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Title: The air defence task : understanding what motivates automation usage to support classification decisions in practice
Author: Barrett-Pink, Chloë
ISNI:       0000 0004 7656 7724
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2018
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With the growing use of automated systems in military environments it remains vital that research continues to explore the use of such systems operationally. The recent literature has tended to take a systems focused approach, which has concentrated on features of the system and what impact alterations have upon task performance. However, research has begun to see the value in taking a human-centred perspective to understanding the use of automated systems in military environments; asking research questions that remain focused on the human operators that are required to utilise automated systems in increasingly complex environments. Therefore, this thesis contributes to the literature on human-machine-interaction through exploring the operational use of automated systems in the maritime environment. Research into sociotechnical systems is complex, therefore this thesis adopted a Naturalistic Decision Making (NDM) approach utilising mixed-methods to elicit understanding and knowledge from unique access to Royal Navy (RN) Subject Matter Experts (SME). Privileged access to a large number of RN experts (N=53) enabled novel and interesting findings to be drawn from two qualitative surveys. The first explored the stages of the air defence task conducted by RN personnel to better understand where uptake of automation may be beneficial. The findings of this questionnaire revealed that the high-level stages of the air defence task (Observe, Identify and Classify, and Decide and Act) have remained unchanged over the last 20 years and the areas that have previously been identified as potentially benefiting from automated system support remain the same. These findings raised pertinent questions as to why the same areas are still in need of support. Therefore, the second study of this thesis aimed to explore where automated systems have been brought into service to support RN operations to understand how the current procurement process functions. A second questionnaire was developed which allowed RN SME to discuss how automated systems are currently used across all operational settings and where they may be used in the future. Crucially, this second questionnaire explored RN SME opinions towards the existing procurement process. Of concern was that the findings of this study revealed the disconnect that often exists between end user and system designer which has a negative effect on the development of systems being fit for purpose at time of release. This in turn can have severe negative consequences to capability, appropriate system use and can increase the financial costs of developing and implementing new systems. The findings from the first two studies presented in this thesis highlighted the need for, and recommended an increase in use of, immersive simulation environments to support automated system development and research. Therefore, the third part of this thesis presents the development and validation of a simulated microworld, the Automatic Radar Classification Simulation (ARCS). ARCS was designed by the author of this thesis in collaboration with a software engineer to replicate aspects of the air defence task conducted by RN personnel. This design process included 2 pilot studies, the results of which informed developments and changes to ARCS. Overall, this design process took 8 months with several iterations of ARCS being developed. Following the development stage, an experiment was conducted (N=42 university students) to validate the utility of ARCS as a microworld using a holistic real-time scenario to explore individuals' rationales for using a generic automated system when performing a threat detection task. In line with previous research, participants cited workload and managing uncertainty as reasons for selecting to use the automated decision support system. However, unexpectedly task performance was not significantly improved with access to the support system and strong learning effects were observed. Overall, this thesis supports the newly proposed move away from traditional "levels of automation" approaches, advocating for taking a more holistic approach to research into human-machine-interaction. This can be achieved through promoting long-term and continuous engagement between end users and system designers, ensuring that a human-human relationship is maintained throughout the life-cycle of the automated system. Additionally, this thesis highlights the importance of effective communication within and between the military, industry and academia, and the negative implications that ineffective communication has upon naval capability. Finally, this thesis supports the literature that highlights the importance of training in immersive environments and has provided academia with a high-fidelity microworld with which to explore operator use of automated decision support systems in the maritime environment.
Supervisor: Alison, Laurence ; Maskell, Simon Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral