Tag Archives: data science

College Football? There’s an API for that

I’ve always wondered if there is a public source of college football stats to play with, and there is (at least one) called the College Football Database. There’s also an R package that taps it.

Of course, don’t think for a second that you can crunch these numbers and make money through gambling. Only large “professional gamblers” can consistently make money through gambling, by (legally, as I understand it, at least in certain states) cornering the market by manipulating betting spreads. The idea there is that you can bet a large amount of money on the underdog in a contest that is not getting a lot of attention, which will move the spread in favor of the underdog. You can then bet an even larger amount of money on the favorite. If you are able to manipulate the odds in your favor, you will lose this bet less than half the time, and over time you will make money off the backs of us poor schmucks who take bets with expected values less than what we put in. Don’t try this – there are smarter, richer people than you doing it and you can’t beat them. Also, don’t take my word for it that it would be legal. Finally, think of making small, occasional, close-to-even-money bets as a source of cheap entertainment and you’ll be okay, and then only if you do not have a tendency to become addicted.

An API, by the way, is an Application Programming Interface.

In contrast to a user interface, which connects a computer to a person, an application programming interface connects computers or pieces of software to each other. It is not intended to be used directly by a person (the end user) other than a computer programmer who is incorporating it into software. An API is often made up of different parts which act as tools or services that are available to the programmer. A program or a programmer that uses one of these parts is said to call that portion of the API. The calls that make up the API are also known as subroutines, methods, requests, or endpoints. An API specification defines these calls, meaning that it explains how to use or implement them.

Wikipedia

2021: Year in Review

As per usual, I’ll list out and link to the stories I chose as the most frightening, most hopeful, and most interesting each month in 2021. Then I’ll see if I have anything smart to say about how it all fits together.

Survey of the Year’s Stories and Themes

Most frightening and/or depressing stories:

  • JANUARY: A China-Taiwan military conflict is a potential start-of-World-War-III scenario. This could happen today, or this year, or never. Let’s hope for the latter. This is a near-term existential risk, but I have to break my own “rule of one” and give honorable mention to two longer-term scary things: crashing sperm counts and the climate change/fascism/genocide nexus.
  • FEBRUARY: For people who just don’t care that much about plants and animals, the elevator pitch on climate change is it is coming for our houses and it is coming for our food and water.
  • MARCH: In the U.S. upper Midwest (I don’t know if this region is better or worse than the country as a whole, or why they picked it), electric blackouts average 92 minutes per year, versus 4 minutes per year in Japan.
  • APRIL: One of the National Intelligence Council’s scenarios for 2040 involves “far-reaching changes designed to address climate change, resource depletion, and poverty following a global food catastrophe caused by climate events and environmental degradation”.
  • MAY: The Colorado River basin is drying out.
  • JUNE: For every 2 people who died of Covid-19 in the U.S. about 1 additional person died of indirect effects, such as our lack of a functioning health care system and safe streets compared to virtually all our peer countries.
  • JULY: The western-U.S. megadrought looks like it is settling in for the long haul.
  • AUGUST: The U.S. is not prepared for megadisasters. Pandemics, just to cite one example. War and climate change tipping points, just to cite two others. Solutions or at least risk mitigation measures exist, such as getting a health care system, joining the worldwide effort to deal with carbon emissions, and as for war, how about just try to avoid it?
  • SEPTEMBER: The most frightening climate change tipping points may not be the ones we hear the most about in the media (at least in my case, I was most aware of melting ice sheets in Greenland and Antarctica, collapse of ocean circulation patterns). The most damaging may be melting permafrost on land and methane hydrates underwater, both of which contain enormous amounts of methane which could set off a catastrophic and unstoppable feedback loop if released in large quantities.
  • OCTOBER: The technology (sometimes called “gain of function“) to make something like Covid-19 or something much worse in a laboratory clearly exists right now, and barriers to doing that are much lower than other types of weapons. Also, because I just couldn’t choose this month, asteroids can sneak up on us.
  • NOVEMBER: Freakonomics podcast explained that there is a strong connection between cars and violence in the United States. Because cars kill and injure people on a massive scale, they led to an expansion of police power. Police and ordinary citizens started coming into contact much more often than they had. We have no national ID system so the poor and disadvantaged often have no ID when they get stopped. Everyone has guns and everyone is jumpy. Known solutions (safe street design) and near term solutions (computer-controlled vehicles?) exist, but are we going to pursue them as a society? I guess I am feeling frightened and/or depressed today, hence my choice of category here.
  • DECEMBER: Mass migration driven by climate change-triggered disasters could be the emerging big issue for 2022 and beyond. Geopolitical instability is a likely result, not to mention enormous human suffering.

Most hopeful stories:

  • JANUARY: Computer modeling, done well, can inform decisions better than data analysis alone. An obvious statement? Well, maybe to some but it is disputed every day by others, especially staff at some government regulatory agencies I interact with.
  • FEBRUARY: It is possible that mRNA technology could cure or prevent herpes, malaria, flu, sickle cell anemia, cancer, HIV, Zika and Ebola (and obviously coronavirus). With flu and coronavirus, it may become possible to design a single shot that would protect against thousands of strains. It could also be used for nefarious purposes, and to protect against that are ideas about what a biological threat surveillance system could look like.
  • MARCH: I officially released my infrastructure plan for America, a few weeks before Joe Biden released his. None of the Sunday morning talk shows has called me to discuss so far. Unfortunately, I do not have the resources of the U.S. Treasury or Federal Reserve available to me. Of course, neither does he unless he can convince Congress to go along with at least some portion of his plans. Looking at his proposal, I think he is proposing to direct the fire hoses at the right fires (children, education, research, water, the electric grid and electric vehicles, maintenance of highways and roads, housing, and ecosystems. There is still no real planning involved, because planning needs to be done in between crises and it never is. Still, I think it is a good proposal that will pay off economically while helping real people, and I hope a substantial portion of it survives.
  • APRIL: Giant tortoises reach a state of “negligible senescense” where they simply don’t age for a long time. Humans are distant relatives of giant tortoises, so maybe we can aspire to this some day. They are not invulnerable to injury and disease.
  • MAY: An effective vaccine for malaria may be on the way. Malaria kills more children in Africa every year than Covid-19 killed people of all ages in Africa during the worst year of the pandemic. And malaria has been killing children every year for centuries and will continue long after Covid-19 is gone unless something is done.
  • JUNE: Masks, ventilation, and filtration work pretty well to prevent Covid transmission in schools. We should learn something from this and start designing much healthier schools and offices going forward. Design good ventilation and filtration into all buildings with lots of people in them. We will be healthier all the time and readier for the next pandemic. Then masks can be slapped on as a last layer of defense. Enough with the plexiglass, it’s just stupid and it’s time for it to go.
  • JULY: A new Lyme disease vaccine may be on the horizon (if you’re a human – if you are a dog, talk to your owner about getting the approved vaccine today.) I admit, I had to stretch a bit to find a positive story this month.
  • AUGUST: The Nordic welfare model works by providing excellent benefits to the middle class, which builds the public and political support to collect sufficient taxes to provide the benefits, and so on in a virtuous cycle. This is not a hopeful story for the U.S., where wealthy and powerful interests easily break the cycle with anti-tax propaganda, which ensure benefits are underfunded, inadequate, available only to the poor, and resented by middle class tax payers.
  • SEPTEMBER: Space-based solar power could finally be in our realistic near-term future. I would probably put this in the “interesting” rather than “hopeful” category most months, but I really struggled to come up with a hopeful story this month. I am at least a tiny bit hopeful this could be the “killer app” that gets humanity over the “dirty and scarce” energy hump once and for all, and lets us move on to the next layer of problems.
  • OCTOBER: The situation with fish and overfishing is actually much better than I thought.
  • NOVEMBER: Urban areas may have some ecological value after all.
  • DECEMBER: Covid-19 seems to be “disappearing” in Japan, or at least was before the Omicron wave. Maybe lessons could be learned. It seems possible that East Asian people have at least some genetic defenses over what other ethnic groups have, but I would put my money on tight border screening and an excellent public health care system. Okay, now I’m starting to feel a bit depressed again, sitting here in the U.S. where we can’t have these nice things thanks to our ignorant politicians.

