Obsidian Zettelkasten

54 - Internal Models are models that we build up inside our minds over time. They can represent your natural understanding of a subject matter such as the laws of physics or the steps in making the perfect cup of espresso. They are the ones that have become so well ingrained that you stop thinking about them and they become habits.

Internal Models can also take the form of explicit tools that you’ve memorized to help with thinking about problems. Typically internal models start out as explicit ones and naturally turn into implicit ones with repeated use. This is why intuition exists, and is commonly experienced by experts.

55 - External Models are models we build up outside of our mind because of the limiting factors involved in memory. These models can be referenced during special events (e.g. Ray Dalio Archetypes) or just at infrequent intervals. If you end up using the model often, then it will naturally become internalized (memorized).

The zettelkasten is well suited for building external models, as its gives you a permanent structure and reference point as the model gets built up over a long period of time. Reason for this is that you don’t come across all the relevant information in a single block of time, for example see timeline (#excise).

When a section of notes reaches critical mass, you use them to aid with a piece of writing (blog post, research paper, book, etc). In the same way, when an external model reaches critical mass, you have two options. The first option is to leave it be and just reference it when presented with a related problem. The second option is to memorize it so that it becomes an internal model that you can use in your everyday life.

Example of a External Model

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56 - Procedural Models are models about how to carry out tasks. They can be internal models (e.g. steps to start a car and pull out of the drive way) or external models (e.g. guide to healthy eating or preflight checklist for an airplane pilot).

Comes from Procedural Knowledge

57 - Mental Models are internal structures our minds form about reality that helps us predict and navigate a world full of complexity. There are three central explorations that I think about with mental models: understanding of the model, when to use the model, and what models are worth internalizing.

You have to prioritize what mental models you internalize because creating knowledge, which is a step beyond information structures, takes time and effort. You want to memorize the models which have the most applicability (e.g. general thinking concepts) or are of high value (e.g. highly desired skills).

See Similarity between Design Patterns and Mental Models

10e4b - Understanding Models
10e4c - When to use a Model
10e4d - What models are worth Internalizing


58 - Various Definitions of Mental Models

Wikipedia - “A mental model is an explanation of someone’s thought process about how something works in the real world. It is a representation of the surrounding world, the relationships between its various parts and a person’s intuitive perception about his or her own acts and their consequences.”


American Psychological Association - "A mental model is any internal representation of the relations between a set of elements, as, for example, between workers in an office or department, the elements of a mathematics or physics problem, the terms of a syllogism, or the configuration of objects in a space.

Such models may contain perceptual qualities and may be abstract in nature. They can be manipulated to provide dynamic simulations of possible scenarios and are thought to be key components in decision making. In the context of ergonomics, for example, a mental model of a system or product would include its various attributes, rules for operation and handling, and expectations regarding use and consequences and would be used to guide the individual’s interactions with the system or product in question. See also shared mental model."


The Model Thinker: What You Need to Know to Make Data Work for You by Scott Page - "Models are formal structures represented in mathematics and diagrams that help us to understand the world. Mastery of models improves your ability to reason, explain, design, communicate, act, predict, and explore.

This book promotes a many-model thinking approach: the application of ensembles of models to make sense of complex phenomena. The core idea is that many-model thinking produces wisdom through a diverse ensemble of logical frames. The various models accentuate different causal forces. Their insights and implications overlap and interweave. By engaging many models as frames, we develop nuanced, deep understandings."


The Art of Game Design: A Book of Lenses by Jesse Schell - “Reality is amazingly complex. The only way our minds are able to get by at all is by simplifying reality so that we can make some sense of it. Correspondingly, our minds do not deal with reality itself, but instead with models of reality”,

“Our brains do a tremendous amount of work to boil down the complexity of reality into simpler mental models that can be easily stored, considered, and manipulated. And this is not just the case for visual objects. It is also the case for human relationships, risk and reward evaluation, and decision making. Our minds look at a complex situation and try to boil it down to a simple set of rules and relationships that we can manipulate internally.”


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg - “Though we discuss a wide array of topics, we often find common threads—recurring concepts that help us explain, predict, or approach these seemingly disparate subjects. Examples range from more familiar concepts, such as opportunity cost and inertia, to more obscure ones, such as Goodhart’s law and regulatory capture. (We will explain these important ideas and many more in the pages that follow.)”

