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Terrible Advice From a Great Scientist 276

Shipud writes "E.O. Wilson is the renowned father of sociobiology, a professor (emeritus) at Harvard, two time pulitzer prize winner, and a popularizer of science. In a recent article in the Wall Street Journal, Wilson provides controversial advice to aspiring young scientists. Wilson claims that math literacy is not essential, and that scientific models in biology, intuitively generated, can later be formalized by a specialized statistician. One blogger calls out Wilson on his article, arguing that knowing mathematics is essential to generating models, and that lacking what Darwin called the "extra sense" is essentially limiting to any scientist."
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Terrible Advice From a Great Scientist

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  • He's right (Score:5, Insightful)

    by ShanghaiBill ( 739463 ) * on Sunday April 21, 2013 @11:18AM (#43509537)

    Math, intuition, and insight are all important. But they don't all have to come from the same person. I have worked on plenty of teams where the creative work and number crunching tasks were delegated to different people. I am currently working on a 3D educational game, using OpenGL. It involves lots of gnarly trig and vector math, which I am good at. It also involves lots of creative scene design and character development, which I am not good at. So I work with an artsy chick, and we make a good team. I don't see why splitting creativity and implementation shouldn't work for biology as well.

    • Re:He's right (Score:4, Insightful)

      by Alex Belits ( 437 ) * on Sunday April 21, 2013 @11:24AM (#43509569) Homepage

      Science doesn't work like that.

      • Re:He's right (Score:5, Informative)

        by ColdWetDog ( 752185 ) on Sunday April 21, 2013 @11:40AM (#43509665) Homepage

        Increasingly it does (minus the artsy chick, some fantasies never die). Very few current articles in biology have been written by one or two people. Even those articles have a long list of people that the researchers relied on for technical and intellectual support. It's not Charles Darwin walking down the road any more.

        While there may be great insights developed by single 'intuitive' biologists, the intellectual foundations of those insights are going to come from thousands of disparate people. DNA chemistry and sequencing is an example here - how many biologists understand the chemistry of the analyzers? How many chemists understand the software?

        I don't think H.O. is really correct though. At the complexity level that biologists are working at 'intuitive' thinking isn't going to help much. Working the numbers will.

        I'd rather train a mathematician to be a biologist than the other way around.

        • Re:He's right (Score:4, Insightful)

          by drinkypoo ( 153816 ) <martin.espinoza@gmail.com> on Sunday April 21, 2013 @12:28PM (#43509989) Homepage Journal

          I'd rather train a mathematician to be a biologist than the other way around.

          With sarcastic apologies to Alex Belits, it doesn't work like that. I mean, it might, but there's issues of both interest and aptitude. Personally, I think you're both right. The best situation is to have both mathematics ability and some other kind of ability concentrated in a single human. Barring that, you can still get things done, perhaps just not as quickly. Thus, it is still preferable but not essential for everyone to have strong mathematics stills.

        • Re:He's right (Score:5, Informative)

          by Grieviant ( 1598761 ) * on Sunday April 21, 2013 @01:23PM (#43510377)
          You make the assumption that a long list of authors indicates a truly collaborative research effort. In practice, this is very rarely the case. From my experience, nine times out of ten the work is done completely by the primary author or the first two authors. The rest of the authors are supervisors, technical managers, those who secured the funding, possibly a technician who assisted with the experiments, etc., who never even lay eyes on the paper until it's basically finished.
          • Re:He's right (Score:4, Interesting)

            by excelsior_gr ( 969383 ) on Sunday April 21, 2013 @04:49PM (#43511595)

            You are absolutely right, but the GP was making the point that the so-called "interdisciplinary" science is becoming the norm. Taking the author lists as an example was an unfortunate choice for an argument, but that doesn't invalidate his point.

          • You make the assumption that a long list of authors indicates a truly collaborative research effort. In practice, this is very rarely the case. From my experience, nine times out of ten the work is done completely by the primary author or the first two authors. The rest of the authors are supervisors, technical managers, those who secured the funding, possibly a technician who assisted with the experiments, etc., who never even lay eyes on the paper until it's basically finished.

