Kurt Gödel's Open World

Today marks Kurt Gödel's one hundred and eleventh birthday. Along with Aristotle, Gödel is often considered the greatest logician in history. But I believe his influence goes much farther. In an age when both science and politics seem to be riddled with an incessant search for "truth" - often truth that aligns with one's preconceived social or political opinions - Gödel's work is a useful antidote and a powerful reminder against the illusion of certainty.

Gödel was born in 1906 in Brünn, Czechoslovakia, at a time when the Austro-Hungarian empire was at its artistic, philosophical and scientific peak. Many of Gödel's contemporaries, including Ludwig Wittgenstein, distinguished themselves in the world of the intellect during this period. Gödel was born to middle class parents and imbibed the intellectual milieu of the times. It was an idyllic time, spent in cafes and lecture halls learning the latest theories in physics and mathematics and pondering the art of Klimt and the psychological theories of Freud. There had not been a major European conflict for almost a hundred years.

In his late teens Gödel came to Vienna and became part of the Vienna Circle, a group of intellectuals who met weekly to discuss the foundations of philosophy and science. The guiding principle of the circle was the philosophy of logical positivism which said that only statements about the natural world that can be verified should be accepted as true. The group was strongly influenced by both Bertrand Russell and Ludwig Wittgenstein, neither of whom was formally a member. The philosopher Karl Popper, whose thinking on falsification even now is an influential part of science, ran circles around the group, although his love for them seems to be unreciprocated.

It was at the tender age of 25 that young Gödel published his famous incompleteness theorem. He did this as part of his PhD dissertation, making that dissertation one of the most famous in history (as a rule, even most famous scientists don't always do groundbreaking work in graduate school). In a mere twenty-one pages, Gödel overturned the foundations of mathematics and created an edifice that sent out tendrils not just in mathematics but in the humanities, including psychology and philosophy.

To appreciate what Gödel did, it's useful to take a look at what leading mathematicians thought about mathematics until that time. Both Bertrand Russell and the great mathematician David Hilbert had pursued the foundations of mathematics with conviction. In a famous address given in 1900, Hilbert had laid out what he thought were the outstanding problems in mathematics. Perhaps none of these was as important as the overarching goal of proving that mathematics was both consistent and complete. Consistency means that there exists no statement in mathematics that is both true and false at the same time. Completeness means that mathematics should be capable of proving the truth or falsity (the "truth value") of every single statement that it can possibly make. 

In some sense, what Hilbert was seeking was a complete "axiomatization" of mathematics. In a perfectly axiomatized mathematical system, you would start with a few statements that would be taken as true, and beginning with these statements, you would essentially have an algorithm that would allow you derive every possible statement in the system, along with their truth value. The axiomatization of mathematics was not a new concept; it had been pioneered by Euclid in his famous text of geometry, "The Elements". But Hilbert wanted to do this for all of mathematics. Bertrand Russell had similar dreams.

In one fell swoop the 25-year-old Gödel shattered this fond hope. His first incompleteness theorem, which is the most well-known, proved that any mathematical system which is capable of proving the basic theorems of arithmetic is always going to include statements whose truth value cannot be proved using the axioms of the system. You could always 'enlarge' the system and prove the truth value in the new system, but then the new, enlarged system itself would contain statements which succumbed to Gödel's theorem. What Gödel thus showed is that mathematics will always be undecidable. It was a remarkable result, one of the deepest in the annals of pure thought, striking at the heart of the beautiful foundation built by mathematicians ranging from Euclid to Riemann over the previous two thousand years.

Gödel's theorems had very far-reaching implications; in mathematics, in philosophy and in human thought in general. One of those momentous implications was worked out by Alan Turing when he proved a similar theorem for computers, addressing a problem called the "halting problem". Similar to Hilbert's hope for the axiomatization of mathematics, the hope for computation was that, given an input and a computer program, you could always find out whether the program would halt. Turing proved that you could not decide this for an arbitrary program and an arbitrary input (although you can certainly do this for specific programs). In the process Turing also clarified our definitions of "computer" and "algorithm" and came up with a universal "Turing machine" which embodies a mathematical model of computation. Gödel's theorems were thus what inspired Turing's pioneering work on the foundations of computer science.

Like many mathematicians who make seminal contributions in their twenties, Gödel produced nothing of comparable value later in his life. He migrated to the US in the 1930s and settled down at the Institute for Advanced Study in Princeton. There he made a new friend - Albert Einstein. From then until Einstein's death in 1955, the sight of the two walking from their homes to the institute and back, often mumbling in German, became a town fixture. Einstein afforded the privilege of being his walking companion to no one, and seemed to have considered only Gödel as his intellectual equal: in fact he held Gödel in such esteem that he was known to have said in his later years that his own work did not mean much to him, and the main reason he went to work was to have the privilege of walking home with Gödel. At least once Gödel startled his friend with a scientific insight he had: he showed using Einstein's own field equations of gravitation that time travel could be possible.

Sadly, like a few other mathematical geniuses, Gödel was also riddled with mental health problems and idiosyncrasies that got worse as he grew older. He famously tried to find holes in the U.S. Constitution while taking his citizenship exam, and Einstein who accompanied him to the exam had to talk him out of trying to demonstrate to the judge how the U.S. could be turned into a dictatorship (nowadays some people have similar fears, but for different reasons). After Einstein died Gödel lost his one friend in the institute. Since early childhood he had always been a hypochondriac - often he could be seen dressed in a warm sweater and scarf even in the balmy Princeton summer - and now his paranoia about his health greatly grew. He started suspecting that his food was poisoned, and refused to accept anything not cooked by his protective wife Adele; in 1930s Vienna she had once physically protected him from Nazis, and now she was protecting him from imagined germs. When Adele was hospitalized with an illness, Kurt stopped eating completely. All attempts to soothe his fears failed, and on January 14, 1978 he died in Princeton Hospital, weighing only 65 pounds and essentially succumbing to starvation. Somehow this sublimely rational, austere man had fallen prey to a messy, frightful, irrational paranoia; how these two contradictory aspects of his faculties conspired to doom him is a conundrum that will remain undecidable.

He left us a powerful legacy. What Gödel's theorems demonstrated was that not only the world of fickle human beings but also the world of supposedly crystal-clear mathematics is, in a very deep sense, unknowable and inexhaustible. Along with Heisenberg's uncertainty principle, Gödel's theorems showed us that all attempts at grasping ultimate truths are bound to fail. More than almost anyone else, Gödel contributed to the fall of man from his privileged, all-knowing position.

We see his undecidability in politics and human affairs, but it is true even in the world of numbers and watertight theorems. Sadly we seem to have accepted uncertainty in mathematics while we keep on denying it in our own lives. From political demagogues to ordinary people, the world keeps getting ensnared in passionate attempts to capture and declare absolute truth. The fact that even mathematics cannot achieve this goal should give us pause. It should inculcate a sense of wonder and humility in the face of our own fallibility, and should lead us to revel in the basic undecidability of an open world, a world without end, Kurt Gödel's world. 

