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Terrible Advice From a Great Scientist
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."
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.
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'.
Code or be coded.
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.
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.
Lacking <sarcasm> tags,
That's like literature without words...
“He’s not deformed, he’s just drunk!”
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.
while(1) attack(People.Sandy);
Sure, the roles do require "math literacy" which is a lower standard than "sufficient mathematical and comptuational capability to independently produce results for a research journal."
Just like natural language literacy is a lower standard than powerful, skilled writing.
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.
deleting the extra space after periods so i can stay relevant, yeah.
Collecting data without having a darn good grasp of how the data analysis works is a great way to waste a huge amount of time and money collecting mostly useless data. It may not be the same person doing both, but the data-collector definitely needs to be intimately "in the loop" about how their experimental work impacts uncertainties in the final analysis.
See also: Noam Chomsky on language
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
Teams these days are really large, so much so that the data-collector is often not even the person designing the experiment. And that person is not the person doing the analysis of the data, who is not the person designing the mathematical model, who is in turn not the person implementing the simulation software. They all have to communicate in various ways, but they cannot each have all of those skills.
On smaller projects it may be the case that there's a more unified role of "experimental scientist", who does need to do all of understanding the model, designing the experiments, and carrying out the experiments. But on large teams the people actually collecting data need more technical skills, focused on operating various kinds of equipment properly. Someone else has drawn up exactly which experiments need to be run, but getting them run properly is not easy. Hence there are various scientific roles, like laboratory technician, that don't even require advanced degrees.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
Have gnu, will travel.
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.
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.
Without understanding the measurements and statistics involved, the experiment design will most certainly turn out to be crap.
Here, fixed that for ya.
Ezekiel 23:20
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!
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 order to push his ideas on race and eugenics was a highly regarded scientist in the same vein as E.O.Wilson
-The depraved doctor who introduced female genital mutilation to the USA (a practice that was widespread up till the 1960s) was thrown out of the UK, but was given a tremendous reception by the medical community in the USA.
-The depraved monster that attempted (and almost succeeded) in having lobotomy as common as vaccination won the highest scientific awards in the USA.
-The racist filth that created the concept of eugenics, and pushed for programs that eventually led to forced sterilisation in countries all across the globe, were given the highest praise by the scientific community in the USA.
-Even today, male genital mutilation is universal across the USA, originally made popular by madmen like Dr Kellogg in the 19th century as a 'cure' for masturbation. Every 20 years or so the US medical community reaffirms the desirability of MGM by claiming it is a defence against whatever illness is currently significant in the minds of the public. It is notable that all the early studies in Africa discovered circumcised males suffered massively INCREASED rates of AIDS infection. When Jewish and Muslim and evangelical American propagandists took control of WHO research bodies a number of years later, magically the results of the studies reversed.
"Government scientist" is an oxymoron. You are either loyal to the fundamental principles of science, or loyal to a current political agenda. The 'scientists' that the general public hears from are not scientists at all, but propagandists. Sadly, many fields of science are very expensive to pursue, and the people that pay the bills frequently have strong ideas about the 'news' they expect to hear.
'Sociobiology' is just today's eugenics- another branch of pseudo-science strongly linked to religious concepts that are worked in order to create the circumstances for new wars on a global scale. 'Sociobiology' is designed to argue that 'war' is just an extension of evolution, just as eugenics and the theory of 'race' was originally created to give a scientific justification of slavery in the USA during the first half of the 19th century. Eugenics flourished in the USA after slavery was ended, in order to counter the concept of "all men are created equal", and ensure the spread of the 'Jim Crow' laws that existed until the 1960s.
I was a natural sciences major in college and what you're talking about is one or maybe 2 classes worth of math. You don't need calculus or anything beyond that in most cases to design an experiment, obviously depending upon the particular field of study. Statistics itself is heavily derived from a set of formulas that you can look up in a book and the reasoning behind it requires at most intermediate algebra to understand.
I definitely agree that you need an understanding of statistics to design your experiments, but really, the amount of math you really need is surprisingly small given that you're going to want to bring in an expert that's experienced in the specific area you're working anyways. Now, were we to go back in time to days when there wasn't a huge team, that would presumably be a different matter. But, understanding doesn't really require that much math.
TL:DR, you're going to want an expert in dealing with modelling and data of the type you're looking at. It makes more sense than reinventing the wheel every time you do an experiment and forcing people to master not just one specialty, but several of them, and ultimately it's unlikely that they'll achieve a level high enough to compete with the best in both fields.
You make a very strong point. There are often statistical and mathematical modeling assumptions that the researchers are aware of ahead of time, subtle pitfalls in the experimental setup that must be avoided to produce the type of data needed, etc., that the technicians/engineers will be unaware of unless the researchers themselves are directly involved in the experiments. By the same token, it's a good idea to have an engineer involved in the data collection review the research prior to publication to catch any obvious flaws in the modeling assumptions or misuse of the data (even if he doesn't understand everything in the paper). 'Separation of duties' is something that comes from laziness or time/budget constraints rather than being a template for solid scientific work.
Comment removed based on user account deletion
"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
This is not a science.
Science and its requirements are dynamic, and nowhere is this more obvious than in the relationship between maths and biology.
When I was an undergraduate about 20 years ago, biology was the science you did if you liked science but didn't like maths. In the intervening years, largely thanks to the rise of bioinformatics, this is no longer true.
E.O. Wilson didn't need to have a mathematical background back in his day, but that day is now gone. We now have the technology to make quantifiable predictions, but there is a generation of biologists who don't even consult a statistician before designing an experiment.
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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.
Actually, I wrote my thesis on life experience.