Systematizing Creativity - Models and Techniques

Revel in the moment of creation.

Categories of Technique

  1. Mind Wandering, Daydreaming, and Relaxation - Intentionally enter default mode
  2. Abstract and Generalize / Analogize - Transfer over similar problems & solutions
  3. Composition / Recombination
  4. Idea Lists
  5. Decomposition
  6. Randomness
  7. Idea Mapping, Graphs of Relationships between Ideas
  8. Leading questions
  9. Reframe / Question Assumptions
  10. Multiple levels of analysis
  11. Think ground up, from first principles
  12. Automation
  13. Thought Habits / Mental.
  14. Invert
  15. Activities
  16. Social Solutions



Moment of Creation

Techniques

  1. Mind Wandering, Daydreaming, and Relaxation - Intentionally enter default mode
    • Load up an idea / problem / question and:
      • Go for a walk
      • Take a shower
      • Sleep
        • Start to fall asleep, wake up as you do (use alarm or keys in the hand)
        • Hypnagogia
      • Meditation
        • Sit in silence with the target as an object


  2. Abstract and Generalize / Analogize - Transfer over similar problems & solutions
    • Model vs. Technique - see what works in the space, ask why to get a model. Generalize from the model to generate more techniques.
    • Metaphor Generation
      • Idea list over metaphors for a given problem / solution / object
      • Transfer solutions and insights from the related domains
    • Find a source idea, categorize it, generalize to finding more instances of that category.
      • Ex. Properties of Representation, Systematizing Creativity
    • List solutions to a problem and generalize
    • List related problems and generalize from their solutions
    • Operating over your operators


  3. Composition / Recombination
    • Idea List for concept set
    • Run recombination over generated concepts
      1. Hold the concepts in mind, asking how they relate to one another


  4. Idea Lists
    • List Creation + Time Pressure
      • Choose a topic / prompt / question.
      • 10m Time Constraint.
      • Fill list to 10 ideas.
      • If time becomes a limiting factor, let novelty / quality fall.
    • Alternative versions:
      • Go into diffuse mode over an idea list, with no time limit
      • Create a huge list (with a low barrier to idea entry) and prune it
        • This resolves the psychological conflict between creative ideation and rigor / quality


  5. Decomposition
    • Break into component pieces, in multiple directions
      • Ex. Machine learning becomes Linear Algebra + Calculus + Probability Theory + Computer Science, which break into their own subregions
      • Ex. Scientific Field becomes Major Papers + Categories of the topic + Conferences + Major Researchers + Quality Sites
    • Mutually Exclusive, Collectively Exhaustive
    • Deconstruction + Optimization
    • Actually do science ‘to split’


  6. Randomness
    • Randomize. Generate random ideas by specifying some parameters, and make them work / use them as prompts.
    • Randomly show words that serve as prompts
    • Stream of Consciousness


  7. Idea Mapping, Graphs of Relationships between Ideas
    • Create a graph of the relationships between critical ideas in a space


  8. Leading questions
    • Recursive ‘Why?’
    • Questions over Answers
    • Imagine the future (problem is solved, for ex.). What happened? Work backwards.
    • What are the sacred beliefs? What can’t be thought?
    • “what if” questions
    • “how might we” questions
    • Invert - “what if the opposite is true”
    • Eliminate - “does it even matter”
    • “What if I need to solve it once and for all”
    • Scalability - “What if I need to solve it for everyone”
    • What is the meta level idea?
    • What questions do I have about this?
    • What would other people think of?


  9. Reframe / Question Assumptions
    • Constraints
      • Create resource constraints (time, attention, money, assumptions, etc.)
      • Create resource excess (time, attention, money, etc.)
      • Eliminating options
      • What are the upstream constraints in the system?
      • Define boundaries of solution spaces better
        • Find upstream constraints
    • Apply different modes of processing
      • What would a supervillain do? (Prompt framing) / Supervillain mode
      • Emotional - Get into emotional state and generate ideas
        • Anger
        • Arousal
        • Gratefulness
        • Adoration
        • Frustration
        • Excitement
      • Types of Thinker - What would I generate if I was a:
        • Mathematician
        • Technologist
        • Computer Scientist
        • Philosopher
        • Psychologist
        • Economist
      • find inspiration in other areas:
        • math
        • mythology
        • writings about principles
        • Physics
        • Etc
      • Environmental
        • Work in a cluttered environment
      • Game Lenses, list of generic lenses
      • Asking what would Hufflepuff / Gryffindor / me would do
      • Asking what a friend would do
      • Predicting what someone will say and
        • Then asking them, for interesting feedback
    • What? / Why? / How?