Most interesting stories, that were not particularly frightening or hopeful, or perhaps were a mixture of both:

  • JANUARY: There have been fabulous advances in note taking techniques! Well, not really, but there are some time honored techniques out there that could be new and beneficial for many people to learn, and I think this is an underappreciated productivity and innovation skill that could benefit people in a lot of areas, not just students.
  • FEBRUARY: At least one serious scientist is arguing that Oumuamua was only the tip of an iceberg of extraterrestrial objects we should expect to see going forward.
  • MARCH: One study says 1-2 days per week is a sweet spot for working from home in terms of a positive economic contribution at the national scale. I think it is about right psychologically for many people too. However, this was a very theoretical simulation, and other studies attempting to measure this at the individual or firm scale have come up with a 20-50% loss in productivity. I think the jury is still out on this one, but I know from personal experience that people need to interact and communicate regularly for teams to be productive, and some people require more supervision than others, and I don’t think technology is a perfect substitute for doing these things in person so far.
  • APRIL: Hydrogen fuel cells may finally be arriving. Not so much in the U.S., where we can’t have nice things.
  • MAY: I learned about Lawrence Kohlberg, who had some ideas on the use of moral dilemmas in education.
  • JUNE: The big U.S. government UFO report was a dud. But what’s interesting about it is that we have all quietly seemed to have accepted that something is going on, even if we have no idea what it is, and this is new.
  • JULY: “Cliodynamics” is an attempt at a structured, evidence-based way to test hypotheses about history.
  • AUGUST: Ectogenesis is an idea for colonizing other planets that involves freezing embryos and putting them on a spaceship along with robots to thaw them out and raise them. Fungi could also be very useful in space, providing food, medicine, and building materials.
  • SEPTEMBER: Philip K. Dick was not only a prolific science fiction author, he also developed a comprehensive theory of religion which could possibly even be the right one. Also, possibly related but not really, if there are aliens out there they might live in creepy colonies or super-organisms like ants or termites.
  • OCTOBER: I thought about how to accelerate scientific progress: “[F]irst a round of automated numerical/computational experiments on a huge number of permutations, then a round of automated physical experiments on a subset of promising alternatives, then rounds of human-guided and/or human-performed experiments on additional subsets until you hone in on a new solution… [C]ommit resources and brains to making additional passes through the dustbin of rejected results periodically…” and finally “educating the next generation of brains now so they are online 20 years from now when you need them to take over.” Easy, right?
  • NOVEMBER: Peter Turchin continues his project to empirically test history. In this article, he says the evidence points to innovation in military technologies being driven by “world population size, connectivity between geographical areas of innovation and adoption, and critical enabling technological advances, such as iron metallurgy and horse riding“. What does not drive innovation? “state-level factors such as polity population, territorial size, or governance sophistication“. As far as the technologies coming down the pike in 2022, one “horizon scan” has identified “satellite megaconstellations, deep sea mining, floating photovoltaics, long-distance wireless energy, and ammonia as a fuel source”.
  • DECEMBER: Time reminded us of all the industries Elon Musk has disrupted so far: human-controlled, internal-combustion-fueled automobiles; spaceflight; infrastructure construction (I don’t know that he has really achieved any paradigm shifts here, but not for lack of trying), “artificial intelligence, neurotechnology, payment systems and cryptocurrency.” I’m not sure I follow a couple of these, but I think they missed satellites.

Continuing Signs of U.S. Relative Decline

Signs of U.S. decline relative to our peer group of advanced nations are all around us. I don’t know that we are in absolute decline, but I think we are now below average among the most advanced countries in the world. We are not investing in the infrastructure needed in a modern economy just to reduce friction and let the economy function. The annual length of electric blackouts in the U.S. (hours) compared to leading peers like Japan (minutes) is just one telling indicator. In March, I looked at the Build Back Better proposal and concluded that it was more like directing a firehose of money at a range of problems than an actual plan, but I hoped at least some of it would happen. My rather low but not zero expectations were met, as some limited funding was provided for “hard infrastructure” and energy/emissions projects, but little or nothing (so far, as I write this) to address our systemic failures in health care, child care, or education. The crazy violence on our streets, both gun-related and motor vehicle-related, is another indicator. Known solutions to all these problems exist and are being implemented to various extents by peer countries. Meanwhile our toxic politics and general ignorance continue to hold us back. Biden really gave it his best shot – but if this is our “once in a generation” attempt, we are headed down a road where we will no longer qualify as a member of the pack of elite countries, let alone its leader.

