Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed summarizes the key dangers of centrally managed social engineering projects. Its a bit dense, but well worth it. It shows similarities between many seemingly different disasters caused by top-down control and central planning. Case studies include modernist architecture, Soviet collectivization, herding or rural people into villages in Africa,and early errors in scientific agriculture, etc.
Anyone trying to build and manage an organization needs to be aware of the lessons in this book.
One key lesson is that practical knowledge, informal processes, and improvisation in the face of unpredictability are indispensable.
Formal scheme was parasitic on informal processes that alone, it could not create or maintain. The the degree that the formal scheme made no allowance for those processes or actually suppressed them, it failed both its intended beneficiaries and ultimately its designers as well. “
Radically simplified designs for social organization seem to court the same risks of failure courted by radically simplified designs for natural environments.
It makes the case for resilience of both social and natural diversity, and a strong case for limits about what can be known about complex social order. Avoid reductive social science.
Four elements of centrally planned disasters
According to the book, there four elements necessary for a full fledged disaster to be caused by state initiated social engineering.
- Administrative ordering of nature and society
- “High Modernist Ideology” a faith that borrowed the legitimacy of science and technology. Uncritical unskeptical public and therefore unscientific optimism about possibilities for comprehensive planning of human settlement and production. Often with aesthetic terms too.
- Authoritarian state willing to use the full weight of its coercive power for #2
- Prostrate civil society lacking capacity to resist these plans.
“By themselves they are unremarkable tools of modern statecraft; they are as vital to the maintenance of our welfare and freedom as they are to the designs of a would be modern despot. They undergird the concept of citizenship and the provision of social welfare just as they might undergird a policy of rounding up undesirable minorities.”
The discussion of the ecological disasters caused by forestry regulation in 18th and 19th century Germany is instructive:
The metaphorical value of this brief account of scientific production forestry is that it illustrates the dangers of dismembering an exceptionally complex and poorly understood set of relations and processes in order to isolate a single element of instrumental value. The instrument, the knife, that carved out the new, rudimentary forest was the razor sharp interest in the production of a single commodity. Everything that interfered with the efficient production of the key commodity was implacably eliminated. Everything that seemed unrelated to efficient production was ignored. Having come to see the forest as a commodity, scientific forestry set about refashioning it as a commodity machine. Utilitarian simplification in the forest was an effective way of maximizing wood production in the short and intermediate term. Ultimately, however, its emphasis on yield and paper profits, its relatively short time horizon, and , above all, the vast array of consequences it had resoloutley bracketed came back to haunt it.
Department of unintended consequences
I like to joke about wanting to start a department of unintended consequences to oversee economic policy. Often central planners fail because they arrograntly fail to foresee unintended consequences of their policies.
“ the door and window tax established in France under the directory and abolished only in 1917 is a striking case in point. Its originator must have reasoned that the number of windows and doors in a dwelling was proportional to the dwelling a size. Thus a tax assessor need not enter the house or measure it but merely count the doors and windows. As a simple, workable formula, it was a brilliant stroke, but it was not without consequences. Peasant dwellings were subsequently designed or renovated with the formula in mind so as to have as few openings as possible. While the fiscal losses could be recouped by raising the tax per opening, the long-term effects on the health of the rural population lasted for more than a century. “
See also: Goodhart’s Law
To: Democrats, Republicans
CC: Anarchists, Communists, Independents
Re: Department of Unintended Consequences
I don’t talk politics around here much but…
One thing the government needs is a “Department of Unintended Consequences” , or Unintended Consequences Ministry. This department will be in charge of analyzing the potential unintended consequence of any proposed policy put forth by any government department. I suggest that it hire the best computer engineers to help build simulations using the most advanced AI /game techniques. Perhaps this Unintended Consequences Ministry will help the broader government avert misguided actions, avoid long term consequences, and identify prudent courses of action.
This critical department will start it out with a small budget. But funds are tight, so other departments may have to make a few small cuts.
This department may rise in importance to be come a fourth component of the balance of power in the American system. I volunteer to be head of this department, and will accept a market compensation package.
