Mental models – A way to unlock genius

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Mental models or Mental model thinking can help you learn better, get creative, and gain immense insight into the world.

For a minute, think that your mind is a blank canvas.   

But that can’t be true. You are alive and are learning something, absorbing some information, this information.   

Let’s now put that blank canvas on top of your brain. Think of something crazy. That thing you just thought of, draw it on the canvas. The brain will now try to absorb that content and assimilate it into a bio-psychological framework built out of neural structures and a way to access it in meaningful ways.   

Think of a square, a circle, a building. These are objects that the brain has assimilated as concepts.   

Let us now expand the idea of this canvas drawing. Imagine for a moment that you can lay down amazingly complex concepts, big ideas, and processes from many topics onto this canvas. And then, you learn these ideas so that your brain understands them in ways that it understands squares and circles.

You can do this. All you need to do is build mental models!

Every time you learn a new concept, metaphorically speaking, the contents of the canvas percolate into the mind. And then, you can build new concepts with a new canvas on top of this. Each time, creating a more sophisticated engine underneath this canvas.

In today’s age, we need multiple skills and need to be acquainted with ideas and process from a lot of fields. Otherwise, we don’t have any competitive edge. We need to be subject matter experts with executive skill and knowledge about many other allied domains. Mental modeling is one promising way to go about developing this competitive edge.

What are mental models? 

Mental models are a way of representing processes. They are explanatory and descriptive. Mental models bind together the following:

  1. Aspects and variables in a process
  2. A mental picture & imagination of the process
  3. Context (real-world & imaginary) in which they are applicable. 
  4. An intuitive perception of the process

Mental models are usually described and explained via imagery and words. Because images and words are effective in understanding them.  Sometimes, very sophisticated mental models can involve other senses.   

The real process usually exists in the real world as scientific explanations, business processes, math, computer algorithms, etc.

A mental model is a representation of that in ways YOU understand. It lies in your head. It is grounded in words, mental visualization, movement of imaginary components, and abstract ideas.

The image of the world around us, which we carry in our head, is just a model. Nobody in his head imagines all the world, government or country. He has only selected concepts, and relationships between them, and uses those to represent the real system – Jay Forrester

  • Mental models are a symbolic representation of the real world
  • Mental models are mental data visualizations
  • Mental models are graphics in the mind
  • Mental models are a simulation of a real simulation/model
  • Mental models map real information to your understanding

What is the significance of a mental model? 

Go back to the example we began with- understanding what a circle is, what a square is. Your brain assimilates these concepts in ways you can apply anywhere you’d like. Architecture, auditorium seating, graphical design, musical arrangements, writing styles, etc. These are just small mini mental models that are deeply ingrained through our perception of the real world. Why? Because these features exist in objects in our environment.

Such small-scale mental models are related to cognition, perception, logic, reasoning because they form the basis of conceptual understanding.

Once a mental model consolidates, you might find ways to make predictions in your environment as long as your observations can be seen through a model.

Now, imagine increasingly complex concepts such as the distribution of data, probability, natural selection, planetary orbits, bird migration, etc. Certain processes underlie these complex concepts from the real world. We create models to explain them.

Note1: All models are likely to be wrong and incomplete. Some are useful. Thus, we use them.

Note2: Mental models are intended for use in the future. No point modeling something unless one can’t use them for something- be it productivity, lectures, creativity, holding smart conversations, writing Reddit posts (ELI5)[1].

Note3: Mental models are a way to know a little about everything. Once you model processes in your head, you will eventually develop an intuitive understanding of the big ideas across many fields. It is a meta-level skill that you acquire.

Note4: Mental model thinking ends up becoming automatic thinking once you acquire them. Immensely useful to apply them to any walk of life. You would only be limited by the extent of your creativity (which would most likely improve after acquiring mental models). Having a large database of mental models will not only help you gain insight into the variety of process in the world but you’ll have food for creativity. One of the core components of creativity is using ideas from one domain in another domain. This research shows that a lot of creative people in a specific art/skill draw influence from unrelated areas[2].

There is a debate between creativity being a general diffuse-tendency in people or a domain-specific expertise[3]. The debate points to an interaction of both[4]. Mental models contribute to both – a general diffuse tendency of mental learning and specific expertise. Thus, we can count on mental models to aid creativity at some level.  Research in this area is fuzzy owing to the complex nature of creativity itself.

What is the difference between a real model and a mental model? 

