Archive for the ‘Philosophy’ Category

Launch of the PhilMath Archive

Monday, May 29th, 2017

Launch of the PhilMath Archive: preprint server specifically for philosophy of mathematics

From the post:

PhilSci-Archive is pleased to announce the launch of the PhilMath-Archive, a preprint server specifically for the philosophy of mathematics. The PhilMath-Archive is offered as a free service to the philosophy of mathematics community. Like the PhilSci-Archive, its goal is to promote communication in the field by the rapid dissemination of new work. We aim to provide an accessible repository in which scholarly articles and monographs can find a permanent home. Works posted here can be linked to from across the web and freely viewed without the need for a user account.

PhilMath-Archive invites submissions in all areas of philosophy of mathematics, including general philosophy of mathematics, history of mathematics, history of philosophy of mathematics, history and philosophy of mathematics, philosophy of mathematical practice, philosophy and mathematics education, mathematical applicability, mathematical logic and foundations of mathematics.

For your reference, the PhilSci-Archive.


Researchers found mathematical structure that was thought not to exist [Topic Map Epistemology]

Tuesday, November 15th, 2016

Researchers found mathematical structure that was thought not to exist

From the post:

Researchers found mathematical structure that was thought not to exist. The best possible q-analogs of codes may be useful in more efficient data transmission.

The best possible q-analogs of codes may be useful in more efficient data transmission.

In the 1970s, a group of mathematicians started developing a theory according to which codes could be presented at a level one step higher than the sequences formed by zeros and ones: mathematical subspaces named q-analogs.

While “things thought to not exist” may pose problems for ontologies and other mechanical replicas of truth, topic maps are untroubled by them.

As the Topic Maps Data Model (TMDM) provides:

subject: anything whatsoever, regardless of whether it exists or has any other specific characteristics, about which anything whatsoever may be asserted by any means whatsoever

A topic map can be constrained by its author to be as stunted as early 20th century logical positivism or have a more post-modernist approach, somewhere in between or elsewhere, but topic maps in general are amenable to any such choice.

One obvious advantage of topic maps being that characteristics of things “thought not to exist” can be captured as they are discussed, only to result in the merging of those discussions with those following the discovery things “thought not to exist really do exist.”

The reverse is also true, that is topic maps can capture the characteristics of things “thought to exist” which are later “thought to not exist,” along with the transition from “existence” to being thought to be non-existent.

If existence to non-existence sounds difficult, imagine a police investigation where preliminary statements then change and or replaced by other statements. You may want to capture prior statements, no longer thought to be true, along with their relationships to later statements.

In “real world” situations, you need epistemological assumptions in your semantic paradigm that adapt to the world as experienced and not limited to the world as imagined by others.

Topic maps offer an open epistemological assumption.

Does your semantic paradigm do the same?

A Taxonomic Map of Philosophy

Wednesday, August 10th, 2016

A Taxonomic Map of Philosophy by Justin W..

From the post:

Some people go to PhilPapers, get the information they need, and then just go. Not Valentin Lageard, a graduate student in philosophy at Université Paris-Sorbonne. The Categories page at the site caught his eye. He says:

The completeness of their taxonomy was striking and I thought : “Could it be possible to map this taxonomy ?”. I decided it was a nice idea and i started to work on it.

The first step was to select the kind of graph and since their taxonomy includes a hierarchy permitting to sub-categories to be children of more than one parent categories, I selected a concentric circles graph.

Because I’m a python user, I choosed Networkx for the graph part and BeautifulSoup for the scraping part. Furthermore, since Philpapers gives the articles number for each category, I decided to add this data to my graph.

After some configurations of the display, I finally reached my goal: a map of the taxonomy of philosophy. And it was quite beautiful.


[See update, below, for the more detailed 5-layer version]

NEW UPDATE: Here is the 5-layer version. You can view it in more detail here (open it in a new tab or window for best results).

Impressive but is it informative?

In order to read the edge, I had to magnify the graph several times its original size, which then meant navigation was problematic.

Despite the beauty of the image, a graph file that enables filtering of nodes and edges would be far more useful for exploring the categories as well as the articles therein.

