First Principles: Elon Musk on the Power of Thinking for Yourself

snowmobile; the challenges of TFP.

First principles thinking, which is sometimes called reasoning from first principles, is one of the most effective strategies you can employ for breaking down complicated problems and generating original solutions. It also might be the single best approach to learn how to think for yourself.

The first principles approach has been used by many great thinkers including inventor Johannes Gutenberg, military strategist John Boyd, and the ancient philosopher Aristotle, but no one embodies the philosophy of first principles thinking more effectively than entrepreneur Elon Musk.

In 2002, Musk began his quest to send the first rocket to Mars—an idea that would eventually become the aerospace company SpaceX.

He ran into a major challenge right off the bat. After visiting a number of aerospace manufacturers around the world, Musk discovered the cost of purchasing a rocket was astronomical—up to $65 million. Given the high price, he began to rethink the problem.

“I tend to approach things from a physics framework,” Musk said in an interview. “Physics teaches you to reason from first principles rather than by analogy. So I said, okay, let’s look at the first principles. What is a rocket made of? Aerospace-grade aluminum alloys, plus some titanium, copper, and carbon fiber. Then I asked, what is the value of those materials on the commodity market? It turned out that the materials cost of a rocket was around two percent of the typical price.”

Instead of buying a finished rocket for tens of millions, Musk decided to create his own company, purchase the raw materials for cheap, and build the rockets himself. SpaceX was born.

Within a few years, SpaceX had cut the price of launching a rocket by nearly 10x while still making a profit. Musk used first principles thinking to break the situation down to the fundamentals, bypass the high prices of the aerospace industry, and create a more effective solution.

First principles thinking is the act of boiling a process down to the fundamental parts that you know are true and building up from there. Let’s discuss how you can utilize first principles thinking in your life and work.

Defining First Principles Thinking

A first principle is a basic assumption that cannot be deduced any further. Over two thousand years ago, Aristotle defined a first principle as “the first basis from which a thing is known.”

First principles thinking is a fancy way of saying “think like a scientist.” Scientists don’t assume anything. They start with questions like, What are we absolutely sure is true? What has been proven?

In theory, first principles thinking requires you to dig deeper and deeper until you are left with only the foundational truths of a situation. Rene Descartes, the French philosopher and scientist, embraced this approach with a method now called Cartesian Doubt in which he would “systematically doubt everything he could possibly doubt until he was left with what he saw as purely indubitable truths.”

In practice, you don’t have to simplify every problem down to the atomic level to get the benefits of first principles thinking. You just need to go one or two levels deeper than most people. Different solutions present themselves at different layers of abstraction. John Boyd, the famous fighter pilot and military strategist, created the following thought experiment which showcases how to use first principles thinking in a practical way.

Imagine you have three things:

A motorboat with a skier behind it
A military tank
A bicycle

Now, let’s break these items down into their constituent parts:

Motorboat: motor, the hull of a boat, and a pair of skis.
Tank: metal treads, steel armor plates, and a gun.
Bicycle: handlebars, wheels, gears, and a seat.

What can you create from these individual parts? One option is to make a snowmobile by combining the handlebars and seat from the bike, the metal treads from the tank, and the motor and skis from the boat.

This is the process of first principles thinking in a nutshell. It is a cycle of breaking a situation down into the core pieces and then putting them all back together in a more effective way. Deconstruct then reconstruct.

How First Principles Drive Innovation

The snowmobile example also highlights another hallmark of first principles thinking, which is the combination of ideas from seemingly unrelated fields. A tank and a bicycle appear to have nothing in common, but pieces of a tank and a bicycle can be combined to develop innovations like a snowmobile.

Many of the most groundbreaking ideas in history have been a result of boiling things down to the first principles and then substituting a more effective solution for one of the key parts.

For instance, Johannes Gutenberg combined the technology of a screw press—a device used for making wine—with movable type, paper, and ink to create the printing press. Movable type had been used for centuries, but Gutenberg was the first person to consider the constituent parts of the process and adapt technology from an entirely different field to make printing far more efficient. The result was a world-changing innovation and the widespread distribution of information for the first time in history.

The best solution is not where everyone is already looking.

First principles thinking helps you to cobble together information from different disciplines to create new ideas and innovations. You start by getting to the facts. Once you have a foundation of facts, you can make a plan to improve each little piece. This process naturally leads to exploring widely for better substitutes.

The Challenge of Reasoning From First Principles

First principles thinking can be easy to describe, but quite difficult to practice. One of the primary obstacles to first principles thinking is our tendency to optimize form rather than function. The story of the suitcase provides a perfect example.

In ancient Rome, soldiers used leather messenger bags and satchels to carry food while riding across the countryside. At the same time, the Romans had many vehicles with wheels like chariots, carriages, and wagons. And yet, for thousands of years, nobody thought to combine the bag and the wheel. The first rolling suitcase wasn’t invented until 1970 when Bernard Sadow was hauling his luggage through an airport and saw a worker rolling a heavy machine on a wheeled skid.

Throughout the 1800s and 1900s, leather bags were specialized for particular uses—backpacks for school, rucksacks for hiking, suitcases for travel. Zippers were added to bags in 1938. Nylon backpacks were first sold in 1967. Despite these improvements, the form of the bag remained largely the same. Innovators spent all of their time making slight iterations on the same theme.

What looks like innovation is often an iteration of previous forms rather than an improvement of the core function. While everyone else was focused on how to build a better bag (form), Sadow considered how to store and move things more efficiently (function).

How to Think for Yourself

The human tendency for imitation is a common roadblock to first principles thinking. When most people envision the future, they project the current formforward rather than projecting the function forward and abandoning the form.

For instance, when criticizing technological progress some people ask, “Where are the flying cars?”

Here’s the thing: We have flying cars. They’re called airplanes. People who ask this question are so focused on form (a flying object that looks like a car) that they overlook the function (transportation by flight). This is what Elon Musk is referring to when he says that people often “live life by analogy.”

Be wary of the ideas you inherit. Old conventions and previous forms are often accepted without question and, once accepted, they set a boundary around creativity.

This difference is one of the key distinctions between continuous improvementand first principles thinking. Continuous improvement tends to occur within the boundary set by the original vision. By comparison, first principles thinking requires you to abandon your allegiance to previous forms and put the function front and center. What are you trying to accomplish? What is the functional outcome you are looking to achieve?

Optimize the function. Ignore the form. This is how you learn to think for yourself.

The Power of First Principles

Ironically, perhaps the best way to develop cutting-edge ideas is to start by breaking things down to the fundamentals. Even if you aren’t trying to develop innovative ideas, understanding the first principles of your field is a smart use of your time. Without a firm grasp of the basics, there is little chance of mastering the details that make the difference at elite levels of competition.

Every innovation, including the most groundbreaking ones, requires a long period of iteration and improvement. The company at the beginning of this article, SpaceX, ran many simulations, made thousands of adjustments, and required multiple trials before they figured out how to build an affordable and reusable rocket.

First principles thinking does not remove the need for continuous improvement, but it does alter the direction of improvement. Without reasoning by first principles, you spend your time making small improvements to a bicycle rather than a snowmobile. First principles thinking sets you on a different trajectory.

If you want to enhance an existing process or belief, continuous improvement is a great option. If you want to learn how to think for yourself, reasoning from first principles is one of the best ways to do it.

Footnotes

When Musk originally looked into hiring another firm to send a rocket from Earth to Mars, he was quoted prices as high as $65 million. He also traveled to Russia to see if he could buy an intercontinental ballistic missile (ICBM), which could then be retrofitted for space flight. It was cheaper, but still in the $8 million to $20 million range.
“Elon Musk’s Mission to Mars,” Chris Anderson, Wired.
“SpaceX and Daring to Think Big,” Steve Jurvetson. January 28, 2015.
“The Metaphysics,” Aristotle, 1013a14–15
Wikipedia article on first principles
I originally found the snowmobile example in The OODA Loop: How to Turn Uncertainty Into Opportunity by Taylor Pearson.
Story from “Where Good Ideas Come From,” Steven Johnson
Story from “Reinventing the Suitcase by Adding the Wheel,” Joe Sharkey, The New York Times
“A Brief History of the Modern Backpack,” Elizabeth King, Time
Hat tip to Benedict Evans for his tweets that inspired this example.
Stereotypes fall into this style of thinking. “Oh, I once knew a poor person who was dumb, so all poor people must be dumb.” And so on. Anytime we judge someone by their group status rather than their individual characteristics we are reasoning about them by analogy.

How Do You Learn How To Learn? Learn From Learners

Are you learning as fast as the world is changing? A constant state of change requires a constant state of learning. Only a handful of companies, and people, cultivate learning as a skill.

Put simply:

Cultures of innovation = Cultures of learning

With that said, there is one skill that will always be relevant in the future: continuous learning.

There is a dominant belief that learning stops once you put your diploma to use and get a job. Wrong! Learning is a skill that can be improved, and it never stops.

So, how do you learn how to learn?

Learn From Learners

Sound simple, right? Here’s the thing, there are ways to learn faster and better than how one is taught throughout school.

From Chris McCann’s class notes from Class 18 of Stanford University’s CS183C — Technology-enabled Blitzscaling — taught by Reid Hoffman, John Lilly, Chris Yeh, and Allen Blue. This class was an interview by Reid Hoffman of Brian Chesky — the founder and CEO of Airbnb.