The Climate Change, Drought, Food, Natural Disaster, Migration and Geopolitical Instability Nexus

2021 was a pretty bad year for storms, fires, floods, and droughts. All these things affect our homes, our infrastructure, our food supply, and our water supply. Drought in particular can trigger mass migration. Mass migration can be a disaster for human rights and human dignity in and of itself, and managing it effectively is difficult even for well-intentioned governments. But an insidious related problem is that migration pressure can tend to fuel right wing populist and racist political movements. We see this happening all over the world, and the situation seems likely to get worse.

Tipping Points and other Really Bad Things We Aren’t Prepared For

We can be thankful that nothing really big and new and bad happened in 2021. My apologies to anyone reading this who lost someone or had a tough year. Of course, plenty of bad things happened to good people, and plenty of bad things happened on a regional or local scale. But while Covid-19 ground on and plenty of local and regional-scale natural disasters and conflicts occurred, there were no new planetary-scale disasters. This is good because humanity has had enough trouble dealing with Covid-19, and another major disaster hitting at the same time could be the one that brings our civilization to the breaking point.

So we have a trend of food insecurity and migration pressure creeping up on us over time, and we are not handling it well even given time to do so. Maybe we can hope that some adjustments will be made there to get the world on a sustainable track. Even if we do that, there are some really bad things that could happen suddenly. Catastrophic war is an obvious one. A truly catastrophic pandemic is another (as opposed to the moderately disastrous pandemic we have just gone through.) Creeping loss of human fertility is one that is not getting much attention, but this seems like an existential risk if it were to cross some threshold where suddenly the global population starts to drop quickly and we can’t do anything about it. Asteroids were one thing I really thought we didn’t have to worry much about on the time scale of any human alive today, but I may have been wrong about that. And finally, the most horrifying risk to me in the list above is the idea of an accelerating, runaway feedback loop of methane release from thawing permafrost or underwater methane hydrates.

We are almost certainly not managing these risks. These risks are probably not 100% avoidable, but since they are existential we should be actively working to minimize the chance of them happening, preparing to respond in real time, and preparing to recover afterward if they happen. Covid-19 was a dress rehearsal for dealing with a big global risk event, and humanity mostly failed to prepare or respond effectively. We are lucky it was one we should be able to recover from as long as we get some time before the next body blow. We not only need to prepare for much, much worse events that could happen, we need to match our preparations to the likelihood of more than one of them happening at the same time or in quick succession.

Technological Progress

Enough doom and gloom. We humans are here, alive, and many of us are physically comfortable and have much more leisure time than our ancestors. Our social, economic, and technological systems seem to be muddling through from day to day for the time being. We have intelligence, science, creativity, and problem solving abilities available to us if we choose to make use of them. Let’s see what’s going on with technology.

Biotechnology: The new mRNA technology accelerated by the pandemic opens up potential cures for a range of diseases. We need an effective biological surveillance system akin to nuclear weapons inspections (which we also need) to make sure it is not misused (oops, doom and gloom trying to creep in, but there are some ideas for this.) We have vaccines on the horizon for diseases that have been plaguing us for decades or longer, like malaria and Lyme disease. Malaria kills more children worldwide, year in and year out, than coronavirus has killed per year at its peak.

Promising energy technologies: Space based solar power may finally be getting closer to reality. Ditto for hydrogen fuel cells in vehicles, although not particularly in the U.S. (I’m not sure this is preferable to electric vehicles for everyday transportation, but it seems like a cleaner alternative to diesel and jet fuel when large amounts of power are needed in trucking, construction, and aviation, for example.)

Other technologies: We are actually using technology to catch fish in more sustainable ways, and to grow fish on farms in more sustainable ways. We are getting better at looking for extraterrestrial objects, and the more we look, the more of them we expect to see (this one is exciting and scary at the same time). We are putting satellites in orbit on an unprecedented scale. We have computers, robots, artificial intelligence of a sort, and approaches to use them to potentially accelerate scientific advancements going forward.

The State of Earth’s Ecosystems

The state and trends of the Earth’s ecosystems continue to be concerning. Climate change continues to churn through the public consciousness and our political systems, and painful as the process is I think our civilization is slowly coming to a consensus that something is happening and something needs to be done about it (decades after we should have been able to do this based on the evidence and knowledge available.) When it comes to our ecosystems, however, I think we are in the very early stages of this process. This is something I would like to focus on in this blog in the coming year. My work and family life are busy, and I have decided to take on an additional challenge of becoming a student again for the first time in the 21st century, but somehow I will persevere. If you are reading this shortly after I write it in January 2022, here’s to good luck and prosperity in the new year!

Pension funds should never rely on correlation

Pension funds should not rely on correlations between mean annual return and variance in annual return when deciding how much stocks and bonds to own, according to this article on which Nassim Nicholas Taleb (the Black Swan guy) is the second author. To paraphrase/oversimplify my understanding of the article greatly, the main arguments are that (1) data from the past is not a perfect predictor of the future, and (2) short term volatility is not a good measure of the risk of achieving a long term goal.

In engineering, I hear #1 all the time from people – why don’t we rely on data instead of “modeling” when trying to predict the future? Of course we do both – try to understand the underlying structure of the system we are dealing with, then use data from the past to try to confirm that we got it right, at least for the conditions that prevailed when the data were collected (and assuming the data themselves are reasonably accurate or at least any measurement error is not biased one way or the other), and then use the resulting model of the system to try to predict the future. Conditions in the future may be different than conditions in the past, and that is why we don’t “just rely on data”. If external conditions are different but the underlying structure of the system doesn’t change (much), we can come up with reasonable predictions of the future. The only true test of whether the prediction is right comes from data which will be collected in the future, but is not available today when a decision has to be made. A lot of decisions are really just playing the odds about what might work in the most likely future, or what might work across several different possible futures that collectively are very likely (a “robust” decision). The decision that is best for the single most likely condition and a group of very likely conditions may not be the same one – now you are a gambler trying to decide whether you go for the biggest possible payoff while accepting a larger chance of a loss, or whether you want to maximize your chances of a positive payoff while giving up your shot at a really big payoff. You would think the pension fund would go for the latter.

#2 makes sense to me. Variability in annual returns doesn’t matter much if you are 25 and investing money you plan to need at 65. A pension fund is a little different, because it is essentially immortal but has obligations it has to meet each year.

