material to escape. There are also many backup systems that prevent radiation release; if one fails another takes over. Nuclear power plants release very little radioactivity during their normal functioning; in fact you get more radioactivity from eating a banana than by living near a nuclear reactor! Many people in the US and all over the world live nuclear power plants without any problems.

Can the material from a nuclear reactor be stolen by a terrorist to make a bomb?

A: It would be highly unlikely for a terrorist to steal material from a nuclear reactor and make a bomb with it. The material is usually very well shielded, it is contaminated with other undesirable materials which have to be separated, and the amount of radioactivity is very high. A terrorist would risk his life when stealing such highly radioactive material, and the time it would take for him to do this would probably be more than enough for the police to get there and capture him.

Is all radiation bad?

A: No, all radiation is not bad, only high levels can sometimes cause harm. One important thing to remember is that radiation is not something only associated with nuclear power; we are surrounded by radiation at all times. We get radiation when we do an x-ray test, when we travel in airplanes and when we eat bananas. These low levels of radiation are all safe for you; so are those that you get from living around a nuclear power plant.

Chemists need to move from designing structure - exemplified by this synthetic receptor - to designing function (Image: Max Planck Institute).

Yesterday I wrote a post about a perspective by multifaceted chemist George Whitesides in which he urged chemists to broaden the boundaries of their discipline and think of big picture problems. But the article spurred me to think a bit more about a question which I (and I am sure other chemists) have often thought about; what’s the next big challenge for chemistry?

And when I ask this question I am not necessarily thinking of specific fields like energy or biotechnology or food production. Rather, I am thinking of the next outstanding philosophical question confronting chemistry. By philosophical question I don’t mean an abstract goal which only armchair thinkers worry about. The philosophical questions in a field are those which define the field’s big problems in the most general sense of the term. For physicists it might be understanding the origin of the universe, for biologists the origin of life. These problems can also be narrowly defined questions that nonetheless expand the understanding and scope of a field; for instance in the early twentieth century physicists were struggling to make sense of atomic spectra, which turned out to be important for the development of quantum theory. It’s also important to note that the philosophical problems of a field change over time, and this is one reason why chemists should be aware of them; you want to move with the times. If you were a “chemist” in the sixteenth century the big question was transmutation. In the nineteenth century when chemistry finally was cast in the language of elements and molecules the big question became the constitution of molecules in the form of atomic arrangements.

Synthesis is no longer chemistry’s outstanding general problem

When I think about the next philosophical question confronting chemistry I also feel a sense of despondency. That’s because I increasingly feel that the great philosophical question that chemists are going to face in the near future is emphatically not one whose answer they will locate in the all-pervasive activity that always made chemistry unique: synthesis. What always set chemistry apart was its ability to make new molecules that never existed before. Through this activity chemistry has played a central role in improving our quality of life.

The point is, synthesis was the great philosophical question of the twentieth century, not the twenty-first. Now I am certainly not claiming that synthesizing a complex natural product with fifty rotatable bonds and twenty chiral centers is even today a trivial task. I am also not saying that synthesis will cease to be a fruitful source of solutions for humanity’s most pressing problems, such as disease or energy; as a tool the importance of synthesis will remain undiminished. What I am saying is that the general problem of synthesis has now been solved in an intellectual sense (as an aside, this would be consistent with the generally pessimistic outlook regarding total synthesis seen on many blogs.)

The general problem of synthesis was unsolved in the 30s. It was also unsolved in the 50s. Then Robert Burns Woodward came along. Woodward was a wizard who made molecules whose construction had defied belief. He had predecessors, of course, but it was Woodward who solved the general problem by proving that one could apply well-known principles of physical organic chemistry, conformational analysis and spectroscopy to essentially synthesize any molecule. He provided the definitive proof of principle. All that was needed after that was enough time, effort and manpower. If chemistry were computer science, then Woodward could be said to have created a version of the Turing Machine, a general formula that could allow you to synthesize the structure of any complex molecule, as long as you had enough NIH funding and cheap postdocs to fill in the specific gaps. Every synthetic chemist who came after Woodward has really developed his or her own special versions of Woodward’s recipe. They might have built new models of cars, but their Ferraris, Porches and Bentleys – as elegant and impressive as they are – are a logical extension of Woodward and his predecessor’s invention of the internal combustion engine and the assembly line.

A measure of how the general problem of synthesis has been solved is readily apparent to me in my own small biotech company which specializes in cyclic peptides, macrocycles and other complex bioactive molecules. The company has a vibrant internship program for undergraduates in the area. To me the most remarkable thing is to see how quickly the interns can bring themselves up to speed on the synthetic protocols. Within a month or so of starting at the bench they start churning out these compounds with the same expertise and efficiency as chemists with PhDs. The point is, synthesizing a 16-membered ring with five stereocenters has not only become a routine, high-throughput task but it’s something that can be picked up by a beginner in a month. This kind of synthesis might have easily fazed a graduate student twenty years ago and taken up a good part of his or her PhD project. The bottom line is that we chemists have to now face an uncomfortable fact: there are still a lot of unexpected gems to be found in synthesis, but the general problem is now solved and the incarnation of chemical synthesis as a tool for other disciplines is now essentially complete.

Functional design and energetics are now chemistry’s outstanding general problems

So if synthesis is no longer the general problem, what is? My own field of medicinal chemistry and molecular modeling provides a good example. It may be easy to synthesize a highly complex drug molecule using routine techniques, but it is impossible, even now, to calculate the free energy of binding of an arbitrary simple small molecule with an arbitrary protein. There is simply no general formula, no Turing Machine that can do this. There are of course specific cases where the problem can be solved, but the general solution seems light years away. And not only is the problem unsolved in practice but it is also unsolved in principle. Sure, we modelers have been saying for over twenty years that we have not been able to calculate entropy or not been able to account for tightly bound water molecules. But these are mostly convenient questions which when enunciated make us feel more emotionally satisfied. There have certainly been some impressive strides in addressing each of these and other problems, but the fact is that when it comes to calculating the free energy of binding, we are still today where we were in 1983. So yes, the calculation of free energies – for any system – is certainly a general problem that chemists should focus on.

But here’s the even bigger challenge that I really want to talk about: We chemists have been phenomenal in being able to design structure, but we have done a pretty poor job in designing function. We have of course determined the function of thousands of industrial and biological compounds, but we are still groping in the dark when it comes to designing function. Here are a few examples: Through combinatorial techniques we can now synthesize antibodies that we want to bind to a specific virus or molecule, but the very fact that we have to adopt a combinatorial, brute force approach means that we still can’t start from scratch and design a single antibody with the required function (incidentally this problem subsumes the problem of calculating the free energy of antigen-antibody binding). Or consider solar cells. Solid-state and inorganic chemists have developed an impressive array of methods to synthesize and characterize various materials that could serve as more efficient solar materials. But it’s still very hard to lay out the design principles – in general terms – for a solar material with specified properties. In fact I would say that the ability to rapidly make molecules has even hampered the ability to think through general design principles. Who wants to go to the trouble of designing a specific case when you can simply try out all combinations by brute force?

I am not taking anything away from the ingenuity of chemists – nor am I refuting the belief that you do whatever it takes to solve the problem – but I do think that in their zeal to perfect the art of synthesis chemists have neglected the art of de novo design. Yet another example is self-assembly, a phenomenon which operates in everything from detergent action to the origin of life. Today we can study the self-assembly of diverse organic and inorganic materials under a variety of conditions, but we still haven’t figured out the rules – either computational or experimental – that would allow us to specific the forces between multiple interacting partners so that these partners assembly in the desired geometry when brought together in a test tube. Ideally what we want is the ability to come up with a list of parts and the precise relationships between them that would allow us to predict the end product in terms of function. This would be akin to what an architect does when he puts together a list of parts that allows him to not only predict the structure of a building but also the interplay of air and sunlight in it.

I don’t know what we can do to solve this general problem of design but there are certainly a few promising avenues. A better understanding of theory is certainly one of them. The fact is that when it comes to estimating intermolecular interactions, the theories of statistical thermodynamics and quantum mechanics do provide – in principle – a complete framework. Unfortunately these theories are usually too computationally expensive to apply to the vast majority of situations, but we can still make progress if we understand what approximations work for what kind of systems. Psychologically I do think that there has to be a general push away from synthesis and toward understanding function in a broad sense. Synthesis still rules chemical science and for good reason; it’s what makes chemistry unique among the sciences. But that also often makes synthetic chemists immune to the (well deserved) charms of conformation, supramolecular interactions and biology. It’s only when synthetic chemists seamlessly integrate themselves into the end stages of their day job that they will learn better to appreciate synthesis as an opportunity to distill general design principles. Let the synthetic chemist interact with the physical biochemist, the structural engineer, the photonics expert; let him or her see synthesis through the requirement of function rather than structure. Whitesides was right when he said that chemists need to broaden out, but another way to interpret his statement would be to ask other scientists to channel their thoughts into synthesis in a feedback process. As chemists we have nailed structure, but nailing design will bring us untold dividends and will help make the world a better place.

Climate change denial, laissez-faire capitalism and conspiracy theories may have more in common than we think (Image: David Suzuki foundation)

Climate change denial, laissez-faire economics, conspiracy theorizing. A new study suggests that these rather diverse belief systems may lie on a continuum. That climate change denialists don’t believe in anthropogenic global warming is a given, but are there other more general indicators of their belief system that include climate change denial as a subset?

This is the question that a group of psychologists from the University of Western Australia and the University of Zurich sought to answer. They found that climate change denialists also seem to display two other characteristics; a belief in laissez-faire capitalism and more troublingly, a tendency to espouse conspiracy theories. The correlation of climate change denial with free market capitalism was stronger and not completely unsurprising but the correlation with a conspiratorial mindset is more unexpected and intriguing.