This is Brian’s response on an audience question about learning how to learn:

I don’t have all the answers but here’s a tip.
If I was to ask you to learn about a topic in a week ex. the basics of UI design — how would you do it?
Read a ton of books, talk to people, do exercises? This is a fairly exhaustive process but you could do it.
Now what if I said in the same week you have to learn UI design, front end development, accounting, and how to incorporate a company — how would you do it?
There isn’t enough hours in the day to learn everything. So you have to short circuit the process somehow.
One approach is to learn from definitive sources. The downside is, if you pick the wrong source, you learn the wrong thing; however, if you pick the right source, you don’t have to read anything else.
For example with management I read High Output Management. I just read one book so I don’t need to read anything else about management. Paul Grahamwas a version of this at Y Combinator and he would point us to the resources that mattered.
One benefit of being more successful is you have access to talk to more successful people. But even before being successful, you can read about the best people.
Another tip is most people will help you if you ask a question — we are here to share information and knowledge. I was shameless in asking Reid Hoffman questions — I was probably annoying but I didn’t care — I just wanted to learn.

My own method for learning varies, but right off the bat I develop a list of questions about a topic, ask people in the know, and immerse myself in the topic. I also read lots of biographies of interesting people; my goal is to understand how they think and then add that to my cognitive toolbox.

Hack Learning By Breaking It Down

Some people have even hacked the learning process. For example, Tim Ferrisshas made his name from hacking fitness and cooking. In doing so he identified a process for quickly mastering any skill, which he shares in a talk:

Ferriss has taken his method a step further, and also has a well known podcast where he interviews interesting people who share their own approach to how they learn.

Similar to Ferris, Josh Kaufman has taken a similar approach to hack learning:

Put Yourself In The Context Of What You Want To Learn

Learning how others learn isn’t the only way to understand a topic quickly, putting yourself in the context of what you want to learn is another approach.

For example, my buddy Ivan, who I recently had on the podcast to discuss the ethics of artificial intelligence, is a self-taught programmer. How did he do it? He started hanging out with other programmers and got involved in their projects; and then coded is own projects.

It took him time, but that’s what it takes.

Start From The Basics

Another well known innovator who learns quickly is Elon Musk.

How does he do it?

He learns the foundations and then moves from there.

Here’s what Elon responded to a question on Reddit AMA about how he learns so much so fast:

I think most people can learn a lot more than they think they can. They sell themselves short without trying.
One bit of advice: it is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, ie the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang on to.

Interestingly, as I’ve written about before, starting from first principles is an effective approach to innovation.

Leaders Are Learners

Great leaders simply aren’t satisfied with what they know. They possess an insatiable curiosity for discovery and learning – they are in constant pursuit of what they don’t know.

That’s why the best and most innovative leaders are pattern thinkers, that is they are intensely and endlessly curious. They all have that in common, the skills necessary to innovate: ask questions, pay attention, seek and talk to interesting people and lastly, experiment with ideas.

Bottom line: When we stop learning we stop growing. Continuous learning is a life skill, an antidote to irrelevance. So teaching yourself to master any skill is a powerful investment in yourself.

Learn Anything In 20 Hours With This Four-Step Method

With just 20 hours of focused, deliberate practice, you can go from knowing absolutely nothing to performing well. That’s the message from Josh Kaufman, author of The First 20 Hours. In the video above, he reveals the four steps to learning any new skill, fast.

It’s a long, 20-minute TEDx Talk, but entertaining and enlightening too. The four steps in Kaufman’s method are:

Deconstruct the skill: Break down the parts and find the most important things to practice first. If you were learning to play a musical instrument, for example, knowing just a few chords gives you access to lots of songs. If you want to learn a new language, learn the most common 2000 words and you’ll have 80 per cent text coverage.
Self-correct: Use reference materials to learn enough that you know when you make a mistake so you can correct yourself.
Remove barriers to learning: Identify and remove anything that distracts you from focusing on the skill you want to learn.
Practise at least 20 hours.

20 hours amounts to just 40 minutes a day for a month, so what are you waiting for?

The First 20 Hours

Tim Ferriss Will Teach You How To Quickly Master Any Skill

How do you get good at anything? Let’s count the ways (four, of course) with a man who is clearly very good at counting.

Tim Ferriss is a human guinea pig: in his researching the 4-Hour Workweek, Body, and Chef, the author has thrown himself into deadlifts and omelets and French–and from all that experimentation, a meta-sequence of contrarian best practices emerged.

During a talk at the Next Web Conference in Amsterdam, Ferriss unpacked–or is it deconstructed?–the madness to his methodology.

To begin, dissemble all parts.

The first stage of skill acquisition, behavior change, or however you want to call improving yourself is deconstruction, the art of breaking a complex practice into small tasks. Within that deconstruction, Ferriss says, you can suss out the failure points of your potential practice and avoid them for the first five sessions, after which it can become a habit.

Ferriss learned to swim only five years ago, he says, because he had a hard time breathing and kept getting exhausted from kicking. Then he discovered Total Immersion Swimming, which sidestepped those pain points.

Then find where the value comes from.

Next is selection: he anchors his argument to the Pareto principle, stating that you get 80% of your value from 20% of the work. The key, then, is locating those most valuable factors of a given undertaking, going all-in on them, and cutting away excess distractions. As we learned in the breakfast nook, you can accelerate your productivity–and save yourself stress–by making decisions about the way you make decisions. A prime example of that creative reductionism is Axis of Awesome, the Australian band that can teach you to play guitar using only four chords.

And nail the timing.

Then comes what Ferriss says is the secret sauce: sequencing, or determining what order you should learn those most important factors. Again he eschews the received wisdom: The dude became a tango champion because he learned the following, or traditionally female role, in the dance, rather than the more complex lead role.

Another hack with sequencing is being able to find places to fit in “no stakes” practice. The worst time to learn how to cook, Ferriss says, is when you’re trying to make a meal. Take, for instance, growing your cooking techniques–if you click to 17.43 in the video, you’ll see a slide of him kneeling and holding a pan. What’s he up to?

“I’m learning how to sauté. I’m practicing the wrist motion with dry beans in a skillet. Kneeling on a carpet so they don’t fly everywhere on a hardwood floor. [If] you do this for 20 minutes, two or three times, you’ll have the motion down, and you can use two hands over the stove–no problem. No omelets on walls.”

But you need proper motivation

Finally, you’ll never integrate the practice into your life unless you have stakes, he says. You don’t get fired from your diet if you don’t follow through; you just stay the same. So, Ferriss says, you need to build a way for you to lose something.

He mentions Stickk, a site that catalyzes that incentive process: You choose your goal, a referee (possibly “a merciless friend who will punish you”), and an anti-charity to give to (the highest on Stickk is the George W. Bush Memorial Library, Ferriss reports). The data is telling: When you give someone stakes and a referee, the rate of compliance hikes from 25% to more than 70%.

In other words, you can change your behavior when you create the right situation–if you are impeccable about the way you structure your efforts. The process is one of creative reduction, Ferriss says:

“Decision is related to the word incision, it means ‘to cut off.’ It means to cut away other options and to commit and to focus on whatever skill you have in [your] head.”

Tim Ferriss shares how to master any skill by deconstructing it [Video]

[Image: Flickr user Katherine McAdoo]

The “Thinking” in Systems Thinking: How Can We Make It Easier to Master?

Despite significant advances in personal computers and systems thinking software over the last decade, learning to apply systems thinking effectively remains a tough nut to crack. Many intelligent people continue to struggle far too long with the systems thinking paradigm, thinking process, and methodology.

From my work with both business and education professionals over the last 15 years, I have come to believe that systems thinking’s steep learning curve is related to the fact that the discipline requires mastering a whole package of thinking skills.

STEPS IN THE SYSTEMS THINKING METHOD

Begin by specifying the problem you want to address. Then construct hypotheses to explain the problem and test them using models. Only when you have a sufficient understanding of the situation should you begin to implement change.

Much like the accomplished basketball player who is unaware of the many separate skills needed to execute a lay-up under game conditions – such as dribbling while running and without looking at the ball, timing and positioning the take-off, extending the ball toward the rim with one hand while avoiding the blocking efforts of defenders – veteran systems thinkers are unaware of the full set of thinking skills that they deploy while executing their craft. By identifying these separate competencies, both new hoop legends and systems thinking wannabes can practice each skill in isolation. This approach can help you master each of the skills before you try to put them all together in an actual game situation.

The Systems Thinking Method

Before exploring these critical thinking skills, it’s important to have a clear picture of the iterative, four-step process used in applying systems thinking (see “Steps in the Systems Thinking Method”). In using this approach, you first specify the problem or issue you wish to explore or resolve. You then begin to construct hypotheses to explain the problem and test them using models whether mental models, pencil and paper models, or computer simulation models. When you are content that you have developed a workable hypothesis, you can then communicate your new found clarity to others and begin to implement change.

When we use the term “models” in this article, we are referring to something that represents a specifically defined set of assumptions about how the world works. We start from a premise that all models are wrong because they are incomplete representations of reality, but that some models are more useful than others (they help us understand reality better than others). There is a tendency in the business world, however, to view models (especially computer-based models) as “answer generators;” we plug in a bunch of numbers and get out a set of answers. From a systems thinking perspective, however, we view models more as “assumptions and theory testers” we formulate our understanding and then rigorously test it. The bottom line is that all models are only as good as the quality of the thinking that went into creating them. Systems thinking, and its ensemble of seven critical thinking skills, plays an important role in improving the quality of our thinking.

The Seven Critical Thinking Skills

As you undertake a systems thinking process, you will find that the use of certain skills predominates in each step. I believe there are at least seven separate but interdependent thinking skills that seasoned systems thinkers master. The seven unfold in the following sequence when you apply a systems thinking approach: Dynamic Thinking, System-as-Cause Thinking, Forest Thinking, Operational Thinking, Closed-Loop Thinking, Quantitative Thinking, and Scientific Thinking.

