Therein lies the power of mistakes as a vehicle for, as Rilke famously put it, “living the questions” and thus advancing knowledge in a way that certainty cannot — for, as Richard Feynman memorably noted, the scientist’s job is to remain unsure, and so seems the philosopher’s. Dennett writes:

The history of philosophy is in large measure the history of very smart people making very tempting mistakes, and if you don’t know the history, you are doomed to making the same darn mistakes all over again. … There is no such thing as philosophy-free science, just science that has been conducted without any consideration of its underlying philosophical assumptions.

Writing and submission. The process of compiling findings, writing accompanying narrative and making this available for public view and scrutiny can be simplified by the use of new improved software. These tools can help identify relevant papers through increasingly powerful learning algorithms (e.g. F1000Workspace, Mendeley, Readcube). They can also enable collaborative authoring (e.g. F1000Workspace, Overleaf, Google docs), and provide formatting tools to simplify the process of structuring an article to ensure all the necessary underlying information has been captured (e.g. F1000Workspace, EndNote). Submission for posting as a preprint, and/or for formal publication and peer review, should be as simple as a single click.

one of the roles of philosophy over the past two and half millennia has been to prepare the ground for the birth and eventual intellectual independence of a number of scientific disciplines. But contra what you seem to think, this hasn’t stopped with the Scientific Revolution, or with the advent of quantum mechanics. Physics became independent with Galileo and Newton (so much so that the latter actually inspired David Hume and Immanuel Kant to do something akin to natural philosophizing in ethics and metaphysics); biology awaited Darwin (whose mentor, William Whewell, was a prominent philosopher, and the guy who coined the term “scientist,” in analogy to artist, of all things); psychology spun out of its philosophical cocoon thanks to William James, as recently (by the standards of the history of philosophy) as the late 19th century. Linguistics followed through a few decades later (ask Chomsky); and cognitive science is still deeply entwined with philosophy of mind (see any book by Daniel Dennett). Do you see a pattern of, ahem, progress there? And the story doesn’t end with the newly gained independence of a given field of empirical research. As soon as physics, biology, psychology, linguistics and cognitive science came into their own, philosophers turned to the analysis (and sometimes even criticism) of those same fields seen from the outside: hence the astounding growth during the last century of so called “philosophies of”: of physics (and, more specifically, even of quantum physics), of biology (particularly of evolutionary biology), of psychology, of language, and of mind.

. Referees ofgrant proposals agree much more about what is unworthy of support than about what does have scientific value. In

A system that assumes a "quite good" institution is unable to get better, and thus denies them the funds that would enable them to get better, is probably not an optimal system for promoting merit. A system that rewards in proportion to merit would at least be able to recognise and reflect the dynamism of university research; research groups wax and wane as people come, go, get disheartened, get re-invigorated.

it could be argued that we don’t just need an elite: we need a reasonable number of institutions in which there is a strong research environment, where more senior researchers feel valued and their graduate students and postdocs are encouraged to aim high. Our best strategy for retaining international competitiveness might be by fostering those who are doing well but have potential to do even better

. I consider that my job, as a philosopher, is to activate the possible, and not to describe the probable, that is, to think situations with and through their unknowns when I can feel them

The science of the individual relies on dynamic systems theory rather than group statistics. Its research methodology is characterized by “analyze, then aggregate” (analyze each subject separately, then combine individual patterns into collective understanding) rather than “aggregate, then analyze” (derive group statistics based on aggregate data, then use these statistics to evaluate and understand individuals).

An all-star international team of astrophysicists used an exquisitely sensitive, $1.1 billion set of twin instruments known as the Laser Interferometer Gravitational-wave Observatory, or LIGO, to detect a gravitational wave generated by the collision of two black holes 1.3 billion light-years from Earth.

Since its start in 1998, Software Carpentry has evolved from a week-long training course at the US national laboratories into a worldwide volunteer effort to improve researchers' computing skills. This paper explains what we have learned along the way, the challenges we now face, and our plans for the future.

While there are some features shared between a university repository and us we are distinctly different for the following reasons: We offer DOIs to all content published on The Winnower All content is automatically typeset on The Winnower Content published on the winnower is not restricted to one university but is published amongst work from peers at different institutions around the world Work is published from around the world it is more discoverable We offer Altmetrics to content  Our site is much more visually appealing than a typical repository  Work can be openly reviewed on The Winnower but often times not even commented on in repositories. This is not to say that repositories have no place, but that we should focus on offering authors choices not restricting them to products developed in house.

educators and business leaders are increasingly recognizing that CS is a “new basic” skill necessary for economic opportunity. The President referenced his Computer Science for All Initiative, which provides $4 billion in funding for states and $100 million directly for districts in his upcoming budget; and invests more than $135 million beginning this year by the National Science Foundation and the Corporation for National and Community Service to support and train CS teachers.

open Science

This has implications far beyond the cryptocurrency

"A friend of mine said a really great phrase: 'remember those times in early 1990's when every single brick-and-mortar store wanted a webmaster and a small website. Now they want to have a data scientist.' It's good for an industry when an attitude precedes the technology."