Paul C Wonk
How can one maximize mental performance? The Organized Mind- Thinking Straight in an Age of Information Overload by Daniel Levitin is a book that works towards an answer to this question. The book’s ideas on offloading things to external systems and organizational techniques are very similar to David Allen’s , Getting Things Done . However, The Organized Mind, provides much more historical and scientific background an context. Further, An Organized Mind avoids being overly prescriptive, and instead gives the reader ideas on how to best optimize for their own situation.
Some of my highlights on the key themes of the book:
Getting the mind into the right mode
One useful framework that the books develops is hte idea of the mind as functioning in different modes. An important component of high performance is the ability to use the right mode at the right time.
There are four components in the human attention system: the mind-wandering mode, the central executive mode, the attention filter, and the attention switch, which directs neural and metabolic resources among the mind-wandering, stay-on-task, or vigilance modes.
Remember that the mind-wandering mode and the central executive work in opposition and are mutually exclusive states; they’re like the little devil and angel standing on opposite shoulders, each trying to tempt you. While you’re working on one project, the mind-wandering devil starts thinking of all the other things going on in your life and tries to distract you. Such is the power of this task-negative network that those thoughts will churn around in your brain until you deal with them somehow. Writing them down gets them out of your head, clearing your brain of the clutter that is interfering with being able to focus on what you want to focus on. As Allen notes, “Your mind will remind you of all kinds of things when you can do.
The task-negative or mind-wandering mode is responsible for generating much useful information, but so much of it comes at the wrong time.
Creativity involves the skillful integration of this time-stopping daydreaming mode and the time-monitoring central executive mode.
Insights into how human memory works
The book delineates the nuances of human memory by comparing it to systems in the physical world.
Being able to access any memory regardless of where it is stored is what computer scientists call random access. DVDs and hard drives work this way; videotapes do not. You can jump to any spot in a movie on a DVD or hard drive by “pointing” at it. But to get to a particular point in a videotape, you need to go through every previous point first (sequential access). Our ability to randomly access our memory from multiple cues is especially powerful. Computer scientists call it relational memory. You may have heard of relational databases— that’s effectively what human memory is.
Having relational memory means that if I want to get you to think of a fire truck, I can induce the memory in many different ways. I might make the sound of a siren, or give you a verbal description (“ a large red truck with ladders on the side that typically responds to a certain kind of emergency”).
This feature can lead to either valuable insights or being overwhelmed, depending on how it is controlled:
If you are trying to retrieve a particular memory, the flood of activations can cause competition among different nodes, leaving you with a traffic jam of neural nodes trying to get through to consciousness, and you end up with nothing.
Categorization is key to mental functioning.
This ability to recognize diversity and organize it into categories is a biological reality that is absolutely essential to the organized human mind.”
Shift burdens to external systems
You might say categorizing and externalizing our memory enables us to balance the yin of our wandering thoughts with the yang of our focused execution.
A lot of time and money is wasted on unnecessary corporate meetings. Since the early days of Amazon , Jeff Bezos has taken a unique approach to meetings.
At a management offsite in the late 1990s, a team of well-intentioned junior executives stood up before top brass and gave a presentation on a problem indigenous to all large organizations: the difficulty of coordinating far-flung divisions. The junior executives recommended a variety of different techniques to foster cross group dialogue and afterward seemed proud of their own ingenuity. Then Jeff Bezos, his face red, and the blood vessel in his forehead pulsating, spoke up.
“I understand what you are saying, but you are completely wrong,” he said.
“Communication is a sign of dysfunction. It means people aren’t working together in a close, organic way. We should be trying to figure out a way for teams to communicate less with each other, not more.”
…At that meeting and in public speeches afterward, vowed to run Amazon with an emphasis on decentralization and independent decision-making. “A hierarchy isn’t responsive enough to change,” he said. “I’m still trying to get people to do occasionally what I ask. And if I was successful, maybe we wouldn’t have the right kind of company.