The first of these skills, Dynamic Thinking, helps you define the problem you want to tackle.

The next two, System-as-Cause Thinking and Forest Thinking, are invaluable in helping you to determine what aspects of the problem to include, and how detailed to be in representing each.

The fourth through sixth skills, Operational Thinking, Closed-Loop Thinking, and Quantitative Thinking, are vital for representing the hypotheses (or mental models) that you are going to test.

The final skill, Scientific Thinking, is useful in testing your models.

Each of these critical thinking skills serves a different purpose and brings something unique to a systems thinking analysis. Let’s explore these skills, identify how you can develop them, and determine what their “non-systems thinking” counterparts (which dominate in traditional thinking) look like.

Dynamic Thinking: Dynamic Thinking is essential for framing a problem or issue in terms of a pattern of behavior over time. Dynamic Thinking contrasts with Static Thinking, which leads people to focus on particular events. Problems or issues that unfold over time as opposed to one-time occurrences are most suitable for a systems thinking approach.

You can strengthen your Dynamic Thinking skills by practicing constructing graphs of behavior overtime. For example, take the columns of data in your company’s annual report and graph a few of the key variables over time. Divide one key variable by another (such as revenue or profit by number of employees), and then graph the results. Or pick up today’s news-paper and scan the head-lines for any attention-grabbing events. Then think about how you might see those events as merely one interesting point in a variable’s overall trajectory over time. The next time someone suggests that doing this-and-that will fix such-and-such, ask, “Over what time frame? How long will it take? What will happen to key variables over time?”

System-as-Cause Thinking: Dynamic Thinking positions your issue as a pattern of behavior over time. The next step is to construct a model to explain how the behavior arises, and then suggest ways to improve that behavior. System-as-Cause Thinking can help you determine the extensive boundary of your model, that is, what to include in your model and what to leave out (see “Extensive and Intensive Model Boundaries”). From a System-as-Cause Thinking approach, you should include only the elements and inter-relationships that are within the control of managers in the system and are capable of generating the behavior you seek to explain.

By contrast, the more common System-as-Effect Thinking views behavior generated by a system as “driven” by external forces. This perspective can lead you to include more variables in your model than are really necessary. System-as-Cause Thinking thus focuses your model more sharply, because it places the responsibility for the behavior on those who manage the policies and plumbing of the system itself.

To develop System-as-Cause Thinking, try turning each “They did it” or “It’s their fault” you encounter into a “How could we have been responsible?” It is always possible to see a situation as caused by “outside forces.” But it is also always possible to ask, “What did we do to make ourselves vulnerable to those forces that we could not control?”

EXTENSIVE AND INTENSIVE MODEL BOUNDARIES

Forest Thinking: In many organizations, people assume that to really know something, they must focus on the details. This assumption is reinforced by day-to-day existence—we experience life as a sequence of detailed events. We can also think of this as Tree-by-Tree Thinking. Models that we create by applying Tree-by-Tree Thinking tend to be large and overly detailed; their intensive boundaries run deep. In using such models, we would want to know whether that particular red truck broke down on Tuesday before noon, as opposed to being interested in how frequently, on average, trucks break down. Forest Thinking–inspired models, by contrast, group the details to give us an “on average” picture of the system. To hone your Forest Thinking skills, practice focusing on similarities rather than differences. For example, although everyone in your organization is unique, each also shares some characteristics with others. While some are highly motivated to perform and others are not, all have the potential to make a contribution. Regardless of the individual, realizing potential within an organization comes from the same generic structure. For example, what is the relationship among factors that tends to govern an individual’s motivation?

Operational Thinking :Operational Thinking tries to get at causality—how is behavior actually generated? This thinking skill contrasts with Correlational or Factors Thinking. Steven Covey’s The Seven Habits of Highly Effective People, one of the most popular nonfiction books of all time, is a product of Factors Thinking. So are the multitude of lists of “Critical Success Factors” or “Key Drivers of the Business” that decorate the office walls (and mental models) of so many senior executives. We like to think in terms of lists of factors that influence or drive some result.

There are several problems with mental models bearing such list structures, however. For one thing, lists do not explain how each causal factor actually works its magic. They merely imply that each factor “influences,” or is “correlated with,” the corresponding result. But influence or correlation is not the same as causality.

For example, if you use Factors Thinking to analyze what influences learning, you can easily come up with a whole “laundry list” of factors (see “Two Representations of the Learning Process”). But if you use Operational Thinking, you might depict learning as a process that coincides with the building of experience. Operational Thinking captures the nature of the learning process by describing its structure, while Factors Thinking merely enumerates a set of factors that in some way “influence” the process.

To develop your Operational Thinking skills, you need to work your way through various activities that define how a business works examine phenomena such as hiring, producing, learning, motivating, quitting, and setting price. In each case, ask, “What is the nature of the process at work?” as opposed to “What are all of the factors that influence the process?”

Closed-Loop Thinking :Imagine discussing your company’s profitability situation with some of your coworkers. In most companies, the group would likely list things such as product quality, leadership, or competition as influences on profitability (see “A Straight-Line vs. a Closed-Loop View of Causality”). This tendency to list factors stems from Straight-Line Thinking. The assumptions behind this way of thinking are 1) that causality runs only one way—from “this set of causes” to “that effect,” and 2) that each cause is independent of all other causes. In reality, however, as the closed-loop part of the illustration shows, the “effect” usually feeds back to influence one or more of the “causes,” and the causes themselves affect each other. Closed-Loop Thinking skills therefore lead you to see causality as an ongoing process, rather than a one-time event.
To sharpen your Closed-Loop Thinking skills, take any laundry list that you encounter and think through the ways in which the driven drives and in which the drivers drive each other. Instead of viewing one variable as the most important driver and another one as the second most important, seek to understand how the dominance among the variables might shift over time.

TWO REPRESENTATIONS OF THE LEARNING PROCESS

Quantitative Thinking: In this phrase, “quantitative” is not synonymous with “measurable.” The two terms are often confused in practice, perhaps because of the presumption in the Western scientific world that “to know, one must measure precisely.” Although Heisenberg’s Uncertainty Principle caused physicists to back off a bit in their quest for numerical exactitude, business folk continue unabated in their search for perfectly measured data. There are many instances of analysis getting bogged down because of an obsession with “getting the numbers right.” Measurement Thinking continues to dominate!

There are a whole lot of things, however, that we will never be able to measure very precisely. These include “squishy,” or “soft,” variables, such as motivation, self-esteem, commitment, and resistance to change. Many so-called “hard” variables are also difficult to measure accurately, given the speed of change and the delays and imperfections in information systems.

A STRAIGHT-LINE VS.A CLOSED-LOOP VIEW OF CAUSALITY

A STRAIGHT-LINE VS.A CLOSED-LOOP VIEW OF CAUSALITS

But let’s return to our “squishy” variables. Would anyone want to argue that an employee’s self-esteem is irrelevant to her performance? Who would propose that commitment is unimportant to a company’s success? Although few of us would subscribe to either argument, things like self-esteem and commitment rarely make it into the spreadsheets and other analytical tools that we use to drive analysis. Why? Because such variables can’t be measured. However, they can be quantified. If zero means a total absence of commitment, 100 means being as committed as possible. Are these numbers arbitrary? Yes. But are they ambiguous? Absolutely not! If you want your model to shed light on how to increase strength of commitment as opposed to predicting what value commitment will take on in the third-quarter of 1997—you can include strength of commitment as a variable with no apologies. You can always quantify, though you can’t always measure.

To improve your Quantitative Thinking skills, take any analysis that your company has crunched through over the last year and ask what key “soft” variables were omitted, such as employee motivation. Then, ruminate about the possible implications of including them systems thinking gives you the power to ascribe full-citizen status to such variables. You’ll give up the ability to achieve perfect measurement. But if you’re honest, you’ll see that you never really had that anyway.

Scientific Thinking: The final systems thinking skill is Scientific Thinking. I call its opposite Proving Truth Thinking. To understand Scientific Thinking, it is important to acknowledge that progress in science is measured by the discarding of falsehoods. The current prevailing wisdom is always regarded as merely an “entertainable hypothesis,” just waiting to be thrown out the window. On the other hand, too many business models are unscientific; yet business leaders revere them as truth and defend them to the death. Analysts make unrelenting efforts to show that their models track history and therefore must be “true.”

Seasoned systems thinkers continually resist the pressure to “validate” their models (that is, prove truth) by tracking history. Instead, they work hard to become aware of the falsehoods in their models and to communicate these to their team or clients. “All models are wrong,”” said W. Edwards Deming. “Some models are useful.” Deming was a smart guy, and clearly a systems thinker.

In using Scientific Thinking, systems thinkers worry less about outfitting their models with exact numbers and instead focus on choosing numbers that are simple, easy to understand, and make sense relative to one another. Systems thinkers also pay lots of attention to robustness they torture-test their models to death! They want to know under what circumstances their model “breaks down.” They also want to know, does it break down in a realistic fashion? What are the limits to my confidence that this model will be useful?

The easiest way to sharpen your Scientific Thinking skills is to start with a computer model that is “in balance” and then shock it. For example, transfer 90% of the sales force into manufacturing. Set price at 10 times competitor price. Triple the customer base in an instant. Then see how the model performs. Not only will you learn a lot about the range of utility of the model, but you also will likely gain insight into the location of that most holy of grails: high-leverage intervention points.

