Are you a life saver or a life enhancer?

Systems-level and analogous problem solving explained

The remote island of Rapa Nui, located approximately 2300 miles off the coast of Chile, has a fascinating security system. Dotting the coastline of this raw landscape are approximately 900 stone sculptures carved to resemble the faces and torsos of men. Each Moai, as they are called, represents a particular deity or figure of importance that the Rapa Nui people believe helps protect their home and culture. The adoption of occult carving practices is not uncommon in isolated societies; however, what is unique about these personified stones is the fact that they weigh roughly 80 tons a piece. Naturally, of all the queries that arise from these sculptures the question regarding their seemingly perfect placement around the island percolates to the top — How did the Rapa Nui people move 72,000 total tons of stone about the island? Scientists have proposed and tested several possibilities and have ultimately come to the conclusion that by using logs as makeshift wheels in conjunction with ropes that stabilize the massive stone heads, the island people would have been able to move the statues most efficiently. The great minds of this civilization understood that they needed to counteract the forces of gravity and resistance-causing friction (although I’m sure they did not have technical words for those entities then) and administer their own force to initiate any kind of movement. So, they developed a system that, through cause and effect, would appropriately maneuver each Moai to a desired location.

Rapa Nui represents a prehistoric example of systems-level (systematic) thinking. By breaking down the problem of translocating the Moai into its constituents (gravity, friction, force, and mass), the people of Rapa Nui were able to solve the most vexing problem facing their civilization. Of course that’s not the only useful problem solving method. It often helps to build off of already known information in order to help sort through an issue. For example, the cotton gin, the innovation that expedited the cleansing of cotton by a hundredfold and catalyzed the entire production line of textiles, is popularly believed to have been invented by Eli Whitney. However, although Whitney did patent the modern cotton gin, he had many predecessors who already relied heavily on single and double cotton rollers (wood and metal) to crudely stimulate the textile process. What Whitney did that was extremely significant is he identified the qualities that the existing cotton gins lacked, and refined his cotton gin so it included a more methodical, machine-like way of separating seeds from cotton. By utilizing already known information, Whitney amalgamated the pre-existing technologies he knew would benefit the production of cotton into his gin. This method of problem solving is known as analogous problem solving and it represents the grand majority of the critical thinking we do in everyday life. By taking a concept, idea or entity we already understand thoroughly and employing said concept, idea or entity as a blueprint for other problems that are difficult to reason through, a basic understanding can be garnered more easily.

Problem solvers often do not have to make a conscientious effort in order to utilize analogous thinking practices. The human brain is naturally hardwired to compare known and unknown entities in an effort to identify similarities or differences between the two. However, like almost everything in life, there are certain people who immerse themselves completely in this frame of thought and excel at this particular method of problem solving. Take tech-guru and the brain behind Apple, Steve Jobs, for example. Jobs created an empire of technologies ranging from his first computers to the iPads and iPhones that can be found abundantly throughout the population today. Jobs is commonly called a genius for his uncanny ability to think innovatively and create products that the masses want, and of course he is indeed a brilliant man. However, what Jobs has truly mastered is the ability to apply analogous reasoning at a Macro-scale. His true genius lies not in the success of his products, but rather the logic he uses to bring them to market.

Over the course of this analysis, it is my goal to illuminate the most effective methods of problem solving (systemic and analogous), identify the differences between them, and expound upon their practical uses in society. Any insight you gain from this piece regarding your own personal problem solving methods could be a useful tool to incorporate into future endeavours, and I encourage you to employ what you learn from this piece in your everyday life. To begin, I would like to continue with the analogous thinking paradigm I spoke of earlier regarding Steve Jobs. In the New Yorker article “The Real Genius of Steve Jobs,” author Malcolm Gladwell provides a holistic profile of Jobs, illustrating both his habitually arrogant side and his oddball, genius side. In the excerpt below, Gladwell highlights the essential premise behind analogous thinking and how Jobs developed a proficiency for employing it in everything he created.