Bezos’s counter intuitive point was that coordination among employees wasted time, and that the people closest to problems were usually in the best position to solve them. That would come to represent something akin to the conventional wisdom in the high-tech industry over the next decade. The companies that embraced this philosophy, like Google, Amazon, and, later, Facebook, were in part drawing lessons from theories about lean and agile software development. In the seminal high-tech book The Mythical Man-Month, IBM veteran and computer science professor Frederick Brooks argued that adding manpower to complex software projects actually delayed progress. One reason was that the time and money spent on communication increased in proportion to the number of people on a project.
When you do have a meeting, make it useful
Of course, some meetings are necessary. There is value to cross-pollination of thoughts among intelligent people. Some processes do require explicit coordination and discussion. However, in practice, many hours are wasted on routine updates, grandstanding, and “thinking out loud”. To ensure meetings were productive Bezos required the person who leads a meeting to write detailed prose explaining their thoughts. The first half hour or so of every meeting would be silent reading time. This ensured everyone thought deeply and expressed complete thoughts cogently.
Meetings no longer started with someone standing up and commanding the floor as they had previously at Amazon and everywhere else throughout the corporate land. Instead, the narratives were passed out and everyone sat quietly reading the document for fifteen minutes—or longer. At the beginning, there was no page limit, an omission that Diego Piacentini recalled as “painful” and that led to several weeks of employees churning out papers as long as sixty pages. Quickly there was a supplemental decree: a six-page limit on narratives, with additional room for footnotes.
Louis L’amour was an autodidact’s autodidact. John Wayne called him the most interesting man in the world. L’amour spent the first couple decades of his adulthood wandering across the country, and around the world, doing odd jobs, and obsessively reading whatever he could find. Only much later did he become a famous novelist. Education of a Wandering Man is a quasi-autobiography, in which he describes the trajectory of his life, and the evolution of his thinking in terms of the places he traveled and the books he read.
L’amour spent years as a hobo, hopping trains from town to town, working various jobs. In each town he would visit the local library.
Its important to note, that unlike a bum, a hobo is ready and willing to work.
To properly understand the situation in America before the Depression, one must realize there was great demand for seasonal labor, and much of this was supplied by men called hoboes.
Over the years the terms applied to wanderers have been confused until all meaning has been lost. To begin with, a bum was a local man who did not want to work. A tramp was a wanderer of the same kind, but a hobo was a wandering worker and essential to the nation’s economy.
…Many hoboes would start working the harvest in Texas, and follow the ripening grain north through Oklahoma, Kansas, and Nebraska into the Dakotas. During harvest season ,when the demand for farm labor was great, the freight trains permitted the hoboes to ride, as the railroads were to ship the harvested grain, and it was in their interest to see that labor was provided.”
He also worked on merchant ships, and traveled throughout Asia and most of the world. He would find books for free or cheap wherever he went, reading 100+ books per year. For example:
Byron’s Don Juan I read on an Arab dhow sailing north from Aden up the Red Sea to Port Tewfik on the Suez Canal. Boswell’s The Life of Samuel Johnson (Penguin Classics) I read while broke and on the beach in San Pedro. In Singapore, I came upon a copy of Annals and Antiquities of Rajasthan, Vol. 1 of 3: Or the Central and Western Rajput States of India (Classic Reprint) by James Tod.
Although he didn’t have real formal degrees, L’amour understood the value of books and knowledge:
Books are precious things, but more than that, they are the strong backbone of civilization. They are the thread upon which it all hangs, and they can save us when all else is lost.
…Knowledge is like money: To be of value it must circulate, and in circulating it can increase in quantity and hopefully, in value. “
He wrote 89 novels, and clearly a lot of ideas came from paying close attention when he travelled:
People are forever asking me where I get my ideas, but one has only to listen, to look, and to live with awareness. As I have said in several of my stories, all men look, but so few can see. It is all there, waiting for any passerby.”
… for a writer, everything is grist for the mill, and a writer cannot know too much. Sooner or later everything he does know will find its uses.
As with reading, L’amour never let the challenges of a transient lifestyle interfere with writing:
“I began my writing in ship’s fo’c’sles, bunkhouses, hotel rooms- wherever I could sit down with a pen and something to write on.”
L’amour also spent time boxing in various small towns, and coaching other fighters. I’ve seen reference online to a 51-8 professional record, although I wasn’t able to verify it.
