This article is concerned with randomness in computation, from the viewpoint of computational complexity. For the question if a randomization significantly improves complexity, two affirmative examples are exhibited; one is probabilistic counting, and the other is the Markov chain Monte Carlo (MCMC) method for high-dimensional volume. I also explain the topic about deterministic random walk, as a possible derandomization of MCMC.
