Systems Thinking builds from a premise that the world is a complex system of constantly moving and interacting parts. There are an infinite number of variables that operate in cause-and-effect relationships that no single person can grasp. Yet we try our best to make sense of what’s unknown, often by taking shortcuts. Specifically, people tend to focus on what is seen – the more obvious, visible data that captures their attention – and ignore what is unseen – everything we do not know because it is less visible. We can peak into the unseen only by utilizing an enormous amount of reasoning, imagination, humility, and curiosity. But putting these into practice is no easy feat given our tendency to default to already established patterns of thought and ideologies that cloud clear thinking with all sorts of biases and emotional triggers.
The economist Frederic Bastiat popularized the distinction between the seen and unseen in his writings about government policies. Every event does not have just one cause, but many; not just one effect, but many. Some effects occur immediately with a cause – these are seen. The other effects emerge only later – these are unseen. It is the existence of these unseen but real mechanisms that lead to many errors in our judgment of how things work, especially in the social sciences.
Systems thinking is concerned with revealing truths of nature, where the unseen is just as important as the seen. To understand the ubiquity of the “unseen”, let’s look at 4 kinds of unseen phenomena:
- We see the short-term but not long-term consequences due to delays
- We see the effects on one group but not all groups due to cause-and-effect occurring in separate places as well as identity tribalism
- We see the visible events but not the opportunity costs (what would have happened otherwise)
- We see what people do or say but not their internal experience (what they value, believe, resent, fear)
Let’s explore each of these in more detail.
First, we see the short-term but not long-term consequences due to delays
A traumatic childhood experience carries impact years or even decades to come. An overworked startup employee burning the midnight oil for weeks shouldn’t be surprised when exhaustion and burnout take claim over his energy. Policies that “kick the can down the road” such as Social Security have been compared to Ponzi Schemes because they shift the economic burdens to future generations and a future leader – the original problem may be disguised beneath the angry cries of the loudest rhetoricians who misplace blame on a more immediate and visible source. Often times the more positive the immediate reward (the seen), the uglier the longer term consequence (the unseen). We see this dynamic play out in the form of various addictions that promise instant gratification but deplete long-term self will.
Second, we see the effects on one group but not all groups due to cause-and-effect occurring in separate places as well as identity tribalism
There’s data that’s in front of my eyes but I don’t notice, and then there’s data that I simply don’t have access to. People often don’t know what they don’t know.
A Dining Experience
When I have a lovely dining experience at a restaurant, I don’t know and can’t know all the details that contribute to making my experience enjoyable. Someone decided on the recipes, and they got their inspirations from somewhere else. The owner went through a process to select the servers, chefs, decorators, and suppliers that make my experience possible. Government regulations that I know little about affect the costs and quantity of the staff, the location, the prices of the dishes, and ultimately the owner’s ability to stay in business. My friends dining with me had experiences earlier in the day that affect their moods when I see them. The recommendation to eat here by a friend with “good” taste primed me to perceive the food to be “tasteful”.
After this experience, I give the restaurant a 5-star review on Yelp and sum up my experience in 3 sentences and 2 photos of dishes I ordered. I have more important things to do than write thorough Yelp reviews that hardly anyone has the time to read.
The Epidemic Plaguing Public Policy
When it comes time to vote on propositions, an optimist would like to believe that the public is weighing the short-term and long-term consequences of each proposition and the impact on all groups involved. In reality, each voter is considering how the policies will benefit their favored group(s) in ways that are seen.
“[There will be policies that] benefit one group only at the expense of all other groups. The group that would benefit by such policies, having such a direct interest in them, will argue for them plausibly and persistently. It will hire the best buyable minds to devote their whole time to presenting its case. And it will finally either convince the general public that its case is sound, or so befuddle it that clear thinking on the subject becomes next to impossible”
– Henry Hazlitt
When a state minimum wage law passes, the average citizen does not evaluate how this effects people in a different place. How will a minimum wage affect people in different geographic counties with different industries? How will it affect large corporations vs. smaller family-owned businesses? How will it affect an employer with high profit margins vs. one scraping by month to month? How will it affect the currently unemployed workers who have skills vs. those who do not? How will it affect non college-educated job-seekers vs. college-educated job-seekers?
A systems thinker asks: How will a given state-wide policy impact the attractiveness of living, working, and running businesses in a particular state relative to another? It requires significant empathy and foresight to reason out the impact of a seemingly simple policy on a population of diverse individuals living in diverse communities working in diverse industries having diverse values needing diverse things right now, all of who will have to respond to a seemingly simple one-size-fits-all minimum wage policy in diverse ways.
Third, we see the visible events but not the opportunity costs (what would have happened otherwise)
We naturally focus on what exists right now that we forget to imagine what could have been instead – it’s literally unseen. Every day you spend at your current job is another day not spent doing something else that you may enjoy more. Our time investment in certain social events is time not spent with others. Sometimes it takes a painful event such as a layoff or breakup or health scare to wake us up to options that we didn’t see before.
