Occam's Razor - Mental Model Series -8

“Nature is pleased with simplicity, and affects not the pomp of superfluous causes”  - Newton

Photo by Stephen H on Unsplash


We often forget what wise men say about simplicity -other things being equal, simpler theories are better. In other words ,when presented with competing hypothetical answers to a problem, one should select the one that makes the fewest assumptions.

 However, Occam's razor only applies when the simple explanation and complex explanation both work equally well. If a more complex explanation does a better job than a simpler one, then you should use the complex explanation.

For our convenience sake, let us tray to define what is Occam's Razor

When presented  with competing  hypothetical answers to a problem, one should select  that makes fewest assumptions.

Here is a real life example of how we applied this principle . My wife had to decide between two offers of employment towards end of her contract at that time. From the beginning ,She was very clear on her priorities . Both offers provided same work- life balance and same customer location and  in terms of monetary benefits , both offers are almost equal. But one offer came from current vendor  and another from another vendor both are for the same client. We have gone for the current vendor as we had to make less assumptions. Since work life balance is her first priority and she is familiar with working conditions and expectations at the work place.

If you take medicine for example , when many explanations are possible for symptoms, the simplest diagnosis is to be tested first . Let' say a child comes with a runny nose , it probably has the common cold than a rare birth defect . I hope you get it now .

A philosophical tool as simple as often very easy to be misused . So please remember the following -

1. This law of simplicity is only applicable when all explanations in question are equally well.
2. Simple and simplistic are not exactly the same. 

Footnote -
What are Mental Models ?
“It’s your mind’s toolbox for making decisions. The more tools you have, the more equipped you are to make good decisions. “
A mental model is an explanation of how something works. It is a concept, framework, or worldview that you carry around in your mind to help you interpret the world and understand the relationship between things. Mental models are deeply held beliefs about how the world works. 

For More , read https://jamesclear.com/feynman-mental-models  

Inversion

Inversion - Mental Model Series -7

"It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent. There must be some wisdom in the folk saying, `It’s the strong swimmers who drown." - Charlie Munger.

What is inversion, exactly?

 Inversion is a highly effective decision-making strategy that can be used in many spheres of life. Many hard problems in life can be  best solved when they addressed in reverse.As an illustrative example, one great way to be happy is to avoid things that make you miserable.

I am going back to another Charlie Munger quote again reinforce the above
“What do you want to avoid? Such an easy answer: sloth and unreliability. If you’re unreliable, it doesn’t matter what your virtues are. You’re going to crater immediately. Doing what you have faithfully engaged to do should be an automatic part of your conduct. You want to avoid sloth and unreliability.”
 By avoiding being sloth and unreliable , you are already reliable and star.your journey to succes start right there.

Why Inversion?

It is not enough to think about difficult problems one way. You need to think about them forwards and backward. Inversion often forces you to uncover hidden beliefs about the problem you are trying to solve.

How to adopt?

We can summarize inverted method to problem solving as below:

step 1.Figure out what you want to achieve.
step 2.What do you don't want to happen? This is the worst-case scenario.
step 3.How could the worst-case scenario happen?
step 4.How can you avoid the worst-case scenario?

let us put the above framework to practice

step 1.Figure out what you want to achieve.
Me : I want to drive safely .
step 2.What do you don't want to happen? This is the worst-case scenario.
Me : i want to avoid accidents
step 3.How could the worst-case scenario happen?
Me : 1. Break or equipment failure,
2.Tire burst
3. Fall asleep while driving ( me or the other vehicle drivers)
4.  Situations at junctions  and
5. Over speeding
step 4.How can you avoid the worst-case scenario?
Me 1. Proper maintenance of Break and car
2. Frequent Tire checks
3. Don't drive at odd hours
4. Proper signaling and using indicators at junctions
5. Do not drive more than permitted speed

So now, this is as easy as it gets. We can make this framework for many of our decisions.

Final word 

Combined with forward thinking, backwards or inversion thinking could help you to unlock solutions to difficult problems that may have been holding you back for years.

Footnote -
What are Mental Models ?
“It’s your mind’s toolbox for making decisions. The more tools you have, the more equipped you are to make good decisions. “
A mental model is an explanation of how something works. It is a concept, framework, or worldview that you carry around in your mind to help you interpret the world and understand the relationship between things. Mental models are deeply held beliefs about how the world works. 

