Addenda to My Conversation With Harold Channer

datePosted on 17 December 2014 by cjf

Harold Channer invited me to the studios of MNN (Manhattan Neighborhood Network) in New York City to record two one-hour editions of the TV program “Conversations with Harold Hudson Channer” on Tuesday the 25th of November, 2014. Since few things I write or speak come out fully baked, I thought I’d add a few additional thoughts to clarify, improve, or correct some of my comments. Since I value discussion, I sprinkled my remarks with many questions which I hope will elicit your feedback in the comments.

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I participated in the ReVIEWING Black Mountain College 4: Looking Forward at Buckminster Fuller’s Legacy conference on September 28-30, 2012 in Asheville, NC, USA. I gave two talks (click on the links below to see the PDF presentations):

  • Education Automation Now and in the Future. In this talk I recognize Buckminster Fuller as one of the conceptual founding fathers of the Open Educational Resources (OER) movement, detail six of his educational ideas, and give a brief review of several OER courses I’ve taken to indicate the kind of comprehensive education now possible using freely available on-line courses.
  • Synergetics and Model Thinking. In this talk I synthesize Scott E. Page’s Model Thinking with Buckminster Fuller’s Synergetics. I introduce both subjects, then discuss the importance of model thinking. Then I sketch some ideas about how Model Thinking and Synergetics can inform a more incisive approach to science.

Please share any thoughts you might have about these presentations in the comments. I would value your feedback.

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Models of Projective Geometry

datePosted on 24 July 2012 by cjf

For me the most enticing facet of projective geometry is the profound way in which it treats duality. Duality is the notion that certain fundamental distinctions have similar structure in their complementary forms. In comparing a form with its dual, the basic structure remains even though the roles of the forms reverse. Inside and outside. Convex and concave. Yin and yang. In 2D (two-dimensional) projective geometry, point is dual with line; in 3D point is dual with plane while lines are self-dual. The relationship of duality is so penetrating and pervasive in projective geometry, that we might consider it the geometry of fundamental duality. It provides a geometrical stage upon which duality can be studied in a pure form.

Another profound aspect of projective geometry is its elementary treatment of incidence where one considers the join (∨) and meet or intersection (∧) of two basic geometrical objects such as point, line, plane, and hyperplane. The most fundamental correspondence of geometrical forms associates points and lines in dual arrangement: the points on a line form a range and the lines through a point form a pencil. The correspondence between a pencil and a range is a basic projection. Next a perspective relation joins a pencil with two ranges or a range with two pencils; that is, by combining two elementary projections. Such a perspectivity maps points to points, or dually, lines to lines as shown in the figure. Point and Line Perspective

In the essay “Design Strategy” in Buckminster Fuller’s book Utopia or Oblivion, he includes projective geometry in his list of recommendations for a curriculum of design science. The connection between projective geometry and design thinking is an area that deserves more attention.

A Catalog of Models of Projective Geometry

The rest of this essay tersely describes a broad listing of some of the more basic models of projective geometry. Models are a powerful tool for learning and for understanding as explained in my essay about the Importance of Model Thinking (based on Scott E. Page’s course). The models included below should provide an introduction to and an overview of projective geometry for those new to the subject (Note: some of these models require background knowledge that is not explained here. They are indicated with a Orange Asterisk from http://www.fatcow.com/free-icons licensed under a Creative Commons Attribution 3.0 License. I encourage you to skim or skip such models, but to read on as later models may be more tractable.) I hope the experts will find the succinct summary and references useful. Although this list is fairly comprehensive, there are many models that are necessarily omitted. If you have a favorite model, please post a comment about it.

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The Importance of Model Thinking

datePosted on 14 June 2012 by cjf

Models can help us understand, predict, strategize, and re-design our worlds. This is the profound lesson from Scott E. Page’s engaging on-line Coursera offering on Model Thinking. I was particularly interested in this 10 week course because Buckminster Fuller instilled in me a deep appreciation for models. With this course, Scott Page reinforced and enhanced that appreciation in spades. Also, like Bucky, Page makes his penetrating approach accessible to a very broad audience. This is a great course for anyone with even rudimentary algebra skills.