For example:


If you are wondering what falls under “whiteness,” apparently studies of “whiteness” in the racial sense but also authors whose surnames are “White.”

As the top of the categories page for whiteness advises:

This category needs an editor. We encourage you to help if you are qualified.

Caution: You may encounter resources at PhilPapers that render you unable to repeat commonly held opinions. Read at your own risk.


Santa Claus is Real

Friday, December 25th, 2015

Santa Claus is Real by Johnathan Korman.

I won’t try to summarize Korman’s post but will quote a snippet to entice you to read it in full:

Santa Claus is as real as I am.

Santa is, in truth, more real than I am. He has a bigger effect on the world.

After all, how many people know Santa Claus? If I walk down Market Street in San Francisco, there’s a good chance that a few people will recognize me; I happen to be a distinctive-looking guy. There’s a chance that one or two of those people will even know my name and a few things about me, but the odds are greatly against it. But if Santa takes the same walk, everybody (or nearly everybody) will recognize him, know his name, know a number of things about him, even have personal stories about him. So who is more real?



Monday, October 19th, 2015


From the webpage:

The CrowdTruth Framework implements an approach to machine-human computing for collecting annotation data on text, images and videos. The approach is focussed specifically on collecting gold standard data for training and evaluation of cognitive computing systems. The original framework was inspired by the IBM Watson project for providing improved (multi-perspective) gold standard (medical) text annotation data for the training and evaluation of various IBM Watson components, such as Medical Relation Extraction, Medical Factor Extraction and Question-Answer passage alignment.

The CrowdTruth framework supports the composition of CrowdTruth gathering workflows, where a sequence of micro-annotation tasks can be configured and sent out to a number of crowdsourcing platforms (e.g. CrowdFlower and Amazon Mechanical Turk) and applications (e.g. Expert annotation game Dr. Detective). The CrowdTruth framework has a special focus on micro-tasks for knowledge extraction in medical text (e.g. medical documents, from various sources such as Wikipedia articles or patient case reports). The main steps involved in the CrowdTruth workflow are: (1) exploring & processing of input data, (2) collecting of annotation data, and (3) applying disagreement analytics on the results. These steps are realised in an automatic end-to-end workflow, that can support a continuous collection of high quality gold standard data with feedback loop to all steps of the process. Have a look at our presentations and papers for more details on the research.

An encouraging quote from Truth is a Lie by Lora Aroyo.

the idea of truth is a fallacy for semantic interpretation and needs to be changed

I don’t disagree but observe a “crowdtruth” with disagreements is a variant of “truth.” What variant of “truth” is of interest to your client is an important issue.

CIA analysts, for example, have little interest in crowdtruths that threaten their prestige and/or continued employment. “Accuracy” is only one aspect of any truth.

If your client is sold on crowdtruths, by all means take up the banner on their behalf. Always remembering:

There are no facts, only interpretations. (Nietzsche)

Which interpretation interests you?

Cause And Effect:…

Tuesday, December 23rd, 2014

Cause And Effect: The Revolutionary New Statistical Test That Can Tease Them Apart

From the post:

…But in the last few years, statisticians have begun to explore a number of ways to solve this problem. They say that in certain circumstances it is indeed possible to determine cause and effect based only on the observational data.

At first sight, that sounds like a dangerous statement. But today Joris Mooij at the University of Amsterdam in the Netherlands and a few pals, show just how effective this new approach can be by applying it to a wide range of real and synthetic datasets. Their remarkable conclusion is that it is indeed possible to separate cause and effect in this way.

Mooij and co confine themselves to the simple case of data associated with two variables, X and Y. A real-life example might be a set of data of measured wind speed, X, and another set showing the rotational speed of a wind turbine, Y.

These datasets are clearly correlated. But which is the cause and which the effect? Without access to a controlled experiment, it is easy to imagine that it is impossible to tell.

The basis of the new approach is to assume that the relationship between X and Y is not symmetrical. In particular, they say that in any set of measurements there will always be noise from various cause. The key assumption is that the pattern of noise in the cause will be different to the pattern of noise in the effect. That’s because any noise in X can have an influence on Y but not vice versa.