Science books for 14-year-olds

A few days back a relative of mine asked me for science book recommendations for a very bright 14-year-old nephew who's a voracious reader. She was looking both for books that would be easy for him to read as well as ones which might be pitched at a slightly higher level which can still give him a good sense of the wonder and challenges of science.

The easiest way to recommend these volumes was for me to think about books that strongly inspired me when I myself was growing up, so here's my top ten list which I copied in my email to her. I think that these books make for excellent reading not just for 15-year-olds but for 40 and 80-year-olds for that matter. Feel free to add suggestions in the comments section.

1. One, Two, Three…Infinity by George Gamow: Physicist George Gamow’s delightful book talks about many fascinating facts in maths, astronomy and biology (Gamow's comparison of "different infinities” had blown my socks off when I first read it).

2. Microbe Hunters by Paul DeKruif: This book tells the stories of the determined and brilliant doctors and scientists who discovered disease-causing bacteria and treatments for them.

3. Men of Mathematics by E. T. Bell: This classic book does for mathematicians what Paul DeKruif’s book does for doctors. Although it romanticizes and in some cases embellishes its stories, it has inspired many famous scientists who read it and later won Nobel Prizes.

4. Almost any book by Martin Gardner is great for mathematical puzzles (for eg. “Perplexing Puzzles and Tantalizing Mathematical Teasers”.)

5. Raymond Smullyan’s “What is the Name of this Book? The Riddle of Dracula and other Logical Puzzles” is another absolutely rib-tickling book on puzzles and brain teasers. What is remarkable about Smullyan's volumes is that many of his apparently silly puzzles are not only quite hard, but they hint at some of the deepest mysteries of math and logic, such as Gödel's Theorems.

6. "My Family and Other Animals" by Gerald Durrell: This delightful book talks about the author’s experiences with animals of all kinds while vacationing on a small Greek island with his family.

7. I would also recommend science fiction books by H. G. Wells if he likes fiction, especially “The Time Machine” and “The War of the Worlds."

8. "Surely you’re joking Mr. Feynman" by Richard Feynman: Feynman was one of the most brilliant physicists of the 20th century, and this very funny autobiography documents his adventures in science and life. Even if he doesn’t understand all the chapters it will give him an appreciation for physics and how physics can be fun.

9. "Uncle Tungsten: Memories of a Chemical Boyhood" by Oliver Sacks. Oliver Sacks was a famous neurologist but this book talks about his exciting adventures with chemistry while growing up.

10. "A Brief History of Time" by Stephen Hawking. Some of the chapters may be advanced for him right now but it will give him a flavor of the most fascinating concepts of space and time, including black holes and the Big Bang.

11. "King Solomon's Ring" by Konrad Lorenz. This utterly entrancing and hilarious account by Nobel laureate Konrad Lorenz talks about his pioneering imprinting and other experiments with fascinating animals like sticklebacks and shrews. The story of Lorenz quacking around on his knees while baby ducks follow him is now a classic in the annals of animal behavior.

Sixty-four years later: How Watson and Crick did it

"A Structure for Deoxyribose Nucleic Acid",
Nature, April 25, 1953 (Image: Oregon State University)

Today marks the sixty-fourth anniversary of the publication of the landmark paper on the structure of DNA by Watson and Crick, which appeared in the April 25, 1953 issue of the journal Nature. Even fifty years later the discovery is endlessly intriguing, not just because it's so important but because in 1954, both Watson and Crick were rather unlikely characters to have made it. In 2012 I wrote a post for the Nobel Week Dialogue event in Stockholm with a few thoughts on what it exactly was that allowed the duo to enshrine themselves in the history books; it was not sheer brilliance, it was not exhaustive knowledge of a discipline, but it was an open mind and a relentless drive to put disparate pieces of the puzzle together. I am reposting that piece here.

Somehow it all boils down to 1953, the year of the double helix. And it’s still worth contemplating how it all happened.

Science is often perceived as either a series of dazzling insights or as a marathon. Much of the public recognition of science acknowledges this division; Nobel Prizes for instance are often awarded either for a long, plodding project that is sustained by sheer grit (solving a protein crystal structure), a novel idea that seems to be an inspired work of sheer genius (formulating the Dirac equation) or an accumulated body of work (organic synthesis).

But in one sense, both these viewpoints of science are flawed since both of them tend to obscure the often haphazard, unpredictable, chancy and very human process of research. In reality, the marathon runner, the inspired genius and every scientist in between the two tread a tortuous path to the eureka moment, a path that’s highlighted by false alleys, plain old luck, unexpected obstacles and most importantly, the human obstacles of petty rivalry, jealousy, confusion and misunderstanding. A scientific story that fully captures these variables is, in my opinion, emblematic of the true nature of research and discovery. That is why the discovery of the double helix by Watson and Crick is one of my favorite stories in all of science.

The reason why that discovery is so appealing is because it really does not fit into the traditional threads of scientific progress highlighted above. During those few heady days in Cambridge in the dawn of those gloomy post-war years, Watson and Crick worked hard. But their work was very different from, say, the sustained effort akin to climbing a mountain that exemplified Max Perutz’s lifelong odyssey to solve the structure of hemoglobin. It was also different from the great flashes of intuition that characterized an Einstein or a Bohr, although intuition was applied to the problem – and discarded – liberally. Neither of the two protagonists was an expert in the one discipline that they themselves acknowledged mattered most for the discovery – chemistry. And although they had a rough idea of how to do it, neither really knew what it would take to solve the problem. They were far from being experts in the field.

And therein lies the key to their success. Because they lacked expertise and didn’t really know what would solve the problem, they tried all approaches at their disposal. Their path to DNA was haphazard, often lacking direction, always uncertain. Crick, a man who already considered himself an overgrown graduate student in his thirties, was a crystallographer. Watson, a precocious and irreverent youngster who entered the University of Chicago when he was fifteen, was in equal parts geneticist and bird-watcher. Unlike many of their colleagues, both were firmly convinced that DNA and not protein was the genetic material. But neither of them had the background for understanding the chemistry that is essential to DNA structure; the hydrogen bonding that holds the bases together, the acid-base chemistry that ionizes the phosphates and dictates their geometric arrangement, the principles of tautomerism that allow the bases to exist in one of two possible forms; a form that’s crucial for holding the structure together. But they were willing students and they groped, asked, stumbled and finally triumphantly navigated their way out of this conceptual jungle. They did learn all the chemistry that mattered, and because of Crick they already understood crystallography.

And most importantly, they built models. Molecular models are now a mainstay of biochemical research. Modelers like myself can manipulate seductively attractive three-dimensional pictures of proteins and small molecules on computer screens. But modeling was in its premature days in the fifties. Ironically, the tradition had been pioneered by the duo’s perceived rival, the chemist Linus Pauling. Pauling who would be widely considered the greatest chemist of the twentieth century had successfully applied his model-building approach to the structure of proteins. Lying in bed with a bad cold during a visiting sojourn at Oxford University, he had folded paper and marked atoms with a pencil to conform to the geometric parameters of amino acids derived from simple crystal structures. The end product of this modeling combined with detailed crystallographic measurements was one of twentieth century biochemistry’s greatest triumphs; the discovery of the alpha-helical and beta-sheet structures, foundational structural elements in virtually every protein in nature. How exactly the same model-building later led Pauling to an embarrassing gaffe in his own structure of DNA that violated basic chemical principles is the stuff of folklore, narrated with nonchalant satisfaction by Watson in his classic book “The Double Helix”.