In the case of investment returns, the approach seems to be almost purely “data-driven” with no real understanding of the underlying system, and this leads to an existential crisis when people try to figure out what asset allocation advice to stake their future on. We understand the real economy to some extent, we think, but we don’t really seem to confidently understand how the real economy and the financial economy are related, especially over shorter time frames. So we are reduced to just describing the data, which might lead to some insights about the system but has limited predictive value. Still, examining the evidence before making a decision seems like a good idea to me. What is the alternative – guessing, wishing, praying?

those wild, wacky Covid-19 data points

I have noticed for awhile that the CDC’s Covid-19 data doesn’t agree with other sources, which don’t agree with each other. Looking at my home city (and County) of Philadelphia, the CDC’s numbers have been consistently higher for many months. This matters because government agencies, employers (including mine), and individuals are basing decisions on these numbers, often the CDC numbers.

Let’s look at today’s numbers for Philadelphia. I’ll look just at “confirmed cases” because that seems to be the most readily available and frequently updated by all sources, although really I think we should be focused more on deaths at this point, because deaths (although morbid) gives you some information on cases and vaccination/immunity combined. In other words, if cases are high but deaths are low, you would have an annoyance but not a major problem. Nonetheless, let’s look at those cases for Philadelphia today! I’m writing this on Sunday, November 21, 2021. I’m using the links from my coronavirus tracker post.

  • CDC: 111.55 / 100,000 population / 7 days (data from November 13-19)
  • Pennsylvania state health department: 86.4 / 100,000 population / 7 days (data from November 12-18)
  • Covid Act Now: 116.2 / 100,000 population / 7 days (data from November 20 which they describe as a 7 day average provided by the New York Times)

There are a number of things that could explain differences in the numbers. First, the time periods the data represent varying slightly by source. Second, whether the data represent the date the test was done, the test was reported, or the estimated date of infection. Generally I think what is reported is the date the test was done. This is hard data of a sort, but it introduces a time lag as numerous and scattered labs report their data. The data you are looking at might not yet represent all the data available on a given day, and it might be corrected retroactively, meaning if you check what today’s number was a week from now, you might see a different number from today. Finally, when reporting data for a location like a county, it may be important whether they are reporting all tests done in that county or matching tests to the home addresses (or employer addresses?) of the individuals tested. Philadelphia, for example, has a huge health care industry with a lot of commuters not just from surrounding counties in Pennsylvania but parts of New Jersey and Delaware. (States were never the right entities to track this pandemic, it should obviously be done by entities covering metro areas.)

If all the sources were using similar data but using slightly different time periods or calculation methods, I would expect some differences but I would expect the differences to be random. The state health department numbers are consistently lower, however. I am hoping that might be because they are doing a better job of matching tests to home addresses.

more Peter Turchin

Here’s a new journal article from Peter Turchin and his Seshat database to empirically test hypotheses about history.

Rise of the war machines: Charting the evolution of military technologies from the Neolithic to the Industrial Revolution What have been the causes and consequences of technological evolution in world history?

In particular, what propels innovation and diffusion of military technologies, details of which are comparatively well preserved and which are often seen as drivers of broad socio-cultural processes? Here we analyze the evolution of key military technologies in a sample of pre-industrial societies world-wide covering almost 10,000 years of history using Seshat: Global History Databank. We empirically test previously speculative theories that proposed world population size, connectivity between geographical areas of innovation and adoption, and critical enabling technological advances, such as iron metallurgy and horse riding, as central drivers of military technological evolution. We find that all of these factors are strong predictors of change in military technology, whereas state-level factors such as polity population, territorial size, or governance sophistication play no major role. We discuss how our approach can be extended to explore technological change more generally, and how our results carry important ramifications for understanding major drivers of evolution of social complexity.

PLOS One

Glancing through the methods confirms my suspicion that big data or machine learning analyses pretty much start from old-school correlation and regression, then branch out (sometimes literally in things called “trees”) from there.

July 2021 in Review

July 2021 is in the books. In current events (I’m writing on Sunday, August 1), the Delta variant of Covid is now ripping through the unvaccinated population in the U.S. and predictably leaking out into the vaccinated population. I wasn’t too focused on Covid in July though, looking at the posts I have chosen below.

Most frightening and/or depressing story: The western-U.S. megadrought looks like it is settling in for the long haul.

Most hopeful story: A new Lyme disease vaccine may be on the horizon (if you’re a human – if you are a dog, talk to your owner about getting the approved vaccine today.) I admit, I had to stretch a bit to find a positive story this month.

Most interesting story, that was not particularly frightening or hopeful, or perhaps was a mixture of both: “Cliodynamics” is an attempt at a structured, evidence-based way to test hypotheses about history.

junkiest junk charts of 2020

Junk Charts is a great blog that takes an example of a data visualization, critiques it systematically, and then either improves it or shows a different way of displaying the same data. The site doesn’t go for overly elaborate graphics, just clear and effective ones. This post has a roundup of the most viewed posts and the author’s favorite posts of 2020.

One thing you probably shouldn’t do is describe interesting graphics in words. Nonetheless, here is some data, which I am not putting in a visual form because it would take exponentially longer than just listing it out:

  • There are 12 graphics covered by the post.
    • 2 scatter plots
    • 3 bar charts
      • 2 horizontal, not stacked – one of these gets changed to a bump chart
      • 1 horizontal, stacked – actually this is more of a “tree plot” where two data points are stacked and then a third is placed underneath
    • 2 pie charts
      • 1 3D pie chart – gets converted to a bump chart
      • 1 is allowed to continue to exist as a pie chart, with minor tweaks
    • 1 “dot matrix” (I’m not even sure if this is the best name, but basically you have empty squares or circles showing the total number of a thing, then some of them get filled in to illustrate how many of that thing fit a certain category)
    • 3 time series plots
      • 2 conventional – although one has two vertical axes, and the author illustrates how the limits can manipulated to suggest to the eye that two trends are related, or not
      • 1 showing shaded regions over time – basically a stacked bar changing over time
    • 538’s election snake

There is something intuitive about pie charts – that is why we explain fractions and percentages to children in terms of pizza or pie, and they grasp it instantly. Pie charts are obviously the wrong way to compare the absolute magnitudes of things.

I do like tree plots. I made one in 2020 and I was proud of myself – it showed the number of acres served by stormwater management controls implemented by three different administrative programs. And then I made a second one where I broke the numbers down further within each of the categories. This was very effective in conveying how much is actually achieved by each of the programs compared to the effort and expense that goes into them.