In addition to reviewing the course, I will also suggest that model thinking is a new more incisive kind of science. This approach and its nascent toolkit for understanding, decision-making, prediction, strategy, and design is vitally important for practitioners of all types. Model thinking may be just the type of tool humanity needs to solve some of its thorniest problems. As such its arrival into broader consciousness is not a moment too soon!

So if you want to be out there helping to change the world in useful ways, it’s really really helpful to have some understanding of models.
— Scott E. Page

Why Model Thinking

There are many ways to model the world. One of the most popular is with proverbs or short pithy sayings (our modern media seem to particularly love this deeply flawed “sound bite” approach to knowledge). As Scott Page points out, there are opposite proverbs too. For instance, the opposite of “nothing ventured, nothing gained” is “better safe than sorry.” Proverbs and their more elaborate cousins, allegories, can model or represent the world with persuasive stories, but they provide little discerning power and little basis for deeper understanding. In contradistinction, model thinking with its greater concern for precision can help us more carefully distinguish a complex of important factors with their interrelationships and behaviors. Therein lies its power!

Is intuition sufficient? No! Philip Tetlock, Robyn Dawes and others have demonstrated that simple naive models outperform experts of all stripes. In 1979 Dawes wrote a seminal paper, The Robust Beauty of Improper Linear Models in Decision Making, which showed the effectiveness of even “improper” linear models in outperforming human prognostication. Tetlock has made the most ambitious and extensive study of experts to date and finds that crude extrapolation models outperform humans in every domain he has studied.

That is not to say that models are “right”. Page emphasizes that all models are “wrong” too! Which leads to his most profound insight in the course: you need many types of models to help think through the logic of any given situation. Each model can help check, validate, and build your understanding. This depth of understanding is essential to make better decisions or predictions or build more effective designs or develop more effective strategies to achieve your goals.

Is intuition important? Yes, absolutely! The many model thinker relies upon intuition to select and critically evaluate a battery of models or to construct new or modified models when appropriate. These models help test our intuition. Intuition helps tests the models! Writing out a model often identifies facets and elements of the situation which intuition misses. Intuition is essential to find the aspects of the models that are a bit off the mark — and all models are a bit off. Model thinking is not “flying on instruments” or turning control over to mathematical or computer models. Instead it is about evaluating and comparing diverse models to test, build, fortify, and correct our intuitions, decisions, predictions, designs, and strategies.

Fascinating Models

Page’s course is filled to the brim with fascinating models! One of the first models Page introduces is Thomas Schelling’s segregation model which represents people as agents on a checkerboard. We discover deep and unexpected insights about how people sort themselves into clusters where everyone looks alike, for example, the segregation of neighborhoods based on race, ethnicity, income, etc. It is the first of many agent-based models to be discussed.

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Dante’s Commedia, written in the early 1300s, is ostensibly an epic poem about a pilgrim who travels through Inferno (hell), Purgatorio (purgatory), and Paradiso (heaven) to encounter God face-to-face and then returns to tell us about it. More interestingly, it is a poem of learning, philosophy, and the struggles of life with more nuances, depth and perspectives than I would have thought possible had I not read it myself. To say that the Commedia is rich in a multidimensional way is an understatement. The Commedia is intricate, dramatic, thrilling, mind-blowing, cosmic, shocking, ineffable, sometimes oppressive, and altogether extraordinary!

Dante In Translation at Open Yale Courses in Giuseppe MazzottaThe pilgrim is Dante himself and his guide through most of the journey is the Roman poet Virgil. Open Yale Courses provides its own able guide in Giuseppe Mazzotta who presents a fascinating and deeply engaging course ITAL 310: Dante in Translation (videos at YouTube). Mazzotta places the Commedia, more commonly entitled The Divine Comedy, in the encyclopedic tradition (a circle of knowledge through the liberal arts) but he also calls it an epic, romantic, autobiographical, and visionary poem. Indeed by the end of the course, I had lost track of how many different angles on the poem Mazzotta had identified: prophetic, philosophical, historical, sublime, humanistic, theological, scientific, geometrical, musical, a poetry of hope, a poetry of the future, etc., etc.!

Dante makes large claims for poetry: poetry is a way of knowing.
— Giuseppe Mazzotta

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It may be that the presumed dichotomy between determinism and randomness is superficial and illusory. Determinism is the world view that events result from an unalterable causal chain. It models the world as a clock whose behavior can be inferred by scientific investigation. Stocasticity or randomness is the world view that uncertainty pervades experience. It models the world as a dice game with unpredictable behavior.