Model building is more art than science. By necessity it consists of patching together imperfect data from multiple avenues and techniques using part rational thinking and part inspired guesswork and then building a picture of reality – only a picture – that’s hopefully consistent with most of the data and not in flagrant violation with important pieces. Even today modeling is often regarded skeptically by the data-gatherers, presumably because it does not have the ring of truth that hard, numerical data has. But data by itself is never enough, especially because the methods to acquire it themselves are incomplete and subject to error. It is precisely by combining information from various sources that one expects to somehow cancel these errors or render them unimportant, so that the signal from one source complements its absence in another and vice versa. The building of a satisfactory model thus often necessarily entails understanding data from multiple fields, each part of which is imperfect.

Watson and Crick realized this, but many of their contemporaries tackling the same problem did not. As Watson recounts it in a TED talk, Rosalind Franklin and Maurice Wilkins were excellent crystallographers but were hesitant to build models using imperfect data. Franklin especially came tantalizingly close to cracking DNA. On the other hand Erwin Chargaff and Jerry Donahue, both outstanding chemists, were less appreciative of crystallography and again not prone to building models. Watson and Crick were both willing to remedy their ignorance of chemistry and to bridge the river of data between the two disciplines of chemistry and crystallography. Through Donohue they learnt about the keto-enol tautomerism of the bases that gave rise to the preferred chemical form. From Chargaff came crucial information regarding constancy of the ratios of one kind of base (purines) to another (pyrimidines); this information would be decisive in nailing down the complementary nature of the two strands of the helix. And through Rosalind Franklin they got access – in ways that even today spark controversy and resentment – to the best crystallographic data on DNA that then existed anywhere.

What was left to do was to combine these pieces from chemistry and crystallography and put together the grand puzzle. For this model building was essential; since Watson and Crick were willing to do whatever it took to solve the structure, to their list of things-to-do they added model building. Unlike Franklin and Wilkins, they had no qualms about building models even if it meant they got the answer partially right. The duo proceeded from a handful of key facts, each of which other people possessed, but none of which had been seen by the others as part of an integrated picture. Franklin especially had gleaned very important general features of the helix from her meticulous diffraction experiments and yet failed to build models, remaining skeptical about the very existence of helices until the end. It was the classic case of the blind men and the elephant.

The facts which led Watson and Crick down the road to the promised land included a scattered bundle of truths about DNA from crystallography and chemistry; the distance between two bases (3.4 Å), the distance per turn of the helix (34 Å) which in turn indicated a distribution of ten bases per turn, the diameter of the helix (20 Å), Chargaff’s rules indicating equal ratios of the two kinds of bases, Alexander Todd’s work on the points of linkage between the base, sugar and nucleotide, Donohue’s important advice regarding the preferred keto form of the bases and Franklin’s evidence that the strands in DNA must run in opposite directions. There was another important tool they had, thanks to Crick’s earlier mathematical work on diffraction. Helical-diffraction theory told them the kind of diffraction pattern that would expect if the structure were in fact helical. This reverse process – predicting the expected diffraction parameters from a model – is today a mainstay of the iterative process of structure refinement used by x-ray crystallographers to solve structures as complex as the ribosome.

Using pieces from the metal shop in Cambridge, Watson gradually accumulated a list of parts for the components of DNA and put them together even as Crick offered helpful advice. Once the pieces were in place, the duo were in the position of an airline pilot who has every signpost, flag and light on the runway paving his way for a perfect landing. The end-product was unambiguous, incisive, elegant, and most importantly, it held the key to understanding the mechanism of heredity through complementary base-pairing. Franklin and Wilkins came down from London; the model was so convincing that even Franklin graciously agreed that it had to be correct. Everyone who saw the model would undoubtedly have echoed Watson and Crick’s sentiment that “a structure this beautiful just had to exist”.

In some sense the discovery of the DNA structure was easy; as Max Perutz once said, the technical challenges that it presented were greatly mitigated because of the symmetry of the structure compared to the controlled but tortuous asymmetry inherent in proteins. Yet it was Watson and Crick and not others who made this discovery and their achievement provides insight into the elements of a unique scientific style. Intelligence they did not lack, but intelligence alone would not have helped, and in any case there was no dearth of it; Perutz, Franklin, Chargaff and Pauling were all brilliant scientists who in principle could have cracked open the secret of life which its discoverers proudly touted that day in the Eagle Pub. 

But what these people lacked, what Watson and Crick possessed in spades, was a drive to explore, interrogate, admit ignorance, search all possible sources and finally tie the threads together. This set of traits also made them outsiders in the field, non-chemists who were trying to understand a chemical puzzle; in one sense they appeared out of nowhere. But because they were outsiders they were relatively unprejudiced. Their personalities cast them as misfits and upstarts trying to disrupt the established order. Then there was the famous irreverence between them; Crick once said that politeness kills science. All these personal qualities certainly helped, but none was as important as a sprightly open-mindedness that was still tempered by unsparing rigor, the ability to ask for and use evidence from all quarters while constraining it within reasonable bounds all the time; this approach led to model building almost as a natural consequence. And the open-mindedness also masked a fearlessness that was undaunted by the imperfect nature of the data and the sometimes insurmountable challenges that seemed to loom.

So that’s how they did it; by questioning, probing, conjecturing and model building even in the presence of incomplete data, and by fearlessly using every tool and idea at their disposal. As we approach problems of increasing biological complexity in the twentieth century, this is a lesson we should keep in mind. Sometimes when you don’t know what approach will solve a problem, you try all approaches, all the time constraining them within known scientific principles. Richard Feynman once defined scientific progress as imagination in a straitjacket, and he could have been talking about the double helix.

R. B. Woodward, general problems and the importance of timely birth

History has its own way of securing rewards for those who ride its crests. That's especially true of scientists. If we look at the greatest scientists in history, there is no doubt that being born at the right place at the right time is paramount in scientific success. One of the main reasons for this is that certain times are ripe for solving general problems, and the specific examples that are then attacked are only special cases, presumably choice fodder for 'lesser' minds.

R B Woodward, who celebrates his 100th birthday this week, is certainly a case in point. He showed us how to synthesize almost any complex molecule, and it’s not possible to see how someone could do that again. Until Woodward did it many believed that it might be impossible to synthesize molecules as complex as reserpine, chlorophyll, cholesterol and vitamin B12, and after he did it there was no doubt in anyone's mind. Now there are still undoubtedly challenges in synthetic organic chemistry, and particular examples abound, but the general problem was solved by Woodward and there is no chance that someone can solve it again. Contrast that with a field like computational chemistry, where the general problem of efficiently computing the free energy of binding of a small molecule to a protein is far from being solved.

