We Need To Finally Break Free Of The Engineering Mindset
In 2014, when Silicon Valley was still largely seen as purely a force for good, George Packer wrote in The New Yorker how tech entrepreneurs tended to see politics through the lens of an engineering mindset. Their first instinct was to treat every problem as if it could be reduced down to discrete variables and solved like an equation.
Despite its romantic illusions, the digital zeitgeist merely echoed more than a century of failed attempts to generalize engineering approaches, such as scientific management, financial engineering, six sigma and shareholder value. All showed initial promise and then disappointed, in some cases catastrophically.
Proponents of the engineering mindset tend to blame its failures on poor execution. Surely, logic would suggest that as long as a set of principles are internally consistent they should be externally relevant. Yet the problem is that reality is not simple and clear-cut, but complex and nonlinear, which is why we need be ready to adapt to the unexpected and nonsensical.
The Rise Of The Engineering Mindset
In the 1920s , a group of intellectuals in Berlin and Vienna, much like many of the Silicon Valley digerati today, became enamored with the engineering mindset. By this time electricity and internal combustion had begun to reshape the world and Einstein’s theory of relativity, confirmed in 1919, had reshaped our conception of the universe. It seemed that there was nothing that scientific precision couldn’t achieve.
Yet human affairs were just as messy as always. Just a decade before Europe had blundered its way into the most horrible war in history. Social scientists still seemed no more advanced than voodoo doctors and philosophers were still making essentially the same arguments the ancient Greeks used two thousand years before.
It seemed obvious to them that human endeavors could be built on a more logical basis and saw a savior in Ludwig Wittgenstein and his Tractatus, which described a world made up of “atomic facts” that could be combined to create “states of affairs.” He concluded, famously, that “Whereof one cannot speak, thereof one must remain silent,” meaning that whatever could not be proved logically must be disregarded.
The intellectuals branded their movement logical positivism and based it on the principle of verificationism. Only verifiable propositions would be taken as meaningful. All other statements would be treated as silly talk and gobbledygook. Essentially, if it didn’t fit in an algorithm, it didn’t exist.
A Foundational Crisis
Unfortunately, and again much like Silicon Valley denizens of today, the exuberant confidence of the logical positivists belied serious trouble underfoot. In fact, while the intellectuals in Berlin and Vienna were trying to put social sciences on a more logical footing, logic itself was undergoing a foundational crisis.
At the root of the crisis was a strange paradox, which can be illustrated by the sentence, “The barber shaves every man who does not shave himself.” Notice the problem? If the barber shaves every man who doesn’t shave himself, then who shaves the Barber? If he shaves himself, he violates the statement and if he does not shave himself, he also violates it.
It seems a bit silly, but the Barber’s Paradox is actually a simplified version of Russell’s Paradox involving sets that are members of themselves, which had baffled mathematicians and logicians for decades. Clearly, for a logical system to be valid and verifiable, statements need to be provably true or false. 2+2 for example, needs to always equal four. Yet the paradox exposed a hole that no one seemed able to close.
Eventually, the situation came to a head when David Hilbert, one of the most prominent logical positivists, proposed a program that rested on three pillars. First, mathematics needed to be shown to be complete in that it worked for all statements. Second, mathematics needed to be shown to be consistent, no contradictions or paradoxes allowed. Finally, all statements need to be computable, meaning they yielded a clear answer.
The hope was that the foundational crisis would be resolved, the hole at the center of logic could be closed and the logical positivists could move along with their project.
The System Crashes
Hilbert and his colleagues received and answer faster than most had expected. In 1931, just 11 years after Hilbert proposed his foundational problems, 25-year-old Kurt Gödel published his incompleteness theorems. It wasn’t the answer anyone was expecting. Gödel showed that any logical system could be either complete or consistent, but not both,
Put more simply, Gödel proved that every logical system will always crash. It’s only a matter of time. Logic would remain broken forever and the positivists hopes were dashed. Obviously, you can’t engineer a society based on a logical system that itself is hopelessly flawed. For better or for worse, the world would remain a messy place.
Yet the implications of the downfall of logic turned out to be far different, and far more strange, than anyone had expected. In 1937, building on Gödel’s proof, Alan Turing published his own paper on Hilbert’s computability problem. Much like the Austrian, he found that all problems are not computable, but with a silver lining. As part of his proof, he included a description of a simple machine that could compute every computable number.