At some eighty-three (83) pages, this is going to take a while to digest. One of the reasons for mentioning it as a couple of holidays approach in many places.

I don’t think the authors are using “cause and effect” in the same sense as Hume and Ayer but that remains to be seen. Just skimming the first few pages, this is going to be an interesting read.

The post is based on:

Distinguishing cause from effect using observational data: methods and benchmarks by Joris M. Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, and Bernhard Schöt;lkopf.


The discovery of causal relationships from purely observational data is a fundamental problem in science. The most elementary form of such a causal discovery problem is to decide whether X causes Y or, alternatively, Y causes X, given joint observations of two variables X, Y . This was often considered to be impossible. Nevertheless, several approaches for addressing this bivariate causal discovery problem were proposed recently. In this paper, we present the benchmark data set CauseEffectPairs that consists of 88 different “cause-effect pairs” selected from 31 datasets from various domains. We evaluated the performance of several bivariate causal discovery methods on these real-world benchmark data and on artificially simulated data. Our empirical results provide evidence that additive-noise methods are indeed able to distinguish cause from effect using only purely observational data. In addition, we prove consistency of the additive-noise method proposed by Hoyer et al. (2009).

Thoughts and comments welcome!

Friedrich Nietzsche and his typewriter – a Malling-Hansen Writing Ball

Monday, November 24th, 2014

Friedrich Nietzsche and his typewriter – a Malling-Hansen Writing Ball

keyboard of typing ball

typing ball, full shot

From the webpage:

The most prominent owner of a writing ball was probably the German philosopher, Friedrich Nietzsche (1844-1900). In 1881, when he was almost blind, Nietzsche wanted to buy a typewriter to enable him to continue his writing, and from letters to his sister we know that he personally was in contact with “the inventor of the typewriter, Mr Malling-Hansen from Copenhagen”. He mentioned to his sister that he had received letters and also a typewritten postcard as an example.

Nietzsche received his writing ball in 1882. It was the newest model, the portable tall one with a colour ribbon, serial number 125, and several typescripts are known to have been written by him on this writing ball. We know that Nietzsche was also familiar with the newest Remington typewriter (model 2), but as he wanted to buy a portable typewriter, he chose to buy the Malling-Hansen writing ball, as this model was lightweight and easy to carry — one might say that it was the “laptop” of that time.

Unfortunately Nietzsche wasn’t totally satisfied with his purchase and never really mastered the use of the instrument. Until now, many people have tried to understand why Nietzsche did not make more use of it, and a number of theories have been suggested such as that it was an outdated and poor model, that it was possible to write only upper case letters, etc. Today we can say for certain that all this is only speculation without foundation.

The writing ball was a solidly constructed instrument, made by hand and equipped with all the features one would expect of a modern typewriter.

You can now read the details about the Nietzsche writing ball in a book, “Nietzches Schreibkigel”, by Dieter Eberwein, vice-president of the International Rasmus Malling-Hansen Society, published by “Typoscript Verlag”. In it, Eberwein tells the true story about Nietzche’s writing ball based upon thorough investigation and restoration of the damaged machine.

If you think of Nietzsche‘s typing ball as an interface, it is certainly different from the keyboards of today.

I am not sure I could re-learn the “home” position for my fingers but certainly would be willing to give it a try.

Not as far fetched as you might think, a typing ball. Matt Adereth posted this image of a prototype typing ball:

proto-type typing ball

Where would you put the “nub” and “buttons” for a pointing device? Curious about the ergonomics. If anyone decides to make prototypes, put my name down as definitely interested.

I saw this earlier today in a tweet by Vincent Zimmer although I already aware of
Nietzsche’s typing ball.

Deeper Than Quantum Mechanics—David Deutsch’s New Theory of Reality

Thursday, November 6th, 2014

Deeper Than Quantum Mechanics—David Deutsch’s New Theory of Reality

From the post:

Their new idea is called constructor theory and it is both simpler and deeper than quantum mechanics, or indeed any other laws of physics. In fact, Deutsch claims that constructor theory forms a kind of bedrock of reality from which all the laws of physics emerge.

