TY - JOUR
AU - Leimeister, Jan
AB - Bus Inf Syst Eng 61(5):637–643 (2019) https://doi.org/10.1007/s12599-019-00595-2 CATCHWORD • • • Dominik Dellermann M.Sc. Philipp Ebel Matthias So ¨ llner Jan Marco Leimeister Received: 30 October 2017 / Accepted: 7 November 2018 / Published online: 28 March 2019 Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019 Keywords Hybrid intelligence  Artificial intelligence  performing these tasks. This triggers new heated debates of Machine learning  Human-computer collaboration  when machines will ultimately replace humans (McAfee Machines as teammates  Future of work and Brynjolfsson 2017). While previous research has proved that AI performs well in some clearly defined tasks such as playing chess, playing Go or identifying objects on 1 Introduction images, it is doubted that the development of an artificial general intelligence (AGI) which is able to solve multiple Research has a long history of discussing what is superior tasks at the same time can be achieved in the near future in predicting certain outcomes: statistical methods or the (e.g., Russell and Norvig 2016). Moreover, the use of AI to human brain. This debate has repeatedly been sparked off solve complex business problems in organizational con- by the remarkable technological advances in the field of texts 
TI - Hybrid Intelligence
JF - Business & Information Systems Engineering
DO - 10.1007/s12599-019-00595-2
DA - 2019-03-28
UR - https://www.deepdyve.com/lp/springer-journals/hybrid-intelligence-FL0pWPEL2Y
SP - 637
EP - 643
VL - 61
IS - 5
DP - DeepDyve
ER -