alt Hacker NewsLooking 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)
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> 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.
> '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.
Exactly. The lede buried here is, as you say,
accurate prediction is not better understanding
Less "accurate" model can lead to better prediction
A better understanding encodes more info about how much more it can be improved, when compared to a less good understanding
Explained by this wonderful series
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.
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.
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> 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