Many thinkers including Einstein, Buckminster Fuller, and D’Arcy Wentworth Thompson have argued in support of the traditional deterministic world view[1]. However, Quantum mechanics, machine learning, and behavioral economics are three prominent areas which have helped realign modern thinking to apprehend that randomness and uncertainty may be fundamental and pervasive. Leonard Mlodinow in a 2008 book goes further and argues that randomness rules our lives.

In preparing for and discussing randomness at a recent meetup of the Ben Franklin Thinking Society, I started to gravitate to the hypothesis that uncertainty and determinism may be like inside and outside or concave and convex. They may be both real, both partially right and partially wrong, both revelatory and misleading. It may be that each perspective is a “tuning in” to only part of a reality that is both-neither[2].

The principle of functions states that a function can always and only coexist with another function as demonstrated experimentally in all systems as the outside-inside, convex-concave, clockwise-counterclockwise, tension-compression couples.

— R. Buckminster Fuller, Synergetics 226.01

Here are several ways to see the dual and co-occurant qualities of the stochastic and deterministic models or world views.

In a deterministic model of the world, the fixed set of laws that govern everything apply to every quanta of energy or their constituents. So computing the state of the world requires applying these fixed laws to each such quanta from some initial state and iterating through each picosecond of time. Clearly, this is computationally infeasible except for the computer known as Universe itself. So any effective simulation or calculation will entail estimates and approximations, that is, randomness. Unwittingly, randomness imposes itself into the system!

Conversely, in a stochastic model the relationships between data are given by frequencies with respect to their sample space, the set of possible outcomes. What could be more deterministic than the elementary counting of frequencies? Indeed probability is basically a form of advanced counting in ratios. Deterministic indeed!

Now consider measurement. The basis of a scientific model involves measurable parameters. Data are measurements. Science has determined that all measurements involve uncertainty. MIT physicist Walter Lewin puts it emphatically: “any measurement that you make without any knowledge of the uncertainty is meaningless!” Measurement theory is built upon the law of error which is a principle of the science of randomness. Hard data acquires its validity and persuasiveness from the science of chance!

The key to understanding measurement is understanding the nature of the variation in data caused by random error.
Leonard Mlodinow

On the other hand, the law of error is a central principle in statistics, the science of inferring probabilities from observed data. Such inference is the gold standard of scientific truth. The techniques of scientific inference are based on the mathematics of randomness. Like all mathematics, the theory is definite, rigorous, and repeatably verified by logic, proof and experiment. The sciences of probability and statistics are rigorous and deterministic like all mathematics!

Even in a fundamentally deterministic world, our understanding, decision-making, strategies, predictions, measurements, and designs are predicated upon uncertainty and randomness. To be effective we must be cognizant of these lingering unavoidable uncertainties.

Conversely, even in a fundamentally uncertain world ruled by randomness, pattern and order emerge and can be identified. To be effective we can and should seek the design and structure permeating through the apparent randomness.

From these considerations, I conclude that randomness and determinism always and only coexist. They are inseparable. Each provides a spectacular, incisive perspective on reality. The careful thinker or practitioner should be facile in using both types of models to get a more wholistic, more complete picture of the world in which we find ourselves. This is evidence that both-neither should be our guiding principle in seeking truth!

Do you find the argument compelling? Is it sound? Can you help me improve it? Do you see other ways in which these two models interpenetrate and interaccommodate? How do you see the interrelationship between determinism and randomness?

To better develop my understanding of a more complete set of models (beyond superficial determinism vs. stochasticity), I am excited about Scott E. Page‘s new and just started on-line video course on Model Thinking. I think we need many diverse models to sharpen our thinking and uncover subtleties in the complex systems and theories upon which our civilization is built. I am looking forward to wrapping my head around the 21 or so models in this course. You can register for the Model Thinking course by filling out the form at http://www.modelthinker-class.org/.

So if you want to be out there helping to change the world in useful ways, it’s really really helpful to have some understanding of models.
— Scott E. Page

Finally, here are three good audio-visual resources that explore issues of randomness further:


[1] Click here to read my previous essay on randomness where arguments for determinism are discussed.
[2] Credit to Tom Miller for the wonderful expression both-neither.