A Divide and Conquer Strategy

As the success of Peter Senge’s The Fifth Discipline: The Art & Practice of the Learning Organization has shown, systems thinking is both sexy and seductive. But applying it effectively is not so easy. One reason for this difficulty is that the thinking skills needed to do so are many in number and stand in stark contrast to the skill set that most of us currently use when we grapple with business issues (see “Traditional Business Thinking vs. Systems Thinking Skills”).

By separating and examining the seven skills required to apply systems thinking effectively, you can practice them one at a time. If you master the individual skills first, you stand a much better chance of being able to put them together in a game situation. So, practice . . . then take it to the hoop!

“Barry Richmond is the managing director and founder of High Performance Systems, Inc. He has a PhD in system dynamics from the MIT Sloan School of Management, an MS from Case Western Reserve, and an MBA from Columbia University”

TRADITIONAL BUSINESS THINKING VS. SYSTEMS THINKING SKILLS

Elon Musks’ “3-Step” First Principles Thinking: How to Think and Solve Difficult Problems Like a Genius

Mayo Oshin

By the age of 46 years old, Elon Musk has innovated and built three revolutionary multibillion dollar companies in completely different fields — Paypal (Financial Services), Tesla Motors (Automotive) and SpaceX (Aerospace).

This list doesn’t even include Solar City (Energy), which he helped build and acquired for $2.6 Billion recently.

At first glance, it’s easy to link his rapid success, ability to solve unsolvable problems and genius level creativity to his incredible work ethic.

Musk himself stated that he worked approximately 100 hours a week for over 15 years and recently scaled down to 85 hours. Rumour also has it that he doesn’t even take lunch breaks, multitasking between eating, meetings and responding to emails all at the same time.

No doubt work ethic plays an important role in unlocking your inner creative genius and becoming the best at what you do — but there’s more to this — there are extremely hard-working people who still make little progress in life and die before sharing their best work with the world.

What then is this missing link for innovative creativity and accelerated success?

Just like Musk, some of the most brilliant minds of all-time — Aristotle, Euclid, Thomas Edison, Feynman and Nikola Tesla — use this missing link for accelerated learning, solving difficult problems and creating great work in their lifetime.

This missing link has little to do with how hard they work. It has everything to do with how they think.

Let’s talk about how you can quickly use this genius problem solving method.

First Principles Thinking

During a one on one interview with TED Curator, Chris Anderson, Musk reveals this missing link which he attributes to his genius level creativity and success. It’s called reasoning from “First Principles.” [1]

Musk: Well, I do think there’s a good framework for thinking. It is physics. You know, the sort of first principles reasoning. Generally I think there are — what I mean by that is, boil things down to their fundamental truths and reason up from there, as opposed to reasoning by analogy.

Through most of our life, we get through life by reasoning by analogy, which essentially means copying what other people do with slight variations.

In layman’s terms, first principles thinking is basically the practice of actively questioning every assumption you think you ‘know’ about a given problem or scenario — and then creating new knowledge and solutions from scratch. Almost like a newborn baby.

On the flip side, reasoning by analogy is building knowledge and solving problems based on prior assumptions, beliefs and widely held ‘best practices’ approved by majority of people.

People who reason by analogy tend to make bad decisions, even if they’re smart.

FOOTNOTES

In this interview, Musk talks about this 100 hour work week. This is his interview on TED about first principles thinking.
Musk gave this answer to a question from a reader asking him how he learns so fast. (source)
Musk’s interview with Kevin Rose on first principles thinking and battery analogy.
This is not always easy. In fact, sometimes it can be a tough mental workout to use first principles thinking simply because it’s much easier to default back to what you already ‘know.’ Because of our prior assumptions and limiting beliefs, we have a tendency to only think of a very limited range of creative uses or solutions to any given problem. This is more formally known as “functional fixedness”.Dr.Tony McCaffery, Cognitive Psychologist and Innovation expert, has developed a simple method that can help us overcome this tendency and uncover creative solutions. You can read about his “general parts technique” here.
Thanks to peter at renaissance man journal for some inspiring insights on first principles thinking.

Techniques for Establishing First Principles

There are many ways to establish first principles. Let’s take a look at a few of them.

Socratic Questioning

Socratic questioning can be used to establish first principles through stringent analysis. This a disciplined questioning process, used to establish truths, reveal underlying assumptions, and separate knowledge from ignorance. The key distinction between Socratic questioning and normal discussions is that the former seeks to draw out first principles in a systematic manner. Socratic questioning generally follows this process:

Clarifying your thinking and explaining the origins of your ideas (Why do I think this? What exactly do I think?)
Challenging assumptions (How do I know this is true? What if I thought the opposite?)
Looking for evidence (How can I back this up? What are the sources?)
Considering alternative perspectives (What might others think? How do I know I am correct?)
Examining consequences and implications (What if I am wrong? What are the consequences if I am?)
Questioning the original questions (Why did I think that? Was I correct? What conclusions can I draw from the reasoning process?)

This process stops you from relying on your gut and limits strong emotional responses. This process helps you build something that lasts.

“Because I Said So” or “The Five Whys”

Children instinctively think in first principles. Just like us, they want to understand what’s happening in the world. To do so, they intuitively break through the fog with a game some parents have come to hate.

“Why?”

Here’s an example that has played out numerous times at my house:

“It’s time to brush our teeth and get ready for bed.”

“Why?”

“Because we need to take care of our bodies, and that means we need sleep.”

“Why do we need sleep?”

“Because we’d die if we never slept.”

“Why would that make us die?”

“I don’t know; let’s go look it up.”

Kids are just trying to understand why adults are saying something or why they want them to do something.

The first time your kid plays this game, it’s cute, but for most teachers and parents, it eventually becomes annoying. Then the answer becomes what my mom used to tell me: “Because I said so!” (Love you, Mom.)

Of course, I’m not always that patient with the kids. For example, I get testy when we’re late for school, or we’ve been travelling for 12 hours, or I’m trying to fit too much into the time we have. Still, I try never to say “Because I said so.”

People hate the “because I said so” response for two reasons, both of which play out in the corporate world as well. The first reason we hate the game is that we feel like it slows us down. We know what we want to accomplish, and that response creates unnecessary drag. The second reason we hate this game is that after one or two questions, we are often lost. We actually don’t know why. Confronted with our own ignorance, we resort to self-defense.

I remember being in meetings and asking people why we were doing something this way or why they thought something was true. At first, there was a mild tolerance for this approach. After three “whys,” though, you often find yourself on the other end of some version of “we can take this offline.”

Difference between Analogy and The F.P

Another way to think about this distinction comes from another friend, Tim Urban. He says^[3] it’s like the difference between the cook and the chef. While these terms are often used interchangeably, there is an important nuance. The chef is a trailblazer, the person who invents recipes. He knows the raw ingredients and how to combine them. The cook, who reasons by analogy, uses a recipe. He creates something, perhaps with slight variations, that’s already been created.

The difference between reasoning by first principles and reasoning by analogy is like the difference between being a chef and being a cook. If the cook lost the recipe, he’d be screwed. The chef, on the other hand, understands the flavor profiles and combinations at such a fundamental level that he doesn’t even use a recipe. He has real knowledge as opposed to know-how.

Examples of First Principles in Action

So we can better understand how first-principles reasoning works, let’s look at four examples.

Elon Musk and SpaceX

Perhaps no one embodies first-principles thinking more than Elon Musk. He is one of the most audacious entrepreneurs the world has ever seen. My kids (grades 3 and 2) refer to him as a real-life Tony Stark, thereby conveniently providing a good time for me to remind them that by fourth grade, Musk was reading the Encyclopedia Britannica and not Pokemon.

What’s most interesting about Musk is not what he thinks but how he thinks:

I think people’s thinking process is too bound by convention or analogy to prior experiences. It’s rare that people try to think of something on a first principles basis. They’ll say, “We’ll do that because it’s always been done that way.” Or they’ll not do it because “Well, nobody’s ever done that, so it must not be good. But that’s just a ridiculous way to think. You have to build up the reasoning from the ground up—“from the first principles” is the phrase that’s used in physics. You look at the fundamentals and construct your reasoning from that, and then you see if you have a conclusion that works or doesn’t work, and it may or may not be different from what people have done in the past.^[4]

His approach to understanding reality is to start with what is true — not with his intuition. The problem is that we don’t know as much as we think we do, so our intuition isn’t very good. We trick ourselves into thinking we know what’s possible and what’s not. The way Musk thinks is much different.

Musk starts out with something he wants to achieve, like building a rocket. Then he starts with the first principles of the problem. Running through how Musk would think, Larry Page said in an

interview, “What are the physics of it? How much time will it take? How much will it cost? How much cheaper can I make it? There’s this level of engineering and physics that you need to make judgments about what’s possible and interesting. Elon is unusual in that he knows that, and he also knows business and organization and leadership and governmental issues.”^[5]

Rockets are absurdly expensive, which is a problem because Musk wants to send people to Mars. And to send people to Mars, you need cheaper rockets. So he asked himself, “What is a rocket made of? Aerospace-grade aluminum alloys, plus some titanium, copper, and carbon fiber. And … what is the value of those materials on the commodity market? It turned out that the materials cost of a rocket was around two percent of the typical price.”^[6]

Why, then, is it so expensive to get a rocket into space? Musk, a notorious self-learner with degrees in both economics and physics, literally taught himself rocket science. He figured that the only reason getting a rocket into space is so expensive is that people are stuck in a mindset that doesn’t hold up to first principles. With that, Musk decided to create SpaceX and see if he could build rockets himself from the ground up.

