> it is a computer algorithm, so by definition it is trivial to reproduce results, you just run the program again.

Not really. Deep learning is still quite a lot of dark voodoo where random initialization and data shuffling can matter significantly. People also adapt hyperparameters manually during training, stop early with no clear metric, and don't share their code for preprocessing the data or even the exact architecture of the network.

It's certainly better than in other fields, but it's not trivial.