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Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

Postal Subscription Code 80-905

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Front. Eng    2018, Vol. 5 Issue (2) : 182-194    https://doi.org/10.15302/J-FEM-2018085
RESEARCH ARTICLE
The imperative need to develop guidelines to manage human versus machine intelligence
Donald KENNEDY1(), Simon P. PHILBIN2
1. Freerange Buddy Publications, Edmonton, Alberta T5A 0A7, Canada
2. Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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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.
Keywords human intelligence & machine intelligence      HI-MI      decision-making      artificial intelligence     
Corresponding Author(s): Donald KENNEDY   
Just Accepted Date: 19 March 2018   Online First Date: 13 April 2018    Issue Date: 28 June 2018
 Cite this article:   
Donald KENNEDY,Simon P. PHILBIN. The imperative need to develop guidelines to manage human versus machine intelligence[J]. Front. Eng, 2018, 5(2): 182-194.
 URL:  
https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2018085
https://academic.hep.com.cn/fem/EN/Y2018/V5/I2/182
Fig.1  Original piping design
Fig.2  Model parameters as input into stress analysis model
Fig.3  Proposed piping design to satisfy stress analysis model
Fig.4  More representative model for real situation
Fig.5  Stresses introduced by proposed support C during thermal contraction
Fig.6  Proposed support C during thermal expansion
Fig.7  Conceptual framework to support HI-MI decisions based on a multi-criteria decision-making (MCDM) approach
Human factors Machine factors Knowledge factors Process factors
• Engineering team’s lack of flexibility in regard adapting the stress model for the process piping.
• Recognizing minor impact of nonzero factors.
• Pride and professional reputation.
• Situational bias.
• Personality conflicts.		 • Algorithms for stress analysis (based on a deterministic model approach using finite element analysis).
• Scope for reduced bias.
• Repeatability associated with machine operation.
• Difficult to question machine-based outputs.		 • Tacit knowledge of the client engineers on process history.
• Need for strict adherence to the stress analysis model for consultants.
• Consultants have wide experience in different industrial settings.
• Client has deep knowledge base in the engineering application.		 • Company adoption of ISO 9001 quality management system.
• Standard operating procedures (SOPs) for each client.
• Flexibility for in-house decisions.
• Contractually binding processes for the outsourced design.
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