Simple problems may be hard to solve because they are really hard problems underneath the surface. Let me explain a little bit of why I think this is so. The reason it may look simple is the way the problem is stated in words and simple arithmetics in the first place. Our traditional understanding of simple number theory and counting like adding, multiplying and dividing numbers we learn very early and is part of some human culture.
The problem of stating problems this simple way is that the underlying mechanics of the problem is hidden from the observer. Numbers in base $10$ may look simple because we are used to count and we learn simple rules. However when we iterate those rules they become more and more complex as the numbers change. The $3n+1$ problem is a very good example of this. If you study the complexity in base $2$ you start to see some features that is difficult to see in base $10$, you could also find simple rules that produce the complexity that we see. See ref. The 3x+1 Problem: A Quasi Cellular Automaton by Thomas Cloney, Eric Goles and Gérard Y. Vichniac.
A quote from the paper:
Base 2 is a natural choice because of the control role of the parity of each iterate under eqn.(1) and because it lends itself to detailed high-resolution graphic display. The bit representation displays the "insides" of the iterates, in contrast with number theory approaches that focus only on iterate size, a more limited form of information represented by the envelope of the binary evolution.
If you're not familiar with Cellular Automata, I suggest reading a few tutorials or explanations from Stephen Wolfram or if you have access to the book NKS - before reading this paper. I suggest learning or get an intuition on how simple Automaton rules produce complex output then you can start to connect the dots, atleast get an idea or a sense of what might be going on.
Cloney, Thomas; Goles, Eric; Vichniac, Gérard Y., The (3x+1) problem: A quasi cellular automaton, Complex Syst. 1, No. 2, 349-360 (1987). ZBL0662.10010.