Is Kolmogorov-random nonsensical for small numbers?

Question

The Wikipedia definition of Kolmogorov-random defines a string (usually of bits) as being random if and only if it is shorter than any computer program that can produce that string.

Aren't nearly¹ all strings shorter than a certain length² going to be Kolmogorov-random?

1. If a random Turing machine is chosen, then programs that output short strings will almost always be longer than the strings. If the programming language used for measurement is optimized for outputting a short string, then only the complexity of a subset of short strings can be made lower than their length. For example, if a Turing complete language defines $0$ as an operation that outputs 0 and halts, the program for outputting 1 and halting is forced to be longer than the length of its output.

2. The exact length below which this occurs will depend on the programming language chosen. The length is 41 bits using 5 state, 2 symbol Turing machines.

Answer 1

Is Kolmogorov-random nonsensical for small numbers?

Although one could pick a specific description language to make Kolmogorov complexity into
a function from ​ {0,1}^* ​ to ​ {0,1,2,3,...} , ​ most people don't pick as described ​ ( 0 , 1 , 2 , 3 ) ,
so basically:

Kolmogorov complexity is only defined up to an additive O(1), so one
needs an infinite set of strings to make sense of Kolmogorov randomness.
In particular, yes, Kolmogorov-randomness is nonsensical for small numbers.

Answer 2

I think that K-complexity, at least as an indication of randomness, becomes much more meaningful above the "water line" of string size N where you start having K(x) < N/10, although I'm not sure where that water line should sit. You might look into a concept called algorithmic specified complexity, which is a kind of randomness deficiency like computational depth. For an appropriate probability measure, a short but "random" K-complexity might still be a meaningful idea but not necessarily as randomness per se.