There is no escaping the fact that you can fail to make your contribution to a scientific paradigm simply because you are born a few years too late. A great example is the golden age of physics in the twenties when people like Heisenberg, Dirac, Pauli and Schrodinger others laid the foundations of quantum mechanics. With the glaring exception of Schrodinger, all the others were in their mid twenties and in fact were born within a year or two of each other (1900-1902). Once they invented quantum theory nobody could invent it again. Dirac in particular was not only one of the founding fathers of quantum mechanics but was also the founding father of quantum electrodynamics; thus, the stunning success of that field after World War 2 by Feynman and others built on his work.

This meant that if you were unfortunate enough to be born just a few years later, say between 1906 and 1910, you would miss your chance to contribute to these developments no matter how talented you were. Examples of people in this category include Robert Oppenheimer, Hans Bethe and Edward Teller. All of them, and especially Bethe, made seminal contributions to physics, but they missed the bus on laying the foundations. They matured at a time when the main task of physicists was to apply the principles developed by men only a few years older than they were to existing problems. Bethe and others achieved great success in this endeavor but there was no way they could replicate the success of their predecessors. Quantum mechanics was perhaps a rare example since the time window during which the fortuitous confluence of brilliance, data, geographic proximity and collaboration bore copious fruit was remarkably narrow, but it does underscore the general point that the period during which one can make fundamental contributions to a field might be preciously rare. As a more recent example, think of particle physics. After the discovery of the Higgs boson, how easy would it be for someone just entering the field to make a fundamental discovery of comparable magnitude? What are the chances that a particle as important as the quark or the neutron would again be discovered? It's quite clear that while there's still plenty of important discoveries to be made in physics, one could make a good case that the age of fundamental discovery at the level of the atom might be over. That is why one cannot help but feel a bit sorry for someone like Edward Witten, perhaps the greatest mathematical physicist since Paul Dirac. If Witten had been born in 1900 he might well have formulated quantum theory or discovered the uncertainty principle, but being born in 1951, he had to be content with formulating string theory instead, a field struggling to find experimental validation.

A similar theme applies to chemistry. Woodward was heads and shoulders ahead of many of his contemporaries but he also had the advantage of being born a few years earlier. Thus, his first synthetic success came with quinine in 1944, a time when many future leaders in the field like E. J. Corey, Carl Djerassi, Samuel Danishefsky, Gilbert Stork were just entering high school or graduate school. This was still the case when Woodward synthesized two other landmarks, strychnine (1954) and reserpine (1956). Being a titan certainly entails being born with great intellectual gifts but it also benefits tremendously if you are born at the right time. Woodward matured when the conditions in organic chemistry were right for a man of his stature to revolutionize the field. The British chemist Robert Robinson and others had just described the electronic theory of organic chemistry which charted movements of electrons in organic reactions, UV and infrared spectroscopy were coming into vogue and structure determination by chemical degradation had reached its zenith. Woodward combined all these tools to invent a superb new methodology of his own and then applied it to scale hitherto unscaled peaks. He pioneered spectroscopy as an alternative to tedious chemical degradation for determining the structure of molecules and applied sound theoretical principles for making complex molecules. Another specific example is his development of the Woodward-Hoffmann rules; these are rules which allow chemists to predict the course of many key reactions that are of both of pure and applied interest. In formulating these reactions with Roald Hoffmann, Woodward again was in a rather unique position to appreciate both observations arising from his synthesis of vitamin B12 and the widespread dissemination of molecular orbital principles which were ripe for application. After he did all this that was it; while the others also made highly innovative contributions, in many ways they were duplicating his success.

This discussion also has a bearing on the frequent debate about awarding Nobel Prizes to one discipline or another. The fact is that we are very unlikely to see Nobel Prizes in organic synthesis in the future because many of the fundamental problems in the field have been solved. There has not been a general organic synthesis prize awarded since 1990 (Corey) and for good reason. Methodology has been recognized more often, but even the two  most recent methodology prizes (2005 and 2011) stem from work done about twenty years earlier. There is of course a chance that some transition metal may further the cause of efficient, high-yielding and environmentally friendly synthesis in a significant manner but these achievements are likely to be rare.

There is a very important lesson to be learnt from all this regarding the education of students in the history of science. Students should never be discouraged from studying particular scientific fields, but graduate students at the cusp of their research careers should be given a good idea of where the greatest opportunities in science lie. There’s still nothing to stop a Phil Baran (widely considered to be the brightest synthetic organic chemist of his generation) from venturing into organic synthesis, but he should do so with full knowledge of what Woodward and Corey have done before him. One way to ensure success in science is of course to work in the “hottest” fields, and while history often has its own peculiar way of defining what these are, it’s sometimes clearer which ones have passed their prime. And it’s important to drive home this point to young researchers.

Intramolecular Hydrogen Bonds, We Hardly Knew Thee

Intramolecular hydrogen bonds (IHBs) are interesting beasts. They can be used to improve the potency of a drug by constraining it in a bioactive conformation, and they can be used to hide polarity and improve permeability; cyclosporin being the classic example of the latter.

But the exact amount of potency gain you get through formation of an intramolecular hydrogen bond is not clear. Conformationally you could constrain a molecule through an IHB, but you would still be introducing polarity and hydrogen bond donors and acceptors, and this will lead to some desolvation penalties that would have to be exactly compensated for by the IHB to lead to a net positive effect. There's a group from D. E. Shaw and AstraZeneca who have now looked at about 1200 cases of matched molecular pairs and their biological activities to figure out the contribution of IHBs to potency. The average gain they see? Close to zero. This means that on average, an IHB is as likely to blunt your potency as it is to improve it.

What's more interesting are the outliers. A small but distinct fraction of results display matched molecular pairs in which there is a gain of at least 2 to 3 log units. Inspection of these results sheds light on why these cases really benefit from the formation of IHBs, but it's also important to not overemphasize the positive role of the IHBs in every instance, especially in cases where the non-IHB matched pair displays particular severe repulsive interactions. 

For instance there's an N-Me vs N-H pair in which the latter can form an IHB while the former cannot. But not only can the former not form this bond, the N-Me probably causes a steric repulsion and causes a very different conformational profile, perhaps leading to a conformational penalty in binding to the target. Similarly in another case, the matched pair presents an N-H vs O difference. Here again, not only can the oxygen not form the bond, but it likely strongly repels the other oxygen participating in the IHB. Thus, these outliers are outliers not because the IHB is particularly stable, but because the complementary arrangement is particularly unstable.

Nonetheless, this is a nice study to keep in mind every time you want to use an IHB as a tactic for improving potency or permeability. It may well work, but then it may well not. As in most cases in drug discovery, the decision to incorporate an IHB-forming element will be dictated by many other factors including cost, resources and synthetic accessibility. As with many other tactics in the field, when it comes to IHBs, caveat emptor.

Richard Feynman's sister Joan's advice to him: "Imagine you're a student again"

Richard and Joan at the beach

Richard Feynman might have been the most famous Feynman of the twentieth century, but his younger sister Joan - who turned 90 a few days ago -  was no slouch. At a time when it was difficult for women to enter and thrive in science, she became a noted astrophysicist in her own right, investigating stellar nucleosynthesis and the aurora among other topics. By all accounts the two also enjoyed a warm relationship, with Richard encouraging Joan's scientific interests from an early age.