Constructor theory is a radically different way of thinking about the universe that Deutsch has been developing for some time. He points out that physicists currently ply their trade by explaining the world in terms of initial conditions and laws of motion. This leads to a distinction between what happens and what does not happen.

Constructor theory turns this approach on its head. Deutsch’s new fundamental principle is that all laws of physics are expressible entirely in terms of the physical transformations that are possible and those that are impossible.

In other words, the laws of physics do not tell you what is possible and impossible, they are the result of what is possible and impossible. So reasoning about the physical transformations that are possible and impossible leads to the laws of physics.

That’s why constructor theory is deeper than anything that has gone before it. In fact, Deutsch does not think about it as a law of physics but as a principle, or set of principles, that the laws of physics must obey.

If that sounds like heavy sledding, see: : Constructor Theory of Information.


We present a theory of information expressed solely in terms of which transformations of physical systems are possible and which are impossible – i.e. in constructor-theoretic terms. Although it includes conjectured laws of physics that are directly about information, independently of the details of particular physical instantiations, it does not regard information as an a priori mathematical or logical concept, but as something whose nature and properties are determined by the laws of physics alone. It does not suffer from the circularity at the foundations of existing information theory (namely that information and distinguishability are each defined in terms of the other). It explains the relationship between classical and quantum information, and reveals the single, constructor-theoretic property underlying the most distinctive phenomena associated with the latter, including the lack of in-principle distinguishability of some states, the impossibility of cloning, the existence of pairs of variables that cannot simultaneously have sharp values, the fact that measurement processes can be both deterministic and unpredictable, the irreducible perturbation caused by measurement, and entanglement (locally inaccessible information).

The paper runs thirty (30) pages so should give you a good workout before the weekend. 😉

I first saw this in a tweet by Steven Pinker.

Lance’s Lesson – Gödel Incompleteness

Friday, October 10th, 2014

Lance’s Lesson – Gödel Incompleteness by Lance Fortnow.

The “entertainment” category on YouTube is very flexible since it included this lesson on Gödel Incompleteness. 😉

Lance uses Turing machines to “prove” the first and second incompleteness theorems in under a page of notation.

Gödel for Goldilocks…

Sunday, October 5th, 2014

Gödel for Goldilocks: A Rigorous, Streamlined Proof of Gödel’s First Incompleteness Theorem, Requiring Minimal Background by Dan Gusfield.


Most discussions of Gödel’s theorems fall into one of two types: either they emphasize perceived philosophical “meanings” of the theorems, and maybe sketch some of the ideas of the proofs, usually relating Gödel’s proofs to riddles and paradoxes, but do not attempt to present rigorous, complete proofs; or they do present rigorous proofs, but in the traditional style of mathematical logic, with all of its heavy notation and difficult definitions, and technical issues which reflect Gödel’s original exposition and needed extensions by Gödel’s contemporaries. Many non-specialists are frustrated by these two extreme types of expositions and want a complete, rigorous proof that they can understand. Such an exposition is possible, because many people have realized that Gödel’s first incompleteness theorem can be rigorously proved by a simpler middle approach, avoiding philosophical discussions and hand-waiving at one extreme; and also avoiding the heavy machinery of traditional mathematical logic, and many of the harder detail’s of Gödel’s original proof, at the other extreme. This is the just-right Goldilocks approach. In this exposition we give a short, self-contained Goldilocks exposition of Gödel’s first theorem, aimed at a broad audience.

Proof that even difficult subjects can be explained without “hand=waiving” or “heavy machinery of traditional mathematical logic.”

I first saw this in a tweet by Lars Marius Garshol.

Category Theory (Stanford Encyclopedia of Philosophy)

Saturday, October 4th, 2014

Category Theory (Stanford Encyclopedia of Philosophy)

From the entry:

Category theory has come to occupy a central position in contemporary mathematics and theoretical computer science, and is also applied to mathematical physics. Roughly, it is a general mathematical theory of structures and of systems of structures. As category theory is still evolving, its functions are correspondingly developing, expanding and multiplying. At minimum, it is a powerful language, or conceptual framework, allowing us to see the universal components of a family of structures of a given kind, and how structures of different kinds are interrelated. Category theory is both an interesting object of philosophical study, and a potentially powerful formal tool for philosophical investigations of concepts such as space, system, and even truth. It can be applied to the study of logical systems in which case category theory is called “categorical doctrines” at the syntactic, proof-theoretic, and semantic levels. Category theory is an alternative to set theory as a foundation for mathematics. As such, it raises many issues about mathematical ontology and epistemology. Category theory thus affords philosophers and logicians much to use and reflect upon.

