The quest for truth is as old as our species, and likely far older. Organisms have always used misdirection, misrepresentation, and outright deception to get what they want and need, whether it be food, shelter, or mates. Modern humans, however, show a particular affinity for fabrication. For some, lying is a pastime, an entertainment; for others, it’s a sign of emotional illness, a compulsion. Yet everyone is less than completely honest at least some of the time, and correctly assessing reality is of critical importance if one is to flourish in complex environments in which few are expert in more than a few areas. Sussing out truth from fiction, therefore, is a constant effort within our brains, particularly when we’re weighing direct statements from one another.
This is not a trifling issue. In the world of 2019, with the exponential growth of information sources, we’re all having to suss more and more, faster and faster. The real and the fake are increasingly intertwined, to the point of being indistinguishable from one another. Even worse, individual biases, preferences, and styles (among innumerable other factors) can lead to assumptions, which lead to conclusions that just validate the original assumption. One person’s well-vetted report becomes another’s thinly disguised piece of propaganda. Getting to a reality that at least most of us can agree on is increasingly difficult, but it’s never been more important.
Quality’s holy grail
A large part of my professional background comes from the world of quality assurance, which pursues verity with a vengeance. That makes sense, because without a complete and accurate understanding of the true performance of a process, one cannot hope to improve it.
For most of the industrial age, the dearth of data was the death knell of pristine quality, acting as a sort of speed limit for continuous improvement. The tools of the trade—the hardware measuring activity, and, later, the software that helped interpret that acquired data—just weren’t fast or robust enough to offer more than scattered snapshots of any given process. Those snapshots, correctly deciphered, provided a piece of reality, a small slice of truth, but there was never enough quantity or granularity to push quality to its outer limits. Getting enough data to really understand a process from the inside out became a holy grail of sorts for quality people.
But then, a bit more than two decades ago, things began to change. The accuracy and speed of measuring equipment began to soar, and it was matched by the rapid expansion of functionality and power in software. Data that once trickled in grain by grain soon began to drop in clump by clump. Eventually it poured in boulder by boulder until it collected in huge mountains. Quality engineers and data scientists went from delight to apprehension to something akin to fear. “How are we going to sort through all this stuff?” they wondered. In the years shortly after Y2K, the age of Big Data had fully arrived, by which time the holy grail had been transformed into a holy terror.
Yet today, data analysis is one of the key disciplines for any quality professional. We reached this point because the tools continued to evolve, as did the attitudes of the women and men doing the work. The point of Big Data is not to get and use all the data possible. That’s impossible. No, the job is to use the software, to construct programs, and to distill all that data into information that’s accessible and meaningful to whatever process you are trying to improve. Discernment was, and still is, the order of the day.
Big Data software systems help quality managers make sense of the sheer weight of data and better understand the actual performance of any given process by utilizing tools like machine learning, sampling, and predictive analysis. That works fine in, say, a manufacturing environment where facts are valued and indisputable; as we’ll see, however, these tactics tend to be suboptimized in situations where truth is transactional, fluid, and debatable.
Media’s big ugly truth and pretty little lies
Anyone who has reported anything professionally will tell you that producing news for a mass audience is more art than science.
Although this may be shocking for some, it seems self-apparent to me. News emerges from multiple sources, some of whom are quoted directly and some who wish to remain anonymous. All are vetted to the best of the ability of the reporter, not to mention layers of fact-checkers, editors, and sometimes, lawyers. But bear in mind that even the most honest and well-intentioned source can be mistaken, or confused, or unintentionally misleading.
But OK, let’s assume all sources are completely unimpeachable. Once the story with these unchallenged facts moves up the chain of command, a line editor plucks away at it, changing some words and tightening up the structure. Next a story editor or two takes a whack at it, blurring context, shuffling paragraphs, shifting tone. The art director chooses images that, in about equal measure, illuminate and obfuscate the underlying message of the words. Finally, a managing editor decides where and when the content will run, and at what length.
The sad, unattractive, and unvarnished truth about the media is that it cannot be truth—not the whole truth, anyway. It’s not intentional, and it has less to do with bias than it does with the children’s game of Telephone. Perception becomes a form of reality that carries the consumer of said news item further, not closer, to any original truth, if original truth actually existed in any recognizable form at all.