  10. Multiple levels of analysis
    • Multiple levels of abstraction - ask what alternate levels of analysis exist, through decomposition and abstraction over the current level of analysis
      • Multiple frames - think at lower and higher levels of analysis, simultaneously. Ask how they interact.
    • Meta-object two space
      • Simultaneously optimizing the object and the meta level


  11. Think ground up, from first principles
    • Ask what the underlying goal is for a space, and for what solutions would serve that goal. For each solution, think of the components necessary to make that solution happen.
      • What are the basic principles of x?


  12. Automation [See Expanded Version]



  13. Thought Habits / Mental
    • Idea List Habitually
    • Brainstorm Habitually
    • Create and refine a distinct open mode
    • Create imminent desire for coming up with relevant ideas
    • System 1 + Generalization
      • Take an intuitive response and understand its mechanism. Turn the mechanism into a generator.


  14. Invert
    • Take any technique, and do the opposite over some parameter
    • Imagine ways of not doing it, or preventing the goal from being reached: adversarial


  15. Activities
    • List Creation + Time Pressure
    • Writing
      • Write freely over the topic / question / prompt
    • Brainstorm [thought dumping]
    • Defend a difficult position, adversarial conversation
    • Drawing
    • Giving a speech to the air
    • Improv Games


  16. Social Solutions
    • Crowdsourcing ideas
    • Read Books / Articles on Topic
    • Debate the topic
    • Look up what other people have been saying about it
      • discuss things with others
      • check social media
      • find differing discussions online
      • Mapping ideas generation for other people!
    • Work with other dissimilar people

Great thanks to Hikari Sorensen, Alton Sun, Parnian Barekatain, Romeo Stevens, Gavan Wilhite, June Bossman, Michael Andregg, Mark Estefanos, and everyone else that inspired and contributed to this beautiful body of ideas.

Recombination

Recombination is a fabulous generator of ideas. Take existing concepts and ask how are they related, how can they be combined. Walk away with new conceptions.

For example, combining evolution and identity leads to considering sub-personalities in a selection context for mindshare, each attempting to shape the world for the benefit of itself. Combining evolution and ideas gives you memetics. The hierarchical structure of most ideas allows for meaningful recombinations, and often the rediscovery of critical concepts.

Run over quality targets or reframes or prompts, self-generated or otherwise, and ask how they can be recombined with each other. You can do this between lists or intra-list, and over what you generated versus the prompts.

  1. What does a supervillian with only 5 hours a week do to finish the thing do?
  2. How would Nietzsche answer the Thiel questions?

Body of Practice. Recombine ideas over each other until something feels like it clicks. Each person is going to have different levels of closeness, similarity, and relatedness between these ideas.

Or, play recombination hotseat!
Sit one person up front of a few other creative minds. Have them throw out two seemingly unrelated terms. The player in the seat has to generate a novel, interesting, or valuable composition of the two words thrown out, in real time.

Questioning Assumptions & Reframes

Our mind implicitly assumes a solution space. This solution space may not be optimal. We can reframe the solution space by explicitly playing with assumptions. Assumptions like:

Reframe / Question Assumptions
- Constraints
- Create resource constraints (time, attention, money, assumptions, etc.)
- Create resource excess (time, attention, money, etc.)
- Eliminating options
- Independent plans
- What are the upstream constraints in the system?
- Define boundaries of solution spaces better
- Find upstream constraints
- Apply different modes of processing
- What would a supervillain do? (Prompt framing) / Supervillain mode
- Emotional - Get into emotional state and generate ideas
- Anger
- Arousal
- Gratefulness
- Adoration
- Frustration
- Excitement
- Types of Thinker - What would I generate if I was a:
- Mathematician
- Technologist
- Computer Scientist
- Philosopher
- Psychologist
- Economist
- find inspiration in other areas:
- math
- mythology
- writings about principles
- Physics
- Etc
- Environmental
- Work in a cluttered environment
- Game Lenses, list of generic lenses
- Asking what would Hufflepuff / Gryffindor / me would do
- Asking what a friend would do
- Predicting what someone will say and
- Then asking them, for interesting feedback
- What? / Why? / How?