Several tweets contained “category theory” and links to this entry in the Stanford Encyclopedia of Philosophy. The entry was substantially revised as of October 3, 2014, but I don’t see a mechanism that allows discovery of changes to the prior text.

For a PDF version of this entry (or other entries), join the Friends of the SEP Society. The cost is quite modest and the SEP is an effort that merits your support.

As a reading/analysis exercise, treat the entries in SEP as updates to Copleston‘s History of Philosophy:

A History of Philosophy 1: Greek and Rome

A History of Philosophy 2: Medieval

A History of Philosophy 3: Late Medieval and Renaissance

A History of Philosophy 4: Modern: Descartes to Leibniz

A History of Philosophy 5: Modern British, Hobbes to Hume

A History of Philosophy 6: Modern: French Enlightenment to Kant

A History of Philosophy 7: Modern Post-Kantian Idealiststo Marx, Kierkegaard and Nietzsche

A History of Philosophy 8: Modern: Empiricism, Idealism, Pragmatism in Britain and America

A History of Philosophy 9: Modern: French Revolution to Sartre, Camus, Lévi-Strauss


Avoid Philosophy?

Thursday, May 8th, 2014

Why Neil deGrasse Tyson is a philistine by Damon Linker.

From the post:

Neil deGrasse Tyson may be a gifted popularizer of science, but when it comes to humanistic learning more generally, he is a philistine. Some of us suspected this on the basis of the historically and theologically inept portrayal of Giordano Bruno in the opening episode of Tyson’s reboot of Carl Sagan’s Cosmos.

But now it’s been definitively demonstrated by a recent interview in which Tyson sweepingly dismisses the entire history of philosophy. Actually, he doesn’t just dismiss it. He goes much further — to argue that undergraduates should actively avoid studying philosophy at all. Because, apparently, asking too many questions “can really mess you up.”

Yes, he really did say that. Go ahead, listen for yourself, beginning at 20:19 — and behold the spectacle of an otherwise intelligent man and gifted teacher sounding every bit as anti-intellectual as a corporate middle manager or used-car salesman. He proudly proclaims his irritation with “asking deep questions” that lead to a “pointless delay in your progress” in tackling “this whole big world of unknowns out there.” When a scientist encounters someone inclined to think philosophically, his response should be to say, “I’m moving on, I’m leaving you behind, and you can’t even cross the street because you’re distracted by deep questions you’ve asked of yourself. I don’t have time for that.”

“I don’t have time for that.”

With these words, Tyson shows he’s very much a 21st-century American, living in a perpetual state of irritated impatience and anxious agitation. Don’t waste your time with philosophy! (And, one presumes, literature, history, the arts, or religion.) Only science will get you where you want to go! It gets results! Go for it! Hurry up! Don’t be left behind! Progress awaits!

There are many ways to respond to this indictment. One is to make the case for progress in philosophical knowledge. This would show that Tyson is wrong because he fails to recognize the real advances that happen in the discipline of philosophy over time.


I remember thinking the first episode of Tyson’s Cosmos was rather careless with its handling of Bruno and the Enlightenment. But at the time I thought that was due to it being a “popular” presentation and not meant to be precise in every detail.

Damon has an excellent defense of philosophy and for that you should read his post.

I have a more pragmatic reason for recommending both philosophy in particular and the humanities in general to CS majors. You will waste less time in programming than you will from “deep questions.”

For example, why have intelligent to the point of being gifted CS types tried repeatedly to solve the issues of naming by proposing universal naming systems?

You don’t have to be very aware to know that naming systems are like standards. If you don’t like this one, make up another one.

That being the case, what makes anyone think their naming system will displace all others for any significant period of time? Considering there has never been a successful one.