Ironically, Turing’s machine would usher in a new era of digital computing. These machines, constructed on the basis that they would all eventually crash, have proven to be incredibly useful, as long as we accept them for what they are — flawed machines. As it turns out, to solve big, important problems, we often need to discard up our illusions first.
We Need To Think Less Like Engineers And More Like Gardeners
The 20th century ushered in a new era of science. We conquered infectious diseases, explored space and unlocked the genetic code. So it was not at all unreasonable to want to build on that success by applying an engineering mindset to other fields of human endeavor. However, at this point, it should be clear that the approach is far past the point of saving.
It would be nice if the general well-being could be reduced to a single metric like GDP or the success of an enterprise could be fully encapsulated in a stock price. Yet today we live, as Danny Hillis has put it, in an age of the entanglement, where even a limited set of variables can lead to the emergence of a new and unexpected order.
We need to take a more biological view in which we think less like engineers and more like gardeners that grow and nurture ecosystems. The logical positivists had no idea what they were growing, but somehow what emerged from the soil they tilled turned out to be far more wondrous—not to mention exponentially more useful—than what they had originally intended.
As I wrote at the beginning of this crazy year, the time has come to rediscover our humanity. We are, in so many ways, at a crossroads. Technology will not save us. Markets will not save us. We simply need to make better choices.
– Greg
Image: Pixabay
Greg,
This great! But how can you convince politicians:
– who want to prove their success by ever growing GDP
– who seek reelection based on false macronumbers
-who do not understand that they can spend tremendeous amount of money on technology, but if they spend nothing on education, skills and human well-being, no development will be achieved
Also how can you convince business leaders who are in perfect cooperation with the above mentioned politicians, therefore
– they can spend a lot – very often from the state budget – on technologies (5G, automotive proving grounds etc.), but do not care about their workers, neither the needs of the everyday citizens,
– who produce a lot of money based on local subsidies and low wages, and happily repatriate it home.
Well this is how technology orientation looks like from the perspective of a less developed country citizen.
Magdolna
excellent humanist extrapolation, Greg.
Thanks Robin!
Thanks Magdolna. We have many of the same issues in the US. It’s on of the reasons that
I wrote my book, Cascades. You may also find this article in HBR helpful: https://hbr.org/2019/08/4-tips-for-managing-organizational-change
Greg
Wow! Thanks for facilitating this impactful dialogue. You certainly woke up the elephant in the room. I’ve spent a good portion of my work life on teams with logical/analytic people from engineers to accounts and financial analysts. I can say in all cases that their predisposition to a logical/fixed mindset was essential to helping our team reach goals and achieve our purpose. I especially enjoyed watching the logical minded people participate in and expand the outcomes of creative activities. Given my own biases, I was surprised how much they enjoyed breaking out of the logical mindset or “I got the right answer” box and just envision possible solutions to problems or identification of opportunities without having to make sure they were logical and right… Bottom line logical/analytical people can expand their box and actually contribute meaningfully to creative initiatives. It is also true the agile/flexible mindset people can make decisions influenced by logic.
Over the years, I’ve come to see logic destroy my good ideas, especially, if leaders used it to squelch new ways of doing things because they value the status quo. At the same time, a willingness to ask good questions rather than always have a right answer promotes innovation and creativity. As you said in the article, “the problem is that reality is not simple/or clear but complex and nonlinear, which is why we need to be able to adapt to the unexpected.”
Organizations and their teams need a variety of skilled people with both logical and agile mindsets to achieve individual, team and corporate purposes during times of crisis. When teams can actually articulate a common purpose, they can live it day-to-day. These teams are built on a trust, resilience, inquiry, and shared values.
We are now working in a team-based organizational structure rather than top down hierarchical organizations. We need to look beyond S-Term results and strive for long term impact. This means that people need to consider how their work is fitting into the bigger picture This means we need to have groups made up of people with diverse capabilities that are open to learn new approaches and are willing to adapt their mindsets to the situation required. This is why aligning individual purpose with team and corporate purpose is so critical… what I call “Where you find meaning…”
Thank you again… for encouraging us to think.
G
Great points! Thanks George.
– Greg
As the modern world continues to be dominated and subservient to the whims of algorithms, everything becomes mechanised, leaving out our human intimations with the ethereal and the intuitive. As you brilliantly put it, not everything about reality is computable. Hopefully, the world would open itself to a balance between engineering and the humanities.
An insightful essay.
Thanks so much Chris.