Critical mass of social contagion and Covid-19

You can understand the Covid-19 pandemic and its impacts better with the latticework of mental models. You can also become better prepared for future pandemics with the latticework. Even though the virus is a biological phenomenon, it spreads through social contagions when the critical mass is achieved. If you understand social contagions better, you can see what needs to be done and how to cope with the pandemic better.

Covid-19 as a social contagion

Covid-19 spreads through the population with close human contacts. Like all social contagions, it has three parts. First, there are a significant few. They are people who spread the disease faster than the rest of the population. Second, social contagion needs to be sticky to spread. Third, it needs the right environment to spread. When all these three parts are in place, the virus soon becomes unstoppable, after the critical mass is achieved, unless you do something. When the critical mass is achieved, the growth accelerates exponentially, until it starts to decelerate. The contagion collapses eventually.

Let us start with the significant few who spread the virus faster than the rest of us. What is common with these people is that they have a better possibility to spread the virus. They meet lots of people and they have close contacts or they have close contacts with these people. They can be real estate agents, work in junk food restaurants or work in call centers, etc. They live in dense urban areas or use public transportation to commute to work. They are also people who have to work for a living, are workaholics, or do not care about minor illnesses like flu. The best way to stop or slow the pandemic is to focus on finding the significant few who spread the virus faster. Then you have to limit their odds of spreading the virus which means that you have to stop them to meet anyone.

In the second part, the stickiness factor is simple. One reason why COVID-19 is so sticky is that many people who spread it do not know they have it. They can spread it without knowing it and it is a problem. This fact is important because they have not tested people who do not have any symptoms. The other reason why it is sticky is explained by the fact that it does not kill people easily or fast. It is not like Sars which killed many more people compared to the number of infections and disappeared fast. The third factor which made it sticky is the length of high odds of spreading. Covid-19 can spread about two weeks from the first symptoms. One problem is that we do not know if it can spread even before the first symptoms arrive. I am not a professional. I have no exact data about the disease.

The environment is simple. Covid-19 spreads through social contacts. Urban areas with dense populations are ideal places to spread. It is hard to avoid social contacts when you live in a place like them. You cannot avoid all people in dense areas. It also spreads in events and places in which many people gather together closely. These events and places include sports events, weddings, public transportation, etc. These events and places have to be shut down when you want to avoid spreading the virus. All you need is a one-person with the virus and it spreads like a wildfire in a dry season.

The faster you can address all these factors and manipulate them, the less the virus spreads. If I am right about the latter, the first wave of the disease decelerates its spread faster in the countries which have focused on the factors than public offices have predicted. Time will tell us whether that is the case. When the contagions are dangerous like the pandemic, it is better to overreact than undermine its effect. If you want to stop spreading your actions have to be fast and decisive. Therefore, the actions that the public feels are not necessary, are smart things to do when it comes to social contagions with highly negative effects. And because this pandemic is a power-law event, you cannot predict it or its impact on societies.

The next text is about Covid-19 and evolution.

Until then,

-TT

PS. Do you consider yourself as a helpful person? If you found anything useful in this text, teach it to your friends.

Power law distributions

The last text was about Mediocristan and Extremistan. Let's forget the former and focus on the latter. Extremistan is a world in which the enormous outcomes are the results of small causes. 80/20 rule is the best known power-law distribution. It states that 80 percent of the outcomes come from 20 percent of the causes. This is just one power-law distribution and there are uncountable amounts of them. Do not focus on the 80/20 rule when you think about power-law distributions. Covid19-epidemic is an extreme example of a power-law distribution. Even though it is not sure, it likely started when one person ate some part of an animal he should not have. Millions of people will suffer from the virus.

The good, the bad and the irrelevant

It is not important to only understand that a minority of causes or inputs produce the majority of effects and outputs. Understanding that the majority of causes or inputs produce a minority of causes and outputs is equally important. Let's say that your causes and effects have 80/20 distribution. Then 80 percent of your causes and inputs are irrelevant. Their effects and outputs are close to zero. It is safe to say that 20 percent of your causes and inputs have large positive and negative effects and outputs. If your life is good, then your 20 percent has larger positive than negative effects. If your life is bad, the negative effects of that 20 percent are larger.

You do not have to be a rocket scientist to understand you have to enlarge the effects of positive causes and inputs in your life and diminish the negative ones. You can change to get rid of some of the irrelevant 80 percent of the causes and inputs. Change them into positives. It is unlikely you can get rid of all the negative causes and inputs. You can find ways to diminish some of the effects and outputs. You can transform some of them into irrelevant ones.