Resolution for 2021 is to play with “dot matrix” plots at some point (and maybe learn what the best name for these is.) I think these are effective in putting numbers in context of bigger numbers, regardless of units. For example, my city has around 80,000 cumulative confirmed coronavirus cases, maybe 5,000 confirmed active infections (about the number of confirmed cases in the last 10 days), maybe between 80,000 and 800,000 actual cumulative infections, and a population of about 1.6 million. I don’t know how many have been vaccinated at this point, but probably a few thousand. So maybe I would make 16 or 160 boxes each representing a chunk of people, and start coloring them in. Then we could see at a glance how much of the population might have some immunity to the virus right now, and how much does not. You could slice and dice the data many ways. Of course, some people died or moved away, and others were born or moved in. Incidentally, about 2,600 people died of Covid, 400 were murdered, and 120 died in and around motor vehicles. I haven’t seen numbers on suicides or drug overdoses but they are always horrifying. Around 1% of any given population dies in any given year from a combination of preventable and not preventable causes, which is sad but news flash: we are mortal beings.

This site doesn’t do maps, which is fine. I am a big fan of maps. But I have a very simple test – is the data geographic in nature? Then make a map. But often, some other types of graphs and tables will further illuminate the data, and those often work well alongside your map rather than being shoehorned into your map where they don’t really belong. And I also find it clunky trying to do any type of mathematical analysis in mapping software when the analysis is not spatial in nature.

2020 in Review

2020 has been quite a year for the U.S. and the world, but you don’t need me to tell you that! My work and family life was disrupted, but I have been lucky enough not to lose any family members or close friends to Covid-19 so far. If anyone reading this has lost someone, I want to express my condolences.

Now I’ll get right down to some highlights of my 2020 posts.

Monthly Highlights from 2020

Most frightening or depressing stories:

  • JANUARY: Open cyberwarfare became a thing in the 2010s. We read the individual headlines but didn’t connect the dots. When you do connect the dots, it’s a little shocking what’s going on.
  • FEBRUARY: The Amazon rain forest may reach a tipping point and turn into a dry savanna ecosystem, and some scientists think this point could be reached in years rather than decades. Meanwhile, Africa is dealing with a biblical locust plague. Also, bumble bees are just disappearing because it is too hot.
  • MARCH: Hmm…could it be…THE CORONAVIRUS??? The way the CDC dropped the ball on testing and tracking, after preparing for this for years, might be the single most maddening thing of all. There are big mistakes, there are enormously unfathomable mistakes, and then there are mistakes that kill hundreds of thousands of people (at least) and cost tens of trillions of dollars. I got over-excited about Coronavirus dashboards and simulations towards the beginning of month, and kind of tired of looking at them by the end of the month.
  • APRIL: The coronavirus thing just continued to grind on and on, and I say that with all due respect to anyone reading this who has suffered serious health or financial consequences, or even lost someone they care about. After saying I was done posting coronavirus tracking and simulation tools, I continued to post them throughout the month – for example herehereherehere, and here. After reflecting on all this, what I find most frightening and depressing is that if the U.S. government wasn’t ready for this crisis, and isn’t able to competently manage this crisis, it is not ready for the next crisis or series of crises, which could be worse. It could be any number of things, including another plague, but what I find myself fixating on is a serious food crisis. I find myself thinking back to past crises – We got through two world wars, then managed to avoid getting into a nuclear war to end all wars, then worked hard to secure the loose nuclear weapons floating around. We got past acid rain and closed the ozone hole (at least for awhile). Then I find myself thinking back to Hurricane Katrina – a major regional crisis we knew was coming for decades, and it turned out no government at any level was prepared or able to competently manage the crisis. The unthinkable became thinkable. Then the titans of American finance broke the global financial system. Now we have a much bigger crisis in terms of geography and number of people affected all over the world. The crises may keep escalating, and our competence has clearly suffered a decline. Are we going to learn anything?
  • MAY: Potential for long-term drought in some important food-producing regions around the globe should be ringing alarm bells. It’s a good thing that our political leaders’ crisis management skills have been tested by shorter-term, more obvious crises and they have passed with flying colors…doh!
  • JUNE: The UN just seems to be declining into irrelevancy. I have a few ideas: (1) Add Japan, Germany, India, Brazil, and Indonesia to the Security Council, (2) transform part of the UN into something like a corporate risk management board, but focused on the issues that cause the most suffering and existential risk globally, and (3) have the General Assembly focus on writing model legislation that can be debated and adopted by national legislatures around the world.
  • JULY: Here’s the elevator pitch for why even the most hardened skeptic should care about climate change. We are on a path to (1) lose both polar ice caps, (2) lose the Amazon rain forest, (3) lose our productive farmland, and (4) lose our coastal population centers. If all this comes to pass it will lead to mass starvation, mass refugee flows, and possibly warfare. Unlike even major crises like wars and pandemics, by the time it is obvious to everyone that something needs to be done, there will be very little that can be done.
  • AUGUST: We just had the 15-year anniversary of Hurricane Katrina, a major regional crisis that federal, state, and local governments failed to competently prepare for or respond to. People died, and decades later the recovery is incomplete. Coronavirus proves we learned nothing, as it is unfolding in a similar way on a much larger and longer scale. There are many potential crises ahead that we need to prepare for today, not least the inundation of major cities. I had a look at the Democratic and (absence of a) Republican platforms, and there is not enough substance in either when it comes to identifying and preparing for the risks ahead.
  • SEPTEMBER: The Covid recession in the U.S. is pretty bad and may be settling in for the long term. Demand for the capital goods we normally export (airplanes, weapons, airplanes that unleash weapons, etc.) is down, demand for oil and cars is down, and the service industry is on life support. Unpaid bills and debts are mounting, and eventually creditors will have to come to terms with this (nobody feels sorry for “creditors”, but what this could mean is we get a full-blown financial panic to go along with the recession in the real economy.
  • OCTOBER: Global ecological collapse is most likely upon us, and our attention is elsewhere. The good news is we still have enough to eat (on average – of course we don’t get it to everyone who needs it), for now.
  • NOVEMBER:  It seems likely the Clinton-Bush-Obama-Trump U.S. foreign wars may just grind on endlessly under Biden. Prove us wrong, Joe! (I give Trump a few points for trying to bring troops home over the objections of the military-industrial complex. But in terms of war and peace, this is completely negated and then some by slippage on nuclear proliferation and weapons on his watch.)
  • DECEMBER: The “Map of Doom” identifies risks that should get the most attention, including antibiotic resistance, synthetic biology (also see below), and some complex of climate change/ecosystem collapse/food supply issues.