There was one time however when it was Joan who gave Richard a very valuable piece of advice for solving a thorny scientific problem, and not only did it serve him well throughout his future career, but it's also one that all of us can really benefit from. In the 1950s, during the heyday of particle physics, Feynman was at a conference in Rochester where there was word of a profoundly deep potential discovery - so-called 'parity violation'. Parity violation means that left and right are not the same, a fact that seems to go against very fundamental physical laws: for instance, in chemistry there is no a priori reason why the parity or 'handedness' of amino acids should be left instead of right, and most researchers think that the only reason we have left handed amino acids is because of an initial accident that then got perpetuated. And yet there were some unstable particles whose decay into simpler ones seemed to violate parity.

At the conference Feynman read a paper by Chen Ning Yang and Tsung Dao Lee, two Chinese-American physicists who had theoretically showed that parity could be violated in certain ways. At that point in time Feynman was in the middle of a kind of scientific slump. He had made his most famous, Nobel Prize winning discovery - the reformulation of quantum electrodynamics - about ten years earlier, and was looking for fresh scientific questions to ponder. Parity violation seemed exactly like the kind of bold and potentially revolutionary problem that would benefit from an unconventional mind like this. But he felt stuck. At that point Joan came to his rescue. As he writes in his memoirs,

“During the conference I was staying with my sister in Syracuse. I brought the paper home and said to her, “I can’t understand these things that Lee and Yang are saying. It’s all so complicated.”

“No,” she said, “what you mean is not that you can’t understand it, but that you didn’t invent it. You didn’t figure it out your own way, from hearing the clue. What you should do is imagine you’re a student again, and take this paper upstairs, read every line of it, and check the equations. Then you’ll understand it very easily.”

I took her advice, and checked through the whole thing, and found it to be very obvious and simple. I had been afraid to read it, thinking it was too difficult.”

And this was sound advice indeed. Feynman thought hard about parity violation, and along with his 'frenemy' Murray Gell-Mann came up with a theory of beta decay that was one of his most significant contributions to physics (it would be the only paper the two would jointly co-author). He got out of his scientific slump and went on to invent a startlingly original theory of superfluidity. But Joan's advice - for which he deeply thanked her later - was pivotal in getting him started on this path.

The advice may seem obvious, and yet it's something that we often forget once we graduate from college or graduate school and progress in our scientific careers. One of my college professors once offered another related piece of advice: "Nothing's difficult, only unfamiliar". When we are students we are used to actually studying difficult topics and walking through them line by line (perhaps because it's required for the final exam, but nonetheless!). Later somehow we seem to lose the zeal and inclination for sustained, serious study of the kind that we did as eager college students. 

What Joan was telling Richard that it's only prolonged attacks on tough subject material that can yield insights. When you don't invent something - and that applies to most things - you do have to go back to basics and try to understand it from scratch. That approach of taking everything apart and understanding it from a fresh perspective played right into the Feynman playbook; it was what had enabled him to reinvent quantum mechanics. When it came to parity violation the strategy clearly worked for him. And there is no reason why it should not work for lesser mortals. We didn't invent many things, but we can understand most things.

On the absurdity of classified information

The problem with keeping information secret is not that secrecy is never warranted, it's that it is always easier to classify something as secret than not, and this leads not just to the withholding of potentially important information from the public but also to all kinds of absurd contradictions. Imagine a bored low-level bureaucrat whose job is to stamp national security documents as secret. It is always going to be easier for him to not take the trouble to go through every line in the document and decide whether to redact it or not; it's far easier to mark everything as secret and stash it away in the archives.

One of the absurdities of secrecy was illustrated by Freeman Dyson a few years ago in a review of the book "David and Goliath" in the New York Review of Books. Dyson was talking about a report called Project Oregon Trail written by academic historians during the Vietnam War that analyzed the results of 'asymmetric wars' in which a larger adversary is fighting a smaller one. The report especially focused on the kinds of conflicts in which a large colonial or imperial power is fighting a small country. It concluded that when the imperial power spends most of its resources on military means, it usually loses. When it spends most of its resources on civilian measures intended to win the hearts and minds of people, it usually wins. The Vietnam War which was then not going well was clearly going down the first road; the disastrous Iraq War went down the same road forty years later, as did any number of attempts by large powers to defeat small insurgent groups using purely military means. The powers in charge did not want to hear the inconvenient truth that they were adopting the wrong strategy. 

There was another report at the same time, published by the RAND Corporation, which analyzed potential conflicts between the two countries using game theory. This was a valuable study which was legitimately classified as secret. But to avoid embarrassment and prevent the results of Project Oregon Trail from being released to the public, the government bound the two reports together and stamped both of them as secret. The valuable, purely historical, Project Oregon Trail is still secret fifty years later. Dyson appealed to the government to release the historical study. I submitted a FOIA request for it more than two years ago, and I am still waiting.

Even legitimate secrecy can sometimes make it embarrassingly easy to let someone with the time and effort know what you are hiding. The nuclear weapons expert Carey Sublette put together a detailed archive of supposedly classified data on nuclear weapons by looking at different classification sources that had redacted the same document in different parts, subjectively exposing and redacting sections of the document according to whim; thus, what one source left out another source disclosed. By looking at a specific document from multiple sources, Sublette was essentially able to reconstruct entire classified papers.

Sometimes it is the omission of information that can alert an adversary to valuable secret information. At the end of the Manhattan Project, the Smyth Report was published to give a general description of the atomic bomb to the lay public. The first edition of this report contained an important fact about the poisoning of nuclear reactors with fission byproducts; it was a problem that had frustrated scientists and taken them quite a while to surmount. When General Leslie Groves who was the head of the project saw this included in the Smyth Report, he ordered it taken out in the next edition. When the Soviets read the second edition and compared it to the first one, they knew exactly what was so valuable and secret.

In the London Review of Books, the physicist and writer Jeremy Bernstein who worked closely with Dyson, Robert Oppenheimer, Hans Bethe and others talks about his own take on the absurdity of secrecy. In 1958 he was invited by Dyson and others to work on a spaceship powered by hydrogen bomb explosions. This was an audacious scheme which several brilliant scientists and engineers seriously worked on for a few years. One of the key calculations in exploring this idea involved using the opacities of elements; the opacity of an element gives us an idea of its capacity to absorb or repel electromagnetic radiation. As Bernstein puts it:

"A couple of physicists at Los Alamos had had the idea that small nuclear devices could be used as propellants for space travel. They would be dropped from the bottom of the ship sequentially and the detritus from the explosions would act as an efficient propellant. Dyson had gone to La Jolla to work on the design of the ship. There was to be a large flat metallic plate, known as the ‘pusher’, attached to the body of the ship by springs that would absorb the shocks of the explosions.

The question was whether the pusher would ‘ablate’ away under the influence of the successive bombs. This depended in large measure on the opacity – the capacity to absorb radiation – of the materials involved. They were to be relatively light elements. At the time I didn’t appreciate the importance of this limitation. Any information, theoretical or experimental, on the opacity of any element heavier than lutetium was and is classified. This includes gold, platinum and lead. To compute an opacity is a problem in quantum mechanics and atomic physics. Anyone can try to do it, but if you do it for lead, the result is classified. Is anything more absurd? Dyson had an idea for a ‘super Orion’ with a pusher made of uranium, which might have been used as fuel for, say, a return trip to Mars. But the opacity of uranium was classified, though it might be an interesting project for a graduate student."