1. “The Real Genius of Steve Jobs”

Malcolm Gladwell. The New Yorker, 12.2.16

“Jobs’s sensibility was editorial, not inventive. His gift lay in taking what was in front of him — the tablet with stylus — and ruthlessly refining it. Was Steve Jobs a Samuel Crompton or was he a Richard Roberts? In the eulogies that followed Jobs’s death, last month, he was repeatedly referred to as a large-scale visionary and inventor. But Isaacson’s biography suggests that he was much more of a tweaker.

Comparing Jobs to industrial revolution innovators begs the declaration of Apple’s necessity in today’s society, but as the quote states, Jobs really got the ideas for all of Apple’s products from pre-existing entities. Gladwell refers to Jobs as a tweaker because of his role in refining products that were inefficient in his mind’s eye. Through analogous reasoning, Jobs recognized the best characteristics of existing products and combined them into an innovative creation, which often resembled a refinement of something already on the market — a better touchscreen phone, a more efficient computer, etc. In another New Yorker article titled, “Apple: You’ve seen it all before, and nothing else like it,” author Joshua Topolsky further corroborates the idea that Job’s true genius lies in his ability to apply analogous reasoning to existing products rather than invent something completely new.


2. “Apple: You’ve seen it all before, and nothing else like it”

Joshua Topolsky. The New Yorker, 12.2.16

“That’s partly Apple’s magic show: being able to blend the familiar, the known, and the obvious with something (even a little bit) totally new… You’ve got to hand it to Apple: the company has the uncanny ability to make ideas that you’ve seen and heard before seem like things that have just sprung, fully formed, from the elastic mind of Jony Ive (Apple’s design team leader).

By combining known technologies (phones, watches, music) with technologies that are unknown to that particular sector (apps like mobile banking, better cameras, touchscreen watches, etc.), Jobs and the entire Apple team use analogous reasoning to excel in their field. Jobs’s refinements are now tallied in the millions globally, and the widespread dispersal of his innovations demonstrates the efficacy of analogous thinking in identifying solutions targeted at expediting communication and augmenting the ease of life.

To contrast the analogous thinking employed above, now consider critical thinking that can occur independently of previously known information. This method of problem solving, which was identified in the opening paragraphs as systems-level thinking, relies instead on a keen ability to identify a problem’s constituent causes, and then consequently, the actions that could be taken to address these underlying issues. An excellent example of an individual who has become impressively adept in this frame of thought is Tesla CEO and founder Elon Musk. Musk has gone on to invest both his time and money in solar technology development, sustainable energy research, and even his own personal space initiative, due to his strong belief that these are the underlying issues that society must address in order to survive. In each of his individual projects, Musk always works through problems by relying on basic principles of physics and chemistry in order to establish a cause and effect relationship that will ultimately reveal a beneficial solution for the human race. In a New Yorker article written by Tad Friend, Musk’s plan for a vastly more efficient and potentially life saving method of transport (the Hyperloop) is broken down by the author.


3. “Is Elon Musk’sHyperloop a Pipe Dream?”

Tad Friend. The New Yorker, 12.2.16

“What makes the Hyperloop exciting, as a napkin doodle, is Musk’s ingenious workaround for the Kantrowitz limit, which is the top speed that a pod can go in a given tube due to the resistance from the wall of air it compresses as it moves. (Think of the effort it can take to push air from a syringe.) An electric fan on the pod’s nose would suck in the high-pressure air, which would then get blown out underneath the pod, buoying it like a puck on an air-hockey table. It’s a brilliant judo move.”

What makes this explanation so fascinating is that the author uses analogous reasoning to explain the complex concept (Kantrowitz Limit) to his audience; however, it is apparent that Musk’s plans are entirely based on the principles of systemic thinking as he clearly identifies the problems with his plans for the hyperloop (air pressure-causing resistance) and then appropriately formulates a solution (using the air as a propellant/levitation catalyst) due to his understanding of the underlying issues.

