The imperative need to develop guidelines to manage human versus machine intelligence

Abstract

Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions. Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area.

Blending NLP and Machine Learning for the Development of Winograd Schemas

“…To put it succinctly, by amplifying human and machine intelligence, we can address some of their weaknesses [32]. This is why Human-Computer Interaction has moved to the collaboration era between humans and machines [17]. In essence, our proposed framework utilizes the Winventor replenishment mechanism to inspire and motivate crowdworkers to be creative based on a novel interaction that amplifies human and machine intelligence by combining their complementary strengths.…”