From ugly truth let’s go to pretty lies—which are sometimes indistinguishable from one another. Many relatively well-trusted “news” sources intentionally mislead their consumers, generally to make a buck or to push a cause. And it’s not just words. Photos and even videos are easily doctored, a process which is getting better by the day. Soon bad players will be able to make it appear than anyone said or did anything in the present or the past… and they’ll have the evidence to “prove” it.
Again, these things (the ugly truth and the pretty lies) are easily conflated by a consumer’s eyes, or nose. Both have the sweet scent of possibility, which, depending on one’s perspective, can have a similar aroma to the rotten stench of bias and propaganda.
Which brings us to the root of the problem: How does one tell the difference between these two polarities and make informed decisions about government, or health care, or finance, or, well, anything?
Do consumers of news need discerning and robust systems akin to Big Data analytics to sift the news for us, separating the verifiable wheat from the disreputable chaff? If so, who judges which is which and then crafts the algorithms for these programs?
Controversies abound regarding whether large media companies like Facebook and Twitter are doing their best to identify the sources of the information provided on their platforms. On the flip side of this issue, there’s a fair argument to be made that these platforms can go too far in removing the full spectrum of opinion, which has the effect of further fragmenting news sources into component pieces. As a consequence, users need not suffer from the discomfort of encountering opinions that run counter to their own.
Five or six decades ago, these multiple channels of information didn’t exist. A few monolithic media entities—CBS, The New York Times, Life Magazine—covered the stories of the day, often in extremely similar ways. These media leaned left or right in a general way, but mostly they agreed on what was fair game to report on, and what those stories meant.
All this demonstrates that the media industry and the quality industry operate in significantly different ways, and that trying to adapt an understanding of truth from one doesn’t necessarily apply to the other.
Volatility, uncertainty, complexity, and ambiguity
Sometimes, the truth is not only unknown, but quite possibly unknowable. What does that mean in trying to predict or manage ongoing systemic change?
Fortunately, the U.S. Army has developed an acronym that can help us make sense of a world of apparently conflicting data points. It’s known as VUCA, which stands for volatility, uncertainty, complexity, and ambiguity. When thinking about the nature of reality and truth, the fog of real-time decision making (whether on the battlefield, in the boardroom, or at a fast-approaching highway overpass) calls for a flexible structure that can quickly make order out of chaos. That’s what VUCA is designed to do.
Large systems with lots of real-time velocity tend to be confusing and unstable. Few people’s minds work well under such conditions, so VUCA slows down the process of decision making by relying on anticipation and awareness. That requires a deep and dispassionate analysis of the situation both before entering a state of change, and most importantly, during it. Asking laser-focused questions and pushing for similarly clear answers (given what is, inevitably, a limited set of facts) is key to performing this process well.
We all deal with VUCA all the time; unfortunately, we often run afoul of clarity by guessing or hoping our way toward decisions and/or trusting in the assessments of others who may be inexperienced or deceptive. That’s the way many of us consume and process information: We see a small section of a large picture, don’t probe long enough or hard enough to expand our field of view, and consequently make an impulsive decision about what’s going on and what it all means. That’s a recipe for disaster whether the system is a business enterprise, a battle, a political campaign, or life itself.
VUCA describes a fuzzy world in which all possible outcomes are happening at all possible times. In such an environment, objective truth is of paramount importance even if, strictly speaking, such a thing is almost impossible to determine. Yes, this pursuit will be challenging and never ending, and the results will never be perfect. Yet pursue it we must, for it offers our best hope to lift the fog, if only for a moment, and gain some holistic perspective on reality that can be put to practical use.
Rashomon and the power of faith
Back in 1950, the brilliant quality engineer Joseph M. Juran re-interpreted the Pareto Principle, formerly consigned mostly to the field of economics, by using the concise phrasing of the “vital few” vs. the “useful many.” Many people know this as the “80-20” rule—that 80% of effects, good or bad, come from 20% of causes. Brought down the field of quality, it means that a large number of problems stem from a relatively small number of issues. Finding those vital few causes can be painfully difficult when you have an enormous amount of data to sift through. The truth is out there (or in there, as the case may be) but finding it is never easy. In fact, you might not even recognize it when the truth appears.
