Prof. Jaynes would doubtless be surprised by the power of algorithms such as Markov Chain Monte Carlo

Do you have any idea who you're talking about... no, obviously not. Jaynes knew quite well what MCMC was, dear. Though particle filtering was after Jaynes's time.

Derandomization requires some thought. One doesn't always have the time to put in the thought. And then, after you've put in some thought, it often requires some computing power. Often it isn't worth the computing power. But wherever it is possible to predictably do worse than random, you have prior knowledge about the problem that could let you do predictably better than random. That's one reason derandomization is a minor cottage industry in algorithmics.