4. Human Collaboration Reshaped: Applications and Perspectives

20th century iconic examples of human collaboration are the assembly line, centralised planning, bureaucracies, vote‐based decision making, and school education. These examples, and more generally all forms of human collaboration of the 20th century, are characterized by predefined human roles and little adaptable processes, that is, 20th century collaboration comes at the price of a restricted individual freedom. With the turn of the century, new forms of human collaboration have become widespread that exploit information and communication technologies, data generated by humans, Data Science in general and Machine Learning in particular, and let humans contribute as they like, when they like, and as much as they can, the lack of predefined roles and processes being accounted for by software. The phrase “Human Computation” coined for denoting the new forms of human collaboration stresses a core aspect of the paradigm which can be a downside: With Human Computation, humans become contributors to collaboration‐enabling algorithms that can also control and restrict how collaboration takes place. This article introduces to Human Computation and to its role in applications of Machine Learning, presents Human Computation prototype systems developed during the last decade at Ludwig‐Maximilian University of Munich, discusses ethical issues of Human Computation and Machine Learning, points to on‐going research in the field at Ludwig‐Maximilian University of Munich, and concludes with a reflection on the future of Human Computation. The original contribution of this article is a comprehensive presentation of recent research the main part of which has already been published in more detail elsewhere.