The essence of systematic thinking is the ability to identify intrinsic truths in a problem and reason up from there, as opposed to the reliance on other entities that is so prominent in analogous thinking. This point was captured in a recent TED talk in which Elon Musk was interviewed regarding his ability to so sufficiently develop solutions for global problems. When asked how he has been able to repeatedly take such giant leaps of faith in terms of investing in hyper-risque projects, and in turn succeed in such undertakings, Musk responds by noting his reliance on systems-level thinking.


4. “Elon Musk: The Mind behind Tesla, SpaceX, Solar City…”

Elon Musk. Ted Talk, 12.2.16

“I do think there is a good framework for thinking, it’s physics, this sort of first principles reasoning… What I mean by that is boil things down to their fundamental truths, and reason up from there as opposed to reasoning by analogy … which essentially means kind of copying what other people do with slight variations.”

Obviously this is not meant to be a jab at anyone who commits to the analogous thinking framework, but it does illuminate a certain criticism that genius analogous reasoning yields fairly often. Take another extremely successful entrepreneur and analogous thinker, Mark Zuckerberg, for example. Zuckerberg is the renowned CEO and founder of the social network Facebook. His innovation has helped millions of people from across the world connect with one another, and he has effectively shortened the distance that formerly separated the seven continents by providing a medium through which people could interact in seconds rather than days or weeks. However, even the legitimate parent behind Zuckerberg’s claimed brainchild (Facebook) is not explicit. A few years ago, news surfaced that Zuckerberg may have stolen the idea for a global social network from a few of his colleagues while at school in Boston. In a recent New Yorker article titled “The Face of Facebook,” author Joshua Topolsky explores this topic of intellectual plagiarism while also demonstrating the often close association between “copying” and analogous thinking. The quotes below from this article highlight the analogous thinking employed by Zuckerberg in his creating Facebook, as well as in the programming precursors to his masterpiece.


5. “The Face of Facebook”

Joshua Topolsky. The New Yorker, 12.2.16

“Zuckerberg had a knack for creating simple, addictive software. In his first week as a sophomore, he built CourseMatch, a program that enabled users to figure out which classes to take based on the choices of other students. Soon afterward, he came up with Facemash, where users looked at photographs of two people and clicked a button to note who they thought was hotter, a kind of sexual-playoff system.
“As he tells the story, the ideas behind the two social networks (Harvard Connection and Facebook) were totally different. Their site, he says, emphasized dating, while his emphasized networking.”

Similar to Jobs, Zuckerberg’s genius ability lies in his ability to amalgamate the best technologies of the time and tweak until the finished product is perfect. Zuckerberg didn’t need to break his concepts down in order to reason up to the creation of Facebook because he already knew the mechanisms of operation behind other social networks at the time (Harvard Connection). He therefore, could reason through analogy that if the others could succeed with dating as the central concept, networking would work as well. He similarly, did so with Facemash (2002), which is analogous to early forms of electronic dating and hookup applications such as Match.com (1995) or eHarmony (2000). However, with all of these technologies influencing one another so poignantly it becomes ambiguous and, frankly, unimportant who the original innovator is, and much more about who is able to execute the idea in the most appealing fashion. In the case of Facebook, it was Zuckerberg and his analogous reasoning that brought the idea of a global network to life.

Analogous thinking can be used for much more than just technological innovation of course. In the New Yorker article “How David Beats Goliath,” author Malcolm Gladwell describes the story of a girls basketball league in which an extremely young, undersized and underrated team is able to compete at a national level because of their coach’s ability to reason analogously. Vivek Ranadivé is an Indian born programmer who attended the Massachusetts Institute of Technology and, after college, started a “real-time” processing company in Silicon Valley, CA. When his daughter and her friends needed a basketball coach for their league he stepped in, though he knew little about how the game was played. Taking what he already knew from cricket and soccer, as well as his “real-time” processing company, Ranadivé began to coach the girls to constantly employ a full-court press on defense, a technique that utilized both time and space more efficiently than the half-court press alone, much like his business.