To find out more about the psychology of denialists, the researchers queried about a thousand commenters on eight popular climate science blogs about their general beliefs in various conspiracy theories and free market capitalism. Blogs were picked because these are the sources where deniers and skeptics are most commonly found. A questionnaire listing about 30 miscellaneous statements relating to free markets, environmental issues and conspiracy theories of all flavors were pitched to commenters on these blogs. Interestingly the commenters on “skeptical” climate change blogs declined to answer the questions.

The questionnaire included statements about free markets (usually asking whether unfettered free markets are better for human and environmental welfare than regulated markets) conspiracy theories (“9/11 was an inside job”, “The government has covered up UFO landings in Area 51”, “HIV and AIDS were manufactured by the government”) and the perception that previous environmental problems have been resolved. Commenters had to rate the statements on a four-point scale ranging from “strongly disagree” to “strongly agree”. The results were plugged into a model that calculated correlations between beliefs represented by the various statements.

The results indicated, perhaps not surprisingly, that there is an inverse correlation between espousal of free markets and belief in the scientific consensus on climate change. This free market-dominated rejection of scientific evidence is consistent with denial of important environmental and public health concerns in the past, most notably the link between cigarette smoking and lung cancer and the effects of acid rain on the environment. Once free-market ideologues make up their mind that complete government withdrawal from markets is the only way to ensure prosperity, then it’s not surprising to find them inclined to disbelieve even rigorous scientific evidence that would somehow point to more increased government regulation as a solution. This is of course independent of actual government regulation; all that matters is a belief in future government action. Sadly, the study also found that unfettered belief in free markets seems to make deniers skeptical of any scientific consensus involving the government, no matter what the field of study or the level of rigor. Simply put, ideology trumps facts.

What is much more intriguing is the very modest but positive correlation between rejection of climate change and the presence of a general conspiratorial ideology. People who reject climate change don’t believe equally in all the conspiracy theories listed in the questionnaire, but the general trend seems to hold. It would have been enlightening to know if denialists seem to believe a particular conspiracy theory more than others, but that kind of trend does not really stand out. Finally, perceptions of whether previous environmental issues are resolved or not also track negatively with denialism. So if you believe that the consensus on acid rain is not well established you are also less likely to believe the consensus on climate change.

It’s important to keep a few caveats in mind, the most important one being the nature of the test subjects. The sample size is small and not entirely representative. An Internet sample is often self-selected and is likely to represent the most vocal sample; as bloggers are well aware, many of the most frequent commenters are also the most polarized and the loudest. Ignored is the vast “silent majority” which may hold very different and possibly more moderate views than the vocal majority. Those who are climate change denialists also lie on a continuum when it comes to government regulation of climate markets, so depending on what exactly they believe they may or may not exhibit much fondness for laissez-faire capitalism. This study also does not prove that all climate change deniers are likely to believe in 9/11 conspiracy theories. Rather it draws our attention to the fact that the psychology of climate change denial presents some features that are likely to be shared by conspiracy theorists.

The main goal of the study in my opinion is to inspire more detailed studies on how different mindsets intersect with each other. I consider it to be an intriguing starting point rather than a conclusive study. The most interesting thing about these observations is that they point to deeper psychological connections between different belief systems. The rejection of established science because of its perceived failure to conform to preconceived beliefs is a classic case of motivated reasoning. This would be consistent with the incompatibility of an extreme free-market viewpoint with denial of climate change. Since free-market ideology also usually tracks well with conservative politics, it is not surprising to find most denials of climate change coming from the right.

But what about the correlation with conspiracy theorizing? One of the common characteristics of most conspiracy theories is the omniscience and power they place in the hands of the government. JFK was apparently assassinated not by a single gunman but by a vast conglomerate primarily involving government agencies. The small group of industrial scientists who denied the link between cigarette smoking and lung cancer pointed to a powerful cabal of government-sponsored scientists who were orchestrating a dedicated effort to discredit tobacco companies. From 9/11 denial to HIV denial, the big nemesis is always the government. Some conspiracies by private corporations (for instance those involving vaccines and autism) are rampant on the left, but these pale in comparison to the number involving the government.

Seen through this lens it’s not surprising to find belief in laissez-faire capitalism tracking well with conspiracy theorizing since proponents of laissez-faire are inherently suspicious of the government. For instance the king of climate change denial, Senator James Inhofe, has constantly called climate change a government-sponsored “hoax”. Inhofe thinks that thousands of scientists all over the world combined with dozens of government agencies have somehow had the brilliance and capability to pull the wool over the eyes of the entire world. Scientists and government officials should feel flattered by the omniscience ascribed to them by climate change denialists if they hadn’t caused so much harm.

Unfortunately it’s not easy to disabuse people of a conspiracy mindset since as the article notes, presenting evidence to the contrary only makes them more convinced of the diabolical success of the supposed conspiracy. The one thing we can do is to at least point out to climate change denialists how their beliefs are in fact conspiratorial. Demonstrate the features that climate change conspiracies share with 9/11 denial and Pearl Harbor revisionism. Explain how a true climate change conspiracy would involve a vast number of people in collusion with each other over an incredibly long period of time, with absolutely no possibility of a leak or a whistleblower exposing the truth. Sadly such reasoning is unlikely to convince die-hard deniers. But by noting the similarity of climate change denial with some of the craziest conspiracy theories in history, you can at least improve the chances of having the denialists perhaps take a hard look at what they believe. And in the war against ignorance, even incremental wins are to be savored.

Reference: NASA Faked the Moon Landing – Therefore (Climate) Science is a Hoax; Lewandowsky et al. Psychological Science, 2013, 24, 1.

Einstein's last years were marked by a futile search for a grand unified theory (Image: Wikipedia Commons).

Unification is an ancient goal in physics. From the time that 19th century physicists like Maxwell and Clausius attempted to unite disparate physical phenomena, the search for a grand unified theory that would conjoin every known force and physical law has always been an implicit or explicit dream of physicists. The search for unification is in one sense a search for harmony, a desire to view the whole universe through the lens of a single elegant law or equation that would explain everything.

Most attempts at unification have been remarkably successful. First the pioneers of thermodynamics brought together mechanics and heat and then Faraday and Maxwell achieved the spectacular goal of weaving electricity, magnetism and optics together into a seamless tapestry. Even Einstein’s famous equation can be seen as a kind of unification, serving to underscore how fundamental quantities like matter and energy are just two sides of the same coin.

Unification thinking pervaded the twentieth century, from establishing wave-particle duality to creating a common framework for understanding special relativity and quantum mechanics. Pioneers of particle physics like Feynman, Weinberg and t’ Hooft brought us tantalizingly close to the ultimate goal of a “final” theory. But only tantalizingly so; famously, gravity remained intractable and its union with quantum theory has remained perhaps the greatest unsolved problem in physics for the last fifty years. Many of the world’s best minds from Einstein to Edward Witten have tried to solve the problem with scant success. String theory claims that it can achieve the task, but it is no closer than other theories to making hard, testable predictions to this effect.

From an experimental perspective one of the best bets for probing a quantum theory of gravity is to look for gravitons, particles that are thought to mediate the gravitational force. The fundamental problem with detecting gravitons is the extremely weak nature of the gravitational force. To address this problem researchers have designed exceedingly sensitive equipment that should in principle be able to detect even discrete gravitons. One of the triumphs of this effort is LIGO, the Laser Interferometer Gravitational Wave Observatory, which is using extremely sensitive interferometers to detect the minuscule shifts in space-time caused by the passage of a gravitational wave. LIGO is a marvel of both physics and engineering and has been really designed to detect gravitational waves which are a prediction of classical general relativity. A typical experiment will study the interference of a highly focused laser beam bouncing off two mirrored cavities at a given distance, waiting for a gravitational wave from a defined source to pass between them. Then, as Wikipedia puts it:

When a gravitational wave passes through the interferometer, the space-time in the local area is altered. Depending on the source of the wave and its polarization, this results in an effective change in length of one or both of the cavities. The effective length change between the beams will cause the light currently in the cavity to become very slightly out of phase with the incoming light. The cavity will therefore periodically get very slightly out of resonance and the beams which are tuned to destructively interfere at the detector, will have a very slight periodically varying detuning. This results in a measurable signal. Note that the effective length change and the resulting phase change are a subtle tidal effect that must be carefully computed because the light waves are affected by the gravitational wave just as much as the beams themselves.

Note the last statement that talks about the subtlety of the effect. But the subtlety may be even more amplified when it comes to detecting gravitons themselves. How subtle would the effect of discrete gravitons be? In a chapter in John Brockman’s recent book, Freeman Dyson from the Institute for Advanced Study in Princeton tries to quantify the subtlety (the chapter is reprinted as an essay in the IAS newsletter). In the process he also tells us that the effort to unify gravity and quantum mechanics might be doomed after all. The key effect here is the displacement of the two mirrors induced by the passage of a gravitational wave which causes a change in the interference of the laser beams, leading to a signal. Dyson’s calculations demonstrate that this change might be so small that it would be swamped by “background” quantum fluctuations in space-time. Well then, you might say, we will just make the mirrors heavy enough so that they won’t be perturbed by the quantum fluctuations. Dyson tells us just how heavy they will have to be:

“Because of ambient and instrumental noise, the actual LIGO detectors can only detect waves far stronger than a single graviton. But even in a totally quiet universe, I can answer the question, whether an ideal LIGO detector could detect a single graviton. The answer is no. In a quiet universe, the limit to the accuracy of measurement of distance is set by the quantum uncertainties in the positions of the mirrors. To make the quantum uncertainties small, the mirrors must be heavy. A simple calculation, based on the known laws of gravitation and quantum mechanics, leads to a striking result. To detect a single graviton with a LIGO apparatus, the mirrors must be exactly so heavy that they will attract each other with irresistible force and collapse into a black hole. In other words, nature herself forbids us to observe a single graviton with this kind of apparatus.”