In the later years of his life L’amour spent more time in his personal library. His deep knowledge of the world gave him perspective:
Surely, the citizens and the rulers of Babylon and Rome did not see themselves as a passing phase. Each in its time believed it was the end-all of the world’s progression. I have no such feeling. Each age is a day that is dying, each one a dream that is fading.
Backgammon: the cruelest game provides a guide to some key principles of backgammon, and contains analysis of several games between top players. It also gets philosophical about the vicissitudes of randomness that make backgammon so challenging and intriguing:
From the start there is a complicated interplay of possibilities, probabilities, good fortune and bad, which influences every facet of the game. in backgammon, to seek position is to take certain calculated risks, and because all players are ruled by the dictates of the dice- or by chance, which Karl von Clausewitz, the ninetheenth-century military theorist, described as “an agency indifferent to the actor’s preference for the outcomes” – no player is ever in control of his particular destiny. One of the game’s chief tactics, then, is to shield oneself against the dice. The player with the strongest position can withstand the greater number of unfavorable rolls, or “bad luck,” than can the more weakly protected player, who, because he failed to protect himself, is more easily assaulted and overrun.
Nonetheless, no matter how cunningly you play, you are virtually always vulnerable. One unexpected horror roll can undermine the best positions, and derange the most sensible of plans; this is bot hthe charm and the frustration of the game. The best players know they must employ the craftiest of tactics, not because of the dice, but in spite of them. It is the enormously high luck factor in backgammon that causees it to be a game of skill. Without luck or accident, the game would not only be monotonous, but infinitely less skillfull.
In backgammon, to be skillful is to be self protective. At any given point in the ggame, the better players are aware of Murphy’s Law, which states that if anything can go wrong, it will.” Given the whimsical nature of the dice, all players have a chance in the game, but some players have more chances than others, because they have created in environment in which the more propirious is more likely to occur.
In backgammon, an understanding of the correct percentage moves in specific situations qualifies as “inside information” and will enable you to win in the long run. But not every time, alas, and often nt even in what you believe to be crucial games. This condition must be accepted philosophically, of course, and should not deter you from continuing a detailed study of the game.
Learning to think probabilistically is one of the most critical skills one can master. Nate Silver’s The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t is a valuable book on thinking probabilistically and forecasting in an uncertain environment. It compares and contrasts examples across multiple disciplines, including weather forecasting, seismology, finance, and more.
This book pairs well with Against the Gods, Fortune’s Formula and Superforecasting. Against the Gods is in my opinion, the most important book on the development of probabilistic thinking. Early civilizations were good with geometry and logic, but helpless with uncertainty. Ironically it was gamblers and heretics who moved mankind forward by developing the science of probability, statistics, and ultimately risk management. Fortune’s Formula shows the connection between information theory, gambling, and correct position sizing for investors. It helps the answer the question: when you have a slight edge, how much should you bet? Nate Silver draws heavily on Superforecasting. Particularly important is the idea of “foxes and hedgehogs”. Foxes are multidisciplinary, adaptable, self critical , tolerant of complexity, cautious and empirical. In contrast, Hedgehogs are specialized, stalwart, stubborn, order-seeking, confident, and ideological. As you might expect, foxes make far better forecasters than hedgehogs, even though hedgehogs make for better television.
Anyways, here are a few key insights from my notes on The Signal and the Noise
1) Data is useless without context.
There are always patterns to find in data, but its critical to understand the theory behind the system you are studying to avoid being fooled by noise. This is true in forecasting the weather, investing, betting on sports, or any other probabilistic endeavor. The ability to understand context is also a critical advantage humans have over computer programs.
“Statistical inferences are much stronger when backed up by theory or at least some deeper thinking about their root causes. “
The importance of understanding context comes to the forefront when you compare human’s success with weather forecasting, vs relative failure with earthquake forecasting.