In an interview with Kevin Rose, Musk summarized his approach:

I think it’s important to reason from first principles rather than by analogy. So the normal way we conduct our lives is, we reason by analogy. We are doing this because it’s like something else that was done, or it is like what other people are doing… with slight iterations on a theme. And it’s … mentally easier to reason by analogy rather than from first principles. First principles is kind of a physics way of looking at the world, and what that really means is, you … boil things down to the most fundamental truths and say, “okay, what are we sure is true?” … and then reason up from there. That takes a lot more mental energy.^[7]

Musk then gave an example of how Space X uses first principles to innovate at low prices:

Somebody could say — and in fact people do — that battery packs are really expensive and that’s just the way they will always be because that’s the way they have been in the past. … Well, no, that’s pretty dumb… Because if you applied that reasoning to anything new, then you wouldn’t be able to ever get to that new thing…. you can’t say, … “oh, nobody wants a car because horses are great, and we’re used to them and they can eat grass and there’s lots of grass all over the place and … there’s no gasoline that people can buy….”

He then gives a fascinating example about battery packs:

… they would say, “historically, it costs $600 per kilowatt-hour. And so it’s not going to be much better than that in the future. … So the first principles would be, … what are the material constituents of the batteries? What is the spot market value of the material constituents? … It’s got cobalt, nickel, aluminum, carbon, and some polymers for separation, and a steel can. So break that down on a material basis; if we bought that on a London Metal Exchange, what would each of these things cost? Oh, jeez, it’s … $80 per kilowatt-hour. So, clearly, you just need to think of clever ways to take those materials and combine them into the shape of a battery cell, and you can have batteries that are much, much cheaper than anyone realizes.

BuzzFeed

After studying the psychology of virality, Jonah Peretti founded BuzzFeed in 2006. The site quickly grew to be one of the most popular on the internet, with hundreds of employees and substantial revenue.

Peretti figured out early on the first principle of a successful website: wide distribution. Rather than publishing articles people should read, BuzzFeed focuses on publishing those that people want to read. This means aiming to garner maximum social shares to put distribution in the hands of readers.

Peretti recognized the first principles of online popularity and used them to take a new approach to journalism. He also ignored SEO, saying, “Instead of making content robots like, it was more satisfying to make content humans want to share.”^[8] Unfortunately for us, we share a lot of cat videos.

A common aphorism in the field of viral marketing is, “content might be king, but distribution is queen, and she wears the pants” (or “and she has the dragons”; pick your metaphor). BuzzFeed’s distribution-based approach is based on obsessive measurement, using A/B testing and analytics.

Jon Steinberg, president of BuzzFeed, explains the first principles of virality:

Keep it short. Ensure [that] the story has a human aspect. Give people the chance to engage. And let them react. People mustn’t feel awkward sharing it. It must feel authentic. Images and lists work. The headline must be persuasive and direct.

Derek Sivers and CD Baby

When Sivers founded his company CD Baby, he reduced the concept down to first principles. Sivers asked, What does a successful business need? His answer was happy customers.

Instead of focusing on garnering investors or having large offices, fancy systems, or huge numbers of staff, Sivers focused on making each of his customers happy. An example of this is his famous order confirmation email, part of which reads:

Your CD has been gently taken from our CD Baby shelves with sterilized contamination-free gloves and placed onto a satin pillow. A team of 50 employees inspected your CD and polished it to make sure it was in the best possible condition before mailing. Our packing specialist from Japan lit a candle and a hush fell over the crowd as he put your CD into the finest gold-lined box money can buy.

By ignoring unnecessary details that cause many businesses to expend large amounts of money and time, Sivers was able to rapidly grow the company to $4 million in monthly revenue. In Anything You Want, Sivers wrote:

Having no funding was a huge advantage for me.
A year after I started CD Baby, the dot-com boom happened. Anyone with a little hot air and a vague plan was given millions of dollars by investors. It was ridiculous. …
Even years later, the desks were just planks of wood on cinder blocks from the hardware store. I made the office computers myself from parts. My well-funded friends would spend $100,000 to buy something I made myself for $1,000. They did it saying, “We need the very best,” but it didn’t improve anything for their customers. …
It’s counterintuitive, but the way to grow your business is to focus entirely on your existing customers. Just thrill them, and they’ll tell everyone.

To survive as a business, you need to treat your customers well. And yet so few of us master this principle.

Employing First Principles in Your Daily Life

Most of us have no problem thinking about what we want to achieve in life, at least when we’re young. We’re full of big dreams, big ideas, and boundless energy. The problem is that we let others tell us what’s possible, not only when it comes to our dreams but also when it comes to how we go after them. And when we let other people tell us what’s possible or what the best way to do something is, we outsource our thinking to someone else.

The real power of first-principles thinking is moving away from incremental improvement and into possibility. Letting others think for us means that we’re using their analogies, their conventions, and their possibilities. It means we’ve inherited a world that conforms to what they think. This is incremental thinking.

When we take what already exists and improve on it, we are in the shadow of others. It’s only when we step back, ask ourselves what’s possible, and cut through the flawed analogies that we see what is possible. Analogies are beneficial; they make complex problems easier to communicate and increase understanding. Using them, however, is not without a cost. They limit our beliefs about what’s possible and allow people to argue without ever exposing our (faulty) thinking. Analogies move us to see the problem in the same way that someone else sees the problem.

The gulf between what people currently see because their thinking is framed by someone else and what is physically possible is filled by the people who use first principles to think through problems.

First-principles thinking clears the clutter of what we’ve told ourselves and allows us to rebuild from the ground up. Sure, it’s a lot of work, but that’s why so few people are willing to do it. It’s also why the rewards for filling the chasm between possible and incremental improvement tend to be non-linear.

Let’s take a look at a few of the limiting beliefs that we tell ourselves.

“I don’t have a good memory.” ^[10]
People have far better memories than they think they do. Saying you don’t have a good memory is just a convenient excuse to let you forget. Taking a first-principles approach means asking how much information we can physically store in our minds. The answer is “a lot more than you think.” Now that we know it’s possible to put more into our brains, we can reframe the problem into finding the most optimal way to store information in our brains.

“There is too much information out there.”
A lot of professional investors read Farnam Street. When I meet these people and ask how they consume information, they usually fall into one of two categories. The differences between the two apply to all of us. The first type of investor says there is too much information to consume. They spend their days reading every press release, article, and blogger commenting on a position they hold. They wonder what they are missing. The second type of investor realizes that reading everything is unsustainable and stressful and makes them prone to overvaluing information they’ve spent a great amount of time consuming. These investors, instead, seek to understand the variables that will affect their investments. While there might be hundreds, there are usually three to five variables that will really move the needle. The investors don’t have to read everything; they just pay attention to these variables.

“All the good ideas are taken.”
A common way that people limit what’s possible is to tell themselves that all the good ideas are taken. Yet, people have been saying this for hundreds of years — literally — and companies keep starting and competing with different ideas, variations, and strategies.

“We need to move first.”
I’ve heard this in boardrooms for years. The answer isn’t as black and white as this statement. The iPhone wasn’t first, it was better. Microsoft wasn’t the first to sell operating systems; it just had a better business model. There is a lot of evidence showing that first movers in business are more likely to fail than latecomers. Yet this myth about the need to move first continues to exist.

Sometimes the early bird gets the worm and sometimes the first mouse gets killed. You have to break each situation down into its component parts and see what’s possible. That is the work of first-principles thinking.

“I can’t do that; it’s never been done before.”
People like Elon Musk are constantly doing things that have never been done before. This type of thinking is analogous to looking back at history and building, say, floodwalls, based on the worst flood that has happened before. A better bet is to look at what could happen and plan for that.

“As to methods, there may be a million and then some, but principles are few. The man who grasps principles can successfully select his own methods. The man who tries methods, ignoring principles, is sure to have trouble.”

— Harrington Emerson

Conclusion

The thoughts of others imprison us if we’re not thinking for ourselves.

Reasoning from first principles allows us to step outside of history and conventional wisdom and see what is possible. When you really understand the principles at work, you can decide if the existing methods make sense. Often they don’t.

Reasoning by first principles is useful when you are (1) doing something for the first time, (2) dealing with complexity, and (3) trying to understand a situation that you’re having problems with. In all of these areas, your thinking gets better when you stop making assumptions and you stop letting others frame the problem for you.

Analogies can’t replace understanding. While it’s easier on your brain to reason by analogy, you’re more likely to come up with better answers when you reason by first principles. This is what makes it one of the best sources of creative thinking. Thinking in first principles allows you to adapt to a changing environment, deal with reality, and seize opportunities that others can’t see.

Many people mistakenly believe that creativity is something that only some of us are born with, and either we have it or we don’t. Fortunately, there seems to be ample evidence that this isn’t true.^[11] We’re all born rather creative, but during our formative years, it can be beaten out of us by busy parents and teachers. As adults, we rely on convention and what we’re told because that’s easier than breaking things down into first principles and thinking for ourselves. Thinking through first principles is a way of taking off the blinders. Most things suddenly seem more possible.

“I think most people can learn a lot more than they think they can,” says Musk. “They sell themselves short without trying. One bit of advice: it is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e., the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang on to.”