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The Pickwickian Sentiment

datePosted on 24 January 2012 by cjf

The Pickwick PapersI tuned in to the Pickwickian sentiment some 30 years ago when I first read Charles Dickens’ inaugural novel The Pickwick Papers. Thanks to the impetus of The Free Library of Philadelphia’s celebration of the 200th anniversary of Dickens’ birth, I’ve re-read it and had the chance to think through its meaning more carefully. It seems to me that Pickwickian refers to the quality of certain expeditions, slice of life adventures or ordinary events which entail the strife and mettle incumbent upon most trials and tribulations which with good-heartedness, good-humour, patience, nurturing and some surprise tend to bring forth general benevolence and joy. It is a great sentiment which we could use more of in this world!

It seems to me this Pickwickian sentiment is the thread that holds together the plot of The Posthumous Papers of the Pickwick Club, the title in the original publication. The sentiment emerges explicitly with Mr. Bolton’s clamour in chapter 1 and continues with the cab driver in chapter 2 who assaults Pickwick for taking notes on their conversation. Throughout there are countless incidents of turmoil and challenge which after at least some modicum of sound and fury end with wholesome benevolence and good will.

In the big picture of the novel, it is Pickwick’s relationship with Nathaniel Winkle which exhibits Pickwickianism in its most dramatically nurturing and good-hearted sense. It is Winkle, the sportsman, whose careless shooting wounds fellow Pickwickian, Tracey Tupman. Winkle’s disastrous outing on ice skates results in Pickwick’s scathing admonition “[You're a] humbug, sir. I will speak plainer, if you wish it. An impostor, sir.” Then at Pickwick’s trial, it is Winkle who volunteers the “one instance of suspicious behavior towards females” which helps the jury decide against our good natured and innocent protagonist.

Through all these ills borne of Winkle’s youthful ineptness, our eponymous leader embodies Pickwickian good spirit and supports his protégé. He intervenes after the unfortunate incident with the Dowlers in Bath which sends Winkle in flight. The dénouement of the novel is Pickwick’s difficult mission to reconcile Winkle with his father. I was struck at Pickwick’s remarkable devotion to Winkle and how that relationship exudes the Pickwickian sentiment through and through. Is this the plot that GK Chesterton missed in critiquing the novel?

These good-hearted and good-humoured adventures in the large as well as the innumerable little scenes throughout the novel reinforce my view that the plot of The Pickwick Papers is a tale of adventure showcasing the Pickwickian sentiment which through numerous fun and funny tribulations end with good-humour, pride and exultation. A comedy indeed!

It may be that my exalted view of Pickwick is unjustified. For a more conventional perspective see Edward Pettit‘s write-up Dickens Literary Salon: Pickwick Papers with its sundry references.

How would you characterize “Pickwickian”? Does “the Pickwickian sentiment” constitute a plot?

Pickwick and Bucky

When I discovered Buckminster Fuller it was his benevolence (“the planet’s friendly genius”) that attracted me. Could my enchantment with Pickwick have led me to another humanist like Bucky? I do not know. But both the great character and the great thinker share Pickwickian qualities. The one that seems most striking is Bucky’s Mistake Mystique — Pickwickian indeed!

Do you see connections between Bucky and Pickwick?

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Since databases are a fundamental component of modern information systems, understanding at least their basics is essential knowledge for almost all citizens. Please read my review of Stanford’s excellent free on-line course Introduction to Databases which is posted on the blog Managing FOSS for Business Results at http://blog.remoteresponder.net/2012/01/19/learn-open-source-database-tools-from-stanford-for-free.

Please let me know what you think of it.

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In a poignant lecture on The Logic of Science (412 MB QuickTime video download; 6800 word transcript), Stephen Stearns provides some of the most practical results from the philosophy of science possible in an introductory 45 minute lecture. Together with reading T. C. Chamberlin‘s essay The Method of Multiple Working Hypotheses, watching Kevin Kelly’s lecture The Next 100 Years of Science: Long-term Trends in the Scientific Method (video at fora.tv) and participating in a recent discussion on On the Nature, Being, and Logic of Science at The Ben Franklin Thinking Society, I’m inspired to formulate and share some of my thoughts about the ever-changing “ways of knowing” that we call science. Even more so because the 2011 Design Science Symposium that I am helping to organize will try to broach the subject of the science in Buckminster Fuller’s Synergetics.