Stupid models are extremely useful. They are usefulbecause humans are boundedly rational and because language is imprecise. It is often only by formalizing a complex system that we can make progress in understanding it. Formal models should be a necessary component of the behavioral scientist’s toolkit. Models are stupid, and we need more of them.

Microeconomic models based on rational choice theory are useful for developing intuition, and may even approximate reality in a fewspecial cases, but the history of behavioral economics shows that standard economic theory has also provided a smorgasbord of null hypotheses to be struck down by empirical observation.

Where differences between conditions are indicated, avoid the mistake of running statistical analyses as if you were sampling from a larger population.

A model’s strength stemsfromits precision.

However, I want to be careful not to elevate modelers above those scientists who employ other methods.

Ultimately,the theory has been shown to be incorrect, and has been epistemically replaced by the theory of General Relativity. Nevertheless, the theory is able to make exceptionally good approximations of gravitational forces –so good that NASA’s moon missions have relied upon them.

Table 1.Twelve functions served by false models. Adapted with permissionfrom Wimsatt

To paraphrase Gunawardena (2014), a model is a logical engine for turning assumptions into conclusions.

the stupidity of a model is often its strength. By focusing on some key aspects of a real-world system(i.e., those aspectsinstantiated in the model), we can investigate how such a system would work if, in principle, we really couldignore everything we are ignoring. This only sounds absurd until one recognizes that, in our theorizing about the nature of reality –both as scientists and as quotidianhumans hopelessly entangled in myriad webs of connection and conflict –weignore thingsall the time.

The generalized linear model, the work horse ofthe social sciences, models data as being randomly drawn from a distribution whose mean varies according to some parameter. The linear model is so obviously wrong yet so useful that the mathematical anthropologist Richard McElreathhas dubbed it “the geocentric model of applied statistics,”in reference to the Ptolemaic model of the solar system that erroneously placed the earth rather than the sun at the center but nevertheless produced accurate predictions of planetary motion as they appeared in the night sky(McElreath 2015).

Unfortunately, my own experience working with complex systems and working among complexity scientistssuggests that we are hardly immune to such stupidity. Consider the case of Marilyn Vos Savantand the Monty Hall problem.

Mitch Resnick, in his book Turtles, Termites, and Traffic Jams, details his experiences teaching gifted high school students about the dynamics of complex systems using artificial life models (Resnick 1994). He showed them how organized behavior could emerge when individualsresponded only to local stimuli using simple rules, without the need for a central coordinating authority. Resnick reports that even after weeks spent demonstrating the principles of emergence,using computer simulations that the students programmed themselves, many students still refused to believe that what they were seeing could really work without central leadership.

how

Maybe digital history is at the midway point on the continuum between art and science

As part of EFF’s 25th Anniversary celebrations, we are releasing “Pwning Tomorrow: Stories from the Electronic Frontier,” an anthology of speculative fiction from more than 20 authors, including Bruce Sterling, Lauren Beukes, Cory Doctorow, and Charlie Jane Anders. To get the ebook, you can make an optional contribution to support EFF’s work, or you can download it at no cost. We're releasing the ebook under a Creative Commons Attribution-NonCommercial-No Derivatives 4.0 International license, which permits sharing among users. 

Part of Galileo’s genius was to transfer the spirit of the Italian Renaissance in the plastic arts to the mathematical and observational ones.

Big Sur is our newest Open Rack-compatible hardware designed for AI computing at a large scale. In collaboration with partners, we've built Big Sur to incorporate eight high-performance GPUs

Similarly, in science there exists substantial expertise making brilliant connectionsbetween concepts, but it is being conveyed in silos of English prose known as journalarticles. Every scientific journal article has a methods section, but it is almost impossibleto read a methods section and subsequently repeat the experiment—the English languageis inadequate to precisely and concisely convey what is being done.

As mentioned above category theory has branched out into certain areas of scienceas well. Baez and Dolan have shown its value in making sense of quantum physics, itis well established in computer science, and it has found proponents in several otherfields as well. But to my mind, we are the very beginning of its venture into scientificmethodology. Category theory was invented as a bridge and it will continue to serve inthat role.

In 1980 Joachim Lambek showed that the types and programs used in computerscience form a specific kind of category. This provided a new semantics for talking aboutprograms, allowing people to investigate how programs combine and compose to createother programs, without caring about the specifics of implementation. Eugenio Moggibrought the category theoretic notion of monads into computer science to encapsulateideas that up to that point were considered outside the realm of such theory.

The paradigm shift brought on by Einstein’s theory of relativity brought on the real-ization that there is no single perspective from which to view the world. There is nobackground framework that we need to find; there are infinitely many different frame-works and perspectives, and the real power lies in being able to translate between them.It is in this historical context that category theory got its start.

Agreementis the good stuff in science; it’s the high fives.But it is easy to think we’re in agreement, when really we’re not. Modeling ourthoughts on heuristics and pictures may be convenient for quick travel down the road,but we’re liable to miss our turnoff at the first mile. The danger is in mistaking ourconvenient conceptualizations for what’s actually there. It is imperative that we havethe ability at any time to ground out in reality.