“War Creates Jobs and Boosts GDP”
We see this often in the area of public policy when resources are channeled toward certain causes and proponents point to all the visible good results before them. Going to war may create jobs and increase economic activity due to the surge of hiring and spending in the defense industry – these things are seen. We can cheer for the resulting lower unemployment rates and higher GDP. But how about the unseen? We don’t know what jobs those working in defense could have been doing instead with their diverse talents and dreams. We don’t see what capital investments would have been made had peoples’ money not been taxed and distributed toward war. It would be naive to assume people and capital would just sit idly if a war had not been declared.
And when the war is finished, some will declare it wrong for private defense companies to lay off thousands of workers whose services are no longer needed. What is seen are those people now out of jobs, and since there is power in organizing large numbers of emotionally charged people who feel wronged, those fearing joblessness often form special interest groups to protect the jobs of workers to continue employment for a service that has willing customers. So they benefit by lobbying for policies that create artificial demand to be paid to do something that no one wants. To the extent they succeed, they maintain the status quo in a world that is naturally dynamic and constantly changing. What is unseen are the new opportunities those workers missed to provide other services that people actually want. Change and growth can be challenging especially during times when one’s resources are constrained, but resisting natural forces of change stifles self-development and the opportunity to serve the greater society.
Confusing Schooling For Learning
We tend to hold dear to our traditional education institutions of K-12 schooling followed by a four-year college degree – that path is often endorsed and therefore seen. Because we confuse schooling for learning, we assume more school is good. What’s harder to imagine is the unseen – what would happen if we didn’t have mandatory schooling constraints and the expectation that college is the best route? What if we got rid of grade level segmentation, prepackaged standards of education, laws restricting how and where parents send their children to learn, and regulations that make it difficult and costly to open education institutions that don’t fit “acceptable standards”, which often means tradition?
We get used to the way things have been done, losing context of how and why particular institutions were first created and how social systems operated in a prior time. We then form strong mental models in favor of protecting what has been over what could be. What is unseen are the opportunities not pursued due to fear of the unknown.
Politicians Benefit from the Seen
Politicians are elected with the expectation that they do something – often this means do ing more, not less. And this works out for them because policy beneficiaries are often seen, and those beneficiaries will know who to vote for and who will be receptive to their lobbying efforts. The policy’s victims are often unseen. Most often, these victims don’t know whom to blame for their calamities precisely because it is hard to see the key causal mechanisms that happened in a prior time or place. The victims, suffering and angry, often scapegoat the wrong person for their felt problems, or create abstract categories to place blame – such as the corporations, the rich, or the patriarchy. They often don’t realize that the policies they themselves supported contributed to the cascade of unseen negative consequences they are now experiencing.
Fourth, we see what people do or say but not their internal experience (what they value, believe, resent, fear, etc)
Because each individual is unique in her values, preferences, and fears, we often cannot predict what any one person will do, and certainly cannot predict what a group of people will do in the future. Their internal beliefs are unseen. What we can see are the visible actions they take and information they choose to share, but these seen bits are simplifications of the unseen inner motivations. Each person walking around is carrying identities, ideologies, and a cocktail of triggers and biases accumulated through every experience she has had. Unless you are an acute observer of human behavior and know each individual inside and out, you only scratch the surface of what’s going on in another’s mind.
If you can understand each person’s fears, much of their seen behaviors make a lot more sense. We then have the ability to move from judgment toward understanding. In Silicon Valley, there are people who fear Trump, people who fear being judged for supporting Trump, people who fear their company is burning too much cash, people who fear they can’t afford the standard of living, people who fear Alpha Male characters in the workplace, people who fear emotionally sensitive women in the workplace, people who fear not being appreciated by their managers, people who fear loneliness, people who fear the impact of machine intelligence on the workforce, people who fear the growing technology-driven community, people who fear the Social Justice community, people who fear they are wasting their time not doing work that matters to the, people who fear their careers will never pay enough to be sustainable, etc etc. All these collections of unseen fears can exist within the members of a team while meeting together to talk about progress on work priorities.
Complex social systems are unpredictable precisely because people have diverse unseen motivations that can change any moment. People don’t always say what they think or do what they say. We too often make assumptions about the unseen based only on the seen, and our glimpse of reality – the true drivers of human behaviors – is outside of reach from our perceptions. We don’t have a universal agreed upon standard for greater or lesser happiness other than our individual judgments of value, which are different for various people and even different for the same person at various times. Unfortunately, ethical movements such as utilitarianism that promote acting in a way that brings the greatest good to the greatest number of people overlook the premise that what is “good” is subjective to each person at a particular moment in time. One person cannot assume she knows what is good for others and what is good for the greatest number because people are not homogeneous.