Oh, I forgot, if you don’t know any philosophy, one place this issue gets discussed, or the humanities in general, you won’t be exposed to the long history of language and naming discussions. And the failures recorded there.

I would urge CS types to read and study both philosophy and the humanities for purely pragmatic reasons. CS pioneers were able to write the first FORTRAN compiler not because they had taken a compiler MOOC but because they had studied mathematics, linguistics, language, philosophy, history, etc.

Are you a designer (CS pioneers were) or are you a mechanic?

PS: If you are seriously interested in naming issues, my first suggestion would be to read The Search for the Perfect Language by Umberto Eco. It’s not all that needs to be read in this area but it is easily accessible.

I first saw this in a tweet by Christopher Phipps.

Algebraic and Analytic Programming

Monday, March 10th, 2014

Algebraic and Analytic Programming by Luke Palmer.

In a short post Luke does a great job contrasting algebraic versus analytic approaches to programming.

In an even shorter summary, I would say the difference is “truth” versus “acceptable results.”

Oddly enough, that difference shows up in other areas as well.

The major ontology projects, including linked data, are pushing one and only one “truth.”

Versus other approaches, such as topic maps (at least in my view), that tend towards “acceptable results.”

I am not sure what other measure of success you would have other than “acceptable results?”

Or what another measure for a semantic technology would be other than “acceptable results?”

Whether the universal truth of the world folks admit it or not, they just have a different definition of “acceptable results.” Their “acceptable results” means their world view.

I appreciate the work they put into their offer but I have to decline. I already have a world view of my own.


I first saw this in a tweet by Computer Science.

Information organization and the philosophy of history

Tuesday, May 14th, 2013

Information organization and the philosophy of history by Ryan Shaw. (Shaw, R. (2013), Information organization and the philosophy of history. J. Am. Soc. Inf. Sci., 64: 1092–1103. doi: 10.1002/asi.22843)


The philosophy of history can help articulate problems relevant to information organization. One such problem is “aboutness”: How do texts relate to the world? In response to this problem, philosophers of history have developed theories of colligation describing how authors bind together phenomena under organizing concepts. Drawing on these ideas, I present a theory of subject analysis that avoids the problematic illusion of an independent “landscape” of subjects. This theory points to a broad vision of the future of information organization and some specific challenges to be met.

You are unlikely to find this article directly actionable in your next topic map project.

On the other hand, if you enjoy the challenge of thinking about how we think, you will find it a real treat.

Shaw writes:

Different interpretive judgments result in overlapping and potentially contradictory organizing principles. Organizing systems ought to make these overlappings evident and show the contours of differences in perspective that distinguish individual judgments. Far from providing a more “complete” view of a static landscape, organizing systems should multiply and juxtapose views. As Geoffrey Bowker (2005) has argued,

the goal of metadata standards should not be to produce a convergent unity. We need to open a discourse—where there is no effective discourse now—about the varying temporalities, spatialities and materialities that we might represent in our databases, with a view to designing for maximum flexibility and allowing as much as possible for an emergent polyphony and polychrony. (pp. 183–184)

The demand for polyphony and polychrony leads to a second challenge, which is to find ways to open the construction of organizing systems to wider participation. How might academics, librarians, teachers, public historians, curators, archivists, documentary editors, genealogists, and independent scholars all contribute to a shared infrastructure for linking and organizing historical discourse through conceptual models? If this challenge can be addressed, the next generation of organizing systems could provide the infrastructure for new kinds of collaborative scholarship and organizing practice.

Once upon a time, you could argue that physical limitations of cataloging systems meant that a single classification system (convergent unity) was necessary for systems to work at all.

But that was an artifact of the physical medium of the catalog.

The deepest irony of the digital age is continuation of the single classification system requirement, a requirement past its discard date.

On Philosophy, Science, and Data

Sunday, March 17th, 2013

On Philosophy, Science, and Data by Jim Harris.

From the post:

Ever since Melinda Thielbar helped me demystify data science on OCDQ Radio, I have been pondering my paraphrasing of an old idea: Science without philosophy is blind; Philosophy without science is empty; Data needs both science and philosophy.