These recurring concepts are called mental models. Once you are familiar with them, you can use them to quickly create a mental picture of a situation, which becomes a model that you can later apply in similar situations.


The Great Mental Models: General Thinking Concepts by Shane Parish - "This is the first of a series of volumes aimed at defining and exploring the Great Mental Models—those that have the broadest utility across our lives. Mental models describe the way the world works. They shape how we think, how we understand, and how we form beliefs. Largely subconscious, mental models operate below the surface. We’re not generally aware of them and yet they’re the reason when we look at a problem we consider some factors relevant and others irrelevant. They are how we infer causality, match patterns, and draw analogies. They are how we think and reason.

A mental model is simply a representation of how something works. We cannot keep all of the details of the world in our brains, so we use models to simplify the complex into understandable and organizable chunks. Whether we realize it or not, we then use these models every day to think, decide, and understand our world. While there are millions of mental models, some true and some false, these volumes will focus on the ones with the greatest utility—the all-star team of mental models."


Make It Stick: The Science of Successful Learning by Peter C. Brown - “A mental model is a mental representation of some external reality. With enough effortful practice, a complex set of interrelated ideas or a sequence of motor skills fuse into a meaningful whole, forming a mental model somewhat akin to a “brain app”.”

59 - Public Note Repositories - are collections of peoples personal notes made public. I’m still thinking about the utility of them. On one hand they are a good for showing others a tangible example of how to create a notes collections. My favorite so far is Andy’s Working Notes in terms of layout and quality of content.

It is not a particularly desirable way of communicating information to others because they aren’t structured for easy understanding. Instead what you’d want is either a blog (e.g. Wait But Why, Derek Sivers, and Farnam Street), site of curated articles (e.g. thoughtco or owlcation), or small wikis (e.g. SuperMemo Guru, AskHistorians Wiki). While these options are better than a standalone notes collection they are still lacking. Specifically they don’t do the best job of addressing the issue of match quality in learning.

The direction I am currently leaning is to make a Wiki with an explorable back end that is a zettelkasten. The homepage of the website would be a [table of contents] similar to my old github one which leads to wiki entries of similar size to supermemo guru. Inside each of the entries are links to the zettelkasten notes that were used to build them. You could also access the zettelkasten through an index, which would be a link in the sites navigation bar.

See Curated list of Public Zettelkastens / Second Brains / Digital Gardens


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Similarity between Design Patterns and Mental Models

I think the concept of Design Patterns

In software engineering, a design pattern is a general repeatable solution to a commonly occurring problem in software design.
source

a pattern can contain the description of certain objects and object classes to be used, along with their attributes and dependencies, and the general approach to how to solve the problem
Source

from Software Engineering seems to be an instantiation of Mental Models in software world, particularly bearing resemblance to the following definitions, in that they all prescribe ways to look at relationships between entities which allow for solutions, explanations, predictions.

Differences between Design Patterns and Mental Models

As someone who have been a tutor and a student, I observe a phenomenon where Design Patterns are very difficult to teach to people who haven’t had professional software development experience. My conjecture is that Design Patterns abstract away contexts that gave rise to them in the first place, which is probably a result of the need to formalize them in order to communicate meaningfully with fellow engineers.

In contrast, mental models have been intuitive for me, and some models I explained to my friends were well-received. This difference in comprehensibility may come from the fact that mental models model relationships in the real world, and design patterns model relationships in the software world.

An idea: Can we formalize Mental Models the way we formalized Design Patterns ?

Design patterns usually contain the following information source

  • Name that describes the pattern
  • Problem to be solved by the pattern
  • Context, or settings, in which the problem occurs
  • Forces that could influence the problem or its solution
  • Solution proposed to the problem
  • Context for the solution
  • Rationale behind the solution (examples and stories of past successes or failures often go here)

It seems that these information may be used to describe Mental Models.

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61 - Match Quality in Learning is the idea that you want new information being processed by someone to connect with their prior knowledge such that they are able to understand the new information being taught.

A very easy way to understand this concept is to think about reading. You don’t hand a student a history textbook before they are able to read. They need to have the prior knowledge of letters and words to understand the textbook.