Predicting Hillary vs. Donald
The well-known statistician and sabermetrician Nate Silver’s probability prediction in favor of Hillary Clinton winning the presidency was misleading because empirical statisticians are only trained to make sense of the seen – in this case, past poll results. It doesn’t matter how precise his predicted probability of Clinton winning is (71.4% on election day) if the model he uses ignores that there is an infinite amount of unseen information about human values of diverse Americans. The precision of his probability creates a false impression that the prediction is based on a rigorous and relevant methodology. But an election that is one single event based on the sentiments of millions of people, where any random event like a public relations scandal can sway public opinion in either direction, is not the same mathematical exercise as predicting which baseball team will win in a season of many games containing a small group of players performing in a limited action environment whose average gameplay statistics are well catalogued and fairly consistent. Nassim Taleb, author of The Black Swan, pointed out that in the case of this U.S. election where there was too much volatility in public sentiment toward each candidate day over day, the probability of either candidate winning is 50% – a coin toss. This is because we cannot predict with any degree of certainty what will happen in the public’s collective sentiment leading up to election day – there is too much unseen.
In the months prior to election day, three people in particular had gained attention for their contrarian predictions that Donald Trump would win. They didn’t use statistics based on the seen. They instead incorporated social attitudes and charisma, understanding the law of human nature that we are strongly motivated by emotions. Professor Allan Lichtman developed a model with 13 Yes-or-No questions based on a central premise of social sentiment that election victories are largely influenced by how people felt about the incumbent Party in the White House. The questions dealt with charisma, social unrest, and scandal. Answering these questions does not require the detailed calculations of hyper-intellectual models that don’t acknowledge the role of emotions.
The documentary filmmaker Michael Moore also predicted a Donald Trump victory based on analysis of social attitudes including “the angry white man” problem and Hillary’s charisma problem. Scott Adams, the creator of Dilbert and a trained hypnotist, called Trump’s victory early because he recognized Trump’s wordplay resembling that of a master persuader. By treating facts as obsolete, Trump was able to bend reality as needed. Rather than waste time speaking to people’s reasoning faculties, he appealed more directly to the unseen – their identities and emotions. In doing so, he gained more trust from swing state voters than “crooked Hillary” could.
Dangers of the Seen
The greatest impediment to seeing the unseen is the insistence that there isn’t much more to see. Some people who limit their perspective to the seen insist they have all the information they need. They then draw conclusions about reality – the seen and the unseen – based only on the seen.
Many of these people hold advanced degrees, teach in universities, write influential books, and advise on public policy matters. The public views them as “experts” on topics because they tout credentials, wear fancy suits, and use vocabulary that people don’t understand. But if we stop judging their credibility by the seen and look for the unseen – their mental models, the meanings of the words they use, the soundness of their logical arguments, the validity of their methods – we’ll be able to think more critically about the content of their arguments and be less swayed by our own false beliefs in their superiority.
Empiricism Does Not Have All The Answers
Think about what this means when we try to create detailed empirical and statistical models to explain complex social systems. If much is unseen, then many variables are either not easily measurable, or they’re not obvious to the researcher that they should be measured to answer the question at hand. We are lucky if we can even foresee the important unseen factors. And in order to measure something, we must first have a categorical construct of what it is we are going to measure, which leads experts trained in statistics to only measure what can be seen. If you try to argue otherwise with an empiricist, she often asks you for “evidence”. She mistakes absence of evidence for evidence of absence.
This problem has been amplified with the growth of Big Data and the unhealthy worship of algorithms to do our thinking for us. The management consultant Peter Drucker called the computer the “mechanical moron”. Algorithms can handle quantifiable data with speed, accuracy, and precision, but the relevant unseen events are often qualitative and incapable of quantification. They are not yet “facts” because they have not been defined, classified, and determined relevant. To be able to measure something, the scientist must first have a concept of it by abstracting from the infinite welter of phenomena a specific aspect which must first be named and then quantified.
While being data-driven contributes to the success of many Silicon Valley companies such as AirBnB and Uber, these same entrepreneurs started off without data. They had to imagine a future that did not yet exist, convince prospective customers to change habitual behaviors, and introduce new categories in peoples’ thinking. The act of creating anything new requires appreciation of the unseen, and businesses that want to continuously improve must ensure balance of the seen metrics and unseen possibilities.
Seeing the Unseen
There’s something beautiful about the existence of the unseen – it is what allows for life to be complex and unpredictable. No matter how much we try to predict and control reality, we’ll end up being wrong often. So get curious about the unseen. This curiosity will open your mind and aid your ability to learn and adapt to new, previously unseen information. It gets you in the habit of asking “What don’t I know?” and inspires your search for more information. At first it may seem difficult to draw any strong conclusions, but over time, you’ll have experience of noticing recurring patterns and be able to predict the likely long-term consequences of an action. People who have strong intuitions have cultivated their abilities to see what’s unseen to others.
A systems thinker learns to see the unseen. In doing so, she foresees the unintended consequences that confound others. Where others are looking for empirically observable data, a systems thinker develops true wisdom by seeking to understand reality – the seen and unseen.