            And from my experience, publishing dozens of peer-reviewed scientific articles, your experience is the exception. In fact, many sciences do not even utilize technicians. In the ten or so laboratories that I have worked in/with and the labs of the numerous professors that I talk with about their publication policies, exactly zero will allow someone authorship on a paper that they don't see until it's "basically finished." I'm sure some fall through the cracks, though certainly not the majority. However, I wo

            • Re:He's right (Score:4, Interesting)

              by Squirmy McPhee ( 856939 ) on Monday April 22, 2013 @03:12AM (#43513613)

              And from my experience, publishing dozens of peer-reviewed scientific articles, your experience is the exception. In fact, many sciences do not even utilize technicians. In the ten or so laboratories that I have worked in/with and the labs of the numerous professors that I talk with about their publication policies, exactly zero will allow someone authorship on a paper that they don't see until it's "basically finished." I'm sure some fall through the cracks, though certainly not the majority. However, I would not generalize my experiences and neither should you.

              My experience -- also publishing dozens of peer-reviewed scientific articles -- is quite different from yours and much more like that of the poster to whom you were responding. More than once I've found out that I was a co-author on an article when the publishing company contacted me to let me know that my article had been received for submission. That's even a step beyond what the first poster mentioned -- I didn't even see the article that I supposedly co-authored until after it was submitted for publication! I've also had my authorship credit manipulated so as to imply collaboration where there was none. It was accidental, I think, but afterward there was actually a story in the press about our non-existent collaboration.

        • Comment removed (Score:4, Insightful)

          by account_deleted ( 4530225 ) on Sunday April 21, 2013 @02:49PM (#43510929)
          Comment removed based on user account deletion
        • by pepty ( 1976012 )

          DNA chemistry and sequencing is an example here - how many biologists understand the chemistry of the analyzers? How many chemists understand the software?

          The answer is both most and not enough.

          I don't think you could get through an undergraduate biology degree without being introduced to the basic chemistry underlying traditional (Sanger) sequencing, PCR, etc. Most chemists end up having to do at least some basic scripting if they're going to use automated analytical or synthesis equipment.

          On the other hand, lots of biology papers have proven to be fatally flawed because of poor understanding/poor usage of statistics. Brain functional MRI studies, gene a

      • Re:He's right (Score:4, Insightful)

        by SJester ( 1676058 ) on Sunday April 21, 2013 @12:03PM (#43509825) Journal
        I'm a scientist (well, almost) and it does work like that with a few caveats. As a biologist I'm not called upon to build intricate mathematical models entirely by myself - but I sure as hell need to understand them before I set to work so I can gather data intelligently, and I need to understand math well during and after so I can communicate with collaborators and contribute to the final papers. I need enough math (and programming, in my branch of the family tree) to at least converse intelligently with team members. A grant application went out recently from our facility. It had a biochemist, a neuroscientist, a mathematician, and a computer scientist on it and the goal is to build a giant computational model of some neural signal cascade. Sounds like the setup for a joke but you can see the spectrum we typically span. Those colors need to blend at the edges.
        • I can see it now. At a conference:

          "And then we discovered our data fit this unusual mound-shaped pattern, which I thought was pretty neat..."

          "Isn't that a Gaussian distribution?"

          "Oh, so you've read our paper!"

          ...the day when biology becomes lessintimately connected to stats is the day when there are no more problems to explore. Perhaps when you're studying insect behaviour like E. O. Wilson you care more about intuitively-recognizable patterns, but the team's statistician should be a supplement moreso than

          • Re:He's right (Score:4, Insightful)

            by SomeKDEUser ( 1243392 ) on Sunday April 21, 2013 @12:34PM (#43510037)

            This would be funny if it were not true... Beware the biologists who tells you they found a number N of categories of each suspiciously smaller than the previous one by the same ratio. And never checked for fear that their result might not be publishable after all.

            As in : "This a ground-breaking, paradigm shifting result: these identical individuals are not: some are short-lived, some long-lived, and we found an intermediate category, too" -- "oh, so your mortality curve follows an exponential law".

            • The thing is, it could be worse than that. It could be much, much worse [wordpress.com]. Consider it a blessing that biologists are forced to take as much math as they are.
              • don't get me started on MDs, they should never be allowed near a lab until they get a real university degree in a hard science. Which they should get _after_ their MD.