When I met Dyson last year he told me that he had tried hard to find a flaw in the calculation, to no success. If true this limitation goes much beyond detecting discrete gravitons. It could mean that the world of gravity and the world of subatomic particles will forever stay separate from each other, being disallowed from sampling each other’s domains by a fundamental physical barrier. As Dyson puts it:

Kiera Wilmot, the Bartow High School student who was arrested and expelled for her curiosity (Image: Change.org)

In his delightful memoir “Uncle Tungsten”, the eminent neurologist and writer Oliver Sacks recounts the swashbuckling chemical adventures of his teenage years, sparked when a sympathetic uncle got him hooked on to the wonders of chemistry. For me the most memorable image from that book is one of the young Sacks standing on a bridge on a river and successively dropping a few grams of the alkali metals – from lithium to cesium – in the water to observe their reaction. Lithium causes little reaction, sodium dances on the surface with a flame while cesium roars like a beast with much sound and fury. Sacks says that after that incident he never forgot the trends in reactivity of the alkali metals, an important principle that’s often taught in high school and college. Many prominent scientists, some of whom later won Nobel Prizes, remember similar exciting adventures with chemistry sets as teenagers.

It’s a sad commentary on our alarmist society that a similar deed would probably land a modern day budding Oliver Sacks in jail. That is exactly what it has done to a young aspiring scientist named Kiera Wilmot from Bartow High School in Florida, and in the process it has almost certainly deprived this country of exactly the kind of scientist whose shortage its politicians and educators are so fond of lamenting. The student conducted a common experiment mixing the toilet bowl cleaner The Works and aluminum foil on the grounds of a school (A helpful commenter on the Salon.com reprint of this post pointed out that Ms. Wilmot used The Works, not Drano; both react with aluminum to generate hydrogen gas and heat). The exact details are unknown but the incident led to a minor explosion, hurt nobody and damaged no property. This relatively harmless bit of curiosity led to Ms. Wilmot being handcuffed, arrested and expelled from the school. Irrational State Overreach: 1, The Much Touted American Edge in Science: 0. Whatever else the school was trying to achieve, it definitely succeeded in squelching independent scientific curiosity in its students.

Now let’s get one thing straight. The student was playing with a potentially hazardous mix and she was not using proper protective equipment. She definitely deserved to be reprimanded and perhaps even punished in some way, maybe by putting her on probation. But when you arrest and expel students for slaking their scientific curiosity, whatever the other consequences of that action, be advised that you are almost certainly sacrificing a valuable scientist at the altar of arbitrarily wielded state and school power.

The latest incident however is only a reflection of, on one hand, the draconian measures that our educational and political institutions are taking to achieve the ostensible goal of “disciplining” American children, and on the other hand, the public obsession with chemophobia and “chemicals”. The absurdly named “chemical free” chemistry sets are already depriving students of the joy of chemistry. When I was growing up my chemistry set had a lot of potentially harmful chemicals like copper sulfate and potassium ferricyanide. On every bottle there were clear labels advising us of the hazards of that particular chemical, antidotes against poisoning and the phone number of the poison center. None of these labels deterred me or my parents, and the set opened up the wonderful world of chemistry to me.

I made colorful dyes, generated nasty smells in a test tube and yes, caused minor explosions. Some of these explosions resulted from experimenting with protocols outside those recommended in the set. One time I mixed potassium permanganate with glycerol to spark a bright burning fire (the reaction is highly exothermic), another time I dissolved mom’s safety pins in nitric acid to generate copious amounts of nitrogen dioxide; it was only later that I came to know about the potential toxicity of the greenish-blue gas. Yes, I could have hurt myself, perhaps seriously, but the pleasure of finding things out far outweighed the potential harm that I could have caused myself. There is no doubt that performing chemical experiments exposes you to potential risks, but that is true of every single activity that you indulge in every day. In addition this has always been true of knowledge acquisition, and in my opinion the history of science amply demonstrates that the general ratio of harmful consequences to knowledge gained has been quite low.

Yet we as a society are grabbing on to the Precautionary Principle at every opportunity. We seem to believe that ignorance is better than knowledge since ignorance involves doing nothing and always erring on the side of safety. We think this is ostensibly the safest state of affairs, but it is one which is very much illusory since it’s that same ignorance that unfavorably impacts our long-term security and progress. Time and time again it has been demonstrated that knowledge is better than ignorance even when that knowledge can lead to potential harm, and it’s every inch worth the price we have to pay for accumulating its benefits. This hard won knowledge is now under attack from those who seek to proclaim the safety of their fellow citizens and their children as their highest priority.

Society’s ardent wish to enforce this principle of maximum precaution – whether it involves reacting to terrorism or to school pranks – is turning schools into straitjacketed environments with armed guards and law enforcement where misdemeanors, pranks and honest mistakes that would have gotten a student detention twenty years ago are leading instead to arrests and expulsions. The school environment in many states has turned into an overactive immune system. Any school like Bartow High School which believes that it is setting a good example and improving the safety environment for its students is fooling itself. The New York Times reported that over the years the proportion of harsh punishments for relatively minor misdemeanors has significantly increased. Even pranks like flying paper airplanes in the classroom or using threatening words in front of a fellow student – incidents which would regularly land students into detention or lead to a parent-teacher meeting before – can now get kids expelled or arrested. The current incident falls into the same category. The one goal this kind of excessive disciplinary action achieves is that it leads to a plethora of disgruntled, frightened and disillusioned students who are more likely to engage in criminal behavior. As the Times put it in 2011:

“Schools are right to expel students who pose a threat to others. But suspensions for less serious, nonthreatening behavior have become routine in recent decades, with disastrous consequences. Children who are removed from school are at far greater risk of being held back, dropping out or ending up in the juvenile justice system.”

It does not take much imagination to consider the effects of this environment of handcuffs and arrests on the psychology of young children who are trying to learn and have fun. Schools are already faced with a chorus of hyperactive teenagers who are trying to find their purpose and direction in life. The only way they can do this is by experimenting and they will do this regardless of whether it’s encouraged or not. The last thing the school should be doing is to discourage such experimentation by doling out harsh punishments and cultivating an atmosphere of fear and retribution. Creating an environment for controlled experimentation involves both setting the parameters for that experimentation and creating mechanisms to bring students who might stray from the status quo back into the fold.

Finally, these kinds of punishments are completely self-defeating in a period when lawmakers and educators are urging the country to focus more on science education. What are the chances that Ms. Wilmot will now consider a career as a chemist or even as a scientist? What are the chances of Bartow High School understanding that it has just consigned the career of a potentially promising African-American scientist to the ashes because of its overreaction and overuse of disciplinary power? Is the temporary fear that is put into the minds of students who want to experiment worth killing their interest in science, the same science that countless high school teachers have harnessed as a force for elevating this country’s profile and character over the decades? Bartow High School may have gotten rid of Ms. Wilmot but it will never be able to escape these questions.

I will end by slightly rephrasing a quote from a Founding Father of this country who would have undoubtedly shaken his head at this sad state of affairs. Ben Franklin who did so much to raise the status of science in the public’s consciousness might easily have said that “They who can give up essential knowledge to obtain a little temporary safety, deserve neither”.

And to Kiera Wilmot I say, please don’t give up on yourself because the system failed. Remember the deeds of George Washington Carver and Percy Julian who came before you; both of them rose to prominence in spite of the system and not because of it. Scientific curiosity is too big a deal to be abandoned at the whim of institutional inertia and shortsightedness. In rejecting you this school has rejected its own ideals. You will undoubtedly find another which is more receptive to your curiosity and aspirations. I urge you to carry on.

Note: D. N. Lee has already written an excellent post on this topic. But as a chemist who has experimented with potentially “explosive” chemicals as a teenager, I felt particularly distressed and wanted to weigh in.

Fermilab was designed by Robert Wilson, a physicist who made an impassioned plea for basic research in front of a Congressional committee (Image: Wikipedia Commons)

It’s been said many times. Curiosity-driven research with no immediate application or goal is what has primarily led to science’s greatest discoveries as well as our high standard of living. It is what has led to the ascendancy of American science during the twentieth century. If you want great discoveries to happen, the recipe is clear; get the best scientists together and leave them alone.

And yet politicians just don’t get it. In the latest incarnation of this ignorance, Representative Lamar Smith of Texas wants to tell the NSF how to fund research. And here’s a trivial and forgettable fact: Smith heads the House Committee on Science and Technology. It’s also worth noting that Smith had sponsored the egregious SOPA. Science Magazine has now reported on his lack of understanding of the history of science and technology:

“Science Insider has obtained a copy of the legislation, labeled “Discussion Draft” and dated 18 April, which has begun to circulate among members of Congress and science lobbyists. In effect, the proposed bill would force NSF to adopt three criteria in judging every grant. Specifically, the draft would require the NSF director to post on NSF’s website, prior to any award, a declaration that certifies the research is:

1) “…in the interests of the United States to advance the national health, prosperity, or welfare, and to secure the national defense by promoting the progress of science;

2) “… the finest quality, is groundbreaking, and answers questions or solves problems that are of utmost importance to society at large; and

3) “…not duplicative of other research projects being funded by the Foundation or other Federal science agencies.”