“A philosopher’s job is to find out things about the world by thinking rather than observing,” the philosopher Bertrand Russell once said. One could say a scientist’s job is to find out things about the world by observing and experimenting. In fact, Russell observed that “the most essential characteristic of scientific technique is that it proceeds from experiment, not from tradition.”

Russell also said that “science is what we know, and philosophy is what we don’t know.” However, Stuart Firestein, in his book Ignorance: How It Drives Science, explained “there is no surer way to screw up an experiment than to be certain of its outcome.”

Although it seems it would make more sense for science to be driven by what we know, by facts, “working scientists,” according to Firestein, “don’t get bogged down in the factual swamp because they don’t care that much for facts. It’s not that they discount or ignore them, but rather that they don’t see them as an end in themselves. They don’t stop at the facts; they begin there, right beyond the facts, where the facts run out. Facts are selected for the questions they create, for the ignorance they point to.”

In this sense, philosophy and science work together to help us think about and experiment with what we do and don’t know.

Some might argue that while anyone can be a philosopher, being a scientist requires more rigorous training. A commonly stated requirement in the era of big data is to hire data scientists, but this begs the question: Is data science only for data scientists?

“Is data science only for data scientists?”

Let me answer that question with a story.

There is a book, originally published in 1965, called “How to Avoid Probate.” (Legal proceedings that may follow after death.) It claimed to tell “regular folks” how to avoid this difficulty and was marketed in a number of states.

Well, except that the laws concerning property, inheritance, etc., vary from state to state and even lawyers who don’t practice inheritance law in a state will send you to someone who does.

There were even rumors that the state bar associations were funding its publication.

If you think lawyers are expensive, try self-help. Your fees could easily double or triple, if not more.

The answer to: “Is data science only for data scientists?” depends on the result you want.

If you want a high quality, reliable results, then you need to spend money on hiring data scientists.

If you want input from the managers of the sixty percent (60%) of your projects that fail, you know who to call.

BTW, be able to articulate what “success” would look like from a data science project before hiring data scientists.

If you can’t, use your failing project managers.

There isn’t enough data science talent to do around and it should not be wasted.

PS: Those who argue anyone can be a philosopher get the sort of philosophy they deserve.

Working to change the world

Saturday, September 15th, 2012

Working to change the world by John D. Cook.

From the post:

I recently read that Google co-founder Sergey Brin asked an audience whether they are working to change the world. He said that for 99.9999% of humanity, the answer is no.

I really dislike that question. It invites arrogance. Say yes and you’re one in a million. You’re a better person than the vast majority of humanity.

Focusing on doing enormous good can make us feel justified in neglecting small acts of goodness. Many have professed a love for Humanity and shown contempt for individual humans. “I’m trying to end poverty, cure cancer, and make the world safe for democracy; I shouldn’t be held to same petty standards as those who are wasting their lives.”

I don’t disagree with John’s post but I would emphasize the unknowability of the outcome of our actions.

Relieves me of worrying about tomorrow and its judgement in favor of today and its tasks.

Data Management is Based on Philosophy, Not Science

Tuesday, May 1st, 2012

Data Management is Based on Philosophy, Not Science by Malcolm Chisholm.

From the post:

There’s a joke running around on Twitter that the definition of a data scientist is “a data analyst who lives in California.” I’m sure the good natured folks of the Golden State will not object to me bringing this up to make a point. The point is: Thinking purely in terms of marketing, which is a better title — data scientist or data philosopher?

My instincts tell me there is no contest. The term data scientist conjures up an image of a tense, driven individual, surrounded by complex technology in a laboratory somewhere, wrestling valuable secrets out of the strange substance called data. By contrast, the term data philosopher brings to mind a pipe-smoking elderly gentleman sitting in a winged chair in some dusty recess of academia where he occasionally engages in meaningless word games with like-minded individuals.

These stereotypes are obviously crude, but they are probably what would come into the minds of most executive managers. Yet how true are they? I submit that there is a strong case that data management is much more like applied philosophy than it is like applied science.

Applied philosophy. I like that!

You know where I am going to come out on this issue so I won’t belabor it.

Enjoy reading Malcolm’s post!