Comment by jdw64 | Hacker News Reader

Comment by jdw64 | Hacker News Reader

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Looking at the paper, the core message is 'that even scientists harbor the illusion of understanding more than they actually do'.

In reality, science operates much like a mental model. The paper argues that just because a model predicts future values more accurately, it doesn't mean the model explains the actual causal structure. Yet, the fact that outcomes fall within the predicted range reinforces the illusion that one has truly 'understood' it.

This reminds me of the statistician's aphorism: 'All models are wrong, but some are useful.' Science itself, in a way, is a mental model—a simplification created for humans because the world is a complex system that is cognitively impossible to fully comprehend. Within that framework, certain facts reinforce the mental model, while others weaken it. While mental models vary from person to person, in a broad sense, we are commonly taught to view the macroscopic world through the Newtonian model and the microscopic world through the quantum mechanics model.

Reading this makes me reconsider what 'understanding' truly means. I believe the starting point of genuine understanding is acknowledging that perfect prediction is ultimately impossible, and that when viewing the world through our mental models, what matters is defining what we consider to be acceptable 'lossy information' (or information we can afford to lose)

> This reminds me of the statistician's aphorism: 'All models are wrong, but some are useful.'

It reminded the authors of this too, since they quote and source it

"Some are eclipsed in usefullness by others"

Yes, but isn't since exactly about those models? If you want to calculate how much that steel truss is going to bend when loaded, you need basic mechanics. Sure you could go deeper and think about what actually happens to the metallic structure on an atomic level, you could think about the whole thing in relativistic terms, etc. But this is not going to give you a better bridge.

More accurate theories are important once your requirements are so extreme that without them your prediction is off.

Understanding is about knowing these mental models at the different levels, how they connect to each other and where these models have weird gaps and/or disconnects. Since is and always has been about understanding the best current explaination of the things we observe. Whether it is exactly as you say, or some more elaborate hidden structure is beneath it, is not something you can tell apart, unless you run into the actual limitations of your model.

If you want to land on the moon, you use science, even if it doesn't know everything down to the last particle.

In reality, CAD systems don't provide data structures that let you describe the behaviour of materials, I feel this sends a hint to designers that they don't need to consider those aspects. I did build this into STEP from the start but CAD vendors and users didn't want to implement it, am currently trying to fix this.

When we use computers for everything, the functionality provided by particular software packages can end up constraining how we think about a problem space.

> 'All models are wrong, but some are useful.'

And beyond that: models become most interesting at the point they fail, because that's where you learn something.

The problem is when certain (mental) models are important to a community or science specialization. When these models fail, the community will often enforce the model and censor the opposing facts. I have encountered several such conflicts.

Scientists are still humans. Individual people may be curious and be open to some questioning. But thy find it difficult to discuss such things in the open. It is like a religious dogma.

One example is the model of "colliding magnetic field lines", which is a concept not possible in electron-magnetism (my own expertise). But astronomers use this concept to describe plasma lines that collide with each other on the sun. They call it "magnetic reconnection". I can discuss this problem within communities that know electromagnetism, but not with astronomers. The confusion comes from their model (magnetohydrodynamics) that plasma always follows magnetic field lines. And if plasma collides, so must also the field lines. But in reality (and according tot he inventor of the model, Alphen) the model describes a very special case.

Are you talking about magnetic reconnection? It's not in violation of physical law.

> It is like a religious dogma.

It is religious dogma.

In what way, exactly? It's one thing to assert an analogy between two things, and quite another to assert an identity.

The specific example given was divergent models of colliding magnetic field lines.

How are the models religious?

How are the models dogmatic?

The example under discussion suggests neither in the literal sense.

The previous poster said:

> When these models fail, the community will often enforce the model and censor the opposing facts. I have encountered several such conflicts.

Censoring opposing fact to enforce the wrong model is religious dogma. Or maybe just dogma. Religious or scientific.

At any rate, it's the antithesis of what the scientific method is. The reality is that scientists in general pay lip service to the scientific method, without forgetting where their paychecks come from (government, military or corporations).

> The paper argues that just because a model predicts future values more accurately, it doesn't mean the model explains the actual causal structure.

Yes. Celestial navigation was based on a universe which spun around the earth, which is wrong, but it worked for navigation.

Celestial navigation is still based on a geocentric coordinate system. Modern astronomical ephemerides use the Tychonic model--the sun is modeled as revolving around the Earth, the other planets as revolving around the sun.

Mathematically, in a two-body system, there's no actual difference between saying body A orbits body B or saying body B orbits body A, so in some sense, it's not even wrong.

> Mathematically, in a two-body system, there's no actual difference between saying body A orbits body B or saying body B orbits body A, so in some sense, it's not even wrong.

This isn't what the geocentric model claimed, though. It went beyond just a choice of reference frame, which as you say, you can do in math, or physics.

For a start, the geocentric model claimed a physically preferred reference frame, which already directly contradicts the coordinate relativism you described. In that sense, it was wrong.

Beyond that, it proposed a mathematical model based on epicycles, a model which was eventually falsified due to many failures to match observation. In that sense, it was also wrong.

These points also contradict your other claim:

> Modern astronomical ephemerides use the Tychonic model--the sun is modeled as revolving around the Earth, the other planets as revolving around the sun.

This is misleading at best. The ephemerides you mention are based on modern Newtonian many-body physics, but they do a coordinate transform on the results to express them in a way that's convenient for Earth-bound observers.

This is not "using the Tychonic model" in any meaningful sense. It's using a correct coordinate transform that is equivalent to the overall coordinate system that Tycho tried to use, but failed to get right. It doesn't rely on any aspects of Tycho's model, because that model was largely invalid, and would not produce correct results.

That's instrumentalism in philosophy of sciences. As long as a theory is useful and results in good predictions, without worrying about whether a theory is true or not.

Exactly. The lede buried here is, as you say,

  accurate prediction is not better understanding

Which has a statistician counterintuition

  Less "accurate" model can lead to better prediction

Therefore (in my understanding)

  A better understanding encodes more info about how much more it can be improved, when compared to a less good understanding

Maybe understanding should be related to wisdom rather than intelligence? Like Socrates. AGW?

Explained by this wonderful series

I like the point about improvement. For a long time the geocentric cycle and epicycle models of the solar system generated more accurate predictions in most cases than heliocentric ones. Yet anomalies in planetary motion could never have lead to the discoveries of the outer planets using that approach.

Can you please elaborate on the series ? I didn't get the reference.

Sorry was in a bit of brain fog

https://youtu.be/_Zxr9STGwbQ?t=3m39s

There's an upcoming book, mentioned in the blurb

Seems like a trivial realization written about many decades ago. Join the church of instrumentalism, and just live with it as a fact of daily life. Focus on your predictions and mental models of the world, hone them, and that's about it.

Henri Poincare's works - https://news.ycombinator.com/item?id=48167803

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