6. “How David Beats Goliath”

Malcolm Gladwell. The New Yorker, 12.2.16

“Ranadivé was puzzled by the way Americans played basketball. He is from Mumbai. He grew up with cricket and soccer. He would never forget the first time he saw a basketball game. He thought it was mindless. Team A would score and then immediately retreat to its own end of the court. Team B would inbound the ball and dribble it into Team A’s end, where Team A was patiently waiting. Then the process would reverse itself. A basketball court was ninety-four feet long. But most of the time a team defended only about twenty-four feet of that, conceding the other seventy feet.”

In the article, Gladwell states that Ranadivé recognized basketball as the inefficient batch processing that dominated the stock market and travel industry prior to his company’s emergence. Therefore, through analogous reasoning, Ranadivé employed similar solutions that he used in business for his daughter’s basketball team, and he saw similar success.

Returning to Musk and systems-level thinking, one can begin to see the discrepancies between the two methods of reasoning. These differences were further ascertained in a recent interview between Elon Musk and Sam Altman. Altman, the CEO of Y-Combinator, is a startup catalyst and advisor responsible for aiding and sifting through each years crop of hundreds of startups in tech-centered Silicon Valley. Together he and Musk started a technology initiative known as OpenAI aimed at exploring the future of artificial intelligence. This interview was conducted in an effort to explain what their mutual goals were for the project, but what it really does is highlight the intelligence and reasoning style of Musk. The quote below is Musk’s incredibly insightful response to Altman’s query regarding Musk’s ability to develop solutions that succeed flawlessly.


7. Elon Musk Interview

Elon Musk and Sam Altman. Y Combinator, 12.2.16

“Whatever this thing is that you’re trying to create, (what’s important is) the utility delta, compared to the current state of the art, times the number of people it would affect… Something that makes a big difference but only affects a small number of people is great, just as something that makes a relatively small difference but affects a vast number of people. Both have relatively the same area under the curve.”

One can clearly see the quantitative approach Musk takes to every decision he makes and how he utilizes basic principles to reason through the complex problems facing the world at large (in this case, basic algebraic principles). However, he does not limit this method of reasoning solely to his work; rather he employs it in his everyday life decision-making. Later in this same interview, Musk was asked what led to his decision to drop out of graduate school (Stanford) and enter the blooming technology field that surrounded him. “There does seem to be a particular time for technologies, when you reach a steep point in the inflection curve, and I didn’t want to complete my years at Stanford and just watch it all happen…” His terse response highlights the systems-level thinking his mind is perpetually immersed in and how it enables him to excel in problem solving as well as decisions-making in his field.

Clearly both analogous and systemic thinking demand a high level of intelligence, but the basic fact of the matter is that each method of reasoning involves a different form of intelligence. In the days of Isaac Newton or Albert Einstein, intelligence was based on a single general factor, which was one’s ability to think logically. This logic typically accepted an understanding of math, writing, and/or science, but all other areas of study were excluded as they were not considered to be truly reliant on intelligence. Therefore, Einstein and Newton are often emphasized as the geniuses of this time period while musicians and artists were considered mere peasants. However, in the year 1983, Howard Gardner proposed a new theory of intelligence that would revolutionize the way conventional scholars viewed mental capacity. The paradigm at the time held that intelligence was a single, general ability, dictated by the g-factor, which is one’s general mental ability. In contrast, Gardner’s new model proposed not one, but eight categories of intelligence, each a combination of a particular discipline (language, math, music, etc.) and the general mental ability of said individual. Gardner’s new classifications included musical-rhythmic, visual-spatial, verbal-linguistic, logical-mathematical, bodily-kinesthetic, interpersonal, intrapersonal, and naturalistic. By adjusting the paradigm to include the area of interest that a person is most comfortable with, Gardner stipulated that intelligence is not a rigid entity like intellectuals in the 1600s believed it to be, but instead, a very pliable trait that differs from person to person. Over 30 years later, this proposal falls in line with discrepancies between analogous and systemic thinkers, and explains why they are considered to be equally genius methods of problem solving despite being so vastly different in their approach.

