You can’t just trivially scale up the angular resolution by bolting more sensors together (or similar methods). It gets more difficult to engineer the lenses and sensors to meet super-high specs.
And aside from that, the problem behaves nonlinearly with the amount of atmosphere between you and the plane. Each bit of distortion in the air along the way will combine, potentially pretty harshly limiting how far away you can get any useful image. This may be able to be worked around with AI to reconstruct from highly distorted images, but it’s far from trivial on the face of it.
My guess is the largest contributor is the cultural shift to expecting much more involved parenting (example: the various areas where parents had CPS called on them for letting their kids do what the parents were allowed to do independently as kids)
Another big thing is that you can’t get tone-of-voice information via text. The way that someone says something may convey more to you than what they said, especially for some types of journalism.
I’d imagine that once we see the axis it will probably (~70%) have a reasonably clear meaning. Likely not as obvious as the left-right axis on Twitter but probably still interpretable.
I think a lot of the value that I’d get out of something like that being implemented would be getting an answer to “what is the biggest axis along which LW users vary” according to the algorithm. I am highly unsure about what the axis would even end up being.
To lay out some of the foundation of public choice theory:
We can model the members of an organization (such as the government) as being subject to the dynamics of natural selection. In particular, in a democracy elected officials are subject to selection whereby those who are better at getting votes can displace those who are worse at it, through elections.
This creates a selection dynamic where over time the elected officials will become better at vote-gathering, whether through conscious or unconscious adaptation by the officials to their circumstances, or simply through those who are naturally better at vote-gathering replacing those worse at it.
This is certainly not a bad thing per se. After all, coupling elected officials’ success to what the electorate wants is one of the major purposes of democracy, but “what gets votes” is not identical to “what’s good for the electorate”, and Goodhart’s law can bite us through that gap.
One of the classic examples of this is “doling out pork”, where concentrated benefits (such as construction contracts) can be distributed to a favored sub-group (thus ensuring their loyalty in upcoming elections) while the loss in efficiency from that favoritism is only indirectly and diffusely suffered by the rest of the electorate (making it much less likely that any of them get outraged about it enough to not vote for the pork-doler).
The application of this to market failures is that you can look at a market under government regulation as two systems (the market and the government), each with different incentives that imperfectly bind their constituent actors to the public good. The market generally encourages positive-sum trades to happen, but has various imperfections, especially regarding externalities and transaction costs, and the government generally encourages laws/regulations that benefit the public, but has its own imperfections, such as pork-doling and encouraging actions which look better to the public than their actual results would merit.
The result of this is that it is not necessarily clear whether whether changing how much influence market vs government dynamics have on a specific domain will improve it or not. Moving something to more government control may fix market failures, or it may just encourage good-looking-but-ineffective political posturing, and moving something to the market may cut down on corruption, or may just hit you with a bunch of not-properly-accounted-for externalities.
In the particular case of “government action to solve market failures”, the incentives may be against the government actors solving them, as in the case of the coal industry providing a loyal voting bloc, thereby encouraging coal subsidies that make the externality problem worse.
Therefore, my presentation of the market-failure-idea-skeptic’s position would be something like “we should be wary of moving the locus of control in such-and-such domains away from the market toward the government, because we expect that likely the situation will be made worse by doing so, whether due to government action exacerbating existing market failures more than it solves them, or due to other public-choice problems arising”.
Just because the US government contains agents that care about market failures, does not mean that it can be accurately modeled as itself being agentic and caring about market failures.
The more detailed argument would be public choice theory 101, about how the incentives that people in various parts of the government are faced with may or may not encourage market-failure-correcting behavior.
For chess in particular the piece-trading nature of the game also makes piece handicaps pretty huge in impact. Compare to shogi: in shogi having multiple non-pawn pieces handicapped can still be a moderate handicap, whereas multiple non-pawns in chess is basically a predestined loss unless there is a truly gargantuan skill difference.
I haven’t played many handicapped chess games, but my rough feel for it is that each successive “step” of handicap in chess is something like 3 times as impactful as the comparable shogi handicap. This makes chess handicaps harder to use as there’s much more risk of over- or under-shooting the appropriate handicap level and ending up with one side being highly likely to win.
Also note that socks with sandals being uncool is not a universal thing. For example, in Japan it is reasonably common to wear (often split-toed) socks with sandals, though it’s more associated with traditional garb than modern fashion.
Also related: Yudkowsky on making Solvable Mysteries: