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Human beings adapt to changes in their environment by evolving along three intersecting planes, our biology, our culture, and our technology. Our biology changes very slowly, requiring many generations to incorporate beneficial genetic traits. Technology and culture are both faster than biology, but not by much – at least until very recently.
Cultural adaptations like democracy, rule of law and capitalism have sparked an explosion of technical adaptation. It took us roughly 8,000 years to get from the invention of agriculture to the invention of the iron plow. It took another 600 years to develop the tractor. A century later we have farm equipment guided by satellite navigation. A decade later we are seeing the first fully automated farms.
Two hundred years ago, the mere capacity to read and write was a still limited to elites. Barely one in ten human beings were literate in 1820. Today that proportion has almost entirely reversed. Over centuries, gradual expansions of literacy, education and the spread of printed books created a positive feedback loop. More people exchanging ideas led to a steady refinement of knowledge. Until very recently the pace of that growth was incremental. Social and technological adaptations in the late 20th century, especially the fall of Communism and the invention of the Internet, created an expansion in communications. Growth in data, science and the ideas has accelerated from incremental to exponential.
Robert Metcalfe, one of the early pioneers of computer networking, explained the growth of data and knowledge with a model we now call Metcalfe’s Law. His law states that the value of a network is based on the number of available connections. That number of connections increases at a spectacular rate with the addition of each new node. A single node is useless. Two nodes can make one connection. Five can make ten, and twelve can make 66, and so on. As a metaphor, Metcalfe’s Law helps illustrate how the collapse of physical and geographical barriers to trade, communication, and the flow of ideas over the past few decades fed an explosion of innovation.
Computers that controlled the Apollo 11 spacecraft had less computational power than my coffee maker. Today, a phone included for free with a cellular plan is equipped with millions of times more processing power than every computer NASA owned in 1969 combined. That’s just processing power, the growth in the volume of data has been even more staggering. IBM estimates that 90% of all the data human beings have ever created, across hundreds of thousands of years of thought and development, was generated in the past two years. As the growth of non-human processing power and data generation continues to accelerate, that “data midpoint” is edging ever forward, inching toward a singularity.
By contrast, how much capacity for data has the average human brain added since Apollo 11? Basically, none. Our pace of biological evolution is dictated mostly (though maybe not entirely), by reproduction and mutation. It can take many generations for the simplest genetic adaptations to emerge, and sometimes dozens to hundreds or more for those mutations to take hold. We may adapt our habits, culture, and even our technology to cushion the impact of external conditions, but unaided biology remains slow. Burdened by the pace of biology, and without appropriate social adaptations, our technology can turn us into the equivalent of monkeys with machine guns, wielding far more technological power than we can safely exercise. The pace of disruptive technological change that my grandmother experienced across her lifetime was far faster than human beings had ever before seen. Yet, that pace is still accelerating. Technological replacement has reached a speed that strains our ability to keep pace through cultural adaptions like politics and social change. Our old social institutions are fraying faster than new ones can form. And the pressure this is placing on our biology is relentless, driving rampant drug abuse and mental strain.
We are not merely facing more information and more change than in the past, we are being asked to wrestle with a type of data that was rarely seen by ordinary people when my Grandma was a girl. Information derived from scientific processes presents a unique challenge, particularly when we are asked to use that data to form social or political decisions. When my son tells me that his bicycle is in the garage, that is a bundle of information I can easily comprehend and test. I don’t need a specialized explanation to know what a bicycle looks like or how a garage works. If I question his statement, I can use my eyes to deliver proof. Proving that the bicycle is in the garage does not necessarily require me to place my trust in another person or lean on someone’s expertise.
Galileo, with his experiment at the Tower of Pisa, was charting a course toward a new kind of information – scientific data. Scientific data does not come from the simple sensory observation of the world around us. Scientific data is generated through a process. Some scientific data can be easily verified by a layman, like Galileo’s challenge to Aristotle from the Tower of Pisa. Anyone can climb onto their own roof (carefully) with a bowling ball and a penny and experience for themselves what Galileo’s experiment revealed. Likewise, a scientific process produces the current outdoor temperature. I may or may not understand how that number is derived, but by stepping out onto my porch I can test and understand its relative accuracy.
As science has advanced, it has become far less accessible to laymen. Our most critically valuable discoveries are mostly incomprehensible without specialized knowledge. Scientists test and retest data. What they share with us is metadata, information that describes their underlying data. Are physicists correct to assume that deviations detected in the decays of B mesons indicate a new particle might exist on the high-energy spectrum? It would take a lifetime of dedicated study and a uniquely capable mind to offer the first insight on that question. In a culture that depends on democratic processes for its survival, this sudden, powerful pivot toward the power of elite information poses problems.
Sometimes scientific processes which cannot be easily explained to laymen have serious public policy implications. Our earliest examples were felt in medicine, where we introduced regulations in the early 20th century to curb fraud and improve professional discipline. By the middle of the 20th century we began to wrestle with the impact of environmental pollution and nuclear weapons. Over the past few decades we seem to be overwhelmed with new public policy issues informed by complex science, from genetically modified organisms to drug policy and climate change.
Born in 1902 and 1904, respectively, my Grandma and Grandpa were already elderly when I was born in 1970. A world that was just slipping into hyperdrive was accelerating beyond their reach. I was about ten when my parents bought them a television that featured a remote control. For a long time, Grandpa still insisted on getting out of his chair to change the channel. One day I walked into the living room to find him pointing the business end of the remote to his forehead. I watched silently while he tested the device. He was trying to understand how it worked, pointing it up, backward, against objects in the room and yes, against his forehead. He was using familiar tools to understand an elusive reality. It wasn’t working out.
When he spotted me, he set the remote down and left the room. Later he would accidentally destroy the remote control by opening it up to see what was inside. A reality built on common sense and folklore was, by that time, beginning to fail my grandparents in ways that had material consequences. Tools that worked in one environment were less helpful as that environment changed.
Our political process is premised on the notion that everyone is equal and therefore everyone’s perception of reality deserves a roughly equal weight. Apply this logic to questions of scientific expertise and the results are either comedy and tragedy, sometimes both. When Thomas Jefferson wrote the Declaration of Independence, humans possessed no knowledge that our founders could not hope to grasp and even personally test given a bit of effort and study. When my grandmother was young public policy still had no need to depend on knowledge and engineering inaccessible to a well-read layman. Now, our survival as a species increasingly depends on our capacity to translate elite scientific expertise into public policy. We have not developed mechanisms capable of incorporating expertise into policy without surrendering a disturbing degree of our democratic oversight. Our inefficiency in translating science into policy is becoming an existential threat.