Elon Musk 如何比其他人學得更快更好

為什麼 Elon Musk 可以在四十歲中期於四個不同的領域（軟體、能源、運輸和航太）創造四家數十億的公司？

為了解釋 Elon Musk 的成功，其他人指出了他冒險犯難的工作倫理（他每週定期工作85個小時），替未來設定扭轉現實的願景，以及他難以置信的韌性。

但是所有這些我都覺得不夠解釋他的成功。很多人都有這些特質。我想了解他做了什麼與眾不同的事。

當我不斷閱讀關於 Musk 的幾十篇文章、影片和書籍時，我注意到一大塊拼圖失踪了。傳統的智慧說，要為了成為世界級的人物，我們只應該專注於一個領域。 Musk 破壞了這個規則。他的專長從火箭科學、工程、物理、人造智能到太陽能和能源。

在前一篇文章中，我稱像 Elon Musk 這樣的人為 “專家通才”（由 Bain＆Company 董事長 Orit Gadiesh 創造的一個名詞）。 “專家通才”在許多不同領域廣泛學習，了解連接這些領域較深層的原則，然後將原理應用於其核心專長。

根據我對 Musk 生活的回顧和與學習和專業知識相關的學術文獻，我相信我們應該在多個領域學習，以增加我們突破性成功的機率。

旁注：想把你的學習習慣提升到一個新的水準？我創建了一個免費“學習如何學習”的線上講座，你可能會喜歡。

樣樣通樣樣鬆的迷思

如果你是一個喜歡學不同領域的人，那麼你可能很熟悉這個善意的建議：

“成熟點。專注於一個領域。“

“像傑克那樣什麼都懂，沒一樣專精“。

隱含的假設是，如果你在多個領域學習，你只能學到表面，無法精通。

長時間以來”專家通才”的成功顯示這說法是錯誤的。跨多個領域的學習提供了資訊優勢（因此也是創新的優勢），因為大多數人只關注一個領域。

例如，如果你在技術行業，而其他所有人都只是閱讀科技出版物，但你也對生物學了解很多，你有能力提出幾乎沒有其他人可以想到的想法。反之亦然。如果你在生物學，且你也了解人工智能，那麼你比其他所有人都有資訊優勢。

儘管有這個基本的見解，但是很少有人實際上超越他們所在的行業

我們在自己領域裡其他人陌生的新領域學習，將讓我們做出別人無法做到的組合。這是專家通才的優勢。

一個有趣的研究反應了這個觀點。它研究了20世紀前五十九位歌劇作曲家如何達到精緻工藝。相較傳統說法-表現最好的人只能通過刻意的練習和專業化達到成功，研究員基斯·西蒙頓（Dean Keith Simonton）發現剛好相反：“最成功的歌劇作曲家的作品傾向於推出混合種類的作品，作曲家通過交叉訓練來避免過多的專精（過度訓練）造成的僵化，” 這也總結了 UPENN 研究員Scott Barry Kaufman 在“科學美國”雜誌上的文章內容。

Musk 的“學習轉移”超能力

根據他的兄弟 Kimbal Musk 描述，從他十幾歲的年紀開始，每天都會閱讀兩本不同學科的書。置入這個情境，如果你每個月讀一本書，Musk 可以讀你所讀書籍的60倍。

起初，Musk 的閱讀跨越了科幻小說、哲學、宗教、程式設計和科學家、工程師和企業家的傳記。隨著年齡的增長，他的閱讀和職業興趣擴展到物理、工程、產品設計、商業、技術和能源。這種對知識的渴望使他能夠接觸到他從未在學校學到的各種科目。

Elon Musk 還擅長一種非常具體的學習方法，大多數人甚至不了解的“學習轉移”。

學習轉移正在將我們在一個環境中學到的東西應用到另一個環境中。它可以將我們在學校或書中學到的內容應用到“現實世界”中，也可以將我們在一個行業中學到的東西應用到另一個行業。

這是 Musk 閃耀的地方。他的幾次採訪表明，他有一個獨特的兩步過程來促進學習轉移。

首先，他將知識解構為基本原裡

Musk 在 Reddit AMA 上的答案描述了他如何做到這一點：

將知識視為一種語義樹是重要的 – 確保你在進入葉子/細節之前，了解基本原理，即樹幹和大樹枝，不然沒有辦法掛任何東西在上面。

研究表明，將你的知識轉化為更深層次的抽象原理有助於學習轉移。研究還表明，一種技術特別強大，可幫助人們直覺的潛在原理。這種技術被稱為“對比案例”。

我們來看看它的工作原理：我們假設你要解構一個字母“A”，並明白什麼使“A”成為A較深層的原理。我們進一步說，你有兩種方法可以用來做到這一點：

你認為哪種方法比較有用？

方法＃1。方法1中的每個不同的 A 讓你看出每個 A 哪些一樣哪些不一樣。方法2中的每個 A 都一樣無法讓你有任何洞見。

當我們學習任何東西時，通過觀察許多不同的情況，我們開始直覺什麼是必要的，甚至製作我們自己獨特的組合。

這在我們的日常生活中是什麼意思？當我們進入一個新的領域時，我們不應該只採取一種方法或最佳實踐。我們應該研究很多不同的方法，解構每個方法，然後進行比較和對比。這將有助於我們發現潛在的原則。

接下來，他重建新領域的基本原理

Musk 學習轉移過程的第二步涉及將他把人工智能、技術、物理和工程方面學到的基礎原理重新構建到不同的領域：

在太空領域，如此創造了SpaceX。
在汽車領域，如此創造了特斯拉與自駕車功能。
在火車領域，如此預見了超高速管道列車(Hyperloop)。
在航太領域，如此預見了起飛和垂直著陸的電動飛行器。
在半機器人(cyborg)技術上，如此預見了接觸你的大腦的神經介面。
在支付技術上，如此幫助建立PayPal。
在AI技術上，如此共創 OpenAI，一個非營利、限制AI往負面發展的機率。

加州大學洛杉磯分校心理學教授和世界領先的類比推理思想家 Keith Holyoak 建議人們問自己以下兩個問題，以磨練他們的技能：“這讓我想起什麼？” 和 “為什麼會這會讓我想起那呢”

通過不斷地查看你環境中的物件和你閱讀的資訊，並詢問自己這兩個問題，你可以在大腦中建立起幫助你跨越傳統界限進行連接的肌肉。

底線：這不是魔術。這確實是正確的學習過程

現在，我們可以開始了解 Musk 為何會是世界一流的專家通才：

他花了很多年時間以60倍速度閱讀，盡可能像一個狂熱的讀者。
他廣泛地涉略不同的學科。
他不斷地把所學解構成基本原理，以新的方法重新建構。

在最深層次上，我們可以從 Elon Musk 的故事中學到，我們不應該執著專業化是事業成功和發揮影響力的最佳或唯一的途徑的教條。傳奇的專家通才巴克明斯特·富勒（Buckminster Fuller）總結了我們都應該考慮的思維轉變。他幾十年前就分享了這一點，而今天也是如此：

我們正處於一個時代，狹隘地走向認為專業化趨勢才合乎邏輯、自然以及符合大家想要的;如此想的同時，人類已被剝奪了全面性的理解。專業化促成了個人的孤立感、徒勞感和混亂感。這也導致了個人把思考和社會行為的責任留給其他人。專業化產生的偏見最終會導致國際和意識形態的不和，從而導致戰爭。“

如果我們投入時間學習跨領域的核心概念，並將這些概念關聯回我們的生活和世界，那麼在各個領域之間的轉移變得容易和快速。

隨著我們建立“首要原理”水庫，把這些原理與不同領域聯繫起來，我們突然獲得了能夠進入以前從未學到的新領域的超級力量，並迅速做出了獨特的貢獻。

了解 Elon 的學習超級能力有助於我們深入了解他如何進入一個已經有 100 多年的行業，並改變這領域競爭的整體基礎。

Elon Musk是其中一種，但他的能力並不是神奇的。

想要像 Musk 一樣學習嗎？我建了一個你可能會喜歡的免費“學習如何學習”線上講座。它是基於世界頂尖企業家最佳實踐的學習。

本文獲得原文 How Elon Musk Learns Fast and Better Than Everyone Else 的 Michael Simmons授權。

照片來自 Elon Musk – How I Became The Real ‘Iron Man’ 2017

引發驚人的爆炸力！ Elon Musk 知識軍火庫中最強殺傷力的武器 : 「第一性原理」（ First Principle )

「我會運用「第一性原理」思維而不是「類比」思維去思考問題。在日常生活中，人總是傾向於比較 — — 別人已經做過了或者正在做這件事情，我們也就去做。這樣的結果只能產生細小的叠代發展。「第一性原理」的思考方式是用物理學的角度看待世界的方法，也就是說一層層剝開事物的表象，看到裏面的本質，然後再從本質一層層往上走。」

— SpaceX、Tesla 電動汽車及 PayPal 創辦人 Elon Musk

什麼是「第一性原理」（ First Principle )？

所謂的「第一性原理」是一個量子力學中的一個術語，意思是從頭開始計算，只採用最基本的事實，然後根據事實推論，創造出新價值。在 Elon Musk 開發 Tesla 特斯拉電動車案例中，很多專家覺得電動車是不可能流行起來，因為電池成本在歷史上一直也降不下來。600美元 / 千瓦是市場的公價，電池從一直也是那麼貴，它的改進和降價總是很慢，所以它未來短時間內也不大可能大幅度降低價格。

但 Elon Musk 卻不認同，在他公司新電池的開發階段中，他率先屏棄現時市場所有生產電池組的已有技術，把電池組的構成物質全部分解，還原成最基礎的材料：碳、鎳、鋁及其他用於分離的聚合物，這種還原使他了解到重新構成了製造電池的「基本事實」（ Fact ）是什麼。