Most hopeful stories:

  • JANUARY: Democratic socialism actually does produce a high quality of life for citizens in many parts of the world. Meanwhile, the hard evidence shows that the United States is slipping behind its peer group in many measures of economic vibrancy and quality of life. The response of our leaders is to tell us we are great again because that is what we want to hear, but not do anything that would help us to actually be great again or even keep up with the middle of the pack. This is in the hopeful category because solutions exist and we can choose to pursue them.
  • FEBRUARY: A proven technology exists called high speed rail.
  • MARCH: Some diabetics are hacking their own insulin pumps. Okay, I don’t know if this is a good thing. But if medical device companies are not meeting their patient/customers’ needs, and some of those customers are savvy enough to write software that meets their needs, maybe the medical device companies could learn something.
  • APRIL: Well, my posts were 100% doom and gloom this month, possibly for the first time ever! Just to find something positive to be thankful for, it’s been kind of nice being home and watching my garden grow this spring.
  • MAY: E.O. Wilson is alive and kicking somewhere in Massachusetts. He says if we want to save our fellow species and ourselves, we should just let half the Earth revert to a natural state. Somewhat related to this, and not implying my intellect or accomplishments are on par with E.O. Wilson, I have been giving some thought to “supporting” ecosystem services in cities. When I need a break from intellectual anything, I have been gardening in Pennsylvania with native plants.
  • JUNE: Like many people, I was terrified that the massive street demonstrations that broke out in June would repeat the tragedy of the 1918 Philadelphia war bond parade, which accelerated the spread of the flu pandemic that year. Not only does it appear that was not the case, it is now a source of great hope that Covid-19 just does not spread that easily outdoors. I hope the protests lead to some meaningful progress for our country. Meaningful progress to me would mean an end to the “war on drugs”, which I believe is the immediate root cause of much of the violence at issue in these protests, and working on the “long-term project of providing cradle-to-grave (at least cradle-to-retirement) childcare, education, and job training to people so they have the ability to earn a living, and providing generous unemployment and disability benefits to all citizens if they can’t earn a living through no fault of their own.”
  • JULY: In the U.S. every week since schools and businesses shut down in March, about 85 children lived who would otherwise have died. Most of these would have died in and around motor vehicles.
  • AUGUST: Automatic stabilizers might be boring but they could have helped the economy in the coronavirus crisis. Congress, you failed us again but you can get this done before the next crisis.
  • SEPTEMBER: The Senate Democrats’ Special Committee on the Climate Crisis had the courage to take aim at campaign finance corruption as a central reason for why the world is in its current mess. I hate to be partisan, folks, but right now our government is divided into responsible adults and children. The responsible adults who authored this report are the potential leaders who can lead us forward.
  • OCTOBER: We have almost survived another four years without a nuclear war. Awful as Covid-19 has been, we will get through it despite the current administration’s complete failure to plan, prevent, prepare, respond or manage it. There would be no such muddling through a nuclear war.
  • NOVEMBER: The massive investment in Covid-19 vaccine development may have major spillover effects to cures for other diseases. This could even be the big acceleration in biotechnology that seems to have been on the horizon for awhile. These technologies also have potential negative and frivolous applications, of course.
  • DECEMBER: The Covid-19 vaccines are a modern “moonshot” – a massive government investment driving scientific and technological progress on a particular issue in a short time frame. Only unlike nuclear weapons and the actual original moonshot, this one is not military in nature. (We should be concerned about biological weapons, but let’s allow ourselves to enjoy this victory and take a quick trip to Disney Land before we start practicing for next season…) What should be our next moonshot, maybe fusion power?

Most interesting stories, that were not particularly frightening or hopeful, or perhaps were a mixture of both:

  • JANUARY: Custom-grown human organs and gene editing and micro-satellites, oh my!
  • FEBRUARY: Corporate jargon really is funny. I still don’t know what “dropping a pin” in something means, but I think it might be like sticking a fork in it.
  • MARCH: I studied up a little on the emergency powers available to local, state, and the U.S. federal government in a health crisis. Local jurisdictions are generally subordinate to the state, and that is more or less the way it has played out in Pennsylvania. For the most part, the state governor made the policy decisions and Philadelphia added a few details and implemented them. The article I read said that states could choose to put their personnel under CDC direction, but that hasn’t happened. In fact, the CDC seems somewhat absent in all this other than as a provider of public service announcements. The federal government officials we see on TV are from the “Institute of Allergies and Infectious Diseases”, which most people never heard of, and to a certain extent the surgeon general. I suppose my expectations on this were created mostly by Hollywood, and if this were a movie the CDC would be swooping in with white suits and saving us, or possibly incinerating the few to save the many. If this were a movie, the coronavirus would also be mutating into a fog that would seep into my living room and turn me inside out, so at least there’s that.
  • APRIL: There’s a comet that might be bright enough to see with the naked eye from North America this month. [Update: It wasn’t. Thanks, 2020.]
  • MAY: There are unidentified flying objects out there. They may or may not be aliens, that has not been identified. But they are objects, they are flying, and they are unidentified.
  • JUNE: Here’s a recipe for planting soil using reclaimed urban construction waste: 20% “excavated deep horizons” (in layman’s terms, I think this is just dirt from construction sites), 70% crushed concrete, and 10% compost.
  • JULY: The world seems to be experiencing a major drop in the fertility rate. This will lead to a decrease in the rate of population growth, changes to the size of the work force relative to the population, and eventually a decrease in the population itself.
  • AUGUST: Vehicle miles traveled have crashed during the coronavirus crisis. Vehicle-related deaths have decreased, but deaths per mile driven have increased, most likely because people drive faster when there is less traffic, absent safe street designs which we don’t do in the U.S. Vehicle miles will rebound, but an interesting question is whether they will rebound short of where they were. One study predicts about 10% lower. This accounts for all the commuting and shopping trips that won’t be taken, but also the increase in deliveries and truck traffic you might expect as a result. It makes sense – people worry about delivery vehicles, but if each parcel in the vehicle is a car trip to the store not taken, overall traffic should decrease. Even if every 5 parcels are a trip not taken, traffic should decrease. I don’t know the correct number, but you get the idea. Now, how long until people realize it is not worth paying and sacrificing space to have a car sitting there that they seldom use. How long before U.S. planners and engineers adopt best practices on street design that are proven to save lives elsewhere in the world?
  • SEPTEMBER: If the universe is a simulation, and you wanted to crash it on purpose, you could try to create a lot of nested simulations of universes within universes until your overload whatever the operating system is. Just hope it’s backed up.
  • OCTOBER: There are at least some bright ideas on how to innovate faster and better.
  • NOVEMBER: States representing 196 electoral votes have agreed to support the National Popular Vote Compact, in which they would always award their state’s electoral votes to the national popular vote winner. Colorado has now voted to do this twice. Unfortunately, the movement has a tough road to get to 270 votes, because of a few big states that would be giving up a lot of power if they agreed to it.
  • DECEMBER: Lists of some key technologies that came to the fore in 2020 include (you guessed it) mRNA vaccines, genetically modified crops, a variety of new computer chips and machine learning algorithms, which seem to go hand in hand (and we are hearing more about “machine learning” than “artificial intelligence” these days), brain-computer interfaces, private rockets and moon landings and missions to Mars and mysterious signals and micro-satellites and UFOs, virtual and mixed reality, social media disinformation and work-from-home technologies. The wave of self-driving car hype seems to have peaked and receded, which probably means self-driving cars will probably arrive quietly in the next decade or so. I was surprised not to see cheap renewable energy on any lists that I came across, and I think it belongs there. At least one economist thinks we are on the cusp of a big technology-driven productivity pickup that has been gestating for a few decades.