Perhaps, the most intriguing thing I learned from the Stearns lecture was the importance of the method of multiple working hypotheses. I decided to read the source, a 1965 reprint of T. C. Chamberlin’s classic 1890 essay “The Method of Multiple Working Hypotheses” (here is a printable PDF). I was hit by the insidiousness of the bias inherent in the hypothetico-deductive model of science which unfortunately is still taught as dogma in many science classes today. I was shocked to realize how counterproductive it can be to focus on developing and testing a simple working hypothesis, a style of thinking that I have frequently used and must now grow beyond!

Chamberlin convinced me that in science and in life we must challenge ourselves to imagine a comprehensive array of possible explanations (hypotheses). Only in this way can we get sufficient perspective to clearly see the kind of questions, observations and experiments that might tease out Truth from the inherent complexity of Universe. Wow, isn’t that the essence of Buckminster Fuller’s Synergetics: comprehensive thinking?

[In practicing the method of multiple working hypotheses] the mind appears to become possessed of the power of simultaneous vision from different standpoints. Phenomena appear to become capable of being viewed analytically and synthetically at once. — T. C. Chamberlin, 1890

My next step on the ladder to understanding scientific knowledge was Kevin Kelly’s fascinating 02006 talk on Long-term Trends in the Scientific Method (video). Kelly suggests that science is driven by applying knowledge to itself recursively or self-similarly. Kelly included a timeline which I have modified to give a slice through some milestones in the history of scientific ways of knowing:

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EEB 122:  Principles of Evolution, Ecology, and BehaviorEach of us is connected through our parents and their parents and so forth to a first life form which has no parent and is composed and derived from non-biological forms. So each of us is intimately connected through our genealogical history to the non-biological Universe! Indeed, each of us is connected in this way to the whole Universe!!! It is this type of conceptual, big picture thinking that pervades Stephen Stearns’ free video course EEB 122: Principles of Evolution, Ecology, and Behavior at Open Yale Courses (OYC). Even though I do not think the separation between life and non-life is as clearcut as Stearns suggests, Jeannie and I thoroughly enjoyed our excursion into Biology with Stephen Stearns as our guide at OYC!

The Importance of Biology, Evolution, Ecology, and Behavior

Understanding biology is essential as civilization is inseparable from the great ecosystems upon which it is built and in which it is housed. Our future is inextricably linked to the always changing nature of the Earth-Biosphere system which provides our food and shelter. In EEB 122, we learned that the entire Earth has been sculpted by the biological technology we call “life“. At a more day-to-day human scale, medicine and health care are vital subjects in biology and in our economy (caring for the health of the ecosystem of cells, organs and their microscopic cohabitators known as “human” engages 9% of the economies in most OECD countries and nearly twice that in the USA). EEB 122 has a whole lecture devoted to medicine and more comments throughout the course.

Evolution theory has had a profound influence on modern thinking. From its nascent formulation by Charles Darwin, the theory of evolution has itself changed (evolved!) substantially over its first 150 years. I found it particularly interesting to learn that the modern theory is quite different from what my culture-imbued intuitions misled me to think. This course is eye-opening! Even if you disagree with some of the ideas of evolution (and who doesn’t have some questions and concerns about this subtle subject which is itself changing), this course corrects some of our endemic misperceptions. For example, Stearns asserts in lecture 3 that the notion of “survival of the fittest” is wrong! I had no idea that that iconic “sound bite” is but a dead-end on the road to the modern theory of evolution!

It’s not ignorance does so much damage; it’s knowing so darned much that ain’t so. — Josh Billings

With current concerns about global warming and other stresses on our environment, ecology is a vitally important subject. The point is reinforced by the work of three of the recent winners of the Buckminster Fuller Challenge which deeply engages the subject of ecology. The 2011 winner, Blue Ventures, conserves threatened marine environments. The 2010 winner, Project Hope, restores savannas and grasslands lost to desertification with a comprehensive program featuring cattle management. The 2008 winner, John Todd’s Comprehensive Design for a Carbon Neutral World, restores the ecological devastation of the impact of mining in Appalachia. The principles of biology and ecology are essential to better understand and contribute to these and similar initiatives to improve our management of Earth’s ecosystems while raising the standard of living of every human being. EEB 122 explains some of the vital principles that will underpin any such solution.

