Readit NewsThey pre-rigged the entire field with generic Terminator and Star Trek tropes, any serious attempt at discussion gets bogged down by knee deep sewage regurgitated by some self appointed expert larper who spent ten years arguing fan fiction philosophy at lesswrong without taking a single shower in the same span of time.
As a side note:
> any serious attempt at discussion gets bogged down by [...] without taking a single shower in the same span of time.
This is unnecessary and (somewhat ironically) undermines your own point. I would like to see less of this on HN.
> the primary aim isn't really to find out whether a result is true but why it's true.
But being over in the AI/ML world now, this is my NUMBER ONE gripe. Very few are trying to understand why things are working. I'd argue that the biggest reason machines are black boxes are because no one is bothering to look inside of them. You can't solve things like hallucinations and errors without understanding these machines (and there's a lot we already do understand). There's a strong pushback against mathematics and I really don't understand why. It has so many tools that can help us move forward, but yes, it takes a lot of work. It's bad enough I know people who have gotten PhDs from top CS schools (top 3!) and don't understand things like probability distributions.
Unfortunately doing great things takes great work and great effort. I really do want to see the birth of AI, I wouldn't be doing this if I didn't, but I think it'd be naive to believe that this grand challenge can entirely be solved by one field and something so simple as throwing more compute (data, hardware, parameters, or however you want to reframe the Bitter Lesson this year).
Maybe I'm biased because I come from physics where we only care about causal relationships. The "_why_" is the damn Chimichanga. And I should mention, we're very comfortable in physics working with non-deterministic systems and that doesn't mean you can't form causal relationships. That's what the last hundred and some odd years have been all about.[1]
[0] Undergrad in physics, moved to work as engineer, then went to grad school to do CS because I was interested in AI and specifically in the mathematics of it. Boy did I become disappointment years later...
[1] I think there is a bias in CS. I notice there is a lot of test driven development, despite that being well known to be full of pitfalls. You unfortunately can't test your way into a proof. Any mathematician or physicist can tell you. Just because your thing does well on some tests doesn't mean there is proof of anything. Evidence, yes, but that's far from proof. Don't make the mistake Dyson did: https://www.youtube.com/watch?v=hV41QEKiMlM
People do look, but it's extremely hard. Take a look at how hard the mechanistic interpretability people have to work for even small insights. Neel Nanda[1] has some very nice writeups if you haven't already seen them.
If the self-check is more reliable than the solution-generating process, that's still an improvement, but as long as the model makes small errors when correcting itself, those errors will still accumulate. On the other hand, if you can have a reliable external system do the checking, you can actually guarantee correctness.
Math fans tend to discount and dismiss applied statistics as being not math, in a way that they don't do for physics, for some reason I don't fully grasp.
I think it's because statistics gets a bad reputation from the legions of terrible social scientists in the wild, who can easily publish false but socially interesting results that get applied to our real lives. Mathematically fraudulent physics, on the other hand, usually immediately dies in the engineering phase, leaving just a few rambling cranks that most of everyone ignores.
Also (and related) perhaps, just as dry mathematical statistics ignores real world empirical experimentation, "wet" applied statistics goes to far into ignoring the math completely, because too few empirical scientists are able to understand the math when they would wncounter itm
It's because we're secretly afraid that the physicists are smarter than us.
Less facetiously, physicists keep discovering things that lead to new mathematics we would never have dreamed of ourselves, so we have a healthy respect for how insightful they can be.
And that is for healthier individuals and not including other loans like car loans etc. God (if there is one) help with medical debt.
How do we expect young people to navigate this rigged system?