                MD is a trade, like Carpenter or Mason or Lawyer. A hard one, which requires all sorts of qualities. But it does not qualify you to do science. Not remotely.

                • by chihowa ( 366380 )

                  The MD, PhD program is a popular way now of "legitimizing" an MD's role in science. In these programs, the PhD part of the degree is typically a joke involving no more actual research than than would be involved in an MS. They also get no more rigorous science classwork than they incidentally receive in the training for their MD. While they probably make great doctors, they don't seem to make very impressive scientists, and it's sad that they are seen as adequate replacements for properly trained scientists

      • Science doesn't work like that.

        Presumably you have evidence to back this up, or is it something you know intuitively?

    • Ah, many things can be accomplished by splinting the expertise between two or more people, but many things do require that the expertise be concentrated in a single individual. Especially things that require complex and frequent interactions between them to generate understanding.
    • Re:He's right (Score:5, Insightful)

      by femtobyte ( 710429 ) on Sunday April 21, 2013 @11:35AM (#43509631)

      Intuition and the part of math that involves being good at grinding through lengthy, dense calculations without making sign errors don't have to be the same person. However, a strong and intuitive sense of what math is capable of (which requires advanced mathematical education) do need to go together for scientific productivity. Otherwise, it's just like the techno-incompetent manager asking engineers to implement his "brilliant" physically impossible designs.

    • Re: (Score:2, Informative)

      by Anonymous Coward

      Yeah, a team is important, even if it's only two people. James Watson described his working relationship with Francis Crick in "The Double Helix" - Crick was a polymath and was clearly the senior member of the pair, while Watson was brilliant but lazy (he described himself as "another uneducated Ph.D" whose mind was characterized by "an almost complete lack of chemical facts"). But they both apparently spoke a mile a minute and bounced ideas against each other, until Watson, with the benefit of seeing Ros

    • Re:He's right (Score:5, Insightful)

      by SomeKDEUser ( 1243392 ) on Sunday April 21, 2013 @11:42AM (#43509683)

      I know of certain articles in highly recognised journals which passed the review process, pushed by the editors who liked the message so much.

      I also know that their data was largely noise, because the main authors clearly are math illiterate. Of course not everyone needs to be a mathematician, but every scientist should know the basics of statistics and be able to recognise a binomial or Poisson process after a cursory glance at the data.

      Likewise not everyone should be some über-coder, but every scientist should be able to write small programmes in MATLAB, R, numpy, or whatever is appropriate for their field. These are basic qualifications which prevent you from churning out bullshit.

    • by Molt ( 116343 )
      In your example the coding and art are loosely coupled, it's easy to split them between different people. I suspect that if you knew programming but had no knowledge of 3d maths and there was a third person who knew 3d maths but not programming then you would have a lot more difficulty. Every minor piece of coding would result in a confused conversation where you don't have enough common domain knowledge to communicate effectively, misunderstandings will come in as assumptions are made on both sides, and
    • Re:He's right (Score:5, Insightful)

      by JustinOpinion ( 1246824 ) on Sunday April 21, 2013 @11:47AM (#43509705)
      In your analogy, you're talking about a very high-level split that can be done cleanly. One person does the creative work of coming up with a game design (storyline, play control, etc.) without worrying about the underlying implementation details. Then another person can certainly do the engineering and coding work to implement that.

      But it should be obvious that for some other problems this won't work. For example, it doesn't make sense to try and split the coding into a "creative coder" (who knows nothing about programming) and an "implementation coder" who turns the creative's ideas into actual code. The creative would toss out nonsensical ideas (like "instead of using vectors, why not use genetic algorithms?"), and then the implementer would have to explain why all those ideas are silly... or else they would just have to ignore the creative type and simply code something that makes sense.

      In other words, generating good source code requires someone who knows enough about programming that they can see creative solutions. Their intuition is not separate from their programming talent: their intuition is based upon years of training and experience with source code, math, engineering, and so forth. That's where the good ideas come from.

      Coming up with good scientific ideas is similar. Analysing scientific data even moreso. It's only once you have a deep, subliminal understanding of the important concepts that you're going to make substantive progress. Whether a deep understanding of math counts as an "important concept" depends on the field, of course... but I would argue that for science generally, the more mathematical know-how you have, the more informed and powerful your ideas will be.
    • No he is not right. Research is not like programming. When coding a program the basic framework already exists: someone comes up with an idea and then someone else can write all or part of the code. Now imagine doing the same with research: someone does an experiment and then another person analyses the data. Chances are that this analysis will be worthless because they have not accounted for all the systematic errors and corrections due to nuances of the experiment itself. To analyse the data you need to h
    • "It involves lots of gnarly trig and vector math, which I am good at."

      I'd argue that when someone says "math is important", more often than not is it not about trig functions, vectors, and integrals, but rather about logic, reasoning, and modern statistical inference.

  • Say something wrong that people want to believe, then block the box for 30 years.
  • by void* ( 20133 ) on Sunday April 21, 2013 @11:30AM (#43509599)

    From that WSJ article: "If your level of mathematical competence is low, plan to raise it, but meanwhile, know that you can do outstanding scientific work with what you have."

    I don't really see anything wrong with telling people to still keep thinking about things, find out what they like to study, and get more math. More 'don't let current lack of math get you down' than 'you don't need math at all'.

    • Re: (Score:3, Insightful)

      by Anonymous Coward

      Ssh, we're busy crafting a strawman here, and you're just trying to blow it down!

    • Especially considering the number of students who are in the process of talking themselves out of careers in science because they think they aren't good at math. (Many of them are, but either have friends who have taken more math and belittle them, or lousy math teachers.) Yeesh. I think a lot of the problem is that we still have a culture where it's expected that most people won't ever manage much more than high school algebra... maybe calculus, and likely that by the skin of their teeth.

      In my experience,

  • by stenvar ( 2789879 ) on Sunday April 21, 2013 @11:35AM (#43509639)

    Sociobiology is theories about how observed human behavior and social structures have arise from evolution. Where does cooperation come from? Where does homosexuality come from? How are these traits beneficial for animals and humans, and why haven't they been selected against? Sociobiologists come up with plausible and reasonable sounding theories for many of these, but most of them remain just guesswork if there isn't hard data and hard mathematical modeling (many remain just guesswork even with data and models). Wilson is right that you don't need to be proficient at math to succeed at science. But that's perhaps more a testament to the poor criteria by which some areas of science measure success than to what a scientist actually needs.

  • by overshoot ( 39700 ) on Sunday April 21, 2013 @11:39AM (#43509659)

    Math is not necessary -- in fact it can be a serious liability -- in formulating hypotheses. For instance, much of sociobiology. On the other hand, it's indispensable for testing those hypotheses and sorting the valuable ideas from the attractive bullshit.

    Which category holds much of sociobiology is a question beyond my own skills.

    • Sociobiology- sounds like a psuedo-scienctific discipline, not a hard science. I think he has something of a point, but not much of one. Einstein said he wasn't much of a mathematician himself, but that's not saying much. He certainly spoke the lingo and although STR [wikipedia.org] came to him as a thought experiment he needed mathematics to describe it to the scientific community at large.
  • That's like literature without words...

  • Title and summary (Score:5, Informative)

    by O('_')O_Bush ( 1162487 ) on Sunday April 21, 2013 @11:47AM (#43509711)
    Are sensationalized bullshit. The original article did not make that claim, only that you shouldn't let a fear of maths or advanced maths prevent you from a career in the sciences. Obviously, don't plan a career in Physics, but there are plenty of interesting areas of study that don't require Calculus+ areas of math proficiency (sociobiology being one).

    As an ECE, most of my studies were centered around differential equations. However, my sister, who did biology/chemistry(two hard sciences) with an intent to move on to dental school, hardly had to touch maths at all.
    • The original article did not make that claim


      biology/chemistry(two hard sciences) with an intent to move on to dental school

      Doing original scientific research and merely learning about some of its results aren't quite the same thing. If they were, Scientific American would have already made me an astrophysicist, an economist and a neurologist.

      • I don't disagree. Maybe I should have left out the dental school part because it distracts from the point. The point is, one can survive, at least in the undergraduate level (the starting point of a scientific career, where most students are too discouraged to try) without being heavily involved in maths at all.

