.... that one can get accurate answers via random numbers.
Permit me to comment:
'accurate' only in the sense that a Monte Carlo will provide distribution of possible outcomes [answers] weighted by the probability [strictly: the probability density. That is, probability per unit of output], and the accuracy of this range of answers is highly dependent on the inputs provided to the simulation tool. So, it's still a matter of guarding against "garbage in/garbage out"
Nevertheless, in his clever post, Awati uses simple geometric shapes to demonstrate the answer to that paradox. In the end, I was convinced!