This workshop is about how to design learning problems. The task of designing learning problems can be understood as roughly parallel to the mechanism design problem within economics and game theory. Several recent examples of learning problem design that have appeared include: (1) Converting otherwise-unsupervised problems into supervised problems. (2) The use of algorithm created ancillary prediction problems for improved representation and predictive performance. (3) The method of reduction between learning tasks. This area is new and not entirely defined---it's our goal to bring together people interested in the topic, define what we do and don't understand, and attempt to define the principles of learning problem design. We welcome participation---email jl@hunch.net and beygel@gmail.com if interested.