That’s a lot to unpack, and I’m not sure I can offer a truly brilliant synthesis, but below are a few things that are on my mind as I think through all this.

We Americans affirmed that we care about our parents and grandparents (then failed to fully protect them).

One thing I think we learned is that we still value human lives more than a cold, purely economic calculation might suggest, including the lives of our elderly parents and grandparents. (Though we had significant failures of execution when it came to actually protecting people – more on that later.) We have had this debate before in the U.S., for example when thinking about how much to invest in environmental and safety regulations as I was reminded of by this Planet Money podcast. At one point, politicians (can you guess from which party) proposed valuing the lives of senior citizens at lower rates than everyone else. The backlash was fierce and instant, and the proposal was withdrawn. This year, we did not really have that debate – it was simply accepted, for the most part, that we would be willing to endure significant economy-wide pain to try to protect our parents and grandparents.

I kind of liked how Mr. Money Mustache put it back in April. He gave a “worst case scenario” with 3 million deaths and a “best case scenario” with 200,000 deaths, and the reality is on track to be somewhere in between.

In the worst case, our public officials would all downplay the risk of COVID-19, and we’d keep working and traveling and spreading it freely. We’d maximize our economic activity and let the disease run its course…

In the more compassionate case which we are currently following, we drastically reduce the amount of contact we have with each other for a few months, which cuts the number of deaths in the US down from 3-6 million, down to perhaps 200,000. In exchange, our economy shrinks by several trillion dollars (it was about 21 trillion in 2019) for a year or more.

Assuming we are preventing 3 million early deaths, this means our society is foregoing about one million dollars of economic activity for each person’s life that we extend and frankly, it makes me happy to know we are capable of that.

Mr. Money Mustache

The leaders of some countries like Russia, Brazil, and even Sweden seem to have chosen to accept the consequences of business as usual. Most other countries have chosen to try to save human lives at the expense of short-term economic activity, and some executed this strategy much more effectively than others. In the U.S. and UK, we seem to be bumbling idiots who feel some compassion for one another.

The United States has been slipping for awhile, and in 2020 we faltered.

The U.S. continues to slip below average among its developed country peers in many statistical categories like life expectancy, violence, incarceration, suicide, poverty, and public infrastructure. I picture us like a horse that used to be leading the race, then slipped into the middle of the leading pack, and has now drifted toward the back of the leading pack and is continuing to lose ground. Keep slipping and we would no longer be part of the leading pack.

But then came Covid-19, our horse faltered, and all the other horses went thundering past, leaving us in last place. With the possible exception of the UK, we had the least effective response in the world. Like I said, I think a few countries like Russia, Brazil, and Sweden basically chose to accept the consequences of a limited response, and that is different than a failed response (though not to the people who died or whose loved ones died). We tried to respond, and it turned out our government was unprepared and incompetent even compared to developing countries.

So what happened? Some particular failing of the Anglo-American countries doesn’t explain it, because Canada and Australia both did pretty well. Our lack of a public health system (or even universal access to private care) doesn’t explain it, because the UK, Canada, and Australia all have similar systems to each other and divergent outcomes.

The difference between the extraordinary low rates in Asia, and the higher rates in Europe and the Americas is particularly stark. There are a couple things that I think may explain it. First is good airport screening. I traveled in Asia during the swine flu pandemic, and the screening is robust. The U.S. obviously has to beef up its health infrastructure at international airports and other border crossings (yes, there is a certain irony here that is lost on anti-immigrant types.) Part of this is also beefing up the data systems that track who is coming in from where, where they are going and what their status is. It became obvious within weeks that the CDC’s databases were a complete failure.

I think beyond border screening and data management, the other big difference between East and West is that Asian countries were willing to restrict physical movement and enforce quarantine, whereas western countries mostly were not. Had I exhibited symptoms while I was traveling in Singapore or Thailand during the swine flu, either country would have detained me in a government facility (with three meals a day and wi-fi, one would hope) for 14 days. Asian countries have also been willing to shut down domestic airports, train systems, and highways at times. Most western countries are simply not willing to do this. In the U.S., I think it is partly a matter of law and politics, but also a stupid idea that it would be “too expensive” when quite obviously it would have saved trillions of dollars in the long run. We simply don’t have the political will, the institutional mechanisms, or the basic competence. Covid-19 was a borderline crisis – a lot of people will lose cherished parents and grandparents but it is not an existential threat to our country’s survival. The U.S. needs to plan now to quarantine effectively in an even worse pandemic or god forbid, an incident involving biological weapons.

A few words on government agencies. Hurricane Katrina came up a few times in the monthly picks above. That was a major failure of federal, state, and local governments in the U.S. to plan, respond, and rebuild after a disaster. Before that, I would have assumed FEMA was up to the task, as they seem to have been in the past. Most people’s faith in the CDC was similar or even greater, and they turned out to be bumbling fools. The U.S. will need to fund its public agencies, stock them with competent, well-trained technocrats, and appoint talented political leaders to integrate them with the rest of society if they are going to function competently in the future.

In a hurricane, FEMA basically rolls into your city and takes charge, for better or worse. Early on, there was speculation that the CDC might try to do something similar in a disease outbreak. That didn’t happen. We will also need to adequately fund and train state and local agencies, if we are going to continue to put the lion’s share of the burden on them in a decentralized disaster like this. We could just get rid of the states and have the federal government work directly with metro areas, but this seems like a pretty pie in the sky idea politically.