The first point cannot help but remind me of physicist Robert Wilson’s impassioned plea for basic research; when Wilson was asked by a Congressional committee if the giant particle accelerator he was planning was of any significance to national security, he replied that the kind of research he was doing makes the nation worth securing in the first place. If the Congressman or any number of politicians study even the rudiments of the history of science, they would instantly understand that pure, curiosity-driven research has led to innovations that have been paramount for national security, health and welfare. The Internet, lasers, computers, crop breeding, antibiotics and other drugs, electronics, genetic engineering; every single one of these innovations has emerged from largely idle and speculative research whose only purpose was to further our understanding of the natural and physical universe. It’s all out there, documented and repeated countless times. One would think that the man who heads a congressional committee on science and technology would be aware of at least some of the consequences of this speculative research. Perhaps he can start by reading Abraham Flexner’s “The Usefulness of Useless Knowledge“, a clarion call if there ever was one for the benefits of unfettered thinking.

The second point again demonstrates an almost complete ignorance of how science actually works. It actually sounds like a mandate for a new Italian restaurant in Manhattan (“The finest, most groundbreaking Orecchiette this side of the Mississippi”). Almost none of the research that led to groundbreaking advances was seen as groundbreaking at the time. Or perhaps it was groundbreaking in a pure sense but its groundbreaking applications were far from clear. For instance thermodynamics, botany, electromagnetism and anatomy were all fields whose practical significance was far ahead of their times. Nuclear physics is the perfect example. If he lived in the 1930s, Smith would probably have strongly discouraged research on radioactive transmutations, perhaps even comparing the physicists who were attempting it to harebrained alchemists. He would also have deplored Thomas Hunt Morgan’s research on fruit flies as another spectacular example of wasteful spending (a sentiment we have heard before…). And quantum mechanics? That would probably have seemed to him to be the most outrageous example of speculative science, a set of mind-games and paradoxes pondered by obsessive philosophers and symbol-seekers with too much time on their hands; no matter that it later proved indispensable to an understanding of everything from lasers to biochemistry to astrophysics. Heisenberg would probably have given up trying to get funding from Smith’s NSF.

If scientists working on the frontier of their respective disciplines themselves have had a hard time deciding what constitutes “groundbreaking” work, why would politicians – a fraction of whom have degrees in science – be equipped to know any better or to dictate terms to this effect? Here’s my modest suggestion to Rep. Smith: instead of asking scientists to focus on research that’s of “the utmost importance to society at large”, perhaps what you should appreciate is that giving scientists the freedom to pursue research of their choice is in fact what is “of the utmost importance to society at large”. History amply validates this policy.

Charitably speaking, the last point sounds at least somewhat fair. It is important not to reinvent the wheel. But even this view poses a problem. If a hundred inventors tried to invent the wheel without knowing about each other’s work, they would probably end up with products that were all slightly different from each other and offered slightly different benefits. Plus, the congressman does not really need to tell scientists to not duplicate each other’s work since in this era of cash-strapped funding and tight deadlines, most scientists are well aware of this caveat anyway. No assistant professor wants to spend two years duplicating a piece of research, and he or she would presumably spend enough time doing the homework necessary to ensure novelty.

Science in the United States has led to untold benefits in the post-war years largely due to a lack of interference from politicians. That’s not for lack of trying; there have been scores of instances where politicians have tried to micromanage the details of research funding, along with more serious cases of active political interference, but in the bigger picture most of these attempts have largely been unsuccessful. Funding for science has also been rather independent of the political party in charge in Washington. This relative freedom from politics has undoubtedly been a significant factor in the great success of American science; one has to only look at the political and bureaucratic controls over science in countries like the former Soviet Union, China and India to understand how important it is to keep science and politics separate. There is little doubt that science in this country can only continue to thrive without politicians – and especially those who seem to have scant understanding of how science actually works – dictating the flow of funding and imposing their own politically motivated ideology on the work of scientists. In Robert Wilson’s words, that’s the only thing that will continue to make this country worth defending.

Charles Joseph Minard's famous graph showing the decreasing size of Napoleon's Grande Armée as it marches to Moscow; a classic in data visualization (Image: Wikipedia Commons)

As the economy continues to chart its own tortuous, uncertain course, there seems to have been a fair amount of much-needed discussion on the kinds of skills new grads should possess. These skills of course have to be driven by market demand. As chemist George Whitesides asks for instance, what’s the point of getting a degree in organic synthesis in the United States if most organic synthesis jobs are in China?

Upcoming grads should indeed focus on what sells. But from a bigger standpoint, especially in the sciences, new skill sets are also inevitably driven by the course that science is taking at that point. The correlation is not perfect (since market forces still often trump science) but a few examples make this science-driven demand clear. For instance if you were growing up in the immediate post-WW2 era, getting a degree in physics would have helped. Because of its prestige and glut of government funding, physics was in the middle of one of its most exciting periods. New particles were literally streaming out of woodwork, giant particle accelerators were humming and federal and industrial labs were enthusiastically hiring. If you were graduating in the last twenty years or so, getting a degree in biology would have been useful because the golden age of biology was just entering its most productive years. Similarly, organic chemists enjoyed a remarkably fertile period in the pharmaceutical industry from the 50s through the 80s because new drugs were flowing out of drug companies at a rapid pace and scientists like R. B. Woodward were taking the discipline to new heights.

Demand for new grads is clearly driven by the market, but it also depends on the prevalence of certain scientific disciplines at specific time points. This in turn dictates the skills you should have; a physics-heavy market would need skills in mathematics and electronics for instance, a biology-heavy market would mop up people who can run Western blots and PCR. Based on this trend, what kind of skills and knowledge would best serve graduates in the twenty-first century?

To me the answer partly comes from an unlikely source: Stephen Hawking. A few years ago, Hawking was asked what he thought of the common opinion that the twentieth century was that of biology and the twenty-first century would be that of physics. Hawking replied that in his opinion the twenty-first century would be the “century of complexity”. That remark probably holds more useful advice for contemporary students than they realize since it points to at least two skills which are going to be essential for new college grads in the age of complexity: statistics and data visualization.

Let’s start with the need for statistics. Many of the most important fields of twenty-first century research including neuroscience, synthetic and systems biology, materials science and energy are inherently composed of multilevel phenomena that proliferate across different levels of complexity. While the reductionist zeitgeist of the twentieth century yielded great dividends, we are now seeing a movement away from strict reductionism toward emergent phenomena. While the word “emergence” is often thrown around as a fashionable place-card, the fact is that complex, emergent phenomena do need a different kind of skill set.

The hallmark of complexity is a glut of data. These days you often hear talk of the analysis of ‘Big Data’ as an independent field and you hear about the advent of ‘data scientists’. Big Data now has started making routine appearances in the pharmaceutical and biotech industry, whether in the form of extensive multidimensional structure-activity relationship (SAR) datasets or as bushels of genomic sequence information. It’s also important in any number of diverse fields ranging from voter behavior to homeland security. Statistical analysis is undoubtedly going to be key to analyzing this data. In my own field of molecular modeling, statistical analysis is now considered routine in the analysis of virtual screening hits although it’s not as widely used as it should.

Statistics was of course always a useful science but now it’s going to be paramount; positions explicitly looking for ‘data scientists’ for instance specifically ask for a mix of programming skills and statistics. Sadly many formal college requirements still don’t include statistics and most scientists, if they do it at all, learn statistics on the job. For thriving in the new age of complexity this scenario has to change. Statistics must now become a mandatory part of science majors. A modest step in this direction is the publication of user-friendly, popular books on statistics like Charles Wheelan’s “Naked Statistics” or Nate Silver’s “The Signal and the Noise” which have been quickly devoured by science-savvy readers. Some of these are good enough to be prescribed in college courses for statistics non-majors.

Along with statistics, the other important skill for students of complexity is going to be data visualization and formal college courses should also reflect this increasingly important skill set. Complex systems often yield data that’s spread over different levels of hierarchy and even different fields. It’s quite a challenge to visualize this data well. One resource that’s often recommended for data visualization is Edward Tufte’s pioneering series of books. Tufte shows us how to present complex data often convoluted by the constrains of Excel spreadsheets. Pioneering developments in human-computer interaction and graphics will nonetheless ease visual access to complicated datasets. Sound data visualization is important not just to simply understand a multilayered system or problem but also to communicate that understanding to non-specialists. The age of complexity will inherently involve researchers from different disciplines working together. And while we are at it it’s also important to stress – especially to college grads – the value of being able to harmoniously co-exist with other professionals.

Hawking’s century of complexity will call upon all the tools of twentieth century problem solving along with a few more. Statistics and data visualization are going to be at the forefront of the data-driven revolution in complex systems. It’s time that college requirements reflected these important paradigms.

Parched earth in a drought (Image: Wikipedia Commons)

Most of my day job involves simulating the behavior of molecules like drugs and proteins using computer models. The field is more an art than a science, partially because the systems that are being modeled are too complex and ill-understood to succumb to exact solutions. Success often depends on experience and intuition gained by working on similar systems. That does not mean there are no correct predictions, but it does mean that surprises are more common than we think and that many phenomena are impossible to model within a very precise window of accuracy. The failure of a model can sometimes be traced to a simple inability to simulate the behavior of an essential component of the system. In several cases this component is simply the water that surrounds a protein; water remains a substance that’s as enigmatic as any other. In other cases it could be the entropy of the system. The problem is that these factors are very hard to calculate even when we know that they are responsible for the limitations of our model.

A recent report on the failure of climate change models to predict the timing of major droughts in the Southwest made me think of some of the problems in my own field. Unfortunately the actual paper is not out yet so we will have to wait for the details, but the news piece in Nature has a good summary.