        I realize that going into medicine doesn't make her a scientist, but the starting point for both paths is the same.
    • I'll go with ooBush's analysis over EO Wilson's. I have a degree in math. I have never understood why Calculus is mandatory (4 semesters) for most everyone but statistics is not. Calculus is overkill for most degrees. It should only be mandatory for engineers and math geeks. Statistics is what should be mandatory for everyone with a college degree.

      There is far more to a useful general mathematics education than The Calculus
      • I have never understood why Calculus is mandatory (4 semesters) for most everyone but statistics is not.

        Probably (no pun intended) because one really needs (some) calculus to understand things like continuous probability distributions and the Central Limit Theorem.

        • Exactly. "Statistics for people who don't understand math" courses are counterproductive and actually dangerous to the sciences. They churn out people who treat statistical analysis as a magical black box --- they've memorized which incantation sequences to type into some calculator or statistical analysis software package without the least understanding of what they're doing. The result is folks churning out research analysis applying all sorts of sophisticated-sounding statistical methods in inapplicable

    • there are plenty of interesting areas of study that don't require Calculus+ areas of math proficiency (sociobiology being one).

      Good luck passing the quals in sociology without a boatload of statistics that engineers never see, including formal design of experiments. Biology, at least according to the biologists I know, is much the same.

  • by rickb928 ( 945187 ) on Sunday April 21, 2013 @11:53AM (#43509739) Homepage Journal

    My 'aunt', who still works for a pharmaceutical firm analyzing statistical analyses by researchers, would snort tea out her nose reading this. Doing the research, finding a useful drug, doing minimal testing, and then concocting the analysis to fit the very limited empirical model is not uncommon in the drug industry. Her job was and is to study that 'analysis', identify any problems, send it back for improvement, and repeat until either the researchers give up and move on to something they can demonstrate is effective AND safe enough for the market, or succeed and are able to show provable, reliable results.

    Wilson would not like herm, and for good reason - she would call his methods little more than guessing. She has proven repeatedly that well-meaning researchers can find some statistician to lend unwarranted credence to imaginary results.

    Kinda sad that this passes as science at all. Wilson seems, to me, to be stating that research need not be proven, merely justified.

  • math comes second (Score:2, Insightful)

    by kipsate ( 314423 )
    The math behind quantum physics and relativity is of secondary importance compared to the phenomena they predict and define. Einstein had the insight that everything must be relative, and the math followed from that. Mathematicians merely model nature based on existing insights. But it are these insights that create new science and discoveries, and not the math that models them.
    • Math may come second, but it does need to come. If Einstein had just been the guy who went around saying "dude, everything is like totally relative! Cosmic space-time bendy-warp, all-one time-cube, dude!," and expecting someone else to fill in the mathematical formalism, I doubt he'd be all that famous now. Einstein was able to write down his insights as tensor calculus equations --- that's why he's remembered as a famous scientist, not an incoherent ranting quack.

    • Re:math comes second (Score:4, Interesting)

      by khallow ( 566160 ) on Sunday April 21, 2013 @12:21PM (#43509937)
      Except when the math generates the insights.

      For example, Dirac predicted the existence of anti-matter from a model of the electron with interactions with photons. For the model to work mathematically, he had to have a second particle, the positron which had opposite properties of the electron.

      Then there's the search for missing planets. Neptune was found by noticing that Uranus didn't follow the orbit as predicted by the mathematical model of the then known Solar System.

      Radioactive dating wouldn't be possible without a model of how decay works. That in turn has generated new insights.
    • issues here. One is mathematical thinking—this is intuitive, and very difficult to teach; some people display aptitude for this (logical relationships, congruences, dependencies, correlations across qualitative cases, a "sense" for probability that is remarkably in tune with formal outcomes) and others struggle with it even if they become very proficient with Two, which is notation.

      Too often, we conflate the former with the latter and call the whole package "math." But in fact, it is a deep, intuitive

  • by PPH ( 736903 ) on Sunday April 21, 2013 @12:06PM (#43509845)

    ... is necessary for good experiment design. Trying to fix a poorly conceived experiment or bad data after the fact is like trying to cure diarrhea by messing with the bathroom plumbing.