An interesting feature to note about the success of the individuals above is that each of their endeavours is considered to be in a separate area of expertise. That is to say that they are not rivals in the technological field, and they certainly don’t step on each others toes (Elon Musk has no competition in the area of privately owned rocket technology other than national governments). This suggests that a correlation can be drawn between the method of problem solving and the type of problem that needs to be solved. To provide an example, consider the problem that the systemic thinkers of Rapa Nui were attempting to tackle when they used a system of logs and ropes to efficiently place massive stone sculptures around their island. The entire purpose of such an impossible task was to protect the island and its people from the evil beings of the outside world and to ensure safety. In essence, the assertion being made is that by erecting these massive statues, the people of Rapa Nui were proposing a solution to save their lives. It is unimportant that, in reality, these statues may have had very little to do with their actual safety because the decision to construct them demonstrates the connection between systems-level thinking and the attempt at life saving/protecting. With reference to systemic thinking in today’s society, this same postulate can be applied. Elon Musk uses systems-level reasoning in an effort to design and build technologies that will ultimately save our planet and race in the long run. His advancements in solar technology, electrically powered vehicles and space travel are all strictly directed at curtailing humanity’s current trajectory towards self-destruction, and to propose solutions that will solve global survival problems.

Analogous thinking, on the other hand, is used for a different type of problem than systemic thinking. To recall the example of Eli Whitney’s cotton gin and the analogous reasoning utilized in the creation of this particular innovation, it becomes clear that the effect of such a crucial entity was directed strictly at increasing the production of textiles and making the lives of cotton farmers easier. Applying this same theory to an analogous thinker in today’s society, such as Mark Zuckerberg, the problem can be seen as a lack of global connectivity in an epoch of technology, and Zuckerberg’s solution (Facebook) can be viewed as a network that connects the world and facilitates the life of its users. The theory behind this form of reasoning is that analogous thinking is particularly useful in yielding a solution that expedites a process in life as opposed to actually saving a life. In the New Yorker article “Facebook Live: Now you can never leave,” Facebook’s grand master plan of expansion is depicted as an array of networks that help to connect different areas of the user’s life into one platform, expediting the time spent on the web. Zuckerberg’s dream for Facebook is best illustrated by the quotes below, each of which demonstrates how the analogous thinking process has ultimately produced a solution that makes the lives of people easier.

8. “Facebook Live: Now you can never leave”

Joshua Topolsky. The New Yorker, 12.2.16


Conclusion

Mark Zuckerberg, Vivek Ranadivé, Elon Musk, Steve Jobs, Eli Whitney and the people of Rapa Nui were not the first people to invest in their respective frames of thought, and they will certainly not be the last. Though they may all be considered geniuses in their own right, it is important to recognize that the reasons behind their being considered as such should be due not so much to what they have created, but rather to the route of critical thinking they took to get to a solution. That is to say, the journey of reasoning is more important than the destination. Regardless of whether analogous or systems-level thinking is more your forte, both represent legitimate means of critical thinking and both have practical applications in everyday life, albeit one is more directed at enhancing life whereas the other at saving it. Aristotle was one of the early individuals to espouse something known as the First Principle frame of reasoning, which closely mirrors the systems-level thinking that Musk utilizes today, illustrating the perennial and metamorphic nature of critical thinking. As time progresses inevitably onward, it will be fascinating to see how something as ageless as a paradigm of thought, such as this first principles reasoning, is applied to new challenges and is molded into a slightly new shape in order to conform with the novel problems of an ever-evolving society.