Judgement / Triage / Prioritization

  1. Put a hard constraint on the time you’ll take to make a decision.
    • If you need more information before you decide, realize that decisiveness itself is extremely valuable.
    • Decisiveness as more important than making a better decision.
  2. Collect the candidate plans in one place.
  3. Rank the plans / ideas by likelihood of success / efficacy in accomplishing the goal.
    • Consider how many times you’ve executed successfully on a plan like that in the past.
    • Premortem - Imagine that your plan fails. How will it fail?
  4. Rank the plans / ideas by cost of execution.
    • Consider how long they’ll take you to reach your goal.
  5. Rank the plans / ideas by simplicity. *. Be able to see the causal factors that lead to the success of your plan. *. Ease of tracking the success of the plan. *. This is fundamentally about clarity, and how confident you can be about your judgement of your plan.
  6. Rank the plans by externalities. What positive benifits will they have that aren’t directly related to the goal, like learning, new friends and connections, or reputation? What negative externalities are there?

Idea Lists

Idea Listing:
-Choose a topic to generate 10 ideas over. -10m Time Constraint. Start timer.
-Fill to 10 ideas. Let quality fall if time becomes a limiting factor.
-Optimize for both expected value of the idea and for its novelty -Novelty - Novelty is great but not necessary. Feel free to dial this down as time goes on.



Mechanics: The time constraint accomplishes a number of important things.

  1. Creates the freedom to let all other thoughts, worries and mental activity be released temporarily. The time being explicitly set aside for one task is permission to let go of open loops, freeing those slots in working memory for the task.
  2. Activates an action-oriented mode, a creation rather than consumption mode.
  3. Is a step of momentum towards taking productive action
  4. Creates freedom from other people - they either see it, or you feel comfortable letting them know that you’re busy (but only temporarily, making it feel acceptable).




Examples:
Demonstrate list of idea lists
For Research: Types of Temporal Structure
For Conversation: Interesting Facts in Machine Learning (Linear Regression)
For an Idea: Memetics
For Emotion: Ways to Induce Anger
For ML: Machine Intelligence Contrarian
For Creativity: 17-04-08 Systematizing Creativity
For Learning: Ideas for Learning ML/AI (2015)


  • Credit to James Altucher for this technique!

Limiting Beliefs - Necessity

Creativity and its natural supporters — curiosity, openness, the inquisitive spirit, the itch to know — are often considered opponents of necessity. Necessity, need, the vulgar material world, money are the death of the creative spirit.

Not so. Necessity cuts through reality, sharpens curiosity. We confuse the pressures of necessity, and particularly those impositions made on us by others, with the killing the creative output. Rather, take time and space to think about the problems you deem worthy, that really affect you, that you must solve and you will find your creativity sharpened by the world.

Generalizing the Hamming Question

Over on the other side of the dining hall was a chemistry table. I had worked with one of the fellows, Dave McCall; furthermore he was courting our secretary at the time. I went over and said, “Do you mind if I join you?” They can’t say no, so I started eating with them for a while. And I started asking, “What are the important problems of your field?” And after a week or so, “What important problems are you working on?” And after some more time I came in one day and said, “If what you are doing is not important, and if you don’t think it is going to lead to something important, why are you at Bell Labs working on it?” I wasn’t welcomed after that; I had to find somebody else to eat with! That was in the spring.

In the fall, Dave McCall stopped me in the hall and said, “Hamming, that remark of yours got underneath my skin. I thought about it all summer, i.e. what were the important problems in my field. I haven’t changed my research,” he says, “but I think it was well worthwhile.” And I said, “Thank you Dave,” and went on. I noticed a couple of months later he was made the head of the department. I noticed the other day he was a Member of the National Academy of Engineering. I noticed he has succeeded. I have never heard the names of any of the other fellows at that table mentioned in science and scientific circles. They were unable to ask themselves, “What are the important problems in my field?

Richard Hamming, You and Your Research

The Hamming Challenge

What are the most important problems in your life?

What are the limiting factors on you being order of magnitude greater than you are?

And what are you going to do about them?