  • Is his book, The Social Conquest of Earth, Wilson takes droves of biologists to task for espousing the theory of kin selection to explain altriusm, accusing them of both torturing their "relatedness" math and also essentially back-solving from a desired result. Wilson makes the case that the theory of group selection (one social group besting a neighboring social group) explains altruism more simply, and occam's razor applies.
    • In the article, he suggests that of all the mathematical models in sociobiology, only 10% of them hold up to deeper inspection. Which is a surprisingly bad rate.
  • We have a a professor emeritus at Harvard, two time pulitzer prize winner saying one thing, a blogger saying another, and the headline looks like the blogger wrote it. Bad slashdot.
    • Isn't it great that we have bloggers who can tell us what is right and wrong? What would we ever do without bloggers?

      The funny thing is the mere fact of calling him a 'great scientist' proves the blogger's point wrong, and the bulk of his post is dedicated to trying to explain away that contradiction.
  • Any 4-year degree from the same college costs you the same amount of time and money whether it is a degree in Art History, English or Electrical Engineering.
    The value of the degree in the marketplace tho is totally skewed towards mathematics. The more math you have to take to get your degree, the more money it is worth in the marketplace. Compare Computer Tech degree to Computer Science degree to Computer Engineering degree.

    E.O. Wilson is perhaps technically correct about -needing- math early, but he is
  • The 'great scientist' article is telling people, "don't be afraid of studying science just because you aren't good at math." He points out there are plenty of fields that don't require much math (as opposed to physics). He doesn't say math isn't useful, good or important, he merely says that you can still be great even if you're not good at it.

    The blogger is irate, angry, and irked. He lashes out with his words. Thank goodness we have bloggers in the world to be angry at great scientists.

    There's no reas
  • Of course, all scientists need to conceptually understand basic concepts like the different measures of central tendency, deviation, why normal distribution arises, correlation vs. causation and the difference between predictive and explanatory statistics, robustness, and (this is a biggie) conditional probability. But there's no particular reason why they need to know about the Chi squared distribution or the precise mathematical formulas used to calculate these things.

    I think the problem is grade infl
  • It seems to me that if one were to take this proposition seriously, it should appear as an article in a scientific journal, not the Wall Street Journal.

    While I have no qualms with the Wall Street Journal, it does concern me when an article is published for a bunch of MBAs and CFOs that basically equates scientific research as nothing more than a bunch of individualized technicians. Research is not like web design where you have a design architect and a bunch of coders. But the article, phrased as it is, m

  • by Dr. Spork ( 142693 ) on Sunday April 21, 2013 @12:44PM (#43510131)
    In the article, Wilson talked about how making it through Calculus ended up giving him all the math he needed to do his own work, and would suffice for much other important scientific work. I frankly thought that his target was not simply the population of smart but "merely OK at math" students who are being deterred from scientific fields, but the gatekeepers of the fields themselves, who would probably reject someone like Crick for his C grade in Calculus. He's not arguing for lower standards, but for more diversity in how we see scientific talent. If the litmus test for the "promising future scientist" were based almost entirely on the verbal SAT score, I can imagine that Crick would be railing against that. But as it stands, he simply thinks the pendulum is too far in the math direction, and this is doing a disservice to science. I find that quite reasonable!
  • by Anonymous Coward

    America is the land of pseudo-science, and pseudo-scientists who push the 'right' agendas can easily rise to the top of their profession, and be lavished with all kinds of prizes and recognition.

    -The depraved monsters who created and executed the 'scientific' studies to inject healthy black Americans with syphilis, and watch them suffer untreated, were highly regarded doctors.
    -The depraved monster who photographed generations of young men and women naked at ivy-league universities all across America in orde

  • Wilson states that to do good science and to be a good scientist you don't need to be a math wiz. Iddo states to be employable in the tech and science field the more math the better. Am I the only one who has noticed these aren't the same point? Iddo is worrying that if your C.V. doesn't show enough math you won't get the position to do the science at all. Wilson says you can find a place for yourself that uses the math you already know. Wilson is optimistic, Iddo is realistic/pessimistic. Wilson succeeded