What other government agencies do we have faith in that might have turned into rotten hollow logs while we weren’t paying attention? The Treasury and Federal Reserve do in fact seem to know what they are doing, which has saved us a couple times now in the last couple decades. We assume the military can fight a war if they need to. We assume the Department of Agriculture can feed us. Are we sure?

The democratization of propaganda.

Governments in general, and the U.S. government in particular, are having trouble getting messages out to their citizens. We used to worry about governments and big business controlling the media to put out purely ideological or purely profit-driven messages. Now anyone in the world can pretty much say anything anytime. People have trouble telling which messages are truthful and which are more reliable than others. In the U.S., this is combined with low trust in government and low trust in experts, and the result is that people either didn’t receive important messages about public health, or received a variety of conflicting information and noise and didn’t reach reasonable conclusions reading to reasonable decisions.

We hear a lot about “following the science” and “listening to scientists”, but this is really about policy communication not science communication. Scientists are trained to communicate uncertainty to each other. Often though, the uncertainty is low enough that it is clear one course of action has better odds of a good outcome than others. Media do not communicate this well – they tend to focus on the uncertainty statements scientists make, even when uncertainty is low and the best course of action is clear. The public is not prepared to process this information in a way that will lead to reasonable conclusions and decisions.

So we need to try to educate children to evaluate the source of information and think critically about whether it makes sense in the context of what they know. We need to educate them about uncertainty and decision making. We need to train journalists better to communicate scientific information but especially policy choices. Regulating social media companies might play some small role in this, but in the U.S. at least we don’t want to see a move toward censorship.

Back to the CDC. When Covid-19 hit, I was expecting the CDC to step in and dominate communications from the beginning on the issue. They needed to use all the tools modern advertising has to get messages across. I would have trusted what they said, and I think a lot of people would. If they had seized the initiative, it would have been hard for other voices to compete, and we might be in a better place now. Unfortunately, they have probably suffered a permanent loss of credibility both through poor communication and inadequate action, but better communication would definitely have helped. Make this one more U.S. institution that has lost credibility in my eyes as I have gotten older – Congress, the State Department, and the New York Times after weapons of mass destruction (I never trusted intelligence agencies), the military after the failures in Afghanistan and Iraq (I’m not saying I trusted them per se, but I thought they were good at fighting wars), FEMA after Hurricane Katrina (and more recently the horrific non-response in Puerto Rico), and now the CDC and federal public health establishment.

I have come to respect local public health authorities more through all of this. I actually work in the same building as my local public health agency, and know some people who work there, but I never really saw the connection to the larger health care system or my daily life before this. Part of the federal government’s communication strategy should be to package crystal clear messages for delivery by trusted local individuals like public health workers, family doctors, and school nurses.

Preparing for the big (and small) risks

Covid-19 has caused me to think even more about risk management. A major pandemic was something we knew was virtually certain to happen at some point, and we knew the consequences could be severe. And yet we still failed to adequately plan, prepare, and respond. There are a few other things in this category, like (obviously) another pandemic, a major earthquake, and sea level rise. Then there are risks where we are not sure of the probability, but the consequences could be catastrophic, like nuclear and biological war, ecological collapse, and major food shortages. (Alien invasion? No, I’m not really taking this seriously, but along with things like “gray goo” it should be on the list and discussed, providing a rational basis for taking action or not.) Then there are things that are certain to happen but are geographically limited (storms, fires, floods) or steadily kill a few people here and there adding up to a lot over time (car crashes, air pollution, poor nutrition). I am not sure where some risks fit in, for example cyberattacks or antibiotic resistance – but this is the point of gathering the information and having the discussions in a rational framework. In a rational world, a risk management framework provides a way to allocate finite resources (money, effort, expertise, research) to planning, preparing, mitigating, or simply choosing to accept each of these.

The state of scientific and technological progress (is the Singularity near yet?)

I had a decent technology list under “most interesting post” for December, so I won’t repeat it here.

Above, I find myself referring to the Covid vaccine as a “moon shot”. It is clearly an example of how a big government push can get a new technology over the finish line and bring it into widespread use quickly. I am wondering though if it is a true example of accelerating a scientific breakthrough, an example of accelerating application of a scientific breakthrough to new technology, or simple a case of government correcting a market failure. We had been hearing about mRNA vaccine technology for awhile, and we know a vaccine was developed for SARS but not widely deployed. We have also been hearing for awhile that drug companies were still growing basic childhood vaccines in chicken eggs, and not investing heavily in the mRNA technology, because the market demand and profit potential was not there in the rich countries to make it worth their while. So this was at least partially a case of the U.S. and other governments making that market failure go away by simply paying for everything and simply transferring the profits to those companies. I am not saying this is bad – we do it for arms manufacturers all the time, so why not vaccines?

Vaccines for HIV, dengue fever and other similar mosquito-borne diseases would be nice. One solution to antibiotic resistance might be bacteriophages – viruses tailored specifically to infect and kill specific bacteria. It seems like this technology could be applied to this. If antibiotic resistance is really the medium- to long-term emergency some say it is, maybe this should be a top priority.

This technology is also scary. It is the ability to create a custom organism that can go into a person’s body and have a specific desired effect. Vaccines are obviously a benign application, but somebody, somewhere, sometime will use this technology for evil. This seems like a near-existential risk on the horizon that needs to be dealt with.

I am going to say no, the Singularity is not imminent in 2021. Then again, the idea is that if at some point we hit the knee of the curve on technology and productivity, it will seem to accelerate all at once, because that is the nature of exponential change. If that happens, we will shrug and say we knew it all along. The trick is to find ways to drive innovation and progress while managing the risks that could temporarily but repeatedly set back or permanently derail that path, and without destroying our planetary ecosystem in the process. I am not ready to put odds on what outcome we are headed for, but I am hoping 2021 will at least bring a gradual return to the pre-Covid status quo, and allow us to set the stage for the future.

If anyone has actually read my ramblings all the way to this point, or just skipped to the end, Happy New Year!

2020 visualizations from FiveThirtyEight

Fivethirtyeight.com has a roundup of interesting visualizations they did in 2020. There’s a lot here, but one theme I think I would like to try to make use of is is pretty simple. When you are counting something, put the count in context by first showing a bunch of empty squares that represent the potential or total number of something (voters, or citizens stopped by police, or human beings with potential Covid exposure). Then put dots in some of the boxes, or color in some of the boxes, to illustrate the count. If you want to introduce some additional categories, you can use colors or put boxes around the boxes, or to get really fancy, put groups of boxes on a map. This technique undoubtedly has a name, but the article doesn’t tell me what the name is.