Consider the following two countable sets of numbers $A = \mathbb{N}\smallsetminus 7 \mathbb{N}$ and $B = 7\mathbb{N}$, i.e., the set of natural numbers that are not multiples of 7 and the set of all multiples of 7. It is easy to prove that $|A| = |B|$.
Given these facts, I have been twisting my brain around the following thought experiment that I came up with - imagine you have an infinitely large urn that contains the elements $A \cup B = \mathbb{N}$. The probability that a random element drawn out of this urn is divisible by 7 = $\frac{1}{7}$ even though, according to cardinality, there are an equal number of elements in from both sets in the urn! In fact this argument would suggest that there are 6 times as many numbers in set $A$ than there are in set $B$!
Going strictly by the sizes of the sets, it seems like it should be equally likely to pick elements from set $A$ and from set $B$ which is even stranger since from empirical evidence we know that the probability should be $\frac{1}{7}$.
How do we resolve this paradox? I feel that I have misunderstood some concept pertaining to cardinality of sets, but then again, $\infty$ is a pretty weird monster on its own and hence I am expecting some interesting responses!
There is an obvious bijection between the intervals $A = [0,1)$ and $B = [1,4)$, yet if we define a uniform random variable $X$ whose support is on the union of these intervals, the probability of $X \in A$ versus $X \in B$ are not equal, because when we say "uniform distribution," we have imposed a probability measure on the sample space $A \cup B$.