Influence of human-machine interactions and task demand on automation selection and use

Pien

American J Industrial Med

2020

ObjectiveWork automation is increasing worldwide, and the probability of job automation has been associated with workers' adverse health outcomes. This study aimed to examine the association of occupation‐level automation probability with work stress and workers' health.MethodsWe used data from a national survey of 14,948 randomly selected general workers conducted in 2016. Job control and job demand were assessed by the Job Content Questionnaire, and working hours and job insecurity were self‐reported. Health outcomes were measured according to burnout and work‐related injury or disease. We derived automation probabilities for 38 occupational groups and conducted multilevel analyses to examine the associations between occupation‐level automation probability and workers' safety and health after adjusting for psychosocial work conditions.ResultsParticipants working in jobs with a high probability of automation were more likely to have low job control, higher job insecurity, and work‐related injury and disease prevalence; whereas workers in jobs with a low automation probability had higher psychological and physical demands and burnout prevalence. Furthermore, automation probability significantly predicted workers' health after adjustment for demographic characteristics and psychosocial work conditions.ConclusionsWorkers with low automation probability jobs may experience work stress other than that captured by traditional measures of job strain. Organizational approaches to improve employment security and psychosocial conditions are essential for workers' safety and health in the context of increasing job automation.

Section: Discussionmentioning

confidence: 99%

Occupation‐level automation probability is associated with psychosocial work conditions and workers' health: A multilevel study

Pien

American J Industrial Med

2020

“…HMIs, as filters and converters of system information and controls, play a vital role in mitigating imperfect system design in the context of individual user capabilities (Muslim and Itoh, 2019;Nuamah andSeong, 2017 -2017). Careful selection and visualization of information and interaction have been beneficial in improving information acquisition (Panteli et al, 2013), information analysis (Kondo and Collins, 2014;Plaisant et al, 2002;Doi, 2019), decision-making (Zohrevandi et al, 2022), action selection, and action implementation (Navarro et al, 2018), mental model building (Doi, 2019;Rapp, 2007) and to avoid downturns in process efficiency, operators' competences or even rejection of technology in many experiments.…”

Section: Conducive Design Of User Interfacesmentioning

confidence: 99%

Design of a Teleoperation User Interface for Shared Control of Highly Automated Agricultural Machiness

Lorenz

2023

Proc. Des. Soc.

This paper presents a focused examination of critical performance and design issues for the introduction of highly automated tractors and their user interfaces in agriculture. An industry that as of today mainly uses direct-controlled machines that at least to some extent have partly automated functionalities. Issues include out-of-the-loop unfamiliarity, interface complexity, automation transparency, and changing information modalities in teleoperation scenarios for former cabin-based operated machines. Selected evidence and accompanying concepts and findings from literature are put in context to each issue, informing a systematic design process that utilizes the frameworks of knowledge engineering and ecological interface design. The resulting user interface prototype is built upon the identified requirements in analysis and collected design guidelines, stemming from various research areas. The documentation of the consideration of these in context with additional requirements, such as complexity reduction, information interactivity, and users' existing experiences is meant to provide insights into the often opaque and art-like design space.

“…oddball paradigm). The crucial difference with their simple equivalents is that SYSMON and COMM are embedded in a combination of simultaneously executed tasks in the same display, thus providing an ecologically more valid way of assessing vigilance and attention performance under professional working conditions (see also Navarro et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

A comparison of coffee effects on vigilance and attention in pilots across simple and complex lab environments

Bergen,

Miltenburg,

Stiphout

et al. 2023

Preprint

Professionally realistic multi-task environments, such as the NASA Multi-Attribute Task Battery (MATB-II), are employed for measuring vigilance and attention in professionals. However, it is unclear whether well-known intervention effects on performance during simple lab-based tasks, such as those of caffeine, also translate to these more realistic working situations. In a preregistered, double-blind, randomized, controlled repeated-measures experiment (https://osf.io/2zubx), we compared the performance of thirty-five civil pilots during vigilance- and attention-related tasks in simple (psychomotor vigilance task; auditory oddball detection) versus multitask environments (MATB-II system monitoring; MATB-II communications) after consuming regular vs. decaffeinated coffee. For vigilance tasks, no coffee intervention effects were found. Instead, a reversed task repetition effect was found, with participants being slower in session 2 in the simple task environment, but faster in session 2 in the complex environment. For attention-related tasks, regular coffee improved performance accuracy in the simple, but not the multitask environment. Coffee versus decaf effects in the simple task environment did not correlate with those in the complex task environment, neither for vigilance nor for selective attention. However, an experiment-wide increase in sleepiness was attenuated if participants drank regular coffee in the second session. This finding was supported by heart rate and eye blink measures. Results suggest that intervention-related findings do not easily translate to different vigilance- and attention-related tasks if task environments differ in complexity. The MATB-II multi-task environment, in its current form, is perhaps more suitable for assessing intervention effects on physiological measures of fatigue and vigilance than on cognitive performance.