The Great Mental Models Volume 2: Physics, Chemistry and Biology (Personal Notes)

Summary by GPT-4

The article discusses key concepts and mental models from various scientific disciplines and their real-life applications, such as goal-setting, personal development, and decision-making. Some of the key takeaways include:

1. Inertia: The importance of direction in setting goals and building habits, comparing it to mental capital.
2. Thermodynamics: Humans use analogies to understand complex concepts, such as the brain’s functioning.
3. Reciprocity: Introducing the concept of Exponentially-Weighted Moving Average Generous Tit for Tat (EWMA GTFT) as an adaptive and forgiving strategy in repeated games.
4. Leverage: Adapting language and behavior based on others’ priorities in social situations.
5. Friction and Viscosity: Importance of reducing resistance in goal achievement, illustrated with an example from road cycling.
6. Chemistry: Psychotherapy as a catalytic process, and skill stacking as a powerful combination of skills or insights.
7. Biology: Different systems produce different results in similar environments, demonstrated with the McDonald’s vs. Burger King example. The article also mentions the concept of symmetry breaking and how it relates to different systems producing different results even in the same environment.

Physics

Inertia

The chapter talked about the concept of inertia while creating an analogy in terms of setting goals in life (i.e. direction is just as, if not more, important than your speed).

“If one does not know to which port one is sailing, no wind is favorable.” — Seneca the Younger

This analogy also reminded me of another concept in psychology, namely mental capital.

There’s positive and negative mental capital. Positive mental capital refers to habits we want while negative implies its reverse.

Analogy: Just like an object with a lot of inertia is difficult to stop or change direction, so it is with increasing/reducing positive/negative mental capital (i.e. breaking down bad habits or building up new ones).

It’s also said that pharmacotherapy (e.g. antidepressants) take a couple weeks to take action even though the neurotransmitters themselves and their ratios change immediately when the chemicals enter the brain. This might be because this process could make it easier (hopefully) to break certain synaptic patterns one doesn’t want (e.g. those generating negative thoughts/feelings/habits etc) i.e. negative mental capital, same process but opposite direction with positive mental capital.

Thermodynamics

This chapter mentioned fairy tales and how humans use that to understand things better.

This reminded me of something another book (The Extended Mind: The Power of Thinking Outside the Brain) mentioned, namely how we tend to use analogs to understand the brain as we don’t know well how to brain functions i.e. the brain used to be compared to an abacus, than a calculator, than a computer (a field called connectionism).

Reciprocity

This chapter sparked a (new?) concept inside of me: Exponentially-Weighted Moving Average Generous Tit for Tat (EWMA GTFT).

Exponentially Weighted Moving Average Generous Tit for Tat (EWMA GTFT) would be a strategy that combines the principles of the Exponentially Weighted Moving Average (EWMA) and Generous Tit for Tat (GTFT) in the context of repeated games, such as the Iterated Prisoner’s Dilemma.

In this strategy, a player would maintain an EWMA of the opponent’s past actions, where recent actions have more weight than older actions. This means the player is more influenced by the opponent’s recent behavior rather than their actions from the distant past.

The GTFT aspect of the strategy involves reciprocating the opponent’s actions with some generosity. When the opponent cooperates, the player would cooperate in return. However, when the opponent defects, the player would sometimes still cooperate, depending on a generosity parameter.

In the EWMA GTFT strategy, the player’s decision to cooperate or defect would be based on the EWMA of the opponent’s actions and the generosity parameter. If the opponent’s EWMA score is above a certain threshold, the player would cooperate, showing generosity even if the opponent recently defected. If the opponent’s EWMA score is below the threshold, the player would defect, following the tit-for-tat aspect of the strategy.

Overall, EWMA GTFT would be a more adaptive and forgiving strategy compared to classic Tit for Tat, as it considers the opponent’s recent behavior more heavily and allows for occasional cooperation even after defection. This could lead to better long-term cooperation and higher payoffs in repeated games.

Leverage

Here, the author talked about positive and negative leverage in social situations.

I personally like to make use of this by getting to know what the priorities are of the other and adjusting myself accordingly.

E.g. if someone prioritizes feelings of safety and security, I will ensure to adapt my language (e.g. choice of words) accordingly.

Friction and Viscosity

This chapter talked about why it’s important not just to increase the resources you use when working toward a goal, but it’s also important, if not more, to reduce resistance.

This reminded me of my own sport: road cycling, particularly aerodynamics.

At speeds over 9 mph, it’s the dominant force of resistance. By the time you hit about 30 mph, 90 percent of your power goes into overcoming air resistance.

―Aerodynamic Cycling | Ultimate Guide to All Things Aero in Cycling (bicycling.com)

Chemistry

Catalysts

This reminded me of psychotherapy, namely how you are essentially trying to catalyze the personal development of someone else as optimally as possible e.g. Socratic method.

I am thinking of making an article on how I see psychotherapy as a catalytic process and how to do this.

Alloying

A chapter telling how combination of skills or insights can be more powerful than standalone. It reminded me of this article by Tomas Pueyo:

How to Become the Best in the World at Something

Biology

Ecosystem

Understand that different systems produce different results, even in similar environments

A real-world example of the aforementioned can be McDonald’s vs. Burger King:

• E.g. McDonald’s is aimed more on limited-time offerings and Burger King on permanent items
• The former is more focused on being family-friendly and the latter targets younger people more
• Both started from fast food, which could be an example of symmetry breaking:

A ball is initially located at the top of the central hill ©. This position is an unstable equilibrium: a very small perturbation will cause it to fall to one of the two stable wells left (L) or right (R). Even if the hill is symmetric and there is no reason for the ball to fall on either side, the observed final state is not symmetric. By Tigraan — Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=48446175

Tendency to Minimize Energy Output

This chapter mentioned desire path, which reminded me of ant colony optimization algorithms:

By Nojhan — Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=821076