In summary, OYC’s EEB 122 is an excellent introduction to the basic principles of biology needed to better understand medicine, health care, evolution theory, ecology, the behavior of organisms, and biological technologies such as the enterprising work of the Buckminster Fuller Challenge winners. Finally, and perhaps most importantly, EEB 122 gives a conceptually broad, biologically detailed introduction to one of the most enchanting visions of change ever developed: the theory of the evolution of species.

How We Used the EEB 122 Course Materials

Jeannie and I started watching EEB 122 around New Year’s. We watch courses like this for edutainment. That is, we do not plan to become professional biologists, instead we watch video courses as a form cultural enrichment: How do biologists think? What do they know? What is the current understanding of evolution? I am deeply curious about how the world works. Video courses like EEB 122 are deeply enriching in this regard.

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Sugar is a chronic toxin

datePosted on 21 July 2011 by cjf

After some 30 years of waning, my interest in the assertion that the effects of sugar are poisonous was rekindled in April by reading a piece entitled “Is Sugar Toxic?” by Gary Taubes in the New York Times. When Taubes wrote admiringly of John Yudkin (1910–1995) (whose short 1972 book “Sweet and Dangerous” profoundly influenced me when I read it in the early 80s), the effect was electrifying: maybe he was right … vindicated after all these years! To sober myself up, I began researching our current understanding of the biochemistry and physiology of sugar metabolism. My research supported an interesting three hour discussion at the 10 July 2011 meetup of the Ben Franklin Thinking Society in Philadelphia.

Although the case against sugar is stronger now than it was in the 1970s, there is still no ironclad proof of its toxicity (more on that below). Sentiment against sweeteners with fructose in them (table sugar is one-half fructose) is growing because it has been implicated in several biochemical pathways associated with the so called metabolic syndrome. Metabolic syndrome is a complex of several (usually at least three) of the following factors: abnormal blood fat, high blood pressure, fatty liver, insulin resistance, and new fat deposition. Metabolic syndrome is very important because physicians now realize it is a more accurate predictor for diabetes, heart disease and cancer than any of the symptoms considered separately. The impact of this new perspective and the research that has ensued is starting to challenge conventional wisdom about the dietary factors involved in these diseases.

Taubes’ New York Times article starts by referring to the powerful, “viral”, 90-minute, YouTube video presentation by Dr. Robert Lustig indicting sugar. Lustig and Taubes convincingly lay out the case that fructose is a chronic toxin that causes metabolic syndrome. Therefore, it should be implicated as a causal factor in the obesity, diabetes, and cardiovascular disease pandemics. Taubes ends his article ominously by quoting prominent oncologists (cancer physicians) worrying that cancer could be caused in part by fructose & sugar as well (a claim Lustig did not make).

The Robert Lustig Video: Sugar: The Bitter Truth

Dr. Robert Lustig argues that the “fat is bad craze” has failed us: we reduced our fat intake, but the obesity and diabetes epidemics grew much more intense in the 1990s and 2000s. He observes that the fastest growing epidemic in obesity is among six month old babies! So the disparaging view that gluttony and sloth are the key factors in obesity appears absurd: babies don’t choose gluttony nor sloth — indeed, no one does! Could excess fat be a physiological problem and not a simple issue of “won’t power” (a phrase my grandfather used)? Perhaps our conventional wisdom is wrong? Lustig argues convincingly that a calorie is NOT just a calorie: some have worse physiological effects than others.

Lustig’s main thesis is that fructose acts in the body as a chronic toxin of the liver very much like alcohol. He observes that fructose is implicated in eight of the 12 chronic symptoms attributed to ethanol: high blood pressure, heart attack, abnormal blood fat, inflamation of the pancreas, obesity, liver dysfunction, insulin resistance, and habituation. In his not too difficult (but also not too easy) biochemistry lesson, Lustig points out that fructose and alcohol metabolism are nearly identical. Both hit the liver hard and both share many similar metabolic pathways. He concludes that “hepatic [liver-based] fructose metabolism leads to all of the manifestations of metabolic syndrome”.