Fifty years later, I did a  Google search and am still not sure whether there is a reliable public source listing the opacities of heavy elements. This is in spite of the fact that many graduate students could now accurately calculate and measure these numbers using a variety of techniques.

Finally, no system of government or private enterprise is foolproof, and secrecy is always thwarted when there are either spies or leakers. Sometimes these spies work against the common good (as in the case of Soviet spy Klaus Fuchs), sometimes they work in its favor (as in the case of American spy Edward Snowden). Bernstein describes how Fuchs was ferrying atomic secrets out of Los Alamos on a daily basis.

"In autumn 1945, Enrico Fermi gave a lecture at Los Alamos on Edward Teller’s hydrogen bomb, the Classical Super. Fermi concluded that he did not see how it could be made to work. The audience was all Q-cleared and the lecture was classified. One of the people in the audience was Klaus Fuchs, who turned the lecture over to the Russians. I am not sure they learned anything they did not already know. But the lecture remained classified by the US government even after the Russians had put it on the web. You can download it at your leisure."

I have not looked for this lecture online but we can be sure of two things: firstly, that it exists in the public domain, and secondly, that the government will never acknowledge its existence. The ultimate absurdity of secrecy arises when the government refuses to deny that something is secret even when it is out for all the public to see. The distinction between classified and unclassified itself becomes classified.

Why technology won't save biology

Carl Woese, who saw an integrated view for 21st century
biology; from molecules to communities

Starting today, I will be writing a monthly column for the outstanding website 3 Quarks Daily. My first post deals with the limitations of the technological zeitgeist in understanding biology.

There seems to be no end to biology's explosive progress. Genomes can now be read, edited and rewritten with unprecedented scope, individual neurons can now be studied in both space and time, the dynamics of the spread of viruses and ecological populations can be studied using mathematical models, and vaccines for deadly diseases like HIV and Ebola seem to hold more promise than ever. They say that the twentieth century belonged to physics and the twenty first belongs to biology, and everything we see in biology seems to confirm this idea.

There have been roughly six revolutions in biology during the last five hundred years or so that brought us to this stage. The first one was the classification of organisms into binomial nomenclature by Linnaeus. The second was the invention of the microscope by Hooke, Leeuwenhoek and others. The third was the discovery of the composition of cells, in health and disease, by Schwann and Schleiden, a direct beneficiary of the use of the microscope. The fourth was the formulation of evolution by natural selection by Darwin. The fifth was the discovery of the laws of heredity by Mendel. And the sixth was the discovery of the structure of DNA by Watson, Crick and others. The sixth, ongoing revolution could be said to be the mapping of genomes and its implications for disease and ecology. Two other minor revolutions should be added to this list; one was the weaving of statistics into modern genetics, and the second was the development of new imaging techniques like MRI and CT scans.

These six revolutions in biology resulted from a combination of new ideas and new tools. This picture is consistent with the general two-pronged picture of scientific revolutions that has emerged through the ages: a picture consisting in equal parts of revolutions of ideas and revolutions of technology. The first kind was popularized by Thomas Kuhn in his book "The Structure of Scientific Revolutions". The second was popularized by Peter Galison and Freeman Dyson; Galison in his book "Image and Logic", and Dyson in his "The Sun, the Genome and the Internet". Generally speaking, many people are aware of Kuhn but few people are aware of Galison or Dyson. That is because ideas are often considered loftier than tools; the scientist who gazes at the sky and divines formulas for the universe through armchair calculations is considered more brilliant than the one who gets down on her hands and knees and makes new discoveries by gazing into the innards of machines.

However, this fondness for theory versus experiment paints a false picture of scientific progress. Machines and tools are not just important for verifying theories; they are more often used to discover new things that theory then has to catch up with and explain. In physics, the telescope and the particle accelerator have been responsible for some of the greatest revolutions in our understanding of nature; they haven't just verified existing theories but uncovered the fundamental composition of matter and spacetime. In chemistry, the techniques of x-ray diffraction and nuclear magnetic resonance have not just opened new windows into the structure of molecules, but they have led to novel understanding of molecular behavior in environments as diverse as intricate biological systems and the surfaces of distant planets and galaxies. There is little doubt that new experimental techniques have been as or even more responsible for scientific revolutions as new ideas.

As one example of the primacy of tool-driven revolutions, four of the six milestones in biology noted above can be considered to have come from the development or application of new tools. The microscope itself was a purely technological invention. The structures of cells, bacteria and viruses was made possible by the invention of new forms of microscopy – the electron microscope in particular – as well as new dyes which allowed scientists to distinguish cellular components from each other. The structure of DNA came about because of x-ray diffraction and chemical analysis. The minor revolution of imaging was made possible by concomitant revolutions in electronics and computing. And finally, the revolution in genomics has engendered by chemical and physical methods of rapidly sequencing genomes as well as powerful computers which can analyze this data. The application of all this technology has been a windfall of data which hides gems of understanding. The new science of systems biology promises to tie all this data together and lead to an improved understanding of biological systems.

And this is where the problem begins. In one way biology has become a victim of its success. Today we can sequence genomes much faster than we can understand them. We can measure electrochemical signals from neurons much more efficiently than we can understand their function. We can model the spread of populations of viruses and populations much more rapidly than we can understand their origins or interactions. Moore's Law may apply to computer chips and sequencing speeds, but it does not apply to human comprehension. In the words of the geneticist Sydney Brenner, biology in the heyday of the 50s used to be "low input, low throughput, high output"; these days it's "low input, high throughput, no output". What Brenner is saying is that compared to the speed with which we can now gather and process biological data, the theoretical framework which goes into understanding data as well as the understanding which come out from the other end are severely impoverished. What is more serious is a misguided belief that data equals understanding. The philosopher of technology Evgeny Morozow calls this belief "technological solutionism", the urge to use a certain technology to address a problem simply because you can.

Consider a field like cancer where gene sequencing has come to play a dominant role. The idea is to compare the genome sequences of cancer cells and normal cells, and therefore understand which genes are malfunctioning in cancer cells. The problem is that if you sequence a typical cell from, say, a lung cancer patient, you will find literally hundreds of genes which are mutated. It is difficult to distinguish the mutant genes which are truly important from those which just come along for the ride; the latter are a necessary part of the messy, shotgun process of cancer cell evolution. It is even more difficult to know which genes to target if we want to keep the cancer from growing. For doing this it is important to have a better theory for understanding exactly what genes would be mutated in a cancer cell and why, and what function they serve. While we have made strides in developing such theories, our understanding of the basic causal framework of cancer is far behind our capacity to rapidly sequence cancer genomes. And yet millions of dollars are spent in sequencing cancer genomes, with the expectation that someday the data alone with lead to a quantum leap in understanding. You look for the keys not where they are but where you can easily see them, under the bright light.