Long-term predictions are not smart in Extremistan

You can make predictions in Extremistan and be right for a short time, but the overall results of predictions are usually negative. As I mentioned in the last text, you need 100 billion fold data points in the 80/20 world compared to the normal distribution world. When the power-law distribution is 50/1, you cannot have enough data points or computing power to make any useful predictions. Financial markets and economies are parts of Extremistan. Therefore, an economist, financial pundit, or someone else who believes they can make exact predictions are idiots. Their total effect on the economy is negative. The funny thing is that they believe their predictive models are based on solid math. In short, do not believe anyone who believes they can make any useful long-term predictions in any social interactions. The world today is not predictable.

When predicting is not possible, you have to prepare for everything. How to do it is a whole another ball game. One way to deal with it is to reduce tight interactions. Do not use all your resources to achieve something like putting all of your time or other resources like money into one endeavor. Be less leveraged than you can. Have smaller debts than you can take. Be more independent. Rely less on other people and their resources. Have many income streams. Then you rely less on a single one.

Start making small experiments. Make small and numerous adjustments to your inputs. See what happens. There are lots of examples of what you can do. Make small changes in your marketing materials when you can do them in a cost-efficient way. Change a few words or colors, etc. Make small adjustments to your daily habits like your eating. See what happens if you diminish the availability of bad nutrition and increase the availability of a good one. Put some of your sweets (if you have them at home or work) into somewhere you cannot see them without increased effort in finding them.

Do you consider yourself a helpful person? If you found anything useful in this text, teach it to your friends.

Until next time,

-TT

Mediocristan and Extremistan

There are two statistical worlds in which we live. Nassim Taleb has described them with names Mediocristan and Extremistan. The first world is a normal distribution world and the second world has extreme distributions. In mediocristan, two persons that have a combined length of 4.00 meters are close to each other. For example, they have 2.01meters and 1.99 meters in length. In extremistan, there are two persons whose combined wealth is 10 million. It is most likely that one of them has wealth close to that of 10 million and the other has wealth about 100,000. As you can see, these worlds are totally different from each other. In other words, one figure does not change statistics much in Mediocristan, but one figure can change everything in Extremistan.

Mediocristan

Mediocristan is the world where the majority of the people think we live in. This applies even to the majority of the most educated persons. Success equals effort and skills in this world. Mediocristan applies to most biological effects on humans. Genes work in ways that produce mostly results that can be found the normal distribution. The results that genes produce have high predictability. You can define probabilities to them and they do not change much. Here are some percentages how much some biological or psychological attributes of humans are explained by the genes they inherit:

• Height 70%, Weight 80%
• Reading disability 60%, Verbal ability 60%
• Face remembrance 60%, Spacial ability 70%
• General intelligence 50 %, Personality 40%

As you likely know, your biological parents´ genes affect your biological and psychological traits. If they have some extreme traits, likely, these traits are not so extreme in you. In a world with normal distributions, return to averages happen fast. If you have a height of 2.10 meters, your son´s height will likely be closer to average.

Extremistan

Extremistan is the place where a minority of the people think we live in. Extremistan applies to most social effects on humans. Success is non-linear with effort in this world. Social contagions produce results that produce extreme distributions. Most of them are from Extremistan. Some social attributes that are from Extremistan are book sales per author, wealth, and sizes of companies. There is no predictability in Extremistan. It is almost impossible to predict extreme statistical distributions like changes in stock prices. Even figuring out the mean of a simple 80/20 Pareto distribution requires a sample size of a hundred billionfold compared to normal distribution according to Taleb. Changes in stock prices have much larger extreme distribution. Therefore, they cannot be predicted in any modern computer or human brain. This means is that it is much easier to prove that someone is wrong than what the reality is. Today´s world suffers from the domination of high-effect, low-probability events. Most scientific breakthroughs happen when they are not expected, instead of deadlines put to researchers.

Events and effects that combine both worlds

Some events happen in both worlds. For example, some economic effects from predictable catastrophes like earthquakes have extreme distributions. An earthquake that has twice the power than the other can cause tenfold economic effects on people. The earthquake in the same magnitude as 100 years before can also cause manyfold effects today than it did then. These kinds of socio-economic effects grow in magnitude when more people live in big cities, and we use more of nature´s resources.

The modern world grows larger and larger winner-take-all effects. Even a little bit more skillful athletes can earn ten times more money than athletes a few percentage points below their skill levels. The same effects can apply to authors, musicians, and other artists. But this does not always apply. Even a little bit luckier author with the same skills can make a hundredfold more money than others.

