No search is the same, and no knowledge domain requirements are identical, so how can the full potential of search intelligence be exploited? How can search computation be boosted with intuition, lateral thinking, conceptual associations, trusted opinions and domain knowledge? How can multimedia search be provided with time-space coherence? The CUbRIK (2013-2016) project investigated how to bring the human in the loop of Artificial Intelligence (AI) systems in multimedia search. The human in the loop enhances the search experience to augment precision and the relevance of results when machine intelligence fails or is unable to remove uncertainty. The approach was not to emulate, but rather to incorporate human and social capabilities, from feature extraction to search and validation of a multimedia content and query processing system. In CUbRIK, I was the work package leader for the work on crowdsourcing with a focus on technical, human, and ethical aspects.