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AI in education

With technologies increasingly gaining more data and intelligence, a new era of Human-AI interaction is emerging (Kamar, 2016) . There is ongoing fusion between human and artificial intelligence (AI) into so-called hybrid systems. A defining characteristic of these systems is that the boundaries between AI and human decision-making fluctuate. For example, self-driving cars mostly offload driving to the AI, but in situations that are too complex for the AI to navigate, control is transferred back to the human driver. Consequently, tasks can be offloaded from humans to AI and onloaded from AI to humans (Buxbaum-Conradi et al., 2016) . Hybrid systems offer potential for training complex human skills in the context of education (Harari, 2018) . These systems offer opportunities to offload human intelligence in different ways. Teachers can offload diverse task to an AI which has the potential profoundly change the role and function of the teachers in educational scenarios (read here more about it). For learners the AI can model how to regulate their learning at the start of a learning process (Dellermann, Ebel, Söllner, & Leimeister, 2019) , and onload regulation tasks once learners have developed the prerequisite knowledge and skills. In this transition AI can model and scaffold human learning (read here more about it). With an increased investment and interested around the globe hybrid learning technologies there is a need to further understand how to give form to hybrid human-AI intelligence in the field of education.

Visit this page if you want to read more about our view on Hybrid human-AI learning technologies and the role of the teacher.