We survey some of the recent results on the complexity of recognizing $n$--dimensional linear arrangements and convex polyhedra by randomized algebraic decision trees. We give also a number of concrete applications of these results. In particular, we derive first nontrivial, in fact quadratic, randomized lower bounds on the problems like K Bounded Integer Programming. We formulate further several open problems and possible directions for future research.