  1. Real models describe real phenomena and attempt making correct predictions. Mental models are representations of these.
  2. Real models predict real phenomena. Mental models are assimilated as mental templates to gain an intuition about something. 
  3. Real models are grounded in hard data. Mental models are abstract and are largely Content-Free Content
  4. There are restrictions on real models as they do what they are supposed to do. Work and be used for specific data. Mental models are interactive with one another and other aspects of your thinking & perception. Simply owing to the fact that they become a part of your learning and are tethered to your brain.  

Once you acquire a number of mental models, you’ll develop this large network of advanced ideas.

They would further enable extracting insights from even more advanced ideas. This is a positive feedback loop. (which can itself be a mental model too!).

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I’ll make an obvious assumption here- You have come far in life and learned about a variety of things. Your brain doesn’t go out of capacity. If you haven’t already, how about you acquire a large web of dozens of mental models across a number of knowledge areas!

Charlie Munger (Warren Buffet’s business partner) often talks about acquiring mental models across many of the sciences (economics, psychology, biology, math, physics). Charlie says “You have to learn all the big ideas in the key disciplines in a way that they’re in a mental latticework in your head and you automatically use them for the rest of your life”.

How to make a mental model? 

  1. Review the actual real-world process
  2. Imagine the process
  3. Think of the examples, work them out on paper
  4. Try to manipulate that model in your mind by using it in your personal way of understanding ideas
  5. Use specific words, actions/movement of mental images, and describe it to yourself in an animated fashion
Mental models: a learning technique

Tree diagram

Examples of real models which can be converted into mental models:

These are processes and ideas across a variety of disciplines that you can acquire as mental models.

Guidelines:

Understand the process visually, learn a few examples where they are used, let there be movement & interactions between components, and account for as many variables you can think of.

  1. Game theory[5] (Economics)
  2. Keynesian economics[6] (Economics) 
  3. Natural selection[7] (Genetics)
  4. Artificial selection[8] (Genetics)
  5. Laws of Thermodynamics[9] (Physics)
  6. Newton’s laws of motion[10] (Physics)
  7. General and Special relativity[11] (Physics) 
  8. Normal distribution[12] (Statistics)
  9. Pareto distribution[13] (Statistics) 
  10. Bayes laws[14] (Statistics)
  11. Spreading activation[15] (Cognitive science)
  12. Multi-modal & cross-modal perception[16] (Cognitive psychology)
  13. Hub and spokes model[17] (Cognitive science)
  14. Reflection & refraction[18] (Physics)
  15. Movement of atoms[19] (Chemistry) 
  16. Incentivizing[20] (Psychology)
  17. Interleaving & spacing (Psychology) 
  18. Feedback loops[21] (Everything??)
  19. Schedules of Reinforcement[22] (Behaviour)
  20. Classical and Operant Conditioning[23] (Behaviour) 
  21. Order of magnitude/indices[24] (Math)
  22. Multidimensional algebra[25] (Math) 
  23. Compound interest & simple interest[26] (Economics)
  24. Soundscapes & Equalizing[27] (Music)
  25. Wavelengths, amplitude, frequencies[28] (Acoustics) 
  26. Grammar structure & communication ideas[29] (Linguistics)
  27. Kinetic energy, potential energy[30] (Physics)
  28. Rotational motion[31] (Physics)
  29. Fundamental forces in nature[32] (Physics)
  30. Geodesics[33] (Geometry)
  31. Parallel processing & linear/serial processing[34] (Computer science)
  32. Binary & other base systems[35] (Math)
  33. Nested loops[36] (Computer science)
  34. Matrices[37]  (Math) 
  35. Cognitive biases[38] (Psychology)
  36. Grids & table model[39] (Experimental designs)
  37. ANOVA[40] (Statistics)
  38. Regression & Correlation[41] (Statistics)
  39. Deduction & induction[42] (Logic)
  40. City/Urban planning[43] (Social, Political, Architecture)
  41. Path dependency[44] (Design, Economics)
  42. Dual processing[45] (Cognitive science)

These are 42 processes to convert into mental models. These are my personal recommendations. I wanted to stop at 42 because… you know.  Here is an extra one – signal detection theory.

(I encourage you to snowball around these processes.)

You do not need to be an expert in the field to learn about these processes. As you learn new models, your baseline knowledge will grow.

Do you think of other useful processes? Do leave a comment, I’d appreciate that. Would be happy to extend the list!

Applications of mental models are endless. In summary,

  • You can use mental models to develop an intuitive understanding of natural and human processes
  • Learn a little bit about a lot of things. Know something about everything – challenge accepted?
  • Apply a model across different areas – lets you be innovative and creative
  • Accelerate learning
  • Extract meaningful information through the use of a mental model
  • Understand an overview of almost anything through the use of these mental models

Think about how useful it would be to place these mental models on your mind-brain-canvas and let the brain absorb the model.

