I recently gave a talk[0] to data engineers that is an extension of this idea. The conclusion I came to after years of considering this, the Blub paradox and various other sources, is that we should use more languages.
In the talk I mention Gary Miller, who is working on formalizing the tradeoff between expressiveness (as defined by jumps in the language hierarchy) and decidabilities. The TL;DR is that as you jump up the language hierarchy you lose more decidabilities. A decidability is a question that can be answered with a yes/no. For example: "does this program halt?" is a decidability.
Interestingly this also shows a difference between lambda calculi and universal turing machines. When you go from lambda calculi to UTMs, you lose equational reasoning (but depending on how you define an encoding function, you may also gain intensionality). This of course has some implications, which is pretty much a can of worms that nobody wants to touch (i.e. whether the Church-Turing hypothesis is true)
In the talk I mention Gary Miller, who is working on formalizing the tradeoff between expressiveness (as defined by jumps in the language hierarchy) and decidabilities. The TL;DR is that as you jump up the language hierarchy you lose more decidabilities. A decidability is a question that can be answered with a yes/no. For example: "does this program halt?" is a decidability.
Interestingly this also shows a difference between lambda calculi and universal turing machines. When you go from lambda calculi to UTMs, you lose equational reasoning (but depending on how you define an encoding function, you may also gain intensionality). This of course has some implications, which is pretty much a can of worms that nobody wants to touch (i.e. whether the Church-Turing hypothesis is true)
[0]: https://www.youtube.com/watch?v=KOuwZEtHZ_U