Sloan Coats of Columbia University’s Lamont-Doherty Earth Observatory in Palisades, New York, and his colleagues tested whether a state-of-the-art climate model could simulate the droughts known to have occurred in the southwest during the past millennium. The model incorporated realistic numbers for factors that affect temperature and rainfall, such as atmospheric carbon dioxide levels, changes in solar radiation and ash from volcanic eruptions. It also incorporated changes in the El Niño/Southern Oscillation (ENSO).

The results were puzzling. Although the simulation produced a number of pronounced droughts lasting several decades each, these did not match the timing of known megadroughts. In fact, drought occurrences were no more in agreement when the model was fed realistic values for variables that influence rainfall than when it ran control simulations in which the values were unrealistically held constant. “The model seems to miss some of the dynamics that drive large droughts,” says study participant Jason Smerdon, a researcher at Lamont-Doherty who studies historical climate patterns.

Other climate models tested by the team fared no better, he says. In particular, the models failed to reproduce a series of multi-decadal droughts that occurred in the southwest during the Medieval Climate Anomaly, a period between AD 900 and 1200 when global temperatures were about as high as they are today.

The team goes on to provide several possible explanations for the failure of the models, most likely related to their inability to account for details in the ENSO cycle. The researchers also note that the models may not capture some important features of the biosphere.

In addition to their failure to reproduce El Niño and La Niña, existing models do not fully capture other factors that influence rainfall, such as clouds and vegetation. But Smerdon adds that the atmospheric and oceanic dynamics that inhibit rainfall and favour prolonged drought may be essentially random and so almost unpredictable.

This is in fact a problem that has plagued computer models of climate since their very inception in the 1950s. The early general circulation models (GCMs) included the motion of the atmosphere and factors like wind speed, temperature and pressure. Over time these atmospheric circulation models became quite sophisticated, account for radiation transport and the opacity of various gases. The strengths and weakness of these models largely carried over into modern day climate modeling.

In general the models are quite good at simulating the motions of the atmosphere but are still inadequate in accounting for the complex processes in the biosphere, including the behavior of the soil, forests, rivers, mountains and the various plants and animals that inhabit these environments. This discrepancy between accurate atmospheric simulation and lackluster biospheric simulation may be responsible for many of the defects in climate modeling. And as the researchers say, the models are still not great at capturing fine-grained details of clouds and their influence on water. It’s striking to me that both molecular models and climate models struggle in modeling that simplest and most ubiquitous of substances – water. No wonder they have a hard time predicting droughts and precipitation. Finally, the lack of difference in the results when the key factors are held constant and when they are allowed to vary points to an independent and possibly unknown set of factors that are influencing model results.

Nonetheless as the article says, the major predictions about global precipitation seems to be clearer and are based on extensive field studies across the globe; climate change is much more than computer modeling. The problems though are in predicting local precipitation patterns and unfortunately it’s these kinds of predictions that drive public policy at local and state levels. The most important result from such modeling data of course is the knowledge it provides about the strengths and limitations of climate change models. And knowledge is always useful.

E. O. Wilson (Image: Nature and Culture)

Writing in the Wall Street Journal, biologist E. O. Wilson asks if math is necessary for doing great science. At first glance the question seems rather pointless and the answer trivial; we can easily name dozens of Nobel Prize winners whose work was not mathematical at all. Most top chemists and biomedical researchers have little use for mathematics per se, except in terms of using statistical software or basic calculus. The history of science is filled with scientists like Darwin, Lavoisier and Linnaeus who were poor mathematicians but who revolutionized their fields.

But Wilson seems to be approaching this question from two different perspectives and by and large I agree with both of them. The first perspective is from the point of view of students and the second is from the point of view of research scientists. Wilson contends that many students who want to become scientists are put off when they are told that they need to know mathematics well to become great scientists.

“During my decades of teaching biology at Harvard, I watched sadly as bright undergraduates turned away from the possibility of a scientific career, fearing that, without strong math skills, they would fail. This mistaken assumption has deprived science of an immeasurable amount of sorely needed talent. It has created a hemorrhage of brain power we need to stanch.”

I do not know if this is indeed what students feel, but at least on one level it makes sense. While it’s true that chemists and biologists certainly don’t need to know advanced mathematical topics like topology or algebraic geometry to do good science, these days they do need to know how to handle large amounts of data, and that’s a trend that only going to grow by leaps and bounds. Now analyzing large amounts of data does not require advanced mathematics per se – it’s more statistics than mathematics – but one can see how mathematical thinking can help one to understand the kinds of tools (things like machine learning and principal component analysis) that are standard parts of modern data analysis. So while Wilson may be right that professors should not discourage students by requiring them to know mathematics, they also should stress the importance of abstract mathematical thinking that’s useful in analyzing data in fields ranging from evolutionary biology to social psychology. You don’t have to be a mathematician in order to think like a mathematician, and it never hurts these days for any kind of a scientist to take a class in machine learning or statistics.

At the same time Wilson is quite right that true success in science mostly does not come from mathematics. In many fields math is a powerful tool, but only a tool nonetheless; what matters is a physical feel for the systems to which it is applied. As Wilson puts it, “Far more important throughout the rest of science is the ability to form concepts, during which the researcher conjures images and processes by intuition”. In Wilson’s own field for instance, you can use all the math you like to calculate rising and ebbing populations of prey and predator, but true insight into the system can only come from broader thinking that utilizes the principles of evolution. In fact biology can claim many scientists like John Maynard Smith, J. B. S. Haldane and W. D. Hamilton who were excellent mathematicians, but the fact remains that these men’s great contributions came from their understanding of the biological systems under consideration rather than the mathematics itself.

In my own field of chemistry, math is employed as the basis of several physics-based algorithms that are used to calculate the structure and properties of molecules. But most chemists like me can largely get away by using these algorithms as black boxes; our insights into problems comes from analyzing the results of the calculations within the unique structure and philosophy of chemistry. Knowledge of mathematics may or may not help us in understanding molecular behavior, but knowledge of chemistry always helps. The use of mathematics in a field like quantum chemistry (which is perhaps closest to math among all chemical fields) also makes the distinction between “using” math and “knowing” it quite clear; I don’t really know the math behind many theoretical calculations on molecules, but I certainly use it on a regular basis in an implicit way.

What’s interesting is that mathematics is not even a game changer in the world of physics, the one field where its application is considered to be essential. The physicist Eugene Wigner did write an essay named “The Unreasonable Effectiveness of Mathematics in the Natural Sciences”, but even the greatest theoretical physicists of the twentieth century including Einstein, Fermi, Feynman and Bohr were really known for their physical intuition than for formidable mathematical prowess. Einstein’s strength was to imagine thought experiments, Fermi’s was to do rough back-of-the-envelope calculations. So while mathematics is definitely key to making advances in fields like particle physics, even in those fields what really matters is the ability to imagine physical phenomena and make sense of them. The history of physics presents very few examples – Paul Dirac’s work in quantum mechanics and Hermann Weyl’s work in group theory come to mind – where mathematical beauty and ability alone served to bring about important scientific progress.

This use of mathematics as little more than an elegant tool relates to Wilson’s second point concerning math, this time in the context of collaboration. To me Wilson confirms a quote attributed to Thomas Edison who is purported to have said, “I can hire a mathematician but a mathematician cannot hire me”. Most non-mathematicians can collaborate with a mathematician to firm up their analyses, but without a collaborator in the physical or social sciences mathematicians will have no idea what to do with their equations, no matter how rigorous or elegant they are.

The other thing to keep in mind is that an over-reliance on math can also seriously hinder progress in certain fields and even lead to great financial and personal losses. Finance is a great example; the highly sophisticated models developed by physicists on Wall Street caused more harm than good. In the words of the physicist-turned-financial modeler Emanuel Derman, the modelers suffered from “physics envy”, expecting markets to be as precise as electrons and neutrinos. In one sense I see Wilson’s criticism of mathematics as a criticism of the overly reductionist ethos that some scientists bring to their work. I agree with him that this ethos can often lead one to miss the forest for the trees.

The fact is that fear of math often dissuades students and professionals from embarking on research in fields where data analysis and mathematics-type thinking are useful. Wilson’s essay should assure these scientists that they need not fear math and do not even need to know it too well to become great scientists. All they need to do is to use it when it matters. Or find someone who can. The adage about mathematics being the “handmaiden of the sciences” sounds condescending, but it’s not, and it’s fairly accurate.

1. Symptom – Chemophobes fear “chemicals”: This goes without saying. Chemophobes fear a technically nebulous entity called “chemicals” that’s all too real to them. The problem is that in the jargon of chemistry, “chemicals” essentially means everything in the material world, from fuels and plastics to human bodies and baby oil. Over the years chemophobes have expertly molded the word “chemical” into what’s called a “trigger word”, a stimulus that triggers an emotional rather than a rational response. At best the term “chemicals” is so broad as to be useless, and it also does a disservice to the entire material world. To be fair though, I think most chemophobes when they say “chemicals” are referring to what they are thinking of as “bad chemicals”. One would think that they have a much more benign attitude toward “good chemicals”. But even this poses a problem, as the following point makes clear.

An underlying reason for the fear of chemicals is that chemophobes either have a very poor understanding of chemistry or don’t bother to acquaint themselves with the most basic relevant facts. A common misunderstanding is to confuse ingredients used in the manufacture of certain chemicals products with the products themselves. A rather egregious recent example was from a rampantly chemophobic blog that talked about TBHQ- an additive found in certain food products. The blog claimed that “TBHQ is made from butane (a very toxic gas)”. Anyone who understands basic chemistry would understand how woefully wrong this statement is; in fact it may even pass the “Pauli test”. It would be as wrong as saying that water should be avoided “because it is made from hydrogen (a very flammable gas)”. All it means is that the chemical formula of TBHQ subsumes the chemical formula of butane (four carbon atoms) within itself. One of the cardinal rules of chemistry is that when atoms combine and form bonds with each other they lose their individual properties. This principle should be on your mind the next time you read about an article that tries to blame ingredients used in a product’s manufacture for the product’s properties.