“Chaos theory is a demon that can be tamed- weather forecasts did so, at least in part. But weather forecasters have a much better theoretical understanding of th earth’s atmosphere than seismologists do of the earth’s crust. They know more or less, how weather works, right down to the molecular level. Seismologists don’t have that advantage. “
The ability to understand context is what separates success from failure in all pursuits dealing with uncertainty. The profile of professional sports gambler Bob Voulgaris, is highly instructive. Voulgaris focuses on NBA basketball. A key insight is that Voulgaris has powerful tools for analyzing data, and he makes good use of the data, but he also has deep understanding of the qualitative subletities of how NBA basketball works. Obvious statistical patterns are quickly incorporated into betting lines, whether they are signal or noise. Voulgaris looks deeper, and finds places where the line misprices true probabilities.
“Finding patterns is easy in any data rich environment; thats what mediocre gamblers do. The key is in determining whether the patterns represent noise or signal. “
2) Beware of overconfidence
“… the amount of confidence someone expresses in a prediction is not good indication of its accuracy, to the contrary, these qualities are often inversely correlated. “
3) Think big, and think small. Mix the macro and the micro.
“Good innovators typically think very big, and they think very small. New ideas are sometimes found in the most granular of details where few others bother to look. And they are sometimes found when you are doing your most abstract and philosophical thinking, considering why the world is the way that it is and whether there might be an alternative to the dominant paradigm.”
This is reminiscent of the “global micro” approach used by several manager’s profiled in Inside the House of Money: Top Hedge Fund Traders on Profiting in the Global Markets
4) Recognize the Value of Bayesian Thinking
The work of Thomas Bayes forms the framework underlying how good gamblers think.
Bayes was an English minister who argued in his theological work that admitting our own imperfections is a necessary step on the way to redemption. His most famous work, however, was “An Essay toward Solving a Problem in the Doctrine of Chances,” which was not published until after his death. One interpretation of the essay concerns a person who emerges into the world( ie Adam, or someone from Plato’s cave), and rises to see the sun for the first time:
“At first the does not know whether this is typical of some sort of freak occurrence. However each day that he survives and the sun rises again, his confidence increases that it is a permanent feature of nature. Gradually, through this purely statistical form of inference, the probability that he assigns to his prediction that the sun will rise again tomorrow approaches(although never exactly reaches) 100 percent.”
In essence, beliefs on probability are updated as new information comes in.
Ironically Bayes philosophical work was extended by the mathematician and astronomer Pierre Simon-Laplace, who was likely an atheist. Although Laplace believed in scientific determinism, he was frustrated with the disconnect between (what he believed to be the perfection of nature, and human imperfections in understanding it, in particular with regards to astronomical observations. Consequently, he developed some measuring techniques that relied on probabilistic inferences, rather than exact measurements. “Laplace came to view probability as a waypoint between ignorance and knowledge.” The combined work of Laplace and Bayes led to simple expression that is concerned with conditional probability. In essence Bayesian math can be used to tell us the probability that a theory or hypothesis if some event has happened.
5) The road to wisdom is to be less and less wrong.
forecasting, or at least operating in an uncertain environment, is an iterative process.
Nate Silver titles one of the chapters “Less and Less Wrong, as a homage to the Danish mathematician, scientist, inventor, and poet Piet Hein, author of Grooks:
The road to wisdom? — Well, it’s plain
and simple to express:
and err again
George Soros treats developments in financial markets as a historical process. In The Alchemy of Finance, he outlines his theory of reflexivity, discusses historical developments in markets, and describes a real time “experiment” he undertook while running the Quantum fund in the 1980s.
Markets are an ideal laboratory for testing theories: changes are expressed in quantitative terms, and the data are easily accessible.
Three of the key interrelated concepts in his framework, are anti-equilibrium, Imperfect Knowledge, and Reflexivity.
In markets, equilibrium is a very rare special case. Further, adjustments rarely lead to new equilibrium. The economy is always in adjustment.
According to George Soros:
If we want to understand the real world we must divert our gaze from a hypothetical final outcome , and concentrate our attention on the process of change that we observe all around us.
In trying to deal with macroeconomic developments, equilibrium analysis is totally inappropriate. Nothing could be further removed from reality than the assumptions that the participants base their decisions on perfect knowledge. People are groping to anticipate the future with the help of whatever guideposts they can establish. The outcome tends to diverge from expectations, leading to constantly changing expectations, and constantly changing outcomes. The process is reflexive.