For me the interesting part of Stiegler’s work is the idea that it is technics that invents human beings; it is technics that constitutes the human.

Les représentants de la Bibliothèque nationale de France (BnF) annoncèrent leur objectif de ramener le délai de traitement des documents à six semaines en moyenne

“Many random number generators in use today are not very good. There is a tendency for people to avoid learning anything about such subroutines; quite often we find that some old method that is comparatively unsatisfactory has blindly been passed down from one programmer to another, and today’s users have no understanding of its limitations.”— Donald Knuth; The Art of Computer Programming, Volume 2.

TPOT is a Python tool that automatically creates and optimizes machine learning pipelines using genetic programming. Think of TPOT as your “Data Science Assistant”: TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines, then recommending the pipelines that work best for your data.

Max Planck, when asked how often science changes and adopts new ideas, said, “with every funeral.” And for better or worse, they happen pretty regularly.

Who among us could predict anything five years into the future? What kind of science would science be if it could make reliable predictions about stuff five years out? Science is about what we don’t know yet and how we’re going to get to know it.

I know how crazy that sounds, but it is of course exactly the right way to proceed. If you are reviewing a grant, you should be interested in how it will fail—usefully or just by not succeeding. Not succeeding is not the same as failing. Not in science.

Too often you fail until you succeed, and then you are expected to stop failing. Once you have succeeded you supposedly know something that helps you to avoid further failure. But that is not the way of science. Success can lead only to more failure. The success, when it comes, has to be tested rigorously and then it has to be considered for what it doesn’t tell us, not just what it does tell us. It has to be used to get to the next stop in our ignorance—it has to be challenged until it fails, challenged so that it fails.

According to Mark T. Mitchell, professor of political science at Patrick Henry College in Virginia: Gratitude is born of humility, for it acknowledges the giftedness of the creation and the benevolence of the Creator. This recognition gives birth to acts marked by attention and responsibility. Ingratitude, on the other hand, is marked by hubris, which denies the gift, and this always leads to inattention, irresponsibility, and abuse.

Davidson shocked his professors by taking off for India to explore meditation practice and Buddhist teachings. After three months there and in Sri Lanka, he came back convinced he would do meditation research. He was quickly disabused of this notion by his professors, who let him know that if he had any hope of a career in science, he’d better stow the meditation and follow a more conventional path of research. He became a closet meditator and an affective neuroscientist—a deep student of the emotions.

as Brent Tully (known for his discovery of supergalaxies) observed: “It’s disturbing  that there is a new theory every time there is a new observation.”

when the built environment ceases to accommodate behavioral requirements, people seek to correct the problem through construction, renovation, or moving to a different building

However, if an open access version of a text is available, this must always be treated as the primary text. Here the commercial version of the text becomes the secondary version and it should always be cited second and in a manner that makes this completely clear. For instance, after the primary reference to the full text, you could write: ‘Also available as: ….’

Laboratory analysis of those samples found compounds that are toxic to humans, including acetone and methylene chloride — powerful industrial solvents — along with oil.

warns us against equating changes in scientific understanding of a sense such as smell, what is called “osmology,” with experiential transformations. Attending to the history of smell, he tells us, is also valuable in undermining simple binary oppositions between boundaried individuals and their englobing environ- ment, the basis of Cartesian subject/object dualisms. Instead, it helps situate us in a more fluid, immersive context, where such stark oppositions are understood as themselves contingent rather than necessary

There’s a scale for how to think about science. On one end there’s an attempt to solve deep, fundamental questions of nature; on the other is rote uninteresting procedure. There’s also a scale for creating products. On one end you find ambitious, important breakthroughs; on the other small, iterative updates. Plot those two things next to each other and you get a simple chart with four sections. Important science but no immediate practical use? That’s pure basic research — think Niels Bohr and his investigations into the nature of the atom. Not much science but huge practical implications? That’s pure applied research — think Thomas Edison grinding through thousands of materials before he lit upon the tungsten filament for the lightbulb.

Annual Reviews is collaborating with JSTOR to digitize, preserve and extend access to Annual Review of Anthropology. http://www.jstor.org The Globalization of Pentecostal and Charismatic Christianity

Wouldn’t it be useful, both to the scientific community or the wider world, to increase the publication of negative results?

Unlike most popularizers (at least of mine), this post didn’t describe a completed piece of research. It just served just an opportunity to riff about an idea I found interesting. But blogging made me realize this idea could be more interesting than I had realized. A “motivated view” of empathy could, for instance, help in understanding illnesses like autism and psychopathy, or thinking up techniques to “grow” empathy. I figured it’d be worth sinking some more effort into it, and wrote a long form academic article on the subject. After much work and a long (but productive) peer review process, that article was published just last week! More importantly, the ideas in that piece—taken over by my students—now drive much new work in my lab that might not have happened otherwise.

developed a specific coding scheme for volunteers to follow. As a supplement to that scheme, the following tutorial can be used to gain more facility with identifying article structure and und

Hence the man who makes a good guess at truth is likely to make a good guess at probabilities

It is a subject that can be treated systematically

"science" which can teach us to do under all circumstances the things which will insure our happiness and success.