The document discusses using crowdsourcing for search evaluation and social-algorithmic search. It covers topics like using crowds to collect data for search relevance judging, training machine learning models, and answering queries. It also discusses different crowdsourcing platforms, designing tasks for crowds, and quality control. Examples are given of using crowds for tasks in natural language processing, computer vision, information retrieval and more. The social aspects of search are also discussed, like integrating social networks and allowing community question answering.