A recent paper from the neuroscientist John Krakauer said the same thing about neuroscience. If biology is the science of the twenty first century, neuroscience is probably the cherry on that cake. No other field promises to deliver fundamental insights not just into major mental health disorders but into the very essence of what it means to be human. To understand the brain better, scientists and government launched the Brain Map Initiative a few years ago. The goal of this initiative can be stated very simply: it is to map every single neuron in the brain in space and time and to understand the connections between them. The belief is that understanding the behavior of neurons will lead to an understanding of human behavior. At the heart of the initiative are new methods of interrogating neuronal function, ranging from very precise electrical recording using advanced sensor techniques to studying an inventory of the proteins and genes activated in neurons by modern recombinant DNA technology. These methods will undoubtedly discover new aspects of the brain that were previous hidden. Some of them well lead to groundbreaking understanding. But we do not know whether they will allow us to understand human behavior. As one example, the paper by Krakauer talks about mirror neurons, a specific class of neurons that caused a great stir a few years ago. As their names indicate, mirror neurons in one brain fire when the same class of neurons is activated in another brain. These neurons have thus been proclaimed to be the basis of diverse human emotions, including empathy; understanding them is considered to be integral to understanding social behavior; delicate imaging studies can track their activation and deactivation. But as Krakauer notes, many experiments on mirror neurons have been done on monkeys, and in those cases, little attention if any is paid to the actual behavior of the monkey when the mirror neurons fire. Thus, we seem to know what is going on, but only at the level of the neurons themselves. We do not know what is actually going on in the mind of the monkey in terms of its behavior when the neurons are activated.

To understand why these limitations of technology can hamper our understanding of complex biological systems, we must turn to one of the great philosophical foundation stones of science: the paradigm of reductionism. Reductionism was the great legacy of twentieth century science, and a culmination of everything that came before. It means the breaking up of complex systems into their simpler parts; the idea is that understanding the simpler parts will enable us to understand the whole system. There is little doubt that reductionism has led to spectacular successes in all of science. The entire edifice of twentieth century physics – exemplified by relativity and quantum mechanics – rose from the reductionist program of understanding matter and spacetime using its most basic components; particles and fields. Molecular biology similarly was created when biological matter started to be unraveled at the molecular level. Most of these advances became possible because powerful new technology like particle accelerators and spectrometers allowed us to break and study matter and living organisms at their fundamental level.

But as science overturned one obstacle after another in its confident reductionist march, it became clear that all was not well with this approach. One of the first salvos in what came to be called the "reductionism wars" was from the physicist Philip Anderson who in 1972 wrote an article titled ‘More is Different'. Anderson did not deny the great value of reductionism in science, but he pointed out that complex systems are not always the sum of their constituent parts. More is not just quantitatively different but qualitatively so. Even simple examples illustrate this phenomenon: atoms of gold are not yellow, but gold bars are; individual molecules of water don't flow, but put enough of them together and you get a river which has features that are not directly derived from the molecules themselves. And consciousness may be the ultimate challenge to reductionism; there is absolutely nothing in a collection of carbon, hydrogen, oxygen and nitrogen atoms in a human brain that tells us that if you put enough of them together in a very specific configuration, you will get a human being who would be writing this essay. Rivers, gold bars, human brains; all these systems are examples of emergent phenomena in which the specification of the individual components is necessary but not sufficient to understand the specification of the entire system. This is top-down as opposed to bottom-up understanding.

Why does emergence exist? We don't know the answer to that question, but at least part of it is related to historical contingency. The complexity theorist Stuart Kauffman gives a very good example of this contingency. Consider, says, Kauffman, the structure and function of the human heart. Imagine that you had a super-intelligent demon, a "superfreak" who could specific every single particle in the heart and therefore try to derive the function of the heart from string theory. Imagine that, starting from the birth of the universe, this omniscient superfreak could specify every single configuration of atoms in every pocket of spacetime that could lead to the evolution of galaxies, supernovae, planets, and life. He would still fail to predict that the most important function of the human heart is to pump blood. That is because the heart has several functions (making beating noises for instance), but the function of the heart about which we care the most is a result of historical accident, a series of unpredictable circumstances on which natural selection acted before elevating the pumping of the blood as the quintessential property of the heart. Some of the pressures of this natural selection came from below, but others came from above; for instance, the function of the heart was sculpted not just by the molecules which make up heart muscle but by the functions of the physiological and ecological environments in which ancient heart precursors found themselves. The superfreak may even be able to predict the pumping of blood as one of the many properties of the heart, but he will still not be able to determine the unique role of the heart in the context of the grand tapestry of life on earth. The emergence of the human heart from the primordial soup of Darwin's imagination cannot be understood by understanding the quarks and cells from which the heart is composed. And the emergence of consciousness or the brain cannot be understood merely by understanding the functions of single neurons.

Emergence is what thwarts the understanding of biological systems through technology, because most technology used in the biological sciences is geared toward the reductionist paradigm. Technology has largely turned biology into an engineering discipline, and engineering tells us how to build something using its constituent parts, but it doesn't always tell us why that thing exists and what relationship it has to the wider world. The microscope observes cells, x-ray diffraction observes single DNA molecules, sequencing observes single nucleotides, and advanced MRI observes single neurons. As valuable as these techniques are, they will not help us understand the top-down pressures on biological systems that lead to changes in their fundamental structures.

The failure of reductionist technology to understand emergent biology is why technology will not save the biological sciences. I have a modest prescription to escape from this trap: create technology that studies biology at multiple levels, and tie this technology together with concepts that describe biology at multiple levels. For instance when it comes to neuroscience, it would be fruitful to combine magnetic recording of single neurons (low level) with lower resolution techniques for studying clusters of neurons and modules of the brain (intermediate level) with experiments directly probing the behavior of animal and human brains (higher level). The good news is that many of these techniques exist; the bad news is that many of them exist in isolation, and the researchers who study them don't build bridges between the various levels. The same bridge-building goes for concepts. For instance, at the highest level organisms are governed by the laws of thermodynamics, more specifically non-equilibrium thermodynamics (of which life is an example), but you will not usually see scientists studying collections of neurons taking into consideration the principles of statistical thermodynamics or entropy. For achieving this meld of concepts scattered across different levels of biological understanding, there will also need to be much closer multidisciplinary interactions; physicists studying thermodynamics will need to closely collaborate with geneticists understanding the translation of proteins in neurons. These scientists will in turn need to work together with psychologists observing human behavior or ethologists observing animal behavior; both these fields have a very long history which can inform researchers from other fields. Finally, all biologists need to appreciate better the role of contingency in the structure and function of their model systems. By looking at simple organisms, they need to discuss how contingency can inform their understanding of more complicated creatures.