Decomposition

One powerful generative motion is to take a whole and divide it into its sub-parts. Once cut up, the sub-parts can be [recombined], solved individually, maximized over, or even recursively decomposed.

Decomposition is necessary for turning abstract plans into action. For example, take an action like ‘go to Antartica’. That action isn’t executable - it needs to be decomposed into sub-parts (book a flight, go from where you are to an airport, navagate the airport, fly to southern Argentina, travel to the boat, call a tour operator, acquire a permit, etc.).

The sub-parts are decomposed in turn until a concrete action that can be executed falls out of the plan, bottoming out in unconscious behavior (the tapping of keyboard keys, the dialing of a cell phone).

Many arguments hinge on a concept which, when decomposed, dissolves the entire argument. For example, arguments about Free Will where both parties agree on the low level, grounded scientific reality can still rage on, as the conflation of multiple definitions / implications of free will introduce conflation that decomposition can aleve.

Algorithmically, decomposition is ubiquitous. [Divide and conquer algorithms], such as mergesort, Strassen’s matrix multiplication algorithm and dynamic programming algorithms all leverage this structure.

Naturally, we should decompose decomposition itself. One way is by asking about the properties of our decomposition: is it mutually exclusive? (No overlap between categories?) is it collectively exhaustive? (do we capture all of the decomposed object in our sup-parts?) Do we end at the conceptual level or the concrete, object level? Those properties can serve as guides for the strengths and weaknesses of a particular decomposition.

Decomposition can be thought of as inverting abstraction. Where abstraction is compressive, decomposition is generative. Where abstraction goes from the concrete towards the conceptual, decomposition goes from the conceptual towards the concrete.

One valuable form of decomposition is over a concept.

These concepts can be broken down into their parts. These parts can be further subdivided. We can then solve, think, or recombine these parts. This also lets us take advantage of levels of analysis/abstraction.

For example, most disagreements can be solved by decomposition. Two people talk about love, but one means brotherly love and one means romance. Obviously these are not the same. Higher-level concepts shroud reality. If we decomposed into the set of meanings that are aggregated under the concept of love, often there is no argument. Novel words or variants of words are often an output.

The rationalist community has a specific case of decomposition. If a tree falls in a forest does it make a sound. Decompose sound: do you mean vibrations in the air or the perception of sound by some creature feeling those vibrations? The answer is obvious at this level.

Words that derive their power from being an amalgam of concepts, with multiple meanings — nation, truth, family, identity — are good targets for decomposition: we can actually decide to talk about a particular thing.

Take a concept, quality target, self-generated idea, or prompt rich with ambiguity and decompose it. Ask: what are the sub-pieces of X? If stuck, consult leading questions. Example: How would a Y person thing about X?

Leading Questions for Conceptual Decomposition:

  1. What are all of the ways in which the concept is used?
  2. How is the way we use the concept misleading?
    • What other valuable conceptual schemes are we pushed off of?
  3. What is insufficient about the concept?
  4. What gives the concept its value?
  5. What are many examples of the concept, and how to they differ from one another? What is truly invariant across them?
  6. Is the concept part of a larger conceptual scheme? What concepts does it block, or support?
  7. What is the simplest possible version of the concept? The most complex version?
  8. What are all of the definitions that exist?
  9. What is the concept often conflated with?
  10. What major assumptions does applying or using the concept make? When do these assumptions differ from reality?
  11. What are the differences between the concept in its breath and the particulars of its instantiation?


Abstraction & Generalization

The ability to create and think with concepts is of the most powerful advantages of human cognition.

Good thinkers exploit the concepts embedded in language to generalize discovered patterns across similar problems, solutions and situations.

Great thinkers learn to abstract, and in so doing create entirely new concepts that represent similarities and patterns that are novel, uncaptured by existing conceptual schemes.

What is the most general version of your solution? Of your problem? Of your idea?

By what mechanism causes your favorite technique work? What is the why behind it? And with that causal mechanism in mind, what other techniques can leverage it? And immediately you go from having one technique to having a stable of techniques, unified by their mechanism.

Can you map your problem to a more general representation (ex., from the internet to a graph, or from your leadership structure to a hierarchy) which will let you leverage bodies of existing solutions?

Assume your example, your datapoint, is just one element of an entire class of examples. What is that class? What else is in it? What axes create a space of possible examples?

All of Systematizing Creativity is Abstraction. Where mental motions fall into a category. Where idea listing is one datapoint, one example of the class of techniques that automate creative thinking.

Generating Thiel Answers

The Thiel Question — what is a truth very few people agree with you on — is a fantastic descriptor of contrarian truth, and a terrible generator. Here are some generators for the next time Thiel appears out of nowhere to stump you:

  1. What about the world is broken that no one knows is broken?

  2. What do most people get wrong about everything?

  3. What massive societal change is coming that no one knows is coming?

  4. What massive technological change is coming that no one knows is coming?

  5. What has been fundamentally misunderstood?

  6. What truths are too terrifying for us to admit?

  7. What do you do that you wish everyone did?

  8. What supposedly implausible scenarios are actually possible, or fairly likely?

  9. What dystopian future must actually be guarded against?

  10. What halcyon future may be possible to build?

Lifechange Leading Questions

What we call learning is a pale imitation of generation. Knowing a thing is different from being able to do the thing — though the best way to know a thing is often to do it.

Creativity is best applied to relevant problems in your life. One way to bring these to mind, and which can later operate as raw material to run systematizing creativity on, is to ask leading questions. Use all, some, or none:

  1. What do you want to change in life?

  2. What do you wish was different in your life?

  3. What do you always wish you could do?

  4. What do you think you could never do, but would want to?

  5. What would your friends tell you to do?

  6. What scares you?

  7. What frustrates you?

  8. What confuses you?

  9. What interests you?

  10. What questions are you grappling with right now?

  11. What do most people get wrong?

  12. What do most people get wrong about everything?

  13. What does your personal hell look like?

  14. What does your personal heaven look like?

  15. If you had a week to change you life before it became set in stone, what would you do? What would you focus on?

  16. If you had 10 years to get your life in order, what would you do?

  17. If you have 10 assistants, what would you have them do for you?

  18. If you could change 1 thing about your life, what would it be?

  19. If you could only improve your life an hour a day, what would you do?

  20. What do you wish everyone did?

  21. What is the truth you are too scared to admit?

  22. What is the truth you wish you had courage to admit?

  23. If you could understand 1 thing, what would it be

  24. What are the 10 academic fields you want to understand

  25. What are the tools or technologies you use to improve your life, why do you do so? What are you trying to solve?

  26. What do the qualities of your friends say about your ambitions and desires?

  27. What did you get most mad at yourself this week about? This quarter? The last 10 years?

  28. What were you most proud of this week? This quarter? The last 10 years?

  29. If systematizing creativity went better than your wildest expectations, what happened? What did you focus on?

  30. Create a prompt list of words, concepts, domains, people and ask is there anything you want to adopt, think about, become, take, steal, or use? For example:

    1. Psychology

    2. Economics

    3. Business

    4. Risk

    5. Machine Learning

    6. Mental Models

    7. Writing

    8. Greatness

    9. Nietzsche

    10. Empathy

    11. Social Justice

    12. Intellectual Dark Web

    13. Curiosity

    14. Conscientiousness

    15. Hard Work

    16. Taleb

    17. Gucci

    18. Drake

Jobs & Organizations

Getting a job is part of the general class of problems of getting into an organization. We relate those options here.

  1. Interview track. Find the standard process of interviewing, find the best guides for that process, and execute

  2. Social. Meet with members of the organization, or friends of the organization, until someone clicks and you get invited to join or have a better interview position

  3. Competitors. Get into a competitive organization, use to leverage your position into your desired organization

  4. New team / create a position. Find a new team that is being built within the organization, or that should be. Pitch the relevant person that you should be in or lead this

  5. Acquihire. Build a product the organization needs, then sell yourself

  6. Build your own organization. Hire yourself

Seeming Clever

Sampling over a high-variance distribution lets you hide mistakes, losses, bad outcomes, unluckiness, wild failures and capture the gains of successes, well-thought plans, luck, and wild victories. If failures are hidden and successes visible, this gives the appearance of brilliance. The greater the variance and the more sampling, the greater the brilliance. You take the best of what has been figured out and leave the rest, as in:

  1. Writing pages and pages of ideas over years, sampling the best

  2. Speaking at parties, then compiling and selecting the best

  3. Becoming a venture capitalist, with a portfolio of one Google and 100 Jucieros

  4. As a researcher, running 100 experiments and publishing the one that works

  5. Random selection of books in a library, or video on Youtube, and watching the best after a 30 second test

The safer you are from ruin — from being taken out of the game — the more it pays to be wild.