You’d be supercharged with a meta-skill to be a genius. Perhaps intuitive mental model thinking will equip you with make really strong guesstimates!

P.S. This is an introductory article. Sometime later, I’ll cover more specifics about mental modeling and using it as a mental tool.

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Sources

[1]: https://www.reddit.com/r/explainlikeimfive/
[2]: https://arxiv.org/ftp/arxiv/papers/1508/1508.00073.pdf
[3]: https://www.frontiersin.org/articles/10.3389/fpsyg.2015.01870/full
[4]: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627136/
[5]: http://www.investopedia.com/terms/n/nash-equilibrium.asp
[6]: http://study.com/academy/lesson/supply-and-demand-curves-in-the-classical-model-and-keynesian-model.html
[7]: https://evolution.berkeley.edu/evolibrary/article/0_0_0/evo_25
[8]: https://evolution.berkeley.edu/evolibrary/article/evo_30
[9]: http://physicsforidiots.com/physics/thermodynamics/
[10]: http://teachertech.rice.edu/Participants/louviere/Newton/
[11]: http://www.dummies.com/education/science/physics/einsteins-special-relativity/
[12]: http://www.statisticshowto.com/probability-and-statistics/normal-distributions/
[13]: http://www.statisticshowto.com/pareto-distribution/
[14]: https://www.youtube.com/watch?v=pPTLK5hFGnQ
[15]: https://www.khanacademy.org/science/health-and-medicine/executive-systems-of-the-brain/cognition-2014-03-27T18:40:04.738Z/v/semantic-networks-and-spreading-activation
[16]: https://www.researchgate.net/publication/316092732_The_Kiki-Bouba_paradigm_Where_senses_meet_and_greet
[17]: https://en.wikipedia.org/wiki/Spoke%E2%80%93hub_distribution_paradigm
[18]: http://www.differencebetween.info/difference-between-reflection-and-refraction
[19]: http://www.bbc.co.uk/schools/gcsebitesize/science/aqa/heatingandcooling/heatingrev2.shtml
[20]: https://www.quora.com/What-are-some-mind-blowing-facts-about-social-psychology/answer/Aditya-Shukla-98
[21]: https://www.albert.io/blog/positive-negative-feedback-loops-biology/
[22]: https://www.khanacademy.org/test-prep/mcat/behavior/learning-slug/v/operant-conditioning-schedules-of-reinforcement
[23]: https://www.khanacademy.org/test-prep/mcat/behavior/learning-slug/a/classical-and-operant-conditioning-article
[24]: http://study.com/academy/lesson/order-of-magnitude-definition-examples.html
[25]: http://www.iaeng.org/publication/WCE2010/WCE2010_pp1824-1828.pdf
[26]: https://betterexplained.com/articles/a-visual-guide-to-simple-compound-and-continuous-interest-rates/
[27]: https://www.addictivetips.com/windows-tips/equalizer-frequencies-settings-on-music-players-explained/
[28]: https://www.khanacademy.org/science/physics/mechanical-waves-and-sound/sound-topic/v/sound-properties-amplitude-period-frequency-wavelength
[29]: http://www.english-grammar-revolution.com/sentence-structure.html
[30]: http://www.physicsclassroom.com/mmedia/energy/ce.cfm
[31]: https://www.youtube.com/watch?v=grMWAI1RdVs
[32]: http://www.clearias.com/four-fundamental-forces-of-nature/
[33]: http://www.solitaryroad.com/c335.html
[34]: http://www.bryanburnham.net/wp-content/uploads/2014/01/Logan-2002.pdf
[35]: https://www.mathsisfun.com/numbers/bases.html
[36]: https://www.quora.com/How-would-you-explain-a-nested-FOR-loop
[37]: https://en.wikipedia.org/wiki/Matrix_(mathematics)
[38]: https://en.wikipedia.org/wiki/List_of_cognitive_biases
[39]: https://exceljet.net/blog/5-pivot-tables-you-probably-havent-seen-before
[40]: http://blog.minitab.com/blog/statistics-in-the-field/understanding-anova-by-looking-at-your-household-budget
[41]: http://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_multivariable/bs704_multivariable5.html
[42]: https://www.socialresearchmethods.net/kb/dedind.php
[43]: https://en.wikipedia.org/wiki/Theories_of_urban_planning
[44]: https://www.utdallas.edu/~liebowit/paths.html
[45]: https://en.wikipedia.org/wiki/Dual_process_theory
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