For More , read https://jamesclear.com/feynman-mental-models  

Probabilistic Thinking

Probabilistic Thinking  - Mental Models Series -6

“If we do everything right, if we do it with absolute certainty, there’s still a 30 percent chance we’re going to get it wrong.” — Joe Biden, Former Vice President,US

Do you want to improve the accuracy of your thinking? Probabilistic thinking is for you.

Remember the classic question- " Are you with us /against us?".  Most of you want to distance yourself from binary conclusions and tribes, individualize your opinion, and leave open the possibility that your sliding scale of probability can change with more information,correct? . Then Probabilistic thinking is for you.

Let us follow the following example to understand better -

Teacher : So let’s try an example. Suppose there’s a five percent chance  per month your bike breaks down. In that case…
Student: Whoa. Hold on here. That’s not the chance my bike will break down.
Teacher: No? Well, what do you think the chance is?
Student: Who knows? It might happen, or it might not.
Julia: Right, but can you turn that into a number?
Student: No. I have no idea whether my bike will break down. I’d be making the number up.
Julia: Well, in a sense, yes. But you’d be communicating some information. A 1% chance your bike will break down is very different from a 99% chance.
Student: I don’t know the future. Why do you want to me to pretend I do?

The explanation that the teacher tried to give the  student was that imperfect information still beats zero information. Even if the number “five percent” was made up (suppose that this is a new kind of bike being used in a new way that cannot be easily compared to longevity data for previous bikes) it encodes our knowledge that bike are unlikely to break in any given month. Even if we are wrong by a very large amount (let’s say we’re off by a factor of four and the real number is 20%), if the insight we encoded into the number is sane we’re still doing better than giving no information at all.

So,what is probabilistic thinking?

A willingness to always ask questions like
“What else might happen?”,
“What if we’re wrong?”,
“What could happen next?”,
 and to look at the full range of situations that might come to pass — and at their costs and benefits — rather than to assume that things will go as planned or as the fashionable ideology or favorite administration model would have predicted.


Why is it so important that we learn to reason probabilistically and statistically? 

 There are two main reasons.

 First, we obviously base our plans for and investments in the future around our predictions of what the future will be like. But the future cannot be known with absolute certainty, so we need to make rational decisions around a probable distribution of outcomes.

Thesecond, more fundamental reason for why we need to get better at probabilistic prediction is that offering and then testing predictions is the basis of scientific progress.

To succeed in life we need to predict the future, and in many ways we’re already good at it. For example, as you’re reading this, try to predict the word at the end of this sentence. Did you do it? Our basic intuition is often pretty good at seeing what’s going to happen, and you don’t need any math to use that. But science has shown that there are areas where our intuitions are flawed, and we can do much better by using statistics and other mental tools.


There are three important aspects of probability that we need to explain so you can integrate them into your thinking to get into the ballpark and improve your chances of catching the ball:

1. Bayesian thinking

First of all,We should also refrain from claiming to have absolute certainty when it comes prediction. Even the smallest amount of skepticism is necessary; it’s okay to say that something is incredibly, incredibly, probable — but not that it is 100% certain.

Bayes’s Rule is a theorem in probability theory that answers the question, "When you encounter new information, how much should it change your confidence in a belief?" It’s essentially about making decisions under uncertainty, and how we should update or revise our theories as new evidence emerges.


Imagine that one morning, during a rainy season, you’re wondering whether to take an umbrella with you before you leave your house. You look outside your window to see that the weather is currently sunny. So, your first thought is that rain is unlikely.

However, upon a second glance, you notice some scary-looking dark clouds on the horizon and you decide to take your umbrella after all.

You didn’t have to stop there, of course. You could improve your guess even more by checking the weather forecast on your favorite weather website. What’s important is that your decision is based on your estimate of the probability that it will rain. So, you used information about the current weather conditions (and possibly from other sources) to update your estimate of this probability.

Let’s continue with the weather example. You can ask the question: “What is the probability that it will rain, given that the weather is windy and there are dark clouds in the sky?” Here you aren’t simply interested in the general probability that it will rain. You want to know the probability of rain after taking into account a particular piece of new information (the current weather conditions). In probability theory, such probabilities are called conditional and the notation used for them is:

P(Event-1 | Event-2).