If the match quality is bad then the student becomes confused and frustrated. On the other hand the match quality can be bad because it isn’t new information. For example, say your name is Bob Loblaw. If I repeat the words “your name is Bob Loblaw” over and over again then I am wasting your time because you already know this.

62 - Layers of Structure in a Physical Zettelkasten - When you build a zettelkasten you are adding layers of structure to facilitate note retireval.

  1. The first layer is creating a unified medium of storage such that it makes physical storage of the information manageable. Since paper is the most common form of writing, that is a good starting point. I could technically implement it using crayons and the walls of my house but that’d be subpar (still better than chaos).
  2. The second layer is having a central storage point. I don’t leave my slips of paper all over the house or town because that would make the retrieval of the note a pain in the ass. Instead I put them in the same container/cabinet.
  3. Third layer is having the notes on a restricted size of paper. Luhmann used pieces of paper in DIN-A-6 format. Others prefer using card stock. Fill out why small pieces of paper #todo
  4. Fourth layer is having unique identifiers, which in turn allows you to point towards another piece of relevant information in any given note. Basically allows you to create connections. / Sub Sequence UID Debate #todo
  5. Fifth Layer is using a branching system for the unique identifiers instead of a sequential system. Fill out why you’d want to do branching #todo / Sub Sequence folgzettel Debate #todo - Luhmann did not do [[Thematic Branching]] with his IDs, where you are essentially creating a thematic tree structure. Instead his branching was arbitrary.

Related:

@minhthanh3145 its already being done to a degree. Under mental models I put

“10e4b - Understanding Models
10e4c - When to use a Model
10e4d - What models are worth Internalizing”

Which is my way of a to do list.

Some of the books I listed under that note are attempts at doing so

Not sure if they are as extensive though. For example, some of them don’t really cover much the scenarios you’d want to use them in.

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Excellent set of notes about zettelkasten. Thank you.

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65 - Obsidian Enhancements are the different layers of structure that have already been added and suggested. The base layer for Obsidian is the markdown file. On top of that you have:

  • File Explorer
  • Star Menu
  • Search
  • Graph View
  • Quick Switcher
  • Backlinks
  • Tags Pane
  • Today’s Note
  • Zettelkasten Note
  • Preview Mode
  • Custom CSS

Then you have unofficial enhancements, with my favorite being andy mode.

When thinking about the different native features and plugins, it helps to define the problem you are trying to solve and look at it through the lens of the core note functions.

My current slate of suggestions are:

#todo sort out the quality of life improvements above vs. the functionality improvements.


66 - Layers of Structure are restrictions you place upon your workflow or tools that add order, which in turn creates repeatability. Repeatability is important for effective note taking because it allows for a greater amount of applicability per note. This is the same idea behind creating connections between notes and keeping notes atomic.

Once you get a sufficient amount of layers of structure together then they make up a workflow or system such as zettelkasten, PARA, or IMF.

Same applies to tools such as Obsidian, see 15 - Obsidian Enhancements. You start off by writing on wood and work your way up to complex mediums such as books with developed finding devices.


16b - Layers of Structure in a Wiki

67 - Knowledge Work is the creation, manipulation, and expression of knowledge. Usually it is done with the aim of a solving a problem using cognitive skills. The creation of knowledge can take the form of the remixing ideas (e.g. new music, lateral thinking with withered technology), cutting edge research, and new perspectives. Expression of knowledge can be a teacher explaining concepts to students, a presentation at work, or a doctor giving you a diagnosis.

Knowledge Work is important because it is becoming an ever valuable form of work, especially if you can excel at it. In Cal Newport’s book on skills he puts forth the idea that you can become very successful by learning how to improve in knowledge work because so many suck at doing so. The reason being because the path to improvement isn’t as clearly defined as it is with areas such as sports or more traditional work.

17c - Manipulation of Knowledge
17d - Expression of knowledge
17e - Improving Knowledge Work
17f - Cognitive Skills


Future of Work

Creation of Knowledge

High Yield Knowledge Work

Knowledge Work Feedback Loop

68 - Future of Work - as science advances and we find new ways to streamline or automate tasks, being able to work with knowledge becomes increasingly important. Because of this it is important to develop skills around knowledge work.