Remedy – Understand that the whole material world is made up of chemicals; it’s what our bodies and minds are made up of. Reacting negatively to the word “chemical” is reacting to something that’s vague and undefined. Try to resist the urge to react emotionally rather than rationally when you hear the word; the only way to reduce the impact of trigger words is to counter them with rational thoughts. Most importantly, ask yourself what precise chemical an article is talking about. Where does it come from? How much of it is in the product? What studies have been done on it? How reliable are their conclusions? Try to find out more about it before you reach a judgment. Never accept any article either for or against a particular compound at face value.

2. Symptom – Chemophobes almost never talk about context: Most chemophobes would probably agree that taking political statements out of context can be grossly misleading. Yet they don’t apply the same principles when talking about chemicals. The problem even with denouncing “bad chemicals” is that chemicals can completely change their properties and utility depending on context.

When it comes to chemistry, the biggest aspect of context is the dose; the golden principle of toxicology is the 16^th century natural philosopher Paracelsus’s dictum that “the dose makes the poison”. Botulism toxin or Botox is the ultimate example: a chemical compound that can undoubtedly be fatal under the right circumstances, it has become a staple of aging celebrities wanting to preserve their stunning good looks. On the other hand water, which is generally considered to be a good chemical, can be toxic. What surprises me is that a lot of chemophobes are perfectly aware of how widely used drugs like acetaminophen can be dangerous in excessive doses but are still beneficial in small doses, yet they somehow don’t apply the same thinking to other chemical compounds which they consider toxic, from flame retardants in couches to food additives.

The Botox example also underscores a ubiquitous and deeply flawed belief that “natural’ chemicals are somehow better than “artificial” or synthetic ones. Our standard of living has improved incalculably because of synthetic chemicals like drugs, plastics and fertilizers. Botox which is very natural can be quite bad, and a lifesaving cancer drug which is very artificial can be quite good. About half of all drugs on the market are synthetic and the other half are natural. Both categories have beneficial effects when used as described and ill effects if abused. Thus it’s almost impossible to objectively categorize an individual molecule as “good” or “bad”.

Chemophobes’ cheerful dismissal of context is symptomatic of a bigger problem which is all too common – a lack of appreciation for details which are really at the heart of science. Although many principles of science can be simply explained, the truth is that the meat of science is all about details and subtleties, and it’s very easy to completely misunderstand a scientific study when you shirk from the details. A good example is a recent post on so-called “toxic couches” which are purportedly laced with harmful chemicals. As I made clear in my analysis of the post, it seemed that the author – who has an M.D. degree – had not actually read the primary literature on the compounds which she claimed were poisoning her couch. There was no examination of the actual evidence supposedly implicating the couch chemicals as toxic agents. If the author had done this she would have easily understood that the evidence for her assertions was flimsy at best. This is a common thread underlying almost all articles reflecting chemophobia. There are no references to the underlying literature and no context. One is made to believe that the mere presence of the chemical under consideration makes it a health hazard.

Remedy- Remember that chemicals are no different from most of the technologies that beset us, technologies that can be used for good or evil depending on the context. We cannot divorce their properties from the context and circumstances under which they are being discussed.

When it comes to context, not all of us are inclined or qualified to read the primary literature and analyze detailed chemical or medical studies. So I have found it useful to keep three key context-specific aspects of chemical compound and their effects in mind and to marshal these aspects into a test that any purported chemical should pass to merit the word “dangerous”. These three aspects are dose, sample size and test animal. Even if you don’t know what these are for a particular study, it handsomely pays to at least withhold judgment by asking about them. I will talk about sample size in the next point but let’s focus on the other two for now.

The importance of dose has already been mentioned. Perhaps the most relevant measure of dose in the context of chemophobia is a well-known number called the “LD₅₀” which is the amount of chemical compound that causes death in 50% of the test animals. A lot of times when dangerous chemicals are mentioned by chemophobes, their LD₅₀ is quite low. The nature of test animal (which is already part of the definition of LD₅₀) is also paramount. Many toxicology and chemical studies are done in mice or rats – for good reason – and if there’s one thing you should remember it’s that (with few exceptions) mice and rats are not humans. Although there is some overlap, it’s safe to assume that the effects of a drug or potentially toxic chemical would significantly differ between mice and humans. Another parameter is mode of ingestion; I am sure the material in my t-shirt will probably cause some harm if I ingest it in large quantities but it’s perfectly safe to wear it. The toxicity of a lot of compounds depends on the way they are formulated (solids, liquids, amorphous powders etc.) and therefore the way they are absorbed and excreted by the body. The toxicity also depends on the time they spend inside the body.

Again, the point of this listing is not to enable casual leaders to read the primary literature on LD₅₀, animal studies or formulation but to simply raise questions related to these aspects when they read any article purporting to report the presence of dangerous chemicals in our environment. Vigilance and critical questioning are very effective first barriers to uncritical acceptance.

3. Symptom- For chemophobes everything is “linked to cancer”: Read almost any article about “dangerous chemicals” and you will find them somehow associated with cancer more than with almost any other disease. But the phrase “linked to” is so broad as to be almost useless. Linked to can mean anything from “having a tenuous and unproven connection” to “having a direct correlation” to “considered as a causal factor”. When chemophobes tell us that something is “linked to cancer”, they would have us believe that it “causes” cancer. It is impossible to believe this unless you read the primary literature and in most cases you will find that the truth is quite complex as best.

Again, the devil is in the details, in this case in the devilish complexities of the statistics-based science called epidemiology. As legions of studies have made clear, it is very, very difficult to find a correlation – let alone causation – between any single chemical compound and cancer. Science writer George Johnson wrote an excellent article describing the highly ambiguous correlation between chemicals and cancer in famous cases like the Erin Brockovich story. Part of the reason is that the “natural” cancer background is already very high and we are often challenged by the difficulty of detecting a small excess of cancers in this high background; in fact this high natural background is probably the reason why many chemicals are inevitably associated with cancer in the first place. There have been undoubtedly some cases where this connection has been found, for instance between scrotal cancer and soot or between cigarette smoke and lung cancer. But firstly, these cases are in the minority and secondly, these connections were firmed up only after decades of very exhaustive studies utilizing very large population samples. The same caveat appears to connections between chemicals and almost every other malady. It’s really not possible to draw conclusions unless you scrutinize the statistics.

Remedy - The problem again is that most of us are not inclined or qualified to analyze complex statistical analyses. But statistics is one of those things whose mere awareness gets you brownie points. There are a few simple measures. Going back to the previous point, the single most important question to ask is regarding sample size. A century of statistics has now made it clear that small sample sizes introduce large errors. The “toxic couch” post for instance based its conclusions on a study with a very small sample size. Statisticians have devised ways to deal with small samples, but as a first approximation you should suspect any study that deals with small sample sizes and does not provide error estimates. Other factors to deal with are sample homogeneity and bias and measures of statistical significance. Again, not all of us can become experts in statistics but the very process of asking these questions will make us rightly skeptical of articles evidencing chemophobia.

This is not an “Us vs Them” argument.

I want to end with a plea to build bridges. More than anything else it’s important to empathize with people who fear chemicals. It’s important to understand that these people come in a variety of shades. Many of them simply try to apply the Precautionary Principle and err on the safer side. Many subscribe to the common “Not in My Backyard” sentiment which even chemists would agree with; even if I may fully realize the lack of correlation between, say aniline exposure and cancer, that does not mean I will be ok with tons of aniline being dumped into the soil surrounding my house. Some chemophobes do indeed do it for the publicity even when they know better (anti-industry sentiments almost always sell well on the Internet), and there’s also some who have probably made up their minds and are impervious to reason. Chemophobes thus mirror the same kind of diversity of opinion that you find among climate change skeptics and religious believers and it’s key to not paint all of them with a broad brush. The extremists probably would not be swayed by any kind of argument but I would like to believe that the majority of chemophobes are not in this category and are open to rational argument.

The important thing to realize is that many of these people have at least partially good reasons to express deep skepticism about synthetic chemicals. Even though we as chemists would like to dismiss their fears as irrational, we need to appreciate that Love Canal, Bhopal and Woburn don’t exactly make it easy for us to make our case. In many of these cases the effects of individual chemicals on people’s health were very hard to tease apart. What was uncontested though was the unethical behavior of chemical companies which polluted rivers, soils and groundwater with chemical waste. I just finished Dan Fagin’s superbly researched and written book “Toms River” which documented the unethical and illegal practices of Ciba-Geigy in polluting the environment around Toms River, NJ over a period of thirty years. While this was really the fault of the company and not the chemicals themselves, one must sympathize with the people who waged an expensive campaign against opponents with deep pockets and waited for decades to find an explanation for the heartbreaking early deaths of their sons and daughters. Even if victims of alleged chemical actions may be looking in the wrong places for an answer, their experiences are very real and we don’t have to agree with them in order to empathize with them. We need to do all we can to separate the companies from their products, but we have to appreciate that it’s much harder for a mother who has just lost her 6-year old son to leukemia to do this.

Finally we need to recognize the common bonds that hold all of us together. Scrutinize writers who display chemophobia and we find that many of them share the same goals that we do: to keep our children and our environment safe. Some of them are proponents of healthy eating, others want to hold companies with unethical practices accountable. Look beneath the surface and we find that although our paths may be different, our destination is the same. In JFK’s immortal words, “Our most basic common link is that we all inhabit this planet. We all breathe the same air. We all cherish our children’s future. And we are all mortal.” This parting message should bring chemophobes and chemophiles together; if nothing else, we are all woven from the same chemical tapestry.