Conditional probabilities expresses the probability that Event-1 will occur when you assume (or know) that Event-2 has already occurred. With this notation, you can write “the probability that it will rain, given that the weather is currently windy and cloudy, is equal to 0.85″ as:

P("Rain" |"windy&Cloudy") = 0.85

In summary ,Bayes’ theorem is the excellent mathematical device you can use for updating probabilities in light of new knowledge. No other method is better at this job.

for more understanding , visit here https://www.probabilisticworld.com/what-is-bayes-theorem/

2. Fat-tailed curves

 No one can explain better than Nassim Taleb when it comes to fat tails.
Let’s start with the notion of fat tails. A fat tail is a situation in which a small number of observations create the largest effect. When you have a lot of data, and the event is explained by the smallest number of observations. In finance, almost everything is fat tails. A small number of companies represent most of the sales; in pharmaceuticals, a small number of drugs represent almost all the sales. The law of large numbers: the outlier determines outcomes. In wealth, if you sample the top 1% of wealthy people you get half the wealth. In violence – a few conflicts (e.g. World Wars I and II) represent most of the deaths in combat: that is a super fat tail.- N Taleb

3. Asymmetries 

 Finally, you need to think about something we might call “meta probability” —the probability that your probability estimates themselves are any good.


Case  1.Pull a penny out of your pocket. If you flip it, what’s the probability it will come up heads? 0.5. Are you sure? Pretty darn sure.

Case  2 .What’s the probability that my local high school football team will win its next game? I haven’t a ghost of a clue. I don’t know anything even about school football, and certainly nothing about “my” team. In a match between two teams, I’d have to say the probability is 0.5.

Case 3 My wife asked me today: “Do you think Angpo will have corn floor?” Angpo is our local supermarket. “I don’t know,” I said. “I guess it’s about 50/50.” But unlike school football, I know something about supermarkets. A Fairprice supermarket  is very likely to have dolmades; a 7-11 almost certainly won’t; Angpo is somewhere in between.

How can we model these three cases? One way is by assigning probabilities to each possible probability between 0 and 1. In the case of a coin flip, 0.5 is much more probable than any other probability. in the case of football team,I have no clue what the odds are. They might be anything between 0 to 1.In Angpo's case, I have some knowledge, and extremely high and extremely low probabilities seem unlikely.

Each of these curves averages to a probability of 0.5, but they express different degrees of confidence in that probability.

I hope you got the concept

Final word

Probabilistic thinking can only get you in the ballpark. It doesn’t guarantee 100% success. However ,we can act with a higher level of certainty in complex, unpredictable situations

Footnote -
What are Mental Models ?
“It’s your mind’s toolbox for making decisions. The more tools you have, the more equipped you are to make good decisions. “
A mental model is an explanation of how something works. It is a concept, framework, or worldview that you carry around in your mind to help you interpret the world and understand the relationship between things. Mental models are deeply held beliefs about how the world works. 


For More , read https://jamesclear.com/feynman-mental-models  

Thought experiments

Thought Experiments - Mental Model Series -4

"I was sitting on a chair in my patent office in Bern. Suddenly a thought struck me: If a man falls freely, he would not feel his weight. I was taken aback. This simple thought experiment made a deep impression on me. This led me to the theory of gravity." - Albert Einstein 

Thought experiments are conceptual rather than actual experiments. The constitute a powerful tool for understanding the world. Unlike hypotheses in natural sciences , ethical theories cannot be tested emphirically. Purpose of a thought experiment is to help us to face questions which are difficult to answer and encourage speculation, logical thinking and  paradigm shifts .While it may seem counter-intuitive, many of science’s greatest developments in the last century have come from thought experiments rather than physical ones. 

To understand this concept , let us look at the following example.
Galileo’s thought experiment demonstrating (rather counter-intuitively) that two objects of different weight must fall at the same speed

 (Contrary to popular belief, Galileo never actually climbed the leaning tower of Pisa to do this experiment – he didn’t need to.) Galileo knew Aristotle would have predicted that a heavy body (H) would fall faster than a lighter one (L). But, the Italian scientist reckoned, suppose we connect the two bodies by a string, thereby making the compound object H+L. Following Aristotelian physics, one would predict that H+L should fall faster than H by itself because of the compound weight: therefore H+L > H. However, it’s also possible to use the same logic to claim that the compound body should fall at a slower pace than H because of the drag created by L, so that H+L < H. But this yields a contradiction, which means – by reductio ad absurdum – that really H = L = H+L. Neil Armstrong, the first human to set foot on the moon, dramatically showed the whole world that Galileo was right when he let go of a hammer and a feather in the absence of atmospheric friction while standing on our satellite, and, sure enough, they hit the Moon’s surface at the same time. Such is the predictive power of thought experiments!