Nothing to add,

-TT

Next text delayded due to sickness

Sorry for not publishing anything, but I have been sick for almost two weeks. I hope next post will be ready next week.

-TT

Three levels of causation

What makes you smarter than other animals? You can understand that the stimuli you receive do not represent only facts or data. The latter is the modern word for the former. You can also understand that the stimuli you receive are connected by cause-effect relationships. Your understanding of data consists of these relationships and you can act based on them. You can also imagine new events by using these relationships. No other animal can do it. The ladder of causation consists of three levels of cognitive ability.

The first level, seeing or observing

Your brain is a great pattern detection machine. It can observe and receive stimuli around it. It does that with greater efficiency than you can think. Your brain makes all kinds of associations based on the stimuli you have received in different situations in your life. It can also make good predictions based on those associations which are based on your experiences without specific reasons. The problem is that data is mostly stupid. It does not tell about cause-effect relationships. It does not tell which is the cause and which is the effect. You have to interpret and understand the data. Your brain can make good predictions to questions like ”What if I see x doing y” or ”How are stimuli related to each other?” If artificial intelligence is at this first level, it cannot function in new situations. Every new situation has to program to it by a human being. This level is all about the observed world.

The second level, doing or intervening

When in the first level you can observe things that have already happened, in the second level you can change them on purpose. You cannot understand cause-effect relationships just by observing them without interventions or smart experiments or copy somebody else´s actions. You cannot answer the question: ”What happens to the sales of iPhones if you drop the price by 40%?” if you have no observations beforehand.

Scientific experiments made in controlled conditions are second-level tools. For example, an online retailer can direct different customers to slightly different sales pages that sell the same products. Then, it can see the data about the conversion rate of both of them. Good questions at this level: ”What if you change red to blue color?” or ”What if you ban a person from doing something?” This second level of causation also makes it possible for you to create great causal models based on your observational data. This can be done even without experimentation if the cause-effect relationships are reliable enough. This level is all about an observable new world.

The third level, imagining or retrospection

Imagination can create answers to questions without data at all. For example, you can think about what had happened if you had not done anything. You can more easily understand the reasons behind certain outcomes. For example, you can think about what could have happened if you were unlucky and separate luck from skill. You can compare your observed data to an imaginary world or an imaginary outcome. You can also invent something that is currently not from this world without making any experiments. This level is all about the world that does not exist, yet. Technological developments do not happen without this level. Reaching out beyond the existing reality is not possible.

A simple example of all levels

A simple experiment is to lower the price of something for 50 percent. The first level of causation means that you cannot know what happens unless you have done it before. No statistical methods can be used to discover what happens unless you have experienced the same price reduction before. It is not the same thing to lower the price from 3$ to 1.50$ than from the previous experience: 2$ to 1$. The second level of causation demands experimentation of letting some customers have the price reduction and not giving the same price reduction to others. The second level of causation does not answer the question: What if we had reduced the price to 2$ from 3$? It is the third level question. This requires imagination.

This is all for this time,

-TT

Aging and skills

You have to consider age when you think about skills. Physical and cognitive skills have different perspectives about age. Physical skills like playing basketball have different characteristics than cognitive skills like playing chess. All the statistics about ages are from Michael Mauboussin´s book The Success Equation. It is a good book about skills and luck.

Physical skills

Different physical skills like sports have different optimal ages for peak performance. They are not the exact figures but small ranges of ages. Men and women have small differences between their peak ages depending on the sports. There are no specific ways to determine which physical skills have higher or lower peak ages. A simple answer is that skills that need more fast-twitch muscle fibers have lower peaks and skills that need more slow-twitch muscle fibers to have higher peaks. For example, running fast requires fast fibers, and endurance running requires slow fibers. Peak performance for running fast happens when you are 22-24-year-old male and 21-23 old female. Peak performance for endurance running is 26-28 for both genders.

There are also some other physical characteristics like the visual system and the body-eye-coordination that need to be considered. Visual acuity weakens when you age. Therefore, baseball batters lose their edge after a certain age. Basketball players need both, fast-twitch fibers and great body-eye-coordination, therefore their peak age (24-26) is lower than peak age for baseball (27-29). Athletes that rely only on their body-eye-coordination like golfers (30-35) have higher peak ages than other athletes.

Cognitive skills

Cognitive skills usually mean the ability to make decisions. If you want to make good decisions, you have to be able to understand the stimuli you confront, how it relies on the understanding you already had about the similar or relevant stimuli about the situation, to understand what stimuli to discard and what to use to make a decision and overcoming your intuition if it is needed. Aging has a much slower effect on your ability to use your cognitive skills than using your physical skills. Aging helps in a stable environment and when you have lots of time. Peak age is much lower in an unstable environment with the necessity to make fast decisions.