  • Biology has an advantage over many other sciences. You can apply close study to the subject. But when one crosses over into fields like physics there are situations where the degree of resolution has reached its end and now mathematics becomes almost the singular tool. The ability to use various unusual logics and to reduce the question into equations is perhaps as far as we can ever hope to go. Trying to approach subjects like the underlying fabric that supports the universe or much of qua

  • I keep hearing this over and over from people. It seems like biologists are never educated in certain aspects of basic research. I know a CS grad student (who also has a degree in biology) who was talking about Google Scholar with some other biology grad students; they started taking notes because they'd never heard of it before. I asked how they managed to cite anything, and I was told that they do get the journals as they are published, and they do read, but they never SEARCH for anything.

  • Wilson is (or was) an observational biologist and naturalist. His book "The Ants" is great, but it's a picture book with essays.

    For a science to lead to applications, it must have predictive ability. The hard line on this is from Sir Fred Hoyle: "Science is prediction, not explanation". Much of engineering is about prediction - being able to figure out what will work before you make it. Without that, you can't build anything big or complicated and get it to work.

    The market for scientists in fields with

  • by blue trane ( 110704 ) on Sunday April 21, 2013 @04:37PM (#43511527) Homepage Journal

    "Faraday was an excellent experimentalist who conveyed his ideas in clear and simple language; his mathematical abilities, however, did not extend as far as trigonometry or any but the simplest algebra."

    http://en.wikipedia.org/wiki/Michael_Faraday [wikipedia.org]

  • by Brett Buck ( 811747 ) on Sunday April 21, 2013 @04:54PM (#43511633)

    This is not a science.

  • by fearofcarpet ( 654438 ) on Monday April 22, 2013 @01:24AM (#43513365)

    Did anyone actually read Wilson's article... including the irate, myopic blogger who is projecting his own bias while criticizing Wilson for the same?

    Well, I have a professional secret to share: Many of the most successful scientists in the world today are mathematically no more than semiliterate.

    In my fifteen-or-so years as an academic scientist, I have found this observation to be 100% correct and I have worked with some incredibly famous and well-respected scientists not unlike E.O. Wilson.

    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 other words, math skills have nothing to do with creativity and science is driven, at its most fundamental level, by creative thinking.

    Pioneers in science only rarely make discoveries by extracting ideas from pure mathematics. Most of the stereotypical photographs of scientists studying rows of equations on a blackboard are instructors explaining discoveries already made.

    Math is a descriptive language, not an engine for discovery, duh.

    Ideas in science emerge most readily when some part of the world is studied for its own sake. They follow from thorough, well-organized knowledge of all that is known or can be imagined of real entities and processes within that fragment of existence. When something new is encountered, the follow-up steps usually require mathematical and statistical methods to move the analysis forward. If that step proves too technically difficult for the person who made the discovery, a mathematician or statistician can be added as a collaborator.

    Modern science is too complex for one generalist to do everything (and to take credit for it). These days everyone is a specialist, with a PhD in a very specific subject, and they all work together to bring ideas through to discoveries and eventually to technology. Would anyone argue that the POTUS runs the entire federal government by himself, being a world-class expert in everything from speech writing to foreign policy? Then why is it so hard to imagine that great discoveries are supported by the collaborative efforts of many, with one generally receiving the lion's share of the credit for the actual discovery?

    The response of the blogger focuses on the idea that Wilson is an outlier and that, like Bill Gates dropping out of college, his resume should not be used as a template. But Wilson is not arguing that he was successful because he was semi-literate at math, he is arguing that you can be successful by focusing on what your good at, and complimenting your abilities with fruitful collaboration. His reason for making this argument is simple; too many people that would otherwise make talented scientists shy away from the sciences because they aren't good at math.

    My two cents: there are, very broadly speaking, two principle kinds of scientists (with many exceptions). There the creative types, who are rarely good with math, often lack attention to detail, but who are astonishingly good at creative problem solving. Then there are the analytic types, who are too skeptical to be creative, are often detail-oriented, but who are astonishingly good at analyzing and understanding raw data. The best science is performed by teams comprising both types of people who respect and trust one another.

Nondeterminism means never having to say you are wrong.