In retrospect, 1950 was quite a banner year for truth and ambiguity. While Juran was attempting to codify cause and effect, the noted poker player and junior senator from Wisconsin, Joe McCarthy, anted up and immediately began bluffing in his quest to uncover Communists (real or imagined) in the U.S. government. Meanwhile, half a world away, a little-known Japanese filmmaker named Akira Kurosawa was putting the finishing touches on Rashomon, a motion picture that would bring into sharp focus the very human and very frustrating search for absolute truth.
In brief, this film depicts the murder of a samurai that takes place in medieval Japan. The event is related by the man’s wife, an outlaw, a woodcutter, and the victim himself. All tell a version of the story which contains elements of the truth, and healthy doses of self-interested misdirection as well. Who is deemed trustworthy shifts as the story unfolds, and we gradually come to realize that this deceptively simple story depicts a post-modern, abstract, and relativistic world that has more in common with the paintings of Picasso or the compositions of Stravinsky than the average movie of the era.
In its final moments, Rashomon offers a kind of kaleidoscopic truth, but only in passing. What it’s actual concerned with is faith. We, the audience, find ourselves near the end of the film deeply disturbed by a world in which we can’t ever really know what is and what isn’t. But it turns out that the woodcutter, who is (probably) a thief, also has a sense of morality that redeems both him and us. It turns out that justice and righteousness are the truths that really matter.
Appreciating the absolute necessity of these basic qualities is probably more important that spinning the meaning behind some 448-page report or paring and comparing the arguments for or against mainstream scientific theories or far-fringe belief systems. Wanting or needing something to be true does not make it so, just as denying one’s essential dignity cannot lessen that quality’s vital importance. Some things just are, or are not, regardless of the limited perspective of witnesses.
Who’s fooling whom?
Ask anyone for their perspective on reality and you’ll find a spectrum of belief befitting the vast variety of human experience. Quality professionals would tell you that truth can be discerned from data, properly sifted into actionable information. Creators and consumers of media see fragmented truths, each of which is as valid as any other. Advocates of VUCA believe that preparing for uncertainty can allow one to best understand reality. Juran advocated for acting on the information that matters most; Kurosawa believed that there is no absolute truth aside from the belief in human redemption.
Effectively sorting through these contradictory conceptions requires not only rigorous self-examination; it also means honestly and empathetically exploring their meanings with others. Unfortunately, that’s not how it works, for the search for truth isn’t a pursuit of dispassionate rationalism. Too often, people use their opinion of the truth as a cudgel to beat those on the other side of an issue into submission, with ready-made “facts” that can prove or disprove pretty much anything. This is the blind alley down which we find ourselves in today’s America, with no path forward and little chance of going back. One cannot, after all, un-ring a bell that’s been struck.
The great Scottish engineer and physicist William Thomson (elevated to the peerage as Lord Kelvin in 1892) once said, “When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.” He was speaking, of course, about pure scientific inquiry, the stark and powerful blacks and whites of facts and figures as they represent the natural world. But the quest for immutable truth on which most people in a society can agree is a foundation of the modern world, even as it applies to real-world topics that are, nominally at least, debatable.
Taking accurate measurements is one thing; convincing others of the truth and meaning of those data is something else entirely. The truth of the truth is that it has never been easier or more effective to spread convincing lies to the furthest reaches of the planet instantaneously. This noise can drown out the voices trying to counter it and make it well-nigh impossible for those seeking knowledge to weigh the pros and cons of information.
I think the best way to approach this dilemma is to investigate anything you read or are told as Lord Kelvin or any self-respecting quality assurance professional might: by gathering all the possible data, keeping an open mind, and questioning everything—even yourself.
More than that, I’d recommend good ol’ Occam’s razor, which essentially states that when presented with competing hypotheses, the solution that requires fewer assumptions is generally the preferable one. Occam’s razor has been used for centuries to cut through the chaos inherent in the marketplace of ideas and help individuals apply common sense and critical thinking to the problem of separating fact from fiction.
This is an issue that we need to address quickly because bad actors, particularly those online, are getting better and better at deception. Unless we re-learn the value of truth (and get better at identifying it) we can’t fully enjoy the technological benefits of our interconnected global society. Knowledge is the currency that runs our modern world, and truth is the precious metal that undergirds it. We don’t all need to see things in the same way, but we do need to see clearly and as unambiguously as possible. Only in this way can we agree, or disagree, with sensibility and common, basic respect.