For a wholesome biology to prosper we need both technological and human interactions. But what we need most is an integrated view of biological organisms that moves away from a strict focus on looking at these organisms as collections of particles, fields and molecules. The practitioners of this integrated biology can take a page out of the writings of the late Carl Woese. Woese was a great biologist who discovered an entire new kingdom of life (the Archeae), and one of the few scientists able to take an integrated view of biology, from the molecular to the species level. He pioneered new techniques for comparing genomes across species at the molecular level, but he also had a broader and more eloquent view of life at the species level, one which he set down in an essay titled "A New Biology for A New Century" in 2004, an essay that expanded biology beyond its mechanistic description:

"If they are not machines, then what are organisms? A metaphor far more to my liking is this. Imagine a child playing in a woodland stream, poking a stick into an eddy in the flowing current, thereby disrupting it. But the eddy quickly reforms. The child disperses it again. Again it reforms, and the fascinating game goes on. There you have it! Organisms are resilient patterns in a turbulent flow—patterns in an energy flow. A simple flow metaphor, of course, fails to capture much of what the organism is. None of our representations of organism capture it in its entirety. But the flow metaphor does begin to show us the organism's (and biology's) essence. And it is becoming increasingly clear that to understand living systems in any deep sense, we must come to see them not materialistically, as machines, but as (stable) complex, dynamic organization."

As the quote above observes none of our experiments or theories captures the science at all levels, and it's only by collaboration that we can enable understanding across strata. To enable it we must use technology, but use it not as master but as indispensable handmaiden. We are all resilient organisms in a turbulent energy flow. We live and die in this flow of complex, dynamic organization, and we can only understand ourselves when we understand the flow.

On Albert Einstein's birthday: How Eddington and Einstein set an example for the international fellowship of science

The world woke up on the morning of November 7, 1919, to an amazing piece of news. A few months before in May, the English astronomer Arthur Eddington had led an expedition to the island of Principe off the west coast of Africa to try to observe one of the strangest phenomena ever predicted in the history of the science: the bending of starlight by the gravitational field of the sun. The phenomena could only be observed during a total solar eclipse, when the sun becomes dim enough to track the passage of starlight past it.

Eddington’s analysis proved that the light was bent by an amount that was twice that predicted by Isaac Newton, often considered the greatest scientist who ever lived. The man who trumped the great Sir Isaac’s prediction had until then been a relatively unknown forty-year-old physicist working in Berlin. His name was Albert Einstein, born on this day in 1879.

The observation of starlight bending was the first prediction of Einstein’s then otherworldly-seeming general theory of relativity: “One of the greatest achievements in the history of human thought. It is not the discovery of an outlying island but of a whole new continent of scientific ideas”, quipped the English physicist J. J. Thomson, discoverer of the electron. It was only the first among a stellar set of experimental observations that validated some mind-bending phenomena and ideas: spacetime curvature, black holes, gravitational waves, an expanding universe. It catapulted Einstein to world celebrity, and made him a household name and a part of the history books.

More importantly for the sake of world peace, however, it underscored one of the finest moments in the history of science diplomacy. The world had seen its first brutal world war end just a few months before, when the guns had finally been silenced in August.  The carnage had been unparalleled: more than 38 million casualties, with 17 million deaths. And in the light of this death and destruction, there was one country on which the world’s anger was focused: Germany. It seemed Germany had started the war and continued it, and it was fanatic German militarism that seemed to have sown the seeds of discontent.

In the middle of all that resentment then, it must not have gone unnoticed that an Englishman had confirmed a seminal prediction of a German’s reworkings of our understanding of the cosmos. In fact it was an exceptional gesture that would go down in history as a measure of the international brotherhood of science. Eddington, a pacifist Quaker who loathed war, joined heart and mind with Einstein, another pacifist who loathed war. At a time when the two countries had just come out of a horrific conflict with each other – a conflict streaked with memories of poison gas, trench warfare, dysentery and hand-to-hand combat - here was singular proof that there could be friendship between them again, that it was possible to forgive and move ahead together. The expedition at Principe confirmed a singular fact about science: that it can go beyond petty and deadly territorial disputes, that its bonds go deeper than those of rank or politics, and that, in the hands of men and women with conscience, it can rise above the fray and be the one shining candle in the dark. Einstein never forgot Eddington’s contribution to relativity and the hand of fellowship that bridged two nations who only a few months before had been sworn enemies. At the end of November, he finally gave in to the constant pleas from journalists and the public to hold forth on his theory and wrote a piece for the London Times on relativity. But he began the piece not with a scientific exposition but a human one:

“I gladly accede to the request of your colleague to write something for The Times [London] on relativity. After the lamentable breakdown of the old active intercourse between men of learning, I welcome this opportunity of expressing my feelings of joy and gratitude toward the astronomers and physicists of England. It is thoroughly in keeping with the great and proud traditions of scientific work in your country that eminent scientists should have spent much time and trouble, and your scientific institutions have spared no expense, to test the implications of a theory which was perfected and published during the war in the land of your enemies. Even though the investigation of the influence of the gravitational field of the sun on light rays is a purely objective matter, I cannot forbear to express my personal thanks to my English colleagues for their work; for without it I could hardly have lived to see the most important implication of my theory tested.” 

Einstein’s message here was clear. No matter what the political environment, science should trudge on, and political differences should not be a reason to squelch scientific collaboration. In fact such collaboration may be the only bond joining two countries together when all others have failed.

Eddington and Einstein’s plea for scientific fellowship has again become relevant, even as irrational nationalism has started to rear its ugly head, in the United States, in Europe and beyond. Demagogues with no understanding of science are trying to stem the flow of scientific talent from other countries, and no nation will be hurt more by this backward policy than the United States. More than any other single country, the United States has been the beneficiary of groundbreaking work by émigré scientists; in fact, the U.S. rose to scientific prominence when Jewish scientists fleeing from fascism in Europe migrated to its shores. It rose to world prominence in diverse scientific fields like astronomy, biomedical research and social science as these European immigrants and their students, along with others who came to the country during the last few decades from Asia, Africa, Australia and other continents, massively contributed to new scientific discoveries and inventions and won a string of Nobel Prizes.

If the United States starts appearing as an unwelcome destination for the world’s scientists, doctors and engineers, not only would this be a scientific disaster but it will be a human disaster. Immigrant scientists are often fleeing from persecution, broken economies and shoddy education standards and therefore usually work extra hard to ensure that their work brings success to their adopted countries. They may not all be Christians, but as is clear from the educational attainment and income levels of so many of these immigrant groups, they often live and breathe the Protestant work ethic of hard work, honesty and perseverance. As exemplified by a letter written by the German émigré Hans Bethe to his teacher Arnold Sommerfeld, many of them come to love their country and demonstrate deep loyalty toward it. Einstein himself was of course one of the most important examples of the immigrant experience in this country; when he moved to Princeton in 1933, the center of world physics moved with him. Alienating these people would not just be antithetical to the universal fellowship of science but it would decidedly not be in the United States’ best interests; it is these immigrant scientists and engineers who have started companies worth billions, discovered new drugs, materials and species, and contributed to America's tremendous supremacy in the information age. Supporting these immigrants is in fact putting ‘America First’.

One can have a perfectly reasonable discussion on limits to immigration without keeping talent away from these shores or without alienating potential immigrants who want to succeed in this country through hard work and family values. The current political environment has erased these important distinctions, if not explicitly at least in spirit, and it’s a distinction that we need to all clearly point out. The path ahead will not be easy, but as long as we support and understand each other, as long as we organize panel discussions and conferences and exchange programs which make people appreciate the international nature of science, we will move ahead together. All we need to do is have the Eddingtons and Einsteins among us keep finding each other.