If you do some research on the internet , you will be surprised to learn how thought experiments contributed to new scientific discoveries. Among scientists, Galileo and Einstein were, arguably, the most impressive thought experimenters. One of the main reasons that scientists go for  thought experiments to make their points is that the theories they work with often deal with unobservable phenomena that are either far too large (think black holes), far too small (think fundamental particles), or far to abstract (think space time or the alternate dimensions required by string theory) for people.

you can find some of the interesting thought experiments here. 

https://www.newscientist.com/article/2087688-the-impossible-barber-and-other-bizarre-thought-experiments/

https://stanford.library.sydney.edu.au/archives/fall2009/entries/thought-experiment/

First principles thinking

First principles thinking- Mental Model Series -3

" Deconstruct then reconstruct." - James Clear 

Photo by Steve Johnson from Pexels

We have a complex problem and we have put on our thinking hat and set out on a mission. we always look for an easy solution  first. We look for an already known example which is close enough of the problem on hand and use an analogy.Sometimes work but many times won't. But there is a better way - "First principle thinking".  It is based on the approach to break down a complex problem into basic elements and reassemble them from the ground up. Let us dig deep further.

What is first principle?
A first principle is a basic foundational assumption that cannot be deduced further and that forms the basis of the thinking in its own particular field. All the other works in that field are based on this basic assumption being true and built up from there. 
Each field usually has some assumptions that form the basic building blocks of the knowledge .These assumptions  are considered very rigid in physical sciences and good approximations in social sciences.

In physics, They are called laws. These are for example the laws of thermodynamics, or Newton’s laws of motion. 

In biology, It is evolution. This is the first principle which shapes how all living things live and behave and why they are the way they are.

In economics, for a long time, the basis of all theory and calculations in the field was the assumptions of the rational actor. All the different economic models built on top of this assumption.

With physical sciences, the first principles are what we assume to be true and are usually pretty solid. On the other hand, in social sciences, the first principles are usually just approximations of the world and so not as solid as the first principles of physical science

For our easy understanding,  Some of the examples of first principle are ,2+ 2 = 4, Male has  two  chromosomes(XY), or definitions like " widow is a women whose husband died", The laws of thermodynamics in physics. 

Application of First principles thinking -

Elon Musk of Tesla used this first principle thinking to solve some of his  very complex problems. He said he borrowed this technique from Physics. In physics , typically you start with a set of basic assumptions  that you hold to be true and  cannot be broken down further and reason up from there . He uses this approach to deduce his problems.

 To understand better , let us take his battery example which goes like this,

"And for batteries, they would say, oh, it’s going to cost – you know, historically it’s cost $600 per kWh and so, it’s not going to be much better than that in the future, and you say no, what are the batteries made of? So first principles mean you say okay, what are the material constituents of the batteries? What is the spot market value of the material constituents? So you can say, it’s got: cobalt, nickel, aluminum, carbon and some polymers for separation and a steel can. So break that down on a materials basis and say okay, if we bought that on the London metal exchange, what would each of those things cost? Like, oh, jeez, it’s like $80 per kWh. So clearly, you just have to think of clever ways to take those materials and combine them into the shape of a battery cell. And you can have batteries that are much cheaper than anyone realizes.”

So Musk challenges the popular assumption that  batteries are expensive and not much can be done about it.  He went down to the basic constituents of battery and the raw materials that made them up to turn that impression upside down.

As we can see, First principles thinking is one of the best way to reverse-engineer complicated problems . Why this is one of the best ways?  our survival instincts favor speed and efficiency over novelty and innovation .Naturally we prefer to take the beaten track and iterate what was already done to gain speed. But no original solutions will emerge from this kind of thinking. So first principle thinking helps to throw away the ideas we inherit ,look at the components and then substituting a more effective solution for one of the key component.

However easy this seems to appear , practicing first order thinking is hard but not impossible . Our tendency to imitate will always stand in the way.We need to consciously overcome this barrier and also some of our cognitive biases. 

Please read the following articles to learn more -

https://gainweightjournal.com/a-short-lesson-on-first-principles-thinking/
https://jamesclear.com/first-principles

Footnote -
What are Mental Models ?
“It’s your mind’s toolbox for making decisions. The more tools you have, the more equipped you are to make good decisions. “
A mental model is an explanation of how something works. It is a concept, framework, or worldview that you carry around in your mind to help you interpret the world and understand the relationship between things. Mental models are deeply held beliefs about how the world works. 


For More , read https://jamesclear.com/feynman-mental-models