The stock market, is of course a perfect example:
The concept of an equilibrium seems irrelevant at best and misleading at worst. The evidence shows persistent fluctuations, whatever length of time is chosen as the period of observation. Admittedly, the underlying conditions that are supposed to be reflected in stock prices are also constantly changing, but it is difficult to establish any firm relationship between changes in stock prices and changes in underlying conditions. Whatever relationship can be established has to be imputed rather than observed.
So its better to focus on nature and direction of ongoing adjustments, rather than trying to identify an equilibrium.
Perhaps more problematic with an exclusive focus on rarely occurring equilibrium conditions is the assumption of perfect knowledge. Perfect knowledge is impossible. Everything is a provisional hypothesis, subject to improvement. Soros makes the bias of market participants the center part of his analysis.
In natural sciences, usually the thinking of participants and the events themselves can be separated. However, when people are involved, there is interplay between thoughts and actions. There is a partial link to Heisenberg’s uncertainty principle. The basic deductive nomological approach of science is inadequate. Use of probabilistic generalization, or some other novel scientific method is preferable.
Thinking plays a dual role. On the one hand, participants seek to understand the situation in which they participate; on the other, their understanding serves as the basis of decisions which influence the course of the events. The two roles interfere with each other.
The influence of this idea is inseparable from the theory of imperfect knowledge.
The participants’ perceptions are inherently flawed, and there is a two-way connection between flawed perceptions and the actual course of events, which results in a lack of correspondence between the two.
This two way connection is what Soros called “reflexivity.”
The thinking of participants, exactly because it is not governed by reality, is easily influenced by theories. In the field of natural phenomena, scientific method is effective only then its theories are valid, but in social political , and economic matters, theories can be effective without being valid.
Effective here, means having an impact. For example, in a bubble, the cost of capital for some companies drops to be absurdly low, relative to the risk of their respective enterprises. Consequently, some businesses that would have otherwise died, may go on to survive. (Example from two decades after the Alchemy of Finance was written: Peter Thiel mentions when being interviewed in Inside the House of Money, that Paypal did a massive capital raise right a the height of the tech bubble, even though it didn’t need the money at the time) On the flip side, a depression can be self fulfilling, if businesses are unable to refinance.
This seems to be especially true in the credit markets:
Loans are based on the lender’s estimation of the borrowers ability to service his debt. The valuation of the collateral is supposed to be independent of the act of lending; but in actual fact the act of lending can affect the value of the collateral. This is true of the individual case and of the economy as a whole. Credit expansion stimulates the economy and enhances the collateral values; the repayment or contraction of credit has a depressing influence both on the economy and on the valuation of collateral. The connection between credit and economy activity is anything but constant- for instance , credit for building a new factory has quite a different effect from credit for a leveraged buyout. This makes it difficult to quantify the connection between credit and economic activity. Yet it is a mistake to ignore it.
This is reminiscent of Hyman Minsky’s Financial Instability Hypothesis
In terms of the stock market, Soros asserts (1)Markets are always biased in one direction or another. (2) Markets can influence the events that they anticipate.
In The Landscape of History: How Historians Map the Past, John Gaddis discusses the methods that historians use, comparing them to methods of sciences such as astronomy, paleontology, and geology. The book is a great exploration of different approaches to examining evidence. Here are a few key lessons.
Since we’re historians, not novelists , we’re obliged to tier our narrative as closely as possible to the evidence that has survived: that’s an inductive process. But we have no way of knowing, until we begin looking for evidence with the purposes of our narrative in mind, how much of its going to be relevant: that’s a deductive calculation. Composing the narrative will then produce places where more research is needed, and we’re back to induction again. But that new evidence will still have to fit within the modified narrative so we’re back to deduction. And so on until, as I earlier quoted William H. McNeill, “it feels right, and then I write it up and ship it off to the publisher.” That’s why the distinction between induction and deduction is largely meaningless for the historian seeking to establish causation. The verb “to fit” which implies both procedures, is much better. Its not just tailors who look at what they have to cover, and then what they have with which to cover it, and then back and forth, again and again, until the fit is as good as its going to get.
