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- Hacker News
- Is it a probability that the authors understood the notion of Understanding all wrong?
;).
by dbacar - Who is this for? This section, which is fairly close to a central thesis, contains no citations:
> Illusions of understanding can take several (overlapping) forms. Some that are commonly encountered are: (1) Illusions of explanatory depth (we think we personally understand things in more detail than we do). (2) Illusions of explanatory completeness (even if we don’t think we fully understand it ourselves, we think the best experts do). (3) Illusions resulting from understanding something other than the goal (e.g. we believe we understand the formation of memories because we understand the anatomy of the brain site, the hippocampus, that is needed for such learning). (4) Illusions due to simple statements giving a feeling of insight (such as when tautological statements seem insightful because they are framed in a reductionist manner). (5) Illusions (as described earlier) that one understands the cause of phenomena because there exists a model or procedure that predicts well. (6) Illusions of causal strength (attending to an observed relation makes one believe the causal connection is stronger than it is). (7) illusions that one can describe causes simply. (8) Illusions by the explainer that the recipient understands what the communicator intends. (9) Illusions by the recipient of an explanation that the communicator understands well and that the explanation is correct and complete.
Are we to infer that these observations are unsupported by evidence? Are we to assume that the research work is so poorly constructed that they did not do research to find evidence of the existence of the classifications in existing research?
by smarm52 - The authors of this paper have not studied what historians and philosophers of science have written. They just use 'induction', 'validity', etc. They reinvent the wheel. They write "Of course the validity of that induction depends on a host of other assumptions.". Duhem-Quine thesis is better than this way of formulation, as the latter doesn't use 'validity'.
If authors ever come to this forum, please read Duhem-Quine thesis, over/under determination, inference to the best explanation, Goodman's paradox, also how various theories in philosophy of sciences: from Popper to Kuhn, Lakatos, Laudan, etc.
by raincom - More predictive power is always a good goal, full stop. This is orthogonal to whether the model producing prediction helps with "understanding" directly. Predictability encodes understanding in a strict information theoretic sense, regardless of our ability as humans to access that understanding.by chermi
- It's funny when you think you know something pretty much thoroughly. Then you learn a bit more and realize that your understanding was a bit simplified, had gaps or there was a whole other level to it.
The feeling is a strange mixture of disappointment, awe, annoyance and excitement.
- This is a classic case of overthinking. Induction should not yield new knowledge because nothing new is discovered, but it does. Deduction likewise also cannot establish new knowledge, yet it does. Empirical science is flawed on extremely many levels but it works because on average, over time, many converging observations can build refined and accurate causal theories. It’s a matter of practicality that things cannot be proven fully. Judging from the state of modern medicine, engineering and the sciences, the system works ok regardless
- This is kind of interesting, but I predict that it pleases almost nobody. Philosophy of science types will be kind of annoyed at the preoccupation with statistics, ML people will be annoyed at too much philosophy of science, etc.
I totally support a goal to get those groups talking more but something tighter is probably better. And why isn't it tighter? Without big original contributions, the goal does seem to be a survey
by ian_j_butler - 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)
by jdw64