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M. Riveni, C. Hillen, S. Dustdar:
"Privacy in Human Computation: User Awareness Study, Implications for Existing Platforms, Recommendations, and Research Directions";
in: "Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining", Lecture Notes in Social Networks; N. Agarwal, N. Dokoohaki, S. Tokdemir (Hrg.); Springer Nature Switzerland AG 2021, 2018, (eingeladen), ISBN: 978-3-319-94104-2, S. 247 - 267.

Research and industry have made great advancements in human computation and today we can see multiple forms of it reflected in growing numbers and diversification of platforms, from crowdsourcing ones, social computing platforms (in terms of collaborative task execution), and online labor/expert markets to collective adaptive systems (CAS) with humans-in-the-loop. Despite the advancements in various mechanisms to support effective provisioning of human computation, there is still one topic that seems to be close to neglected both in research and the current design and development of human computation systems, namely privacy. In this work, we investigate this problem. Starting from the fact that user awareness is crucial for enforcing privacy-respecting mechanisms, we conducted an online survey study to assess user privacy awareness in human computation systems and in this paper provide the results of it. Lastly, we provide recommendations for developers for designing privacy-preserving human computation platforms as well as research directions.

Privacy, Privacy Awareness, Social Computing, Human Computation, Crowdsourcing, Collective Intelligence

http://dx.doi.org/10.1007/978-3-319-94105-9_10