Biography, like the larger sphere of history within which it resides is at once a deductive and an inductive exercise. Patterns of human behavior extending across time and space can alert us to the kinds of questions we should be asking about the particular individual we’re dealing with: that’s where deduction comes in.…But these patterns alone can’t determine the answers, for it’s all to easy to to find what you’re looking for when you’ve already decided a head of time what it is. The evidence of particular experience in biography has got to discipline what we know from collective experience: induction is how we do that.
Theories like relativity, plate tectonics, and natural selection emphasize relationships among variables, some of them continuous and others contingent. Regularity and randomness coexist within such theories: they allow for punctuations that upset equilibria such as asteroid impacts, earthquakes, or the outbreak of new and lethal diseases. Nor do they require singling out certain variables as more important than others.Nor do they require singling out certain variables as more important than others: what would the independent variables be for the Andromeda galaxy or the Norwegian coastline, or the Darwin finch? Reductionism in these realms is only a stepping stone towards synthesis.
Historians,however, reject the doctrine of immaculate causation, which seems to be implied in the idea that one can identify, without reference to all that has preceded it, such a thing as an independent variable. Causes always have antecedents. We may rank their relative significance, but we’d think it irresponsible to seek to isolate or “tease out” single causes for complex events. We see history as proceeding instead from multiple causes and their intersections. Interconnections matter more to us than does the enshrinement of particular variables.
Cal Newport defines Deep Work as activities performed in a state of distraction-free concentration that push cognitive capabilities to the limit. Deep Work is essential in order to quickly master new things quickly, and to produce at an elite level in terms of both quality and speed.
Cal Newport quotes A.G. Sertillanges, a Dominican friar and professor of moral philosophy who wrote in The Intellectual Life
Men of genius themselves were great only by bringing all their power to bear on the point on which they had decided to show their full measure.
Winifred Gallagher concludes in the book Rapt: Attention and the Focused Life that management of attention is the key to improving nearly every aspect of existence. Realizing this is the easy part. The hard part is figuring out how to fit Deep Work into a busy schedule. Newport outlines 4 applicable philosophies for fitting deep work into the demands of a modern schedule.
1) The Monastic Philosophy
This is available to a limited pool of people, mainly tenured professors, and successful authors. Examples include computer scientist Donald Knuth and science fiction writer Neal Stephenson, who both go to extreme lengths to eliminate shallow tasks and communication.
2) The Bimodal Philosophy
Practically speaking, this is about taking a proper holiday, or carefully blocking off certain days for different kinds of work. It need not be long. Carl Jung, on several key occasions in the 1920s retreated to a house in the woods in order to work on writing, but spent most of his time to living a very active social life in Zurich. Adam Grant, a famous business school professor is, is very active with university responsibilities most of the time, but when working on a book, he’ll cut himself off from most office communication for 2-4 day periods.
3) The Rhythmic Philosophy
This is perhaps the most practical method for most people. Basically, it means creating a simple regular habit of deep work. Combine a simple scheduling heuristic, and an easy way to keep track.
One suggested method is to get up 90 minutes earlier and spend the extra time on deep work(this happens to be the method used by yours truly to get more reading/writing/coding done )
4) The Journalistic Philosophy
This seems like it could be combined with the rhythmic philosophy. In essence it means getting deep work in whenever you can fit it. It does require strong attention discipline(but like muscles, this can be trained). Walter Isaacson managed to write his first 800+ page book while working full time as a journalist using this method. (us mere mortal can use noise cancelling headphones as an aid in applying the journalistic philosophy of deep work)
Newport also offers two suggestions for ramping up the amount of deep work one does.
- Beware of distractions and looping. This is when the brain wanders into unrelated issues when it should be focused on a critical task. Newport used the example of when his brain would rehash preliminary results over and over again when he was trying to work on a proof.
- Structure deep thinking. Identify relevant variables, define the specific next step questions, and once it is solved , consolidate the gains by reviewing the identified answer. Approach problem solving methodically.