By the end of the sixties mainframe computers were churning out reams of printout, film and television made reference to them complete with blinking lights, and a combination of great social and political upheaval and technological advancement gave a sense that no one could keep up. The time was right and Toffler's Future Shock came along and popularized the notion of information overload.
The truth was no one could keep up for centuries. My friend Andrew has a hobby of studying financial bubbles. He began with the twin 19th century railroad bubbles in England and has extended his work backwards in time to Tulip Mania and beyond. To do this meant spending large amounts of time in serious libraries - first in New York City and then London and beyond. His pieces are wonderful, but there's so much information for him to comb through. Even with the help of others it's taken over a decade. There's simply too much information available. The relevant information to avoid financial ruin was sometimes available at the time, but knowing which information sources were correct meant success and failure often involved chance. Reading Andrew now still makes me wonder how these events can be avoided given the complexity of human psychology.
The history of its information handling in my area is fascinating. England was something of a hotbed as science developed in the 17th and 18th centuries. The Lunar Society of Birmingham ( I've written about them here ) became a centrally important group. For about fifty years people like Josiah Wedgwood, Matthew Boulton, James Watt, Joseph Priestly, James Kier and Erasmus Darwin met under the light of a full moon and exchanged ideas. New ideas were hatched, partnerships formed and they ended up making a considerable dent in the Universe before the the Royal Society in London became the center of scientific thought. Here formal papers were presented along with public showings of new discoveries. It became a repository for the advances in a number of fields. The deluge of information for any dozen people to absorb, so proceedings were published along with condensations to help local and remote members better navigate the constantly expanding change.
Other societies formed in England and around Europe, but commercial advances in chemistry and engineering brought attracted money and colleges and universities started to become deeply involved. Some information was being shared, but the flow even within institutions was a daunting problem. Finally one of the most remarkable inventions of the 19th century arrived: the Cavendish Laboratory at Cambridge - a future machine. Without repeating myself too much it created concentrations of written and institutional information along with a culture which continues to grow and expand even today.
The process of science is very messy and bears little resemblance to the scientific method you learned about in school. There is enormous amount of careful work to separate signal from noise and to constantly question yourself. It's been estimated that over 70% of time spent by physicists goes into looking for holes in their work. I've had three eureka moments in my life and all turned out to be wrong. Discovery usually begins by noticing something isn't working right. It's rarely perfect, but progress is made. There are a number of information flows involved, but I'll skip them for now and focus on what it isn't.
A model that came out of system analysis in the 1930s and was popularized in the 1980s says data → information → knowledge → wisdom. Data is processed or filtered to give information which can further be processed to result in knowledge and so on.. Each step is more valuable - some use the terminology more actionable. I've heard computer programs described as as algorithmic processes that turn data into information. Information is somehow processed to create knowledge which is even valuable and actionable. As I read it the implication is knowledge results from a successive filtering of data and then information. That everything else is some kind of noise. Perhaps this is a useful model for some fields, but not in science.
The concept of knowledge differs from the DIKW construction. Roughly speaking science considers knowledge as a growing collection of beliefs that can be empirically justified by experiment and observation using Nature as a reference standard. The pieces that form the collection can be challenged and improved or overturned as our understanding of Nature grows. Together the pieces form a beautiful collage representing work that spans centuries. The concept of knowledge coming directly from the data→information stream is foreign. Our reality is much messier with discovery, serendipity, curiosity, play, failure, learning from failure, culture, the passage of time and so on being important components. Some pieces are replaced over time, others - like when to use Quantum Mechanics, Relativity or Newtonian Mechanics - are more nuanced. Knowledge becomes an important reference that lets you understand how to use information.
With that detour, how does science - in my case physics and astrophysics - deal with information? The invention of the modern laboratory at Cambridge is a big part of it. Groups of people working along similar paths with access to shared resources - lab equipment, technicians, mathematical tools, a shared culture and knowledge base. Labs across the world interconnect with a rich rapid communication framework quickly raising issues worthy of confirmation or shredding. They provide a sense of direction and make problem spaces and information loads manageable. Local and extended groups are a rich source of new ideas and questions - ultimately new questions are the gold.
Experiments and observations have become more complex and data filtering is common. As an example it's common for a detector at CERN to recognize less than one in hundreds of thousands of collisions is important and pass that on for more detailed analysis. The filters - called triggers - are built on a knowledge base decades deep and are constantly checked. Conceptually they're simple. Two particles collide at extremely high speed and the collision produces a a number of rapidly moving particles. The signature they make as they pass through a series of detectors gives a clue about what they are and what the collision was. Most of the collisions are uninteresting so you need to discard them quickly as you can't store all of them. Much of this is done as the reports from the detectors are progressing so keep/ignore decisions have to be very fast - billionths of a second. The image is from one of my first particle physics experiments. The rats nest of wiring was my work and is part of the logic looking for two types of particle interactions. The messiness results from the need to have signals arrive at exactly the right time - so the length of each cable is a reflection of the speed of light - some signals need to be delayed more than others. There is a constant check on this logic and you're alerted when something was out of wack - a piece of electronics failing, an intermittent cable connection and the like. It was something that had to be attended to daily for over a year. These days triggers are much more complex requiring teams of people using a much deeper knowledge base. Such is progress.
There are problems with this focused approach. Natural boundaries form with specialization and understanding what's going on in other fields is a casualty. There are efforts to increase cross-discipline work, but the culture that produced specialization makes it difficult. Every now and again those barriers fall. That seems to happen more in applied than fundamental research, but when it does major leaps tend to happen.
I've recently become interested in information flow in sports. There are some similarities to what I'm used to but often it seems more complex and my conversations with an articulate athlete have been illuminating. I'm guessing there are nearly as many information flows as there are fields. I'm stuck with my own biases, but suspect using knowledge as a way to use information may be important to many.
aerosol transmission
postscript
Several readers asked for CO2 meter recommendations. I can make a few recommendations, but have only used a few. Stay away from sub $100 units is the only rule of thumb I can offer. Schools should have them in each room as well as stores, offices and so on. You probably don't need one in your home unless you’re curious or want to see how well your windows and HVAC system are working (that can be a big issue).
The seminar talks about airplanes. Air exchanges per hour are very high when the ventilation system is on so airborne infection risk is low inside the cabin. The rest of the trip is questionable - very high levels were found in jetways for example. New York subway trains have good air exchange rates, but I haven’t seen any work on the platforms. Buses vary and I’d be suspicious when the heaters are on in the Winter. I’ve measured a variety of cars. With windows up and two occupants CO2 levels were over 3500 ppm in twenty minutes. That’s extremely dangerous if one of the occupants is contagious. Opening windows helps, but cars vary. The effect isn’t big on very streamlined cars like Teslas. On aerodynamically dirtier cars opening rear windows canincrease air exchange more than front windows as the outside air pressure on a moving car increases towards the rear of the vehicle. You should also turn on air circulation. With just circulation I got readings around 900 ppm and the best readings with windows were in the 700s. I’d stay away from any car if someone outside of your bubble is in it.
An interesting note is some measurements have been done on cognitive ability and alertness. Over 1500 ppm and people become less alert. That can have an impact on the quality of work as well as high attention activities like driving. The few studies that have looked at cognitive ability show declines with increasing CO2 levels. One study saw the decline start around 800 ppm and another around 1500 ppm. Neither study was gold standard robust, but I suspect the effect is real - certainly alertness is real. Many school rooms, offices and homes are normally over those levels so your may want to make changes even after the pandemic.
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