Cognitive skills can be divided into two different groups. The ability to solve new problems and the ability to solve problems that are related to your experiences. The first group is called fluid intelligence. It peaks around 20 and is in constant decline about one percentage point a year until you die or your brain has big damage like Alzheimers-disease. Your ability to resist your intuition when it is wrong declines when you get older so does your ability to plan for the future. In other words, you cannot change your patterns of thought as well as you were younger. Therefore, the faster speed of change in the modern world becomes harder as you become older. You also have to be younger to create new things.

You can grow your ability to use things you learned before grows until you die, but in your early forties, the growth slows. Your peak when you are old is not much higher than you were in your twenties. It is only about 25 percent higher. Your vocabulary, ability to understand historical events, and geography, all grow until you die. If the current situation is just one of those previous events, you probably understand it better than later generations, especially if you have time to think about it. Your creativity in putting together old information and/or being an experimental creator peak later.

The overall cognitive performance declines after a certain age. The peak age is about 45 years. You cannot fool yourself in any way. You have to accept this. Some things that combine novel and old things like personal finance have later peak ages. The peak in the ability to make good decisions on personal finance is about 53 years of age.

You can read more about aging and skills from Mauboussin´s book. Until next time!

-TT

Luck; Skill, or both?

Do you need luck, skill, or both to become successful? You can find many answers to this question. Some people say others have luck and they have great skills. Some people say you need both. The answer to this question starts with words ”It depends on.” and continues with ”what you are doing. Michael Mauboussin has written a great book, ”The Success Equation” which gives more answers to this question than I can give to you in this text.

Let's start with the definition of luck. It can be defined as ”A single unrelated event that gives you an advantage or a disadvantage.” Some people may say that you can work hard to be lucky. They say you can develop yourself to become luckier. These phrases do not apply to the definition of luck. What happens is that when you have better skills in what you do, luck strengthens your success. Skill can be defined as: ”An ability to use your understanding to execute an action or a decision.” The more skilled you are the better ability you have to do this on average. The last two words are the most essential ones. Single actions or decisions that give you a great result do not mean you are skilled. Great executions that you can deliver on an average day by day are the best symptoms of great skills.

Luck-skill-continuum

Different types of actions or decisions can be put into luck-skill-continuum. On one side of the continuum are actions or decisions that need only luck and on the other side are actions or decisions that need only luck. You can find most actions and decisions from the middle of the continuum. They are based on luck and skill. In the middle are the actions that are based on both luck and skill and from this point to the left luck becomes more important and from this point to the right skill becomes more important. Lottery and most games like roulette at the casino are completely on the left side of the continuum and games like chess are on the right side of the continuum. Ask yourself: ”Can you lose on purpose?” if you want to know about the position on the continuum. If you can lose on purpose, you are on the right side of the continuum. If you cannot, you are on the left side of the continuum. In the middle, you can find an author that sells lots of books. Shitty authors cannot sell any books, but good ones can still not sell if they are not lucky.

Three things tell you more about the actions or decisions and whether to put them to the left or right side of the continuum. The first one is the sample size. When you are on the right side of the continuum, even the small sample size of the results can tell you much about skills. For example, the time for a hundred-meter run can tell you whether the runner is a good or a bad one. In the lottery, you can put hundreds of coupons and how much you win tells you nothing. In other endeavors like playing poker, small samples tell you nothing about the skills of the player, but when you play hundreds or thousands of hands, more skilled players win and worse players lose much more.

The second one is the form of feedback you get. When you need to be skilled, the feedback you get is based on clear cause-effect relationships not random or complicated like on the left side of the continuum. In this side, the feedback you get will lead you to problems. You may think that you are skilled even though you are just lucky. This does not happen on the right side of the continuum.

The third one is the return to the average or to mean if you want to use the statistical word. When the endeavor is based on skill, the return to the average happens slowly. When the endeavor is based on luck, the return to the average happens fast. In the middle of the continuum, the speed of the return to the average is somewhere in between.

There is an interesting paradox about the role of luck in the middle of the continuum. The better the relative skills of the performers are, the more luck you need to perform better than average. What I mean with this is that when the average performance is closer to the best one, the more luck you need to succeed and vice versa. The bigger the difference between the average performer and the best performer there is, the less luck the best performers need. When this is the case, you have to be sure you are better than your opposition.

I kept this text short. Sorry for not publishing anything for a long time. Hopefully, I will get something published in the next two weeks after this.

-TT