Perhaps it is a fundamental law of information that the complexity of information increases. In the world of biology, over time organisms become more complex, with new genetic permutations appearing alongside of old genetic pieces. In the hyperastronomical space in the animal genome, nature constantly produces new combinations. In human knowledge and scientific discovery, the same is true. New insights are built on top of old ones. Breakthroughs in insight usually have higher levels of complexity and hence require higher levels of abstraction and difficult codification to accommodate the widening domain covered.
We all know E=MC2 but how many of us really know what it means?
In the world of medicine, treatments are becoming more complex as well. Cancer treatments are becoming more precise and personalized and adapted to your genetic distinctiveness, the way your body metabolizes things and the way your epigenetics unfolds. In some cases, doctors are using forms of treatments that use T-cells as carriers for genetically modified viruses so that treatments are targeted at specific cells. New drugs are modeled on a computer as scientists try to understand the movement of molecules. When drugs are designed to work well with the specific ways proteins in the body fold, their effectiveness increases.
Did you get what I just wrote? Did I?
In the discipline of software engineering and programming, languages have accumulated more libraries, syntactic constructs and development platforms. We have much more variation in tools now than we did 40 years ago. In the realm of warfare, conflict is modeled using game theory and computer simulations, often times pointing out strategies empirically derived that clash with human intuition. One could argue that all of economics is a series of advanced formulas that tell us the economy works remarkably different than our heuristic, common-sense minds thinks it does. History itself is now open for inspection via cliodynamics, which involves the use of computer simulations to understand history. Just recently, Google’s AlphaGo, a computer system powered by new technology called deep learning networks, has just dispatched with its top human adversary in the extremely complex game of Go, perhaps a decade sooner than people thought. Researchers are finding that algorithms can know you better than your Facebook friends. What human skill and knowledge will be displaced next?
All the world is but a jumble of complex, abstract and increasingly technical piece parts. And amidst all this lies a troubling point: a rising complexity spins all minds. The meek will not inherit the gold in this new technocratic future. It is the very, very smart who will.
With this complexifying swirl as the backdrop, the current populist descent into trash-talking, anti-intellectual, rabid, rapid, knee-jerk, feel-good vituperation and the subsequent incoherent and shallow prescriptions for curing what ails us is understandable. More invective leads to less perspicacity. The gulf between the heuristic, fast-thinking mindset that has driven humankind since we became homo sapiens and the devilishly technical and complicated world we live in today that requires tremendous scientific knowledge, and very different decision-making, is producing a backlash.
Various researchers have been furiously collecting data on what describes the Donald Trump voter and a clearer pattern is emerging. Trump supporters are more likely to be male, white, without a high school diploma, authoritarian, in areas of the country that have been economically left behind, afraid of foreigners and most likely believe anti-white bias is a greater threat than addressing other minority needs. In short, these are people who are on the wrong-side of the technocratic divide who are angrily seeking a status quo ante to return to more privileged economic position. For better or for worse, the gulf between these agitated and disaffected and those at the highly technical front lines of the new economy is widening. Worse still, in the 21st century economy, woman and immigrants from all over the world are making their mark in the U.S. economy.
Science, data, and analytics have invaded everything significant in our culture, from philosophy to sports. When the population struggles to appreciate the new scientific fundamentals that are ever-present many begin to reject this body of scientific thought. What one cannot pierce with one’s mind, one pierces with emotion. When this happens, reason, evidence, data, analytics, formulas and esoteric models all get swept aside. Experts are discounted and irrelevance is claimed.
Within the education system in the U.S., we are seeing this new dividing line in our students. On the highly technical side of the line are those who can grasp the deeper conceptual understanding of various subjects, including calculus, statistics, genetics, all things related to molecules, network theory, cognitive and neurocognitive psychology, the complexity sciences, computational linguistics, artificial intelligence, quantum theory and yes, data science and software engineering. One the other side of the line is the rest of humanity who knows little of these things. The line between those most engaged in their society and those least engaged is a now a technocratic one in which education is becoming more important, not less. As Thomas Jefferson advised long ago, education is still one of the best antidotes to tyranny. Especially if it can keep citizens meaningfully involved in the economy.
While my point here appears extremely science and technology-centric, bear with me. I started my academic career in studio art and worked as a journalist before discovering computation. Over the past decade, aided and abetted by the computer, scientists and technologists have invaded nearly every aspect of human existence and now undergird a significant and vital part of the economy. If I wanted to be an artist, a marketer, a writer, a philosopher or a humanist, without some understanding of these technical things there is precious little to opine about or work on. On the more difficult side of this divide are jobs that require less intellectual skill and more social skill where humans need to talk to other humans and where it is easier for human muscle to move things because robotics hasn’t taken over. The human being still has roles to play in this economy, but soon perhaps only where human labor is cheaper than the machine. This polarization of jobs may be contributing to increasing inequality.
There is a new line separating human beings from each other and it is a great technocratic divide. Calling the reaction against this technocratic invasion a Luddite one doesn’t capture the significance of this scientific tsunami. All roads to the future lead through a forest of computing and scientific complexity. There are fewer mentally easy routes to economic prosperity. How the next generation sorts out their place in the 21st century economy will be quite different than in the 20th century economy.
In this regard, both the ISIS throw-back to the 7th century and the recent takeover of a wild life sanctuary in Oregon in the U.S. by an anti-government posse are attempts to recreate and find identity in simpler, less technical times. Both seem wildly anachronistic and stand in stark contrast to the technical vigilantism of the likes of Anonymous and black hat hackers. While the former retrograde upstarts may use technology in their efforts, they tend to adopt non-scientific cultural frames of mind, often literalist in looking at religious or political ‘scripture.’ The group Anonymous, operates differently, adopting 21st century tools and techniques to achieve its aims, using social media, chat rooms and gamification techniques, operating with less organizational structure and opposing autocrats, big corporations and war. In a way, even the aberrant upstarts of our times are sorting into two camps on either side of this technocratic divide.
Scientific insight, connectivity, computing and technology have all reshaped not so much the hard boundaries but the less visible contours of our civilization. We are now in a Machine-Knowledge Age that is still going through its angst of childhood while its parent, the Industrial-Information Age, has withered away into senility, no longer able to guide the new child. Even the term post-industrial, which denotes the shift from a manufacturing to a service economy, is inadequate here. What we have facing us is the full-blown use of advanced computation driving all things in the economy: from manufacturing and services and soon, to many forms of knowledge work. I previously thought this revolution would be a bloodless one. No longer. This technocratic divide does have plenty of promise, but it has its own peril, spilling out right before our eyes.
Those of us who have been designing, selling and implementing these new technical-computing system future overlords have contributed, unwittingly or not, to this fault line. Do we have any ethical or moral accountability for our acts? How should the collective ‘we’ in the center of this technocratic transition attend to these important and now more urgent social and civic responsibilities? How do those on the prosperous side of this divide help in addressing the needs of those on the withering side?
This technocratic divide is widening. It is troubling. If the invisible fingers of the economy and the clumsy thumbs of democratic governance can’t build bridges across this divide, we are likely to see a thousand demagogues as sirens fomenting escalating strife.