The Half-Life of Facts: Why Everything We Know Has an Expiration Date, by Sam Arbesman - exclusive excerpt
And yet modern science doesn't heed it's own rules by conducting research seemingly on the sole basis to back up their specific theory and agenda.
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The Half-Life of Facts: Why Everything We Know Has an Expiration Date, by Sam Arbesman - exclusive excerpt:
Here's an excerpt from The Half-life of Facts: Why Everything We Know Has an Expiration Date, by Sam Arbesman.
Changing information in our modern world is the rule rather than the exception. And as knowledge changes more and more rapidly, the resulting change in society can be drastic. Rather than changes in degree, we have changes in kind. For someone living in a small English village at any point during the early Middle Ages, aside from certain details, there would be little difference in one’s lifestyle between any two years. There might be alterations in fashion, but in one’s overall life— manner of occupation, means of cooking and doing household chores— none of these would be different. In fact, even fashion during the Middle Ages only changed about every fifty years, far slower than shifting every decade or so, which has been happening since the nineteenth century in industrialized countries. Even if you lived during a rare innovative reset during the later medieval period (such as during the introduction of gunpowder), things weren’t so difficult to adapt to, as they occurred only once every several generations.
This has been true for most of human history. But with exponential increases in technology and innovation, these changes are coming much more rapidly. When changes are able to occur very quickly, we are in a special situation: The world around us seems to be ever poised on the edge of some rapid shift in facts and knowledge. A small change can cause a large shift in our knowledge at any moment.
Of course, the world of facts is not the only system that can be in this sort of state; there are many other systems that can have this property. Imagine a complex ecological system in which the slightest change, such as the removal of a single species or the introduction of a pathogen, has the potential to upset the entire system. Or a party, where one person leaving suddenly kills the entire gathering. Or, at an even more basic level, imagine a pile of sand. Take a pile of sand and add a few grains, and the pile gets bigger. But as sand is added a bit more at a time, eventually adding just a few more grains triggers a rapid shift, a sort of avalanche of sand. Why the transition? What about that single grain yields a system that is right on the edge of a rapid shift?
This question was examined in great detail by three physicists: Per Bak, Chao Tang, and Kurt Wiesenfeld. In 1987, they published a simple mathematical model that aimed to understand why small changes can yield a system that is always on the verge of large shifts.
This model uses a grid, where each location is a spot where a grain of sand can be added. And, according to mathematical rules, the model dictates what should happen if the pile of grains at a single location gets too high. Essentially, if the height goes above a single specified value, the grains begin moving to neighboring points, similar to how water will run down a cone if poured onto its tip. When this simulated sandpile reaches what is known as a critical state, it exists in a situation exactly as described above: With the addition of each additional grain, there is absolutely no telling what will happen. There could be a tiny little movement of the sand, or a massive avalanche could be unleashed. Like Jenga or KerPlunk, but with more mathematics, the system is constantly hovering at the brink of the unknown.
It turns out that this sort of system, one that organizes itself to always be at the edge of a total avalanche, is the hallmark of actual systems we find in the real world, perhaps even including the world of knowledge. While a bit overly metaphorical, a world with the constant potential for rapid knowledge change would look just like ours.
Ultimately then, we have to have a constant awareness of changing knowledge. Happily, while facts around us can change, when looked at in the aggregate these changes are far from random. There are patterns to how knowledge grows and spreads and even gets overturned over time. From knowing how long it takes for certain fields of knowledge to be overturned (less than half a decade in certain medical fields) to the mathematical curves that can describe how scientific publications grow over time (exponential growth) to even how social networks allow for the diffusion of facts and ideas, we can now understand how we know what we know.
So, even though our world is constantly on the precipice of rapid knowledge change, there are regularities to how knowledge grows and shifts. And embracing this will leave us better prepared for the exciting change around us.
Adapted from THE HALF-LIFE OF FACTS: Why Everything We Know Has an Expiration Date by Sam Arbesman, by arrangement with Current, an imprint of Penguin Group (USA), Inc., Copyright © Sam Arbesman, 2012.
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The Half-Life of Facts: Why Everything We Know Has an Expiration Date, by Sam Arbesman - exclusive excerpt:
Here's an excerpt from The Half-life of Facts: Why Everything We Know Has an Expiration Date, by Sam Arbesman.
Facts change all the time. Smoking has gone from doctor recommended to deadly. We used to think the Earth was the center of the universe and that Pluto was a planet. For decades, we were convinced that the brontosaurus was a real dinosaur. In short, what we know about the world is constantly changing.
But it turns out there’s an order to the state of knowledge, an explanation for how we know what we know. Samuel Arbesman is an expert in the field of scientometrics—literally the science of science. Knowledge in most fields evolves systematically and predictably, and this evolution unfolds in a fascinating way that can have a powerful impact on our lives.
