Unfortunately, decisions about units are made by a bunch of unaccountable bureaucrats. They would rather define the second in terms that only the techno-aristocracy can understand instead of using a definition that everyone can understand. It's time to turn control over our systems of measurement back to the people !
#DemocratizeUnits
Adding a compass is unlikely to also make the bird disoriented when exposed to a weak magnetic field which oscillates at the right frequency. Which means that the emulated bird will not behave like the real bird in this scenario.
You could add this phenomenon in by hand. Attach some detector to your compass and have it turn off the compass when these fields are measured.
More generally, adding in these features ad hoc will likely work for the things that you know about ahead of time, but is very unlikely to work like the bird outside of its training distribution. If you have a model of the bird that includes the relevant physics for this phenomenon, it is much more likely to work outside of its training distribution.
For this effect to work, it needs a coherence time of at least 100 microseconds, which is long relative to what you would expect in a warm & wet environment, but short compared to the time scales humans usually operate on.
AI Impacts has a related project, where we look at Resisted Technological Temptations and try to figure out "under what circumstances can large concrete incentives to pursue technologies be overcome by forces motivated by uninternalized downsides, such as ethical concerns, risks to other people with no recourse, or risks the decisionmaker does not believe in."
Our current non-exhaustive list of plausible cases includes:
We have not published our investigations into any of these particular cases yet, but hope to soon. If you would like to talk with us about what you would find most decision-relevant from this project, please let me or Rick Korzekwa know.
I find the idea that intelligence is less useful for sufficiently complex systems or sufficiently long time frames interesting. Or at least the kind of intelligence that helps you make predictions. My intuition is that there is something there, although it's not quite the thing you're describing.
I agree that the optimal predictability of the future decays as you try to predict farther into the future. If the thing you're trying to predict in the technical sense, you can make this into a precise statement.
I disagree that the skill needed to match this optimum typically has a peak. Even for extremely chaotic systems, it is typically possible to find some structure to it that is not immediately obvious. Heuristics are sometimes more useful than precise calculations, but building good heuristics and know how to use them is itself a skill that improves with intelligence. I suspect that the skill needed to reach optimum usually monotonically increases with longer prediction times or more complexity.
Instead, the peak appears in the marginal benefit of additional intelligence. Consider the difference in prediction ability between two different intelligences. At small time / low complexity, there is little difference because both of them are very good at making predictions. A large times / complexity, the difference is again small because, even though neither is at optimum, the small size of the optimum limits how far apart they can be. The biggest difference can be seen at the intermediate scales, while there are still good predictions to be made, but they are hard to make.
A picture of how I think this works, similar to Figure 1, is linked here: https://drive.google.com/file/d/1-1xfsBWxX7VDs0ErEAc716TdypRUdgt-/view?usp=sharing
As long as there are some other skills relevant for most jobs that intelligence trades off against, we would expect the strongest incentives for intelligence to occur in the jobs where the marginal benefit of additional intelligence is the largest.
There are examples of measuring lower-order bits without measuring higher-order bits. If something is valuable to measure, there's a good chance that someone has figured out a way to measure it. Here is the most common example of this that I am familiar with:
When dealing with lasers, it is often useful to pass the laser through a beam splitter, so part of the beam travels along one path and part of the beam travels along a different path. These two beams are often brought back together later. The combination might have either constructive or destructive interference. It has constructive interference if the difference in path lengths is an integer multiple of the wavelength, and destructive interference if the difference in path length is a half integer multiple of the wavelength. This allows you to measure changes in differences in path lengths, without knowing how many wavelengths either path length is.
One place this is used is in LIGO. LIGO is an interferometer with two multiple kilometer long arms. It measures extremely small ( $ 10^{-19} $ m) changes in the difference between the two arm lengths caused by passing gravitational waves.