My mental model of a website that replaces the content with some 'sign up now' stuff while I'm trying to read it is that it deserves to get closed and never looked-at again.
All these mental models are simplified maps of an infinitely complex reality. When we rely on them too heavily, do we risk falling into the trap of mistaking the map for the actual territory? The very tools we use to understand the world can end up shaping and even limiting our perspective. That's why being aware of the limitations of the models themselves is just as important as using them.
Your map/territory risk is exactly what this lineage formalizes -- internal maps are necessary but they shape and limit perception. Walter Lippmann (1922) makes "pictures in our heads" the operative reality of public judgment:
voidhorse: "mental model" vs "theory" is a real distinction in the literature. Kenneth Craik frames small-scale models as internal simulations for reasoning, not public theories:
andsoitis: "informal, simplified, personal" models are exactly why systematic errors show up. Daniel Kahneman and Amos Tversky document heuristics and biases when internal maps are over-trusted:
If you want to see Drescher operationalized, MOOLLM turns the schema mechanism into working skills. Schema Mechanism is the causal core, Schema Factory adds a deterministic toolchain and context bundles for LLM reasoning, and Play-Learn-Lift is the governance loop that maps ACT/OBSERVE/ATTRIBUTE/SPIN OFF into audited upgrades. This is GOFAI made practical with LLMs filling the old gaps in grounding and explanation.
It's sad to me that people are apparently so allergic to the term "theory" that we had to come up with this lesser version of it. I guess the key difference is that "mental model" might emphasize dynamics more strongly, which is a flaw in my opinion (logical relationship is what matters, whether those relations are static or dynamic).
LOL. I was looking for an about link to learn who the author is, but there’s isn’t one. The more I scrolled the more I kept seeing these book covers all with the name. So I guess that stands for “about” link. Cheeky.
But what I really wanted to say, this reminds me of Scott E Page’s Coursera course on Model Thinking, and a book: “The Model Thinker
What You Need to Know to Make Data Work for You” also from 2018.
9 comments
[ 2.7 ms ] story [ 28.5 ms ] threadAlways a good read
You can use the Wayback Machine to read the version that was originally discussed.
Will always be grateful to Shane for that!
https://en.wikipedia.org/wiki/Public_Opinion
Frederic Bartlett (1932) defines schemas as memory structures that pre-shape perception and recall:
https://en.wikipedia.org/wiki/Schema_(psychology)
Jean Piaget explains schema updating via assimilation/accommodation when evidence conflicts with the map:
https://en.wikipedia.org/wiki/Assimilation_(psychology)
Edward Tolman introduces cognitive maps, making "map" literal in psychology:
https://en.wikipedia.org/wiki/Cognitive_map
Marvin Minsky formalizes frames as slot-filled expectations that speed inference but can blind you to anomalies:
https://en.wikipedia.org/wiki/Frame_(artificial_intelligence...
voidhorse: "mental model" vs "theory" is a real distinction in the literature. Kenneth Craik frames small-scale models as internal simulations for reasoning, not public theories:
https://en.wikipedia.org/wiki/Kenneth_Craik
Philip Johnson-Laird formalizes mental models as internal simulations used for inference and prediction:
https://en.wikipedia.org/wiki/Philip_Johnson-Laird
andsoitis: "informal, simplified, personal" models are exactly why systematic errors show up. Daniel Kahneman and Amos Tversky document heuristics and biases when internal maps are over-trusted:
https://en.wikipedia.org/wiki/Heuristics_in_judgment_and_dec...
Repair loop: Seymour Papert's microworlds provide controlled sandboxes for testing and revising models:
https://en.wikipedia.org/wiki/Constructionism_(learning_theo...
Gary Drescher gives a schema mechanism for incremental action/outcome updates that rebuild the map from experience:
https://mitpress.mit.edu/9780262517089/made-up-minds/
If you want to see Drescher operationalized, MOOLLM turns the schema mechanism into working skills. Schema Mechanism is the causal core, Schema Factory adds a deterministic toolchain and context bundles for LLM reasoning, and Play-Learn-Lift is the governance loop that maps ACT/OBSERVE/ATTRIBUTE/SPIN OFF into audited upgrades. This is GOFAI made practical with LLMs filling the old gaps in grounding and explanation.
Drescher's Schema Mechanism as Anthropic Skill:
https://github.com/SimHacker/moollm/blob/main/skills/schema-...
Drescher's Schema Factory as Anthropic Skill:
But what I really wanted to say, this reminds me of Scott E Page’s Coursera course on Model Thinking, and a book: “The Model Thinker What You Need to Know to Make Data Work for You” also from 2018.