The implication is to not be fooled by ostensible cleverness, check the base rate. How many experiments, or investments, or investors, would we expect to see succeed by chance alone.

Generating Generators

There’s an algorithm for generating systematizing creativity that I like to describe as to carefully watch a brilliant mind generate creative ideas, and then to 1. through seeing patterns and similarities among the generated ideas, categorize them and 2. create categories for the thought processes or mental motions that generated the ideas.

Those are two generators of generators. What else exists? (Note, these are general enough to be meta-generators)

  1. Categorize ideas using some pattern or notion of similarity. Use the examples to install the pattern, and look for the pattern elsewhere.
  2. Decompose a given pattern, seeing its variants, properties and types. Explicitly try to turn the pattern itself into a generator, as well as all of its decomposed variants.
  3. Recombine your generators with one another
    • Ex., what is the most general version of recombination?
    • If I look at differing types of recombination, how do they differ? In the process, in the inputs, in the outputs?
  4. Read creative authors, subject them to a deep analysis of their conceptual style.
  5. Listen abstractively to people speaking. Name / categorize the mental motions that lead to creative ideas.
  6. Gather powerful solutions to important problems. Ask how / why they work. Turn their source of strength into a property of solutions / ideas that its worth incorporating or founding new solutions on. (Ex., data structures as re-representation / abstraction)
  7. Watch your own thought, especially when you’ve solved something or generated something new. Ask after the prompts that lead to that path of thought.
  8. List the most powerful ideas.
    • Ask, how could I have come up with this, or seen this pattern for the first time?
    • Ask, how can I see this pattern more often when it comes up, and how does that process of pattern recognition work?
    • Often, by seeing many examples of a pattern, you mind starts to pick it up much more easily. So to see patterns that others haven’t seen, look at data that others haven’t looked at.
  9. Learn to see the incompleteness of things (frameworks, conceptual schemes, say checking for collective exhaustiveness, or searching for datapoints that don’t fit) and complete them (or rework the ontology entirely)
    • Apply this to systematizing creativity, taking creative ideas that can’t be explained as a call to enlargen the technical toolset, or make existing techniques more flexible
  10. Create your own concepts, elucidate them in some detail, name them, and then see what patterns exist in your concept creation.
    • This is general to all creative work. Start creating, and watch yourself closely.

The Original Systematizing Creativity

The first version of systematizing creativity came out of applying abstraction and generalization to ideas lists, using idea lists.

The original:

  1. Intentionally enter diffuse mode over ideas
  2. Idea Lists
  3. Transfer / Abstract over similar solutions
  4. Multinomial Trees (Ed Boyden)
  5. Graphs of relationship between ideas (Ex., Optimizer / Model / Loss Function)
    • Optimizing supervised learning with reinforcement learning (architecture search)
    • Optimizing reinforcement learning with supervised learning (Policy Network / Value Network)
  6. Combining, connecting ideas / Idea Sex
  7. Leading questions
    • Resource constraints (time, attention, money, assumptions, etc.)
    • Resource excess (time, attention, money, etc.)
    • Eliminating options
    • Imagine the future (problem is solved, for ex.). What happened? Work backwards.
  8. Brainstorm [thought dumping]
  9. Generalization - if you’ve solved a problem, extend the solution to its farthest reaches
  10. Listing approaches to a body of problems (say ML toolbox, or models in how to think)
  11. Randomize. Generate random ideas by specifying some parameters, and make them work / use them as prompts.
  12. List and reject assumptions
  13. Multiple levels of abstraction
  14. Apply different modes of processing
  15. Current Knowledge frames ideas. Break out of frame with:
    • Looking at problem from perspective of another person, another category of thinker
  16. Defend a difficult position, adversarial conversation
  17. Think ground up, from first principles
  18. Deconstruction + Optimization
  19. Metaphor Generation

4 influenced by Ed Boyden. 2, 6 influenced by James Altucher.

Creating a Creativity Framework

One fascinating experience is to carefully watch a brilliant mind generate creative ideas, and then to 1. through seeing patterns and similarities among the generated ideas, categorize them and 2. create categories for the thought processes or mental motions that generated the ideas.