John Yudkin’s Book “Sweet and Dangerous”

John Yudkin's 1972 book Sweet and Dangerous

John Yudkin was a distinguished nutritionist and MD. He performed experimental studies and analyses of epidemiological data. As early as the 1960s, he concluded that sugar has no nutritional value beyond its calories and that if its effects were present in any other substance, it would be banned. This led to a heated debate with another distinguished nutritionist Ancel Keys who first proposed the link between dietary fat and heart disease. In his famous Seven Countries Study, Keys concluded that increased cholesterol and the western diet with its heavy load of saturated fats led to increases in heart disease and stroke. Keys effectively started the fat is bad craze that led to the US government’s recommendation that we reduce fat consumption from 40% to 30% of calories. Lustig argues that Keys may have done his statistical analysis incorrectly. Could the last 30 years of nutritional guidance be based on a statistics mistake?

On re-reading Yudkin’s book, I was impressed by his penetrating discussion of the techniques to prove causes of disease (a subject known as etiology). Yudkin observes that “absolute” proof requires pairing subjects into two groups who are as alike as possible with the exception of an experimental intervention. This “gold standard” in medical research is known as a clinical trial. Yudkin explains that the ethical and practical complications of such studies are enormous. Therefore, most nutritional and medical data comes from less reliable and more circumstantial evidence. Yudkin explains in basic terms the nature of epidemiological and experimental evidence and its limitations. Yudkin’s book is a great non-technical introduction to medical research.

I wish that more non-technical nutrition and health writing would advise us of the complications in applying insights from new medical research given the inherent limitations especially since so few of us understand reasoning with uncertainty. Health sciences writers would do well to “take a page” from Yudkin’s book.

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Society and Our Technology Built World

datePosted on 2 June 2011 by cjf

The interrelationships between society and technology run deep. We all partake and participate in the unfolding technology evolution “discussion” Invention by Design by Henry Petroski that is our lives. The tools we use, try out, improvise, critique, and/or advocate are our minimal contributions to this discussion. The accidents of technological history set the context for the discussion. We are all technologists entangled in a technological world! Technology has been the main (perhaps the only?) means by which human progress has been achieved with tools like the pencil, slide fastener (or zipper), jet airplane, water systems, skyscrapers, bridges, and computers all dramatically changing society. Henry Petroski’s great short book “Invention by Design: How Engineers Get from Thought to Thing” explores the design and engineering arts in the full richness of their social context in nine intriguing case studies.

I first read Invention by Design in February 1999. Recently I was re-reading it when Michael Tweed of the The Ben Franklin Thinking Society invited me to lead the group’s Science & Technology meetup every month. That led to the Discussion: Engineering Failures & Society on 8 May 2011. Here are some thoughts reflecting on Petroski’s book, the 8 May meetup, and further cogitating about the big picture of society and technology. Hopefully these notes and your feedback will help us better understand the technological world at the core of our ever changing civilization.

What is Technology?

Technology is the catch-all term used to describe objects and the networks, systems, and infrastructures in which they are embedded, as well as the patterns of use that we impose upon them and they upon us. Technology is clearly context-dependent and ever evolving. — Henry Petroski

Petroski’s definition suggests that civilization itself may be technology. So it would seem that technology embraces culture, values, psychology, history, and the multidimensional elements of the environment (materials science, biology, anthropology, geophysics, chemistry, etc.). Buckminster Fuller goes further:

In its complexities of design integrity, the Universe is technology. The technology evolved by man is thus far amateurish compared to the elegance of nonhumanly contrived regeneration. Man does not spontaneously recognize technology other than his own, so he speaks of the rest as something he ignorantly calls nature. — Buckminster Fuller, Synergetics, 172.00-173.00

By taking Petroski’s “networks, systems, and infrastructures” to the next level of “design integrities” and identifying it as technology, Bucky leads us to the biggest of big pictures: Universe itself! As social creatures we often think of society as the big picture. I think his point is well made: technology is an inhernet component of Universe itself. Human society is our storied Earth-developed technology. It seems likely that Human society will become the “brain” managing the regenerative ecological functions of Gaia, the theory that Earth is “alive”. If that happens, the storied technology of Earth would probably become even more syntropic and powerful than what life has achieved thus far. Regardless, society and the technology with which it is built are inextricably intertwined!

Design and Engineering in Society

Design and engineering are the arts of consciously working to evolve and develop our technological infrastructure to improve our worlds. Petroski emphasizes the role of society in the engineering process and vice versa in these illuminating quotes:

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