無可否認，上述的金屬成本如果在市場需求沒有大幅度改變下，是絕對降不下去的，可是他卻發現了當中剩下來的成本還包含了很大部份是屬於「人類協作過程」而生的成本，而他相信凡是人類協進的事情，就必定存在優化空間。

透過這些「基本事實」，Elon Musk 和團隊再把原材料每個部分再細緻分析及實驗，並把每項工作流程再優化重組，比如，在美國生產可能稅費比較高，那就不要在美國生產了；某種原有技術的模塊設計上出了問題，那就改變設計，最後他和團隊把各部份優化原件，加上全面改良的生產方法，整合成現時以能大幅度降低電池的生產成本為前提的電動汽車。

而把「第一性原理」的思想放在 Elon Musk 的 SpaceX 計劃，他也同樣挑戰過去太空運輸技輸產業中「成本就是那麼貴」的專家偏見，他先還原製造火箭「基本事實」，發現了一架火箭的原料成本原來只佔火箭的總成本的2%，而餘下的成本其實是其他製造過程的成本，而有了這層認知，他便朝著優化另外98% 的成本方向，把現時製造火箭的成本，降低了到現時的10% 。

這就是「第一性原理」（ First Principle ) 的爆炸力。

可是為什麼我們明明和 Elon Musk 身處在同一個世界，卻看不到 Elon Musk 看到的「第一性原理」（ First Principle )？為什麼？難道真的只是因為他比較有錢，接觸到較多高級知識份子嗎？總結原因，我認為有三大理由:

一、我們看不到，因為我們缺乏「硬學科」訓練

「第一性原理」（ First Principle ) 其實是事物底層規律的總結，就以泥石流作為例子，當你知道「從山頂上滾下的石頭會愈來愈快」這個基本事實後，如果當你不幸遇上泥石流時，你會選擇儘可能往山的兩側跑，而不是和順著山谷和泥石比拼鬥快，這個知識對你來說，可算是「野外求生」的知識，然而如果你能把這個知識發掘到底層，它其實就是為牛頓第二定律 F＝ma，有了這個底層知識，你不單能避開泥石流，更有可能想出造火箭方法。

而你能把這個大家也看得見的眼前「基本事實」，或「野外求生」知識，向底層發掘為大家也無法輕易以肉見看見的牛頓第二定律 F＝ma，需要的就是「硬學科」，例如數學、物理及化學。這些「硬學科」也許我們在求學時期早已學過，但在現在日常生活中，或許只餘下發薪水或買菜時，常用的加減乘除外，才有用武之地。

那為什麼我們從不會思考過如何融會貫通地使用呢？因為我們不明白這些「硬學科」價值在哪裏。

相比起心理學、經濟學和社會學等人文學科需經常配搭前置假設才能應用，「硬學科」是完全建立在基礎假設及邏輯思維分析之上，例如數學就是一個完全不依托真實存在的世界，透過假定範圍，幾乎所有的推論都是正確，因此它的知識可以算是更可靠，更貼近「第一性原理」（ First Principle ) 的本質。

二、我們看不到，因我們「自以為知道」

在一般學習書藉經常提到 : 個人認知的「知道」與事實上的「知道」的四象限中，我嘗試提再把它演繹為四個不同的層次 :

不知道自己不知道」Level 1 ：以為自己什麼都知道，自以為是的認知狀態
「知道自己不知道」Level 2 ：有敬畏之心，開始空杯心態，準備好投入學習
「知道自己知道」Level 3 ：抓住了事情的規律，提升了自己的認知
「極致的意會」Level 4：對事情的掌握，已經變成一種渾然天成的意會，在別人輾轉思量之際，你已立即能下準確的決定

認知」幾乎是人和人之間唯一的本質差別，技能的差別是可量化，但認知的差別卻是本質性的，不可量化。人和人比拼的除了是實踐力外，更重要是洞察力，

你的求知慾通常是由「你知道了自己不知道」（Level 2 ）開始產生; 人選擇不去求知，主要是因為大部份人一直也停留在「不知道自己不知道」（Level 1 ）。

「不知道自己不知道」（Level 1 ）的狀態是因為自己連那個「不知道」是什麼都沒有搞清楚，這就好比西醫只知「發炎」，而不知何謂「上火」。

對中醫來說，西醫所謂的「發炎」（ Inflammation ），其實是指「上火」，而火是有「實火」與「虛火」之分，而在虛實之中，治療方法也是可以完全截然相反。

而西醫卻因為從不知「上火」一字（或可以說就算就知道，也不重視「上火」在西方醫學知識系統的融合），只相信「發炎」便能解釋一切現象，因此亦錯過了在辨症時，以虛實之火去下更準確的藥方的機會，也錯過了自己發掘應對炎症不同程度症狀的新啟發，這就是「不知道自己不知道」（Level 1 ）的狀態所引發的問題。

三、我們看不到，因為我們「急功近利」的學習態度

學習是需要「基本功」的累積，凡事追根究底，深入學習，是要經歷流汗、未知、腦汁和時間付出。在華人以「考試結果及職業導向為最終學習目的」的情況下，我們早已失去了對學習的深索熱情和樂趣。

當你身邊人也在職場的高速公路上怒奔，大家終日也在看「三分鐘學會Google 的創新法則」，「三十分鐘不敗精讀法」，「三天快速增加你的財富收入」，並和你吹噓著上述的方法是如何啟發及有效，在創業場或職場上同樣具有競爭心的你怎能不焦急？在這裏我和你談學習需要時間練「基本功」，你也許會想 : 「別人都已進步都那麼快，再談基本功我就已做大輸家了！」

可是請停一停，讓我們能否用科學化的方法，再重新思考一下:

在正常人的能力成長曲綫中，其曲線的前期一般會隨著學會了具體方法和技術後快速增加，我們解決問題的時間會愈來愈短，對一些開始時還是有難度的事情，到達中期頂峰階段，經過練習後就會變得易如反掌，可是這個成長曲線到達後期就會失去向上升的動力，為什麼？

因為我們大多數人在日常認識問題時，一般只會依靠直覺、個人經驗、簡單的線性思維、因果關係、意識形態和價值觀偏好，而這些思維卻會引發 :

（1）我們無法發現事情之間深層次的關聯，我們眼前的認知都是一個分散的點，是一種孤立且斷裂式的認知，例如你無法明白到底 SpaceX 和 Tesla 電動汽車到底有什麼關係？

（2）我們面對超出自己日常工作的問題時，不知從何下手，更無法準確把握關鍵環節並合埋地預測事情的發展趨勢，例如你無法理解如何由電池組的構成基本原素，預測到解決澳洲電力危機的解決方向？

我們經常都聽到身邊那些在職場闖蕩了幾年的人會埋怨自己在公司已學不到任何新事物，感覺成長已到達天花板，真正原因不是你成長得太快，而是因為你的天花板太矮了。這個天花板，就是由你急功近利的學習方法所造成，因為你只看到天花板一個個孤立的點，而看不到天花板外原來還有樓宇的鋼筋水泥結構，城市空間的規劃原則，城市的發展的建築歷史。

相反如果我們能反其道，以慢打快，採用「第一性原理」（ First Principle ) 的學習原則，我們的成長曲線就會出現這個模樣 :

我們在學習的前期，雖然會因自己需不斷訓練和掌握基本原則，而令學習速度變慢，但當我們掌握了整個學科的理念和方法後，學習的能力就會大幅提升。

你可以透過「第一性原理」（ First Principle ) ，從底層的規律，以跨領域的方式，不停地活潑游走並累積，而隨著你的知識愈多，你的成長曲線會增長得愈來愈快，而當你能整合的知識愈多，你的知識就開始產生了爆炸性的威力（股神巴菲特最親密的戰友 Charlie Munger 稱之為「Lollapalooza Effect」），透過這種學習和成長，你會更容易獲得對未來更準確的「預測」，從而獲得先機，成為產業中的新先知。

鑽研知識的路，從不擁擠

我曾經聽過長輩感嘆 : 「今天是一個資訊和知識爆炸的社會，比起以往互聯網年代前的世界，當年的世界單純和清靜好多。」我認為這個觀念是謬誤，人類文明的發展，本來就是包含著混亂和喧鬧，以往的世界你覺得清靜，是因為訊息傳遞缺乏效率，而訊息內容的力量在傳遞的過程中，也會像熱力傳遞過程中會逐步遞減，所以接受者才不會有現在如直播般的「衝擊」。

同時，我們必須在一片「資訊和知識已爆炸」喧鬧聲，重新分清在這些爆炸中，到底什麼是「資料」、「資訊」和「知識」（這個分類將會在下一篇文章詳細解釋），現今的社會爆炸的是「資訊」，更正確來說是「垃圾資訊」，而非知識。知識的製造門檻是極高，並非你說爆就爆，因此鑽研知識的路，是又闊又人煙稀少，你以為人多的部份其實也不過追求快速「學習具體技巧」的方法論人群，它們和我們今天所分享的「第一性原理」（ First Principle ) 或底層定律，是完全在處於不同的程度。

總結今天的分享內容，我們理解了 :

1. 「第一性原理」（ First Principle ) 的定義
2. 我們看不到的「第一性原理」（ First Principle ) 的原因 : 缺乏「硬學科」訓練、「自以為知道」「急功近利」的學習態度
3. 我們學習「第一性原理」（ First Principle ) 的好處 : 獲得長遠累進的成長曲線; 得到對未來的洞見及獲得機遇

由今天起，讓我們一起刻意練習（ Deliberate Practice ) ：

最近幾年，有什麼知識是你當初認為是不重要，但後來你才後悔自己沒有早點知道？
反思自己在上述過程中，有什麼關鍵的事件、人物或原因令你醒覺上述的知識真的很重要？
嘗試運用「第一性原理」（ First Principle ) 的思考方式，發掘出你在學習認知中，那些經常見到但自己卻一直沒有觀察到事情，並找出改良方法，例如 :

為什麼我對數字總是很不敏感？

原來過去我總會以「人類是有血有肉，不能被量化」和「人的靈感直覺比機械式操作更重要」這類借口，輕忽了逃避學習數理 ;

那為什麼我會輕忽數理的重要性？

因為我是人文學科的人，所以每次面對數理相關的問題都會總是很沒有安全感，覺得自己比理科生低人一等……

也許你會有興趣

Elon Musk 如何比其他人學得更快更好

附註:

Elon Musk Photo Credit http://media2.govtech.com/

Occam’s Razor: The simplest solution is always the best

Always ask ” Is that necessary to add into it ? ”

” Simple is the best ” —- >> Anthony

Now that we appreciate the need for simplicity in designs better, let’s see another great concept. You may have heard of Occam’s Razor; did you know that you can apply it to web design? When you’ve got it in your “toolbox”, you’ll have an edge in the marketplace.