The REVAi/G-Wiz i electric car charging at an on-street station in London (Image: Wikipedia Commons)

Ever since Gordon Moore came up with the ubiquitous law bearing his name, it has been applied to paradigms far beyond those which it was intended for. This is perhaps not surprising; the history of science and technology – and of religion – has consistently demonstrated that the followers of a prophet usually extend his principles into domains which the prophet never really approved of.

Transistor technology does neatly seem to follow the Moore’s Law curve and a few other cutting-edge technologies like genome sequencing also seem to do this. Yet Moore’s proselytizers have extended his law to pretty much everything. The law especially seems to break down when applied to biomedical research; for instance a review from last year pointed out how the pace of drug development almost seems to have been following a reverse law, titled “Eroom’s Law” of declining productivity. Kurzweilian prognostications notwithstanding, research in neuroscience might follow the same trajectory, with a burst of rapid mapping of neuronal connectivity followed by a long, fallow period in which we struggle to duplicate these processes by artificial means.

The basic reasons why an emerging technology may not follow Moore’s Law is either because we tend to underestimate the complexity of the system to which the technology is applied, or we underestimate the basic principles of physics and chemistry which would inherently constrain a Moore-type breakthrough in that field. In case of medical research both these constraints seem to rear their ugly, emergent heads, and this is the main problem I have with futurists like Ray Kurzweil who seem to imagine an entire universe governed by Moore’s Law-type exponential progress in every field. Not all levels of complexity are created equal, and we just don’t have enough evidence to know how general Moore’s Law (which I think should simply be re-named “Moore’s Observation”) is in the world of practical problem-solving.

The argument about basic science limitations may especially apply to much-touted battery research whose proponents often seem to declare the next breakthrough in battery technology as being just around the corner. But a perspective from Fred Schlachter from the American Physical Society in the Proceedings of the National Academy of Sciences puts a brake on these optimistic predictions. His point is simple: any kind of Moore’s Law for batteries may be limited by the fundamental chemistry inherent in a battery’s workings. This is unlike transistors, where finer lithography techniques have essentially enabled a repetitive application of miniaturization over the years.

There is no Moore’s Law for batteries. The reason there is a Moore’s Law for computer processors is that electrons are small and they do not take up space on a chip. Chip performance is limited by the lithography technology used to fabricate the chips; as lithography improves ever smaller features can be made on processors. Batteries are not like this. Ions, which transfer charge in batteries are large, and they take up space, as do anodes, cathodes, and electrolytes. A D-cell battery stores more energy than an AA-cell. Potentials in a battery are dictated by the relevant chemical reactions, thus limiting eventual battery performance. Significant improvement in battery capacity can only be made by changing to a different chemistry.

And even this different chemistry is going to be governed by fundamental parameters like the sizes of ions and the rates of chemical reactions and current flow. Schlachter goes on to note the problems that lithium batteries have recently encountered, including fires. There is thus no guarantee that there will be a breakthrough in battery technology that’s equivalent to that in computer technology over the last thirty years. And the article is right that while we are waiting for such breakthroughs, it’s a really good idea to push forward with improving energy efficiency in cars, making their lighter, smaller and and more powerful. Energy efficiency would not ultimately solve pollution problems since the cars would still be fueled by gasoline, but it would certainly take us a long way while we are waiting for the next battery breakthrough engineered by Moore’s Law. A law which may not really hold when it comes to next generation electric technology.

A new paper from NASA’s Goddard Institute authored by Pushker Kharecha and James Hansen in the journal Environmental Science and Technology purports to do just that. Hansen is well known as one of the founders of modern global warming science. The authors come up with the striking figure of 1.8 million as the number of lives saved by replacing fossil fuel sources with nuclear. They also estimate the saving of up to 7 million lives in the next four decades, along with substantial reductions in carbon emissions, were nuclear power to replace fossil fuel usage on a large scale. In addition the study finds that the proposed expansion of natural gas would not be as effective in saving lives and preventing carbon emissions. In general the paper provides optimistic reasons for the responsible and widespread use of nuclear technologies in the near future. It also drives home the point that nuclear energy has prevented many more deaths than what it has caused.

Let’s start with the abstract:

“In the aftermath of the March 2011 accident at Japan’s Fukushima Daiichi nuclear power plant, the future contribution of nuclear power to the global energy supply has become somewhat uncertain. Because nuclear power is an abundant, low-carbon source of base-load power, on balance it could make a large contribution to mitigation of global climate change and air pollution. Using historical production data, we calculate that global nuclear power has prevented about 1.84 million air pollution-related deaths and 64 gigatonnes (Gt) CO2-equivalent greenhouse gas (GHG) emissions that would have resulted from fossil fuel burning. Based on global projection data that take into account the effects of Fukushima, we find that by midcentury, nuclear power could prevent an additional 420,000 to 7.04 million deaths and 80 to 240 GtCO2-eq emissions due to fossil fuels, depending on which fuel it replaces. By contrast, we assess that large-scale expansion of natural gas use would not mitigate the climate problem and would cause far more deaths than expansion of nuclear power.”

The authors look at deaths caused by various power sources during the period 1971-2009. To provide a comparison they build a model in which all the power which was provided by nuclear energy was hypothetically replaced by fossil fuel sources. They employ the same technique for the projected 2010-2050 period, assuming that all current nuclear power sources have been replaced by fossil fuels. Two scenarios are considered – one in which nuclear is replaced by coal and another in which it is replaced by gas. This takes into account the uncertainty regarding the nature of fossil fuel usage that’s inherent in future energy projections.

It’s worth noting that the authors consider only deaths and exclude from the model serious health crises such as heart failure, bronchitis and other respiratory problems; including these problems would further weaken the case for fossil fuels. The study also excludes aspects of nuclear power that cannot be easily quantified, such as deaths from nuclear proliferation.

The results are quite clear. In the 2000-2009 period alone nuclear power may have prevented an average of 76,000 deaths. This is an average and the range is quite large, but even the lower limit runs into the tens of thousands. For countries like Germany which have cut back on nuclear, the range of deaths is naturally higher. This is a result that Japan’s current leaders should take to heart.

What is even more starkly clear is that the number of deaths caused by nuclear power is far lower than those saved by it; in fact there’s scant comparison. As the report notes, even the worst nuclear accident in history (Chernobyl) caused about 40 deaths; these include 28 immediate responders and about 15 deaths caused among 6000 victims of excess cancers (it’s always very difficult to detect statistically significant excess cancers in the presence of a high natural background rate). There have been no deaths attributable to the Three Mile Island accident. And while the verdict on Fukushima is still not definitive, the latest report on the accident predicts no direct deaths and a much lower exposure to radiation for the surrounding population than that purported to lead to fatal cancers. The bottom line is that, even assuming pessimistic scenarios, the number of deaths caused by nuclear power is a minuscule fraction of those lives which were saved by nuclear power replacing fossil fuels.

Nuclear-free projections for the next four decades look even more dire. The authors estimate between 4 and 7 million deaths for the “All-Coal” scenario and between 420, 000 – 680, 000 deaths for an “All-Gas” energy policy. This is something which countries like Germany and Japan that are planning to phase out nuclear must seriously consider. Only if all the nuclear power were replaced by equipotent renewable energy sources in the next four decades would these deaths be prevented. This kind of high-capacity deployment of renewables seems quite uncertain for now.

Of course it’s not just the deaths. All the fossil fuel sources replacing nuclear power would contribute a very significant concentration of greenhouse gases to the atmosphere and severely aggravate the effects of climate change. The authors estimate an additional 80 to 240 GtCO₂-equivalents of greenhouse gases from fossil fuel sources in the next forty years if nuclear power were to decline. To put this into perspective, consider that the total amount of “allowable” input of greenhouse gases required to achieve a 350 ppm CO2 target by the end of the century is 500 GtCO2-equivalent. Nuclear power could thus reduce this load by 16-48%. Deploying some of the new promising reactor technologies could reduce this load even more.

The conclusions of the study are quite unambiguous. Even assuming uncertainties, nuclear power has saved at least hundreds of thousands of lives in the past forty years, and possibly millions. This is in stark contrast to the small number of lives lost in only one catastrophic nuclear accident. There are many more millions that would be lost if countries were to embark on a nuclear-free future replaced by fossil fuels. Natural gas might be a reasonable bridge to this future but it’s clear that it cannot be a sustainable one. It would take “heroic” efforts (in the words of the International Energy Agency) to replace all the nuclear power in the world with renewables in the next forty years. New generations of nuclear reactors like the molten salt and pebble bed reactors promise to make nuclear energy even more safe, efficient and cheap. Even Bill Gates is investing in a novel reactor design. The verdict is staring us in the face; we ignore energy from the atom at our own peril, and at the potential cost of a staggering number of lives from our children and grandchildren’s generation. It’s not the kind of legacy we want to be remembered for.

Even an omniscient being like Dr. Manhattan from Watchmen could not have predicted the result of life's accidents (Image: Christian Fearing Godman)

The reductionist zeitgeist of physics cannot “explain” chemistry any more than “entropy” explains the inexorable march of life from birth to death. It’s important to understand what we mean when we say that physics cannot explain chemistry. Physics of course accounts for chemistry in the trite sense that molecules are composed of atoms. But then physics also “accounts for” human behavior since the brain is ultimately composed of atoms too. Yet we have no clue how to get from atoms to things like jealousy and musical creativity. When we say that A explains B, it usually means there is an unbroken and logical thread of continuity connecting A to B by way of which the properties of A are manifestly demonstrated in B. This physics cannot do even in the highly reductionist realm of chemistry, let alone in “higher” realms like neuroscience and sociology. These days emergence has become a fashionable word that’s often thrown around to describe any kind of complexity, but the emergence of chemical and biological properties that cannot be deduced from their underlying physics is in fact quite real.

