CTDT vs. ETDT. Hmm, that's a tough one. First, CTDT allows "screening off" of causes, which makes a big difference.

I liked EY's formulation above: "TDT doesn't cooperate or defect depending directly on your decision, but cooperates or defects depending on how your decision depends on its decision." It's hard to collect evidence, I think, but reasoning about a causal graph gives you the ability to find out how latent decisions affect other outcomes.

So in this case, expected utility based reasoning leaves you in a posiiton where you make some decisions because they seem correlated with good outcomes, while the causal reasoning lets you sometimes see either that the actions and consequences are disconnected or that the causation runs in the opposite direction to what you desire.

ETA: EY's street crossing example is an example of causation running in the opposite direction.