Comment by Barrin92 | Hacker News Reader

Comment by Barrin92 | Hacker News Reader

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This article is right in my opinion. This 'mental model' thinking and the surrounding ecosystem of 'rationalists' where it's super popular to me seems like Oprah for slightly smarter tech bros.

The problem with it really is as the author suggests the lack of authentic experience on the one hand, but I think more importantly it's that the idea of "mental models" just tries to hand people a bag of disjointed tools.

When you look at what it means to really understand something and you look at say a world class pianist or something, then you'll almost certainly find they have an integrated perspective on what they do. They don't have model A and model B and model C and a bag of fortune cookie wisdoms, they have tacit knowledge and beliefs that are coherent and whole. Really understanding something ironically often leads to the inability to articulate how it is one understands it, because it's just become integrated into how someone operates in general.

Umberto Eco once made the great point that unread books are much more important than read books because known knowledge pales in the face of everything that is unknown, no matter how dedicated one is to reading. And it's the same thing with these mental models. You're not smarter because you know 200 models or 300 models or 400 models, just like reading 50 more books per year isn't going to make anyone any smarter in a sort of simple additive way.

This whole article, and your agreement, rests on a false dichotomy. "Fallacy" implies learning about mental models is useless. No one said mental models replace experience any more than good notetaking can replace thought; but both are useful in thinking and learning.

fully agree with this position. Mental models are just that, models. they are abstractions of a particular classification of a thing, they convey information. they carry no guarantee of understanding and (in the odd cases given in the article) no guarantee that understanding winner take all markets means you would instantly be an expert at gaming them. You would hopefully understand the essentials of them and therefore recognise them when you saw them. It seems to be me that some are conflating these abstractions as in some way claiming to convey expertise.

Concur. Knowing the literature isn't the same as having done the research, but it is likely to hasten getting through the learning curve.

i just dont agree with this at all. Mental models make no claims about expertise they are abstractions of accepted knowledge and capture the essence of something. They are, after all, called models. Maybe some have mis-appropriated mental models as being as short cut to expertise they simply arent and cannot be. They are simply models, abstractions of what is known. I dont think anyone is saying you will be smarter but you may be enlightened. Models are good at this. Imagine an abstraction of a computer. when all you know is that a computer is a box then your awareness of what that means is restricted to a cable coming our of a box with a switch in it. Take that a level deeper. look at the abstract model of computer architeture and you are then enlightened with the knowledge that there is a processor that calculates things, there is storage to store things you may want to use and there are primitive outputs for graphics and input from a keyboard or mouse. You dont need to know about nand gates, clean room fabrication, cores, ALUs, storage topology of anything to gain some valuable insight from this abstract model. Indeed im pretty sure many succesful software engineers dont really delve much deeper than this but the model, nevertheless, is useful. I cannot guarantee everyone will understand the model but i know many will and i know it will provide valuable insight. For me this is it with mental models. they convey the essence key information but absolutely not expertise and i am still wondering why many people, as you, are trying to argue the case from this perspective it simply isnt the case.

Any field of knowledge that has been dissected into a taxonomy must be dead. On the other hand, the taxonomy can give you words for what you already know, so it is not entirely useless.

I don't understand how you make the leap from knowledge being equated to the field being dead? Taxonomy provides a foundation for others to learn about something.

Of course. But thinking belongs to the practitioner, the point is that you have to do it and not just study the doing of it.

You acquire a mental model by doing the things that lead to having that mental model, not by reading about the model. Memorizing a taxonomy of cognitive biases doesn't necessarily make you a better thinker, anymore than memorizing design patterns necessarily makes you a better programmer.

> Any field of knowledge that has been dissected into a taxonomy must be dead.

As others have said, this is clearly untrue. Consider algorithms, for instance. We have categories like dynamic programming, and genetic algorithms (a subcategory of evolutionary algorithms).

Building taxonomies is the easy part, and occurs long before a field is 'completed'.

Also, building and learning taxonomies allows for discovery of new knowledge. This is especially obvious in mathematics, where you start with rigorously-defined symbols and operations and very little knowledge, and then manipulate the symbols to gain more knowledge. Indeed, it could be argued that taxonomies are necessary for understanding.

Chemistry, biology, botany, and geology are dead?

i think the point they're making is that many learners in a given field (e.g., undergrads) don't typically critique the textbooks for those subjects. it's as if all the knowledge therein is complete and accurate, and research happens at some amorphous fringe beyond the textbook knowledge. it's intellectually "dead" to those learners, not that the subjects themselves are dead.

That may (how shall we know?) have been the point they intended to make, but the statement we have to work with is: "Any field of knowledge that has been dissected into a taxonomy must be dead."

Is there some nuance of uncertainty in there I'm not picking up on?

The word "dissected" is doing a lot of work there. "Any" makes it, arguably, hyperbolic. Obviously we can't take too literally any statement about a field being alive or dead. Research is alive in these fields but pedagogy is mostly not.

ah, can we know anything at all then? can any statement, no matter how forcefully and obviously effused, be absolutely uncertain?

but i digress... as fun as the debate may be, hn is probably not where we solve epistemic dilemmas.

Well,we can put a man on the moon with less computing power than we carry in our pocket, and that's far from the most impressive thing we've accomplished in a long long list.

> hn is probably not where we solve epistemic dilemmas.

The repulsion to things like logic and epistemology on a programming website isn't the type of thing I believe we should strive for or celebrate, but I certainly can't disagree with your assessment.

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