Where I think this might be wrong is if society fails to live up the challenges presented to us and the social order starts to deteriorate. In my paper zettelkasten I have notes comparing the decline of the Roman Empire to modern times. In this scenario, skills related to everyday living becomes more and more important. This is the everyday work that is less abstracted (farming, resource collection, supply chain management, politics, etc). Note - If I wasn’t optimistic and hopeful than I wouldn’t be writing this zettelkasten.


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WOW, this is a splendid work, congratulations! @lizardmenfromspace

I can foresee a book in the near future and we are so lucky to read it in this birthing stage.:+1:

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70 - Future Skills and Abilities - Professionals of the future need to adopt more flexibility in how they work.

This means meeting people where they are at, engaging with them over social media or other more preferable platforms (Susskind 2015, pg 106). Imagine being able to instant message your doctor.

Future professionals will need to be able to take advantage of the increase and availability of data to come to insights. This involves both the collection and analyzing of data. Either the professionals themselves will work directly with the data or use a middle man that understands both the data and industry (Susskind 2015, pg 107). They will also need to get better at working with new and emerging technology. Those who can effective work alongside machines will see an increase in efficiency and effectiveness (e.g. Advanced Chess).

The final need is for workers to widen their tool set, either through the effective use of technology or introducing a multi-disciplinary approach (Susskind 2015, 108-109). Imagine a “self-help coach” but who has extensive training, such that they work with doctors and psychologists. Taking a more holistic approach to fixing oneself.

71 - Future Roles In the book The Future of the Professions: How Technology Will Transform the Work of Human Experts, author Richard Susskind lays out 12 different roles that will emerge from a “post-professional society”:

  • Craftspeople - people who “craft” stuff that require a difficult skill set, such that they can’t be easily replaced by para-professionals or crowd sourced.
  • Assistants - people who aren’t experts but help out the above mentioned craftspeople (e.g. associates in law firms).
  • Para-professionals - will take over the spot of experts with the help of ever increasingly competent systems and tools.
  • Empathizers - people with extremely good people skills, which will always be important because we have a sociality that is ingrained in our evolutionary biology. Machines will fill the gap, but people who can afford the help of other people will prefer doing so.
  • R&D Workers - research and development will always be desired for the creation of new technology that can allow for a greater reach of solutions or make them more effective.
  • Knowledge Engineers - people who will be designing systems that draw on the sources of existing expertise to disseminate knowledge to the wider public and para-professionals. Early examples may be wikipedia or thoughtCo.
  • Process Analysts - will be the ones deconstructing the work of experts to create the systems and tools used by the above mentioned para-professionals.
  • Moderators - people with deep insight who will help guide the centralization of expertise knowledge either from the masses or a pool of experts. Essentially making sure the quality of “the body of knowledge” stays high.
  • Designers - People who think up and design the various systems described above. If a service or system isn’t well made then people aren’t going to want to use it. You see this with the high salary and importance of UX designers.
  • System Providers - people who are actually providing the systems that the knowledge base is built on, whether it be a foundation (e.g. Wikipedia) or a private company (e.g. Quora).
  • Data Scientists - pretty straight forward field. People who are able to work with big data and come to insights. Two of my data related products are pudding.cool and quid.
  • Systems Engineers - are the people creating our dumb machine helpers (AI, Big Data Systems, etc) or AI overlords

72 - Future Industries - Alec Ross, in his 2016 book Industries of the Future lays out five trends that will shape the future: Robotics, Advanced Life Sciences, Code-ification of Money, Cyber Security, and Big Data. - Source.

Note on the source - I actually own this book and took notes on it. But because I suck and didn’t have a zettelkasten at the time, I have no clue where those notes actually are. One of the helpful layers of structure of the zettelkasten is the centralization of notes.

A good question is how well his argument still holds up 4 years later? Something to think about.

Further planned Research:

  • The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives - 2020
  • The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future - 2017
  • Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will - 2016
  • Rise of the Robots: Technology and the Threat of a Jobless Future - 2016
  • The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant - 2016
  • Average Is Over: Powering America Beyond the Age of the Great Stagnation - 2013

73 - Knowledge is information that has been memorized and integrated into an existing model whether you are consciously aware of the model or not.

When thinking about knowledge it is important to understand how to work with it and what information is worth turning into knowledge.

18d - Procedural Knowledge is used to carry out tasks and is supported by both your specialized and general knowledge.

#todo