There are several reasons why the reductionist approach in science doesn’t always work, but one of the most important ones was alluded to by the physicist and writer Jeremy Bernstein in a Wall Street Journal review of a biography of George Gamow and Max Delbruck:

Some sciences are more unruly than others. Here’s a parable to illustrate what I mean. Imagine that when the first life form appeared there was a super intelligent freak. If this freak had had a complete knowledge of the laws of physics, what could it have predicted? Quite a lot. All atomic nuclei consist of neutrons and protons, and the number of protons determines each element’s chemical nature. Knowing this, the freak could have predicted all the elements that could possibly exist, along with their respective characteristics. Suppose that it also knew all the laws of biology, including the “central dogma,” which explains how genes are expressed as proteins. Even so, it could not have predicted the existence of giraffes, nor even the fact that my brother and I share only half our genes. Both of these are evolutionary accidents. If it had not been for random mutation there would be no giraffes, and my brother and I might have shared all our genes, as male bumblebees do. Biology is not like physics.

This paragraph succinctly drills down to one of the fundamental limitations of physics-based reductionism and it’s a point that applies to chemistry as well. It’s a very important one. The problem is that reductionism cannot account for the role of historical contingency and accident. Even if an all-powerful being could account for all biological scenarios emerging from an initial state of the universe, it could never tell us why one particular scenario is preferred over others. As Bernstein says, evolutionary accidents by definition cannot be predicted from starting conditions because they depend on chance and opportunity.

In addition function can never be uniquely derived from reductionism even if structure is. For instance in his book “Reinventing the Sacred”, the complexity theorist Stuart Kauffman makes a powerful argument that even if one could derive the structure of the human heart from string theory in principle, string theory would never tell us that its most important function is to pump blood. The function of biological organs arose as an adaptive consequence of the countless unpredictable constraints that molded them during evolution. In addition the evolution of both structure and function was a mix-and-match process that depended as much on chance encounters as on strict adaptation. All this can never be captured in a reductionist worldview.

The same principle applies to chemistry. Evolution has fashioned many unique molecules that underpin life’s machinery. The question facing many chemists and especially chemists working on the origins of life is, why this particular molecule and not that one? Here are some more specific conundrums: Why are there only twenty amino acids, why are there alpha amino acids instead of beta or gamma amino acids (which have extra carbon atoms), why is amino acid stereochemistry (molecular “handedness”) L while sugar stereochemistry is D, why does DNA consist of a very specific set of four nucleotides and no other, why did nature choose phosphates in the construction of so many important biomolecules (the chemist Frank Westheimer comes close to answering this question), why does a given protein fold into only one unique functional structure, why is water is the only solvent known to sustain life, and in general why are the myriad small and large molecules of life what they are. In retrospect of course one could provide several arguments for the existence of these molecules based on stability, function and structure but there is no way to predict these parameters prospectively.

The fact is that an all-powerful, super-reductionist freak would have been useless in accounting for the unique existence of life’s chemical precursors. This is because there is nothing in the nature of these molecules which dictates that their presence should have been uniquely determined. For instance we now know from chemical studies that beta and gamma amino acids can also fold into the kind of helix and sheets motifs that are ubiquitous for alpha amino acids. They also have other favorable properties like chemical diversity which might have made them better building blocks compared to alpha amino acids. Yet for some reason they were discarded during evolution. Why? We could come up with several arguments. For instance because of their floppiness, maybe the higher order versions had to pay an unacceptable entropic penalty that could not compensate for their folding propensity. Or maybe a reaction called the Strecker reaction that is thought to produce alpha amino acids could never be superseded by beta amino acid-forming chemical reactions. Or perhaps alpha amino acids shield hydrophobic or water-hating side chains much better than their longer chain counterparts. These are all cogent reasons, and yet I am sure we could find an equal number of arguments against alpha amino acids if we searched hard enough. The truth is that the ultimate failure to find an explanation for the existence of alpha amino acids is a powerful reminder of the importance that chance and circumstance played in the evolution of both biomolecules as well as living organisms. Reductionism does not help us in tracing a path through this random, probabilistic landscape of evolution. The identities of life’s fundamental building blocks were shaped by chance followed by Darwinian natural selection.

This role of contingency and accident is one of the most important reasons why the reduction of chemistry and biology to physics will not work. Even if reductionism could provide us a list of all possible scenarios in chemical and biological evolution, it could never tell us which one would be preferred and for what reason. This is yet another reason why chemistry and biology are not physics.

This is a revised and updated version of a post on The Curious Wavefunction blog.

A bottle of antiseptic mouthwash containing chlorhexidine (Image: HKSCCM)

Apoptosis or programmed cell death is one of the great truths of cellular life, an essential process that’s not only required to make way for new cells but to prevent old cells from going haywire. When cells circumvent this great truth they start dividing uncontrollably and contribute to cancer. Our knowledge of cancer over the last three decades has confirmed the central role that a breakdown in the usual mechanisms of apoptosis plays in pushing a cell across the tipping point into a cancerous state. Of the many strategies to fight cancer, one consists of trying to find drugs that force cells to regain their normal balance of apoptosis. Now this effort may have found an unlikely ally.

Chlorhexidine is an antibacterial and plaque-fighting compound that is a common component of mouthwash, usually present as a 0.1% or 0.2% solution. In a paper published in the journal Angewandte Chemie, scientists in Germany report an unexpected effect of chlorhexidine and its related cousin alexidine: they inhibit cancer cells in the mouth by blocking an important protein-protein interaction. This research opens up new directions in investigating this class of compounds as anticancer agents and also sheds light on the value of finding novel potential uses for everyday chemical compounds. One of the great advantages in this endeavor is that the “repurposed” compounds have already run the gauntlet of safety tests required by the FDA, potentially shortening the period of approval for their new uses.

Protein-protein interactions (PPIs) are often considered the next frontier in drug discovery. They are involved in almost every important molecular-level event in health and disease. Traditional drugs work by blocking the action of single proteins (typically fitting into them like a key fits into a lock) but since there are many more protein-protein interactions than single proteins, there is enormous potential in developing drugs that disrupt these interactions, many of which are upregulated in diseases like cancer. Unfortunately targeting PPIs is difficult because of a variety of reasons; they have large, spread-out interfaces which makes it difficult for small organic molecules to span their surface area, and typically the ones which do are too big to satisfy the many qualities of an ideal drug, such as an ability to get inside cells in the first place.

One of the most well studied PPIs is the interaction between a family of pro-apoptotic and anti-apoptotic proteins called the Bcl-2 family. These proteins are present in all our cells. As their name indicates, one group of proteins speeds up apoptosis while the other group inhibits it. In a normal cell there is a usually a precise balance between these two activities engineered by the two sets of proteins binding to each other and regulating each other’s function. It’s a delicate dance which ensures that the cells are active only when needed and any cells gone haywire are eliminated. In cancer this precise balance is disrupted and the anti-apoptotic proteins are over-expressed and become dominant. One anti-apoptotic protein named Bcl-Xl in particular keeps its usually equipotent pro-apoptotic protein partner named Bak bound up and prevents the cell from committing suicide; this molecular-level feud leads to uncontrolled cell division. Over the years researchers have tried to find many druglike molecules and peptides which could block Bcl-Xl and free up the Bak protein. But none of the attempts have resulted in a clinically marketed drug.

What the researchers in Germany did was to screen about 4000 everyday chemical compounds to look for ones that might block the Bcl-Xl protein. They found two which, surprisingly, had very different uses. Chlorhexidine and alexidine are common components of mouthwash. Both compounds were found to inhibit the Bcl-Xl – Bak interaction at a concentration that’s much lower than that found in mouthwash. Surface-exposed oral cells in the mouth are thus bathed in a rather potent concentration of small molecules that prevent at least one important mechanism involved in cancer from manifesting itself. The researchers also did further experiments, including computer modeling, that localized the site of binding of the two compounds on the Bcl-Xl protein. This site was the same as that occupied by the Bak protein, further supporting the blocking interaction of the mouthwash components with the anti-apoptotic protein.

Finally the researchers tested these two compounds against cancerous cells from the tongue and the pharynx. Both compounds were found to significantly reduce the degree of apoptosis suppression in these cells, connecting the molecular level interaction of the molecules to actual anticancer effects.

This study is interesting for several reasons. It directly leads to a new class of compounds that may have promising anticancer activities; very likely the compounds’ structures would have to be modified by chemists to improve their properties, but this is what chemists have always done best. The therapeutic concentration that’s required for inhibiting the proteins is already exceeded in your garden variety mouthwash; this may also indicate a healthy margin of safety. A more intriguing question to ask is whether the use of mouthwash correlates with lower incidence of oral cancer. The literature on the relationship between mouthwash and oral cancer has been confusing and there don’t seem to be large-scale studies investigating a possible connection. By suggesting a possible mechanism of cancer prevention, this study provides a strong motivation to gather epidemiological data about possible anticancer effects of mouthwash and its components. It’s too early to start dousing your mouth with mouthwash though since these compounds only target one kind of interaction and we don’t have enough data on higher concentrations and long-term effects. But it’s definitely a promising start that points the way to interesting experiments, and that’s what science is best at doing.

Most tantalizingly though, the study asks what other kinds of therapeutic effects may be hidden in everyday chemical products, in our bathroom and kitchen closets. Nature is much more interesting than we think and molecules often lead double lives. Contemplate this the next time you brush your teeth or wash your dishes.