Occam’s Razor, put simply, states: “the simplest solution is almost always the best.” It’s a problem-solving principle arguing that simplicity is better than complexity. Named after 14th-century logician and theologian William of Ockham, this theory has been helping many great thinkers for centuries. Many industries swear by it.

How to Use in Design

In design, Occam’s Razor encourages us to eliminate unnecessary elements that would decrease a design’s efficiency. So, when two products or designs have the same function, Occam’s Razor recommends selecting the simpler. Therefore, when evaluating your designs, analyze each element and remove as many as possible, without compromising the overall function. This should ensure that you remain with elements you have minimized as much as possible but which still work perfectly

With the flexibility and power of the web and our design tools, it’s easy to get carried away. Designers can end up making very complicated sites or designs that may have a lot of functionality and information, but are difficult to use, build and maintain. One might think the site can do more, but it actually accomplishes less.

This is commonly an issue where companies feel the need to put everything they possibly could up on the website in the rare case that someone wants the information. In an increasingly competitive market, the pressure is on to get the message “out there”. What companies often ignore is that the overwhelming majority of the users will access about 20% of the content on the site (see the article on the Pareto principle; you’ll find the link at the bottom). Being ruthless about the value that a page or piece of content provides and removing anything unnecessary will make significantly stronger, more effective designs. It may be hard to weed out those unnecessary parts — you may say your business has nounnecessary parts; look harder.

For designers, using Occam’s Razor is all about careful thinking. It easier than you might fear. For instance, an editor-author who has a fiction career, but who also ghostwrites for clients, calls us. She tells us what she wants in her design:

Big handwritten font — autograph
Her photograph
Large-font mission statement
Contact information
Picture of the ranch where she works
Daily writing tip box.

Right away, we see we’ve got much to work into her design. Our author insists on an elaborate, decorative landing page. She loves her ranch and believes other writers will love it, too, so she wants a large photo of it.

We have to decide how to prioritize these elements. So, let’s see what’s necessary:

Author’s photograph
Signature/autograph—her branding
Mission statement.

These three parts embody her service. We want to present a famous author who can help other writers. However, we can move the unnecessary components to other pages using link buttons:

Daily writing tips
Contact Information
Picture of ranch.

We can show the ranch with her contact information, and we can perhaps design a daily writing tip as a pop-up.

The phone goes; our author loves what we’ve done with the design. However, she wants her ranch to feature on the landing page. We say: “We’ll see what we can do.”

Using Occam’s Razor, we see that we can fade the ranch into the background so that the images are there, but don’t distract. We want to cut out “noise”, which would distract/confuse users. So, we remove everything that would have got in the way. Our author friend is an enthusiastic person, but her enthusiasm gets the better of her. She’s scared of writers not contacting her. That’s the problem: she’s trying to push all her goodies onto the landing page, not appreciating that the flood of information will make user’s go: “What?” Instead of showing her good name and service in the best way, she got desperate and tried to squeeze ideas in, making a maze — walls, pictures, text, and spaces sprawling everywhere. Users coming to her site want help; they don’t want to have to work out how she can help them. Worse, it would tell them that this person can’t get ideas across properly. Why should they want her to write for them?

Occam’s Razor cuts down the walls that keep a message from getting through. Also, this rule speaks to the age-old saying that “A design isn’t finished when there is nothing more to add, but when there is nothing left to take away.” Design simplicity is elegant, sophisticated and much more effective than the complex decorative style that is so prevalent on the web these days.

Simplicity shows care, understanding and effort

Author/Copyright holder: 62 Models. Copyright terms and licence: Fair Use

It’s easy to think that the words “simple” and “easy” might show a lack of sophistication, or that working to produce simple designs means you don’t have to work very much. You might worry that a client will think that it took you 10 minutes to design something that he/she could have made.

Let’s do a reality check. Our author-ghostwriter has noticed the high number of hits her site is getting. She certainly doesn’t think that we’ve been lazy; she knows that we worked magic for her. The proof is in the number of page views — users have found it easy to navigate. Instead of shutting off on the landing page after squinting in confusion, many went on to learn more. The design’s simplicity, showing images and text in the best way (remember the other design principles here, such as the golden ratio), puts them at ease. They have a good user experience; most see her site’s simple, comprehensive design reflecting her skill as a no-nonsense writer who’ll work the same magic for them.

With this in mind, we can pat ourselves on the back for having done it for her. However, let’s look at what we did. We:

Asked how many elements the landing page needed,
including choices or decisions our friend wanted users to make. She wanted them to click on her daily writing tip box so they could see previous days’ tips. We linked this elsewhere.
Asked what she wanted her users to do the most.
She wanted people contacting her for help writing books. So, we highlighted the contact box, but we added one that took users to another page, where they could read all about her services first. This information was far more detailed than the simple description we put on her landing page: “Making manuscripts move into book and movie deals.”
Asked if a user, regardless of background, could get confused/frustrated. Her initial concept was confusing. We imagined approaching the design as ordinary people. Our friend wants to help other writers; well, if an 88 year-old author is looking for someone to clean up his manuscript, he might have had trouble with her design.

In summary, we translated what the writer wanted into a website that was easy to understand and use for the target users. Keeping in mind Occam’s razor, we focused on the key elements and keeping the interface simple.

The Internet is saturated with intricate and exquisitely complex designs. Many flash at us, offering all sorts of benefits, their designers not aware that it’s distracting, commonplace, and cheap-looking, Simplicity is refreshing.

Keeping Accessibility in Mind

Keeping our designs simple means that the websites we build are accessible. Creating a simple layout, with carefully placed images (remember the Rule of Thirds?) and simple, to-the-point, pithy text will keep users on the page.

Author/Copyright holder: Polar Gold. Copyright terms and licence: Fair Use

What gets them navigating to the call for action, such as the shopping cart depends on how you guide them. Did you:

Shave off the unnecessary bits?
Tone down anything loud or distracting?
Use plain language?
Would my 80 year-old neighbor understand what the website is about?
Would my grandmother be able to buy what I offer through my site and feel good?

Or, you can always make a “reality check”:

And above all, will my users understand the website’s added value and how it targets their needs and desires?

The Take Away

Occam’s Razor is a problem-solving principle devised in the 14^thCentury that states that simplicity is better than complexity. It has many applications, running from detective work to deductive reasoning about the cosmos.

We UX designers find that it empowers us to aim past the tendency to over-think our designs. It’s easy to focus on a cool idea, without standing back and asking if it’s essential to what we want to achieve. Occam’s Razor lets us approach and plan a design carefully. Our tendency is to keep adding what seem like great elements, sometimes worrying that if we don’t get all we want in one place, we’ll fail by a) weakening the message, or b) looking lazy.

Think of Apple. Steve Jobs’ philosophy embraced Occam’s Razor. His iPad and iPhone, for example, are the proof: one button on the front of a seamless, self-contained device.

By asking ourselves a few questions about our design and our users’ expectations, and reacting accordingly, shaving off the clutter or moving less important bits to other pages, we’ll serve our users and ourselves best. Remember, your design isn’t ready until you’ve found that you can’t take anything else out. This isn’t like repacking a suitcase to match a weight limit; it’s about deconstructing your design. When you’ve got your piece down to its bare essentials, that economy will pay dividends. By getting in ahead of your user’s eye, you can judge. Their page views and clicks will tell you if you’ve made the right choices.

Okay, so you’ve made it all the way here but you’re thinking: “I live by the principle of the simplest solution is always the best”. Where’s my take away? Now that you have a name for this principle, it is yet another advocacy tool to user with your client, boss, colleague. Whenever they insist about adding more functionalities, more elements, more and more, remind them of the Occam’s Razor.

References & Where to Learn More

Duvall, A. (2015). “Taking the Occam Razor Approach to Design.” Speckyboy Design Magazine. Retrieved from: http://speckyboy.com/2015/05/21/taking-the-occam-razor-approach-to-design/

McConnell, C. (2010). “Occam’s Razor: A Great Principle For Designers.” Web Designer Depot. Retrieved from: http://www.webdesignerdepot.com/2010/07/occams-razor-a-great-principle-for-designers/

Hunt-Barrom (2015?) “Occam’s Razor: More than just a Design Principle.” Clemson Edu. Retrieved from: http://www.clemson.edu/mapcux/classroom/transcripts/occam.pdf

Lant, M. (2010). “Occam’s Razor and the Art of Software Design”. Private Blog. Retrieved from:

Occam’s Razor and the Art of Software Design

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