Hybrid Intelligence – Combining the Human in the Loop with the Computer in the Loop: A Systematic Literature Review
Christina Wiethof, Eva Alice Christiane Bittner · Journal of the Association for Information Systems · 2021
The paper aims at establishing a common ground and understanding of collaborative learning approaches between humans and computers to encourage Hybrid Intelligence. Thereby, we put a special focus on identifying how humans and computers learn from each other through an iterative and interdependent process involving the human-in-the-loop as well as the computer-in-the-loop. To approach this aim, a systematic literature review is conducted. Therefore, we reviewed 2098 publications in three relevant databases and found 33 appropriate publications regarding both human and computer learning. We capture our results by inductively deriving three patterns and three sub-patterns of collaborative learning processes, namely exploration, integration and decision support including assimilation, exploitation and explanation. Additionally, we provide learning measurements from the reviewed literature according to each pattern. Finally, we disclose future research avenues and implications for Hybrid Intelligence in the field of Human-Computer-Interaction, especially collaborative human and machine learning.