The language of science has shifted before; I don't think it's reasonable to assume it won't again.
Then again, English might stay around as a, well, legacy language. I could imagine someone a few hundred years from now studying archaic english, in preparation for a dive into the kernel or whatever. Then again, computer translation will probably have gotten good enough that it won't be necessary.
I mean, bombing Syria does seem farther away, in the geographical (and therefore emotional) sense.
Plus, the United States is sickeningly nationalistic, and still carries a hint of pride about its immigrant origins. "This child wanted to come into the U.S., but the cruel President Trump won't let him!" packs more punch than "President Obama issued a drone strike against one side of a multifaceted conflict in a small country you know nothing about."
There's also the fact that Obama was on the team that typically opposes military intervention and racism (at least ideologically...), and it's harder to get people outraged at their own side. The Republicans might have had trouble riling up their base with drone strikes on muslims, so they went for other hot buttons. The Democrats, on the other hand, are perfectly happy to sink their teeth into the travel ban.
It's generally custom, although we've had teams use ML strategies to tune their bots in the past. (I'm one of the people who runs this competition).
We impose tight runtime limits on the code your AI can run - generally limiting the number of bytecodes the JVM can execute per turn per robot. This is partly pedagogical; it kinda-sorta simulates embedded programming, like for a real robot. It's also practical; it keeps people from accidentally DOS'ing themselves or our servers with infinitely-looping AI.
On the other hand, 20000 instructions per turn doesn't give you much leeway for, say, matrix multiplication, so most sophisticated ML isn't possible at runtime. You can do simple things, but they have to be tightly written.
Then again, English might stay around as a, well, legacy language. I could imagine someone a few hundred years from now studying archaic english, in preparation for a dive into the kernel or whatever. Then again, computer translation will probably have gotten good enough that it won't be necessary.