Doctors with a rough idea of when their knowledge is likely to expire can be better equipped to keep up with the latest research. Companies and governments that understand how long new discoveries take to develop can improve decisions about allocating resources. And by tracing how and when language changes, each of us can better bridge generational gaps in slang and dialect.
Just as we know that a chunk of uranium can break down in a measurable amount of time—a radioactive half-life—so too any given field’s change in knowledge can be measured concretely. We can know when facts in aggregate are obsolete, the rate at which new facts are created, and even how facts spread.
Arbesman takes us through a wide variety of fields, including those that change quickly, over the course of a few years, or over the span of centuries. He shows that much of what we know consists of “mesofacts”—facts that change at a middle timescale, often over a single human lifetime. Throughout, he offers intriguing examples about the face of knowledge: what English majors can learn from a statistical analysis of The Canterbury Tales, why it’s so hard to measure a mountain, and why so many parents still tell kids to eat their spinach because it’s rich in iron.
The Half-life of Facts is a riveting journey into the counterintuitive fabric of knowledge. It can help us find new ways to measure the world while accepting the limits of how much we can know with certainty.
Changing information in our modern world is the rule rather than the exception. And as knowledge changes more and more rapidly, the resulting change in society can be drastic. Rather than changes in degree, we have changes in kind. For someone living in a small English village at any point during the early Middle Ages, aside from certain details, there would be little difference in one’s lifestyle between any two years. There might be alterations in fashion, but in one’s overall life— manner of occupation, means of cooking and doing household chores— none of these would be different. In fact, even fashion during the Middle Ages only changed about every fifty years, far slower than shifting every decade or so, which has been happening since the nineteenth century in industrialized countries. Even if you lived during a rare innovative reset during the later medieval period (such as during the introduction of gunpowder), things weren’t so difficult to adapt to, as they occurred only once every several generations.
This has been true for most of human history. But with exponential increases in technology and innovation, these changes are coming much more rapidly. When changes are able to occur very quickly, we are in a special situation: The world around us seems to be ever poised on the edge of some rapid shift in facts and knowledge. A small change can cause a large shift in our knowledge at any moment.
Of course, the world of facts is not the only system that can be in this sort of state; there are many other systems that can have this property. Imagine a complex ecological system in which the slightest change, such as the removal of a single species or the introduction of a pathogen, has the potential to upset the entire system. Or a party, where one person leaving suddenly kills the entire gathering. Or, at an even more basic level, imagine a pile of sand. Take a pile of sand and add a few grains, and the pile gets bigger. But as sand is added a bit more at a time, eventually adding just a few more grains triggers a rapid shift, a sort of avalanche of sand. Why the transition? What about that single grain yields a system that is right on the edge of a rapid shift?
This question was examined in great detail by three physicists: Per Bak, Chao Tang, and Kurt Wiesenfeld. In 1987, they published a simple mathematical model that aimed to understand why small changes can yield a system that is always on the verge of large shifts.
This model uses a grid, where each location is a spot where a grain of sand can be added. And, according to mathematical rules, the model dictates what should happen if the pile of grains at a single location gets too high. Essentially, if the height goes above a single specified value, the grains begin moving to neighboring points, similar to how water will run down a cone if poured onto its tip. When this simulated sandpile reaches what is known as a critical state, it exists in a situation exactly as described above: With the addition of each additional grain, there is absolutely no telling what will happen. There could be a tiny little movement of the sand, or a massive avalanche could be unleashed. Like Jenga or KerPlunk, but with more mathematics, the system is constantly hovering at the brink of the unknown.
It turns out that this sort of system, one that organizes itself to always be at the edge of a total avalanche, is the hallmark of actual systems we find in the real world, perhaps even including the world of knowledge. While a bit overly metaphorical, a world with the constant potential for rapid knowledge change would look just like ours.
Ultimately then, we have to have a constant awareness of changing knowledge. Happily, while facts around us can change, when looked at in the aggregate these changes are far from random. There are patterns to how knowledge grows and spreads and even gets overturned over time. From knowing how long it takes for certain fields of knowledge to be overturned (less than half a decade in certain medical fields) to the mathematical curves that can describe how scientific publications grow over time (exponential growth) to even how social networks allow for the diffusion of facts and ideas, we can now understand how we know what we know.
So, even though our world is constantly on the precipice of rapid knowledge change, there are regularities to how knowledge grows and shifts. And embracing this will leave us better prepared for the exciting change around us.
Adapted from THE HALF-LIFE OF FACTS: Why Everything We Know Has an Expiration Date by Sam Arbesman, by arrangement with Current, an imprint of Penguin Group (USA), Inc., Copyright © Sam Arbesman, 2012.
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