Quality examples of mental motions include:

  • Assumption Questioning
    • Ontology / Paradigm Questioning (There’s an interconnected memeplex of assumptions)
    • Breakdown of Categories (seeing their brokenness, oneness, or decomposition
  • ‘Control’ - How do I get control over the structure / situation at hand?
  • Abstract & Generalization, Transfer - What is the most general form of this - idea? What other cases can this apply to?
  • Decompose - Ex., Break the concept down into its sub-concepts, break a situation into sub-cases, or add nuance through introducing a conditional.
  • Relatedness / Transfer / Cognitive Fit with something else
  • Prediction / Anticipation of outcome
  • Understand - Explain a part of the system that I don’t know about, resulting from a failed prediction or a sparse decomposition that I want filled
  • Identify the generator of the thought or intuition - why did this person think that thought?
  • Distinction (or introduce conditional)
  • Actions Taken as a Result

We can describe a thinking style as having a prediliction towards particular mental motions. That distribution over patterns of thought categories creates a space of thinking styles that can be navigated, explored, and expanded.

Pathways to Systematizing Creativity

Pathways to Systematizing Creativity

  1. Turn people into creators systematically
    a. Restructure mental habits around idea generation
    b. Free people to think about anything
  2. Create an ideation team of creatives in research
    a. Fill with researchers in touch with reality
  3. Packaging
    a. Undergraduate Class
    b. Create a Consultant group
    c. Create a website
    d. Create a book
  4. Apply sys creativity to generate books, websites, etc.
  5. Create valuable offline workshops where people accelerate their creative work
  6. Generalize to automating creativity in machine intelligence
  7. Find more general principles behind generative modeling, and behind creative concept creation. Literally optimize the process.
  8. Restructure my own mental habits & mental moves towards idea generation
  9. Play! Have fun with creative idea generation.
    a. Make a movement around this
    b. Do this late at night with friends for fun
    c. Creativity parties
  10. Core metric - the rate of closing loops vs. rate of opening loops
  11. Create a group for collaborative problem solving
  12. Find more ways to automate / ritualize this
  13. Identifying asymmetries with these - which are more good than bad and vice versa, which should be shared.
  14. Finding people who are interested in contributing
  15. Hacking projects for practical things
  16. Religion / Cult / Philosophizing
  17. Problem Solving out of Ideation
  18. Put it in the public domain, with blog post
  19. Map Techniques to Tasks
  20. Website
  21. Discoverability
  22. Online Class, something like Udacity
    a. Making this digestible for an online course
    b. Pre-selling them on this module
  23. Offline Workshop
  24. Conference
    a. Submission to a conference
    b. Create a conference
  25. Distinction between Generation vs. Content Value
    a. Going through the process of coming up with the idea makes it stick
    b. Mental models meaningful to you vs other people
  26. Build a Database of all of the ideas
  27. Shape the audience so that the impact is good
  28. Put this into bite sized bits that makes people feel like they discovered it themselves
  29. Clearer Thinking
  30. Start a school! Like Xavier, mutants.
  31. Start a summer camp
  32. Creativity Cult
    a. Strict requirements - cut if you fail on discussed metrics
    b. 4-5 ppl
    c. Devoted ideation on a daily basis
    d. Cover a span of approaches to a problem very quickly
    e. Turn ourselves into geniuses

Revive Mathematics

A mathematician, like a painter or poet, is a maker of patterns. If his patterns are more permanent than theirs, it is because they are made with ideas.

The cultural problem is a self-perpetuating monster: students learn about math from their teachers, and teachers learn about it from their teachers, so this lack of understanding and appreciation for mathematics in our culture replicates itself indefinitely. Worse, the perpetuation of this “pseudo-mathematics,” this emphasis on the accurate yet mindless manipulation of symbols, creates its own culture and its own set of values. Those who have become adept at it derive a great deal of self-esteem from their success. The last thing they want to hear is that math is really about raw creativity and aesthetic sensitivity. Many a graduate student has come to grief when they discover, after a decade of being told they were “good at math,” that in fact they have no real mathematical talent and are just very good at following directions.

Math is not about following directions, it’s about making new directions.

Paul Lockhart, A Mathematician’s Lament