2359 The benefits of automation in safety are undeniable, as it removes humans from hazardous and hostile areas around machinery and unstable ground. However, crucial aspects have been overlooked in the implementation of the automation processes in the mining industry. Automation does not remove the need for human involvement. It changes it, and in some cases, it can be reduced. Automation may have unforeseen impacts on systems' safety and productivity unless the role of humans is carefully considered (Horberry et al., 2016). Lessons from other industries, such as aviation and medicine (where this is common), have been introduced with the belief that human error will be eliminated and operator workload reduced. However, automation can introduce new errors and, in some cases, increase mental workload rather than reduce it (Wickens et al., 2021). A diverse range of authors has expanded the understanding of the effects of automation on situation awareness across different domains. These studies have mainly focused on aviation, medical, and military contexts. However, less is known about this phenomenon in other hazardous industries, such as mining, where errors can cause serious or fatal accidents. To address this gap, this research aimed to provide insights into how autonomous and automated systems affect situation awareness, identifying the aspects to be considered to support automation implementation and ensure safety. This study contributes to the conference theme of Health, Safety and Well-being by examining how automation influences workers’ situation awareness and the associated implications for safe systems of work in mining. 2. BACKGROUND Human factor issues at individual, team and organisational levels have far-reaching implications for safety, productivity, and organisational culture. Findings from studies on automation in aviation, land transportation, and process control indicate that the rise in automation may lead to unforeseen consequences for system safety and efficiency unless the human element is systematically incorporated. In mining, incidents regarding the interaction between human operators and automated systems will continue to occur or increase as automation becomes increasingly complex (Burgess-Limerick, 2020). According to Endsley (2017), automated systems affect situation awareness through three main mechanisms (1) changes in information presentation with automation; (2) operator monitoring, vigilance, and trust; and (3) operator engagement. In the first case, automation interfaces often lack essential information about the automation's status, leaving operators with little feedback on the controlled system's state. Also, automated systems can be unpredictable due to their need for more transparency regarding understandability and predictability. Secondly, automation requires extensive human monitoring; thus, vigilance problems arise, exacerbated by complacency or overreliance on automation. Besides, when people increase their trust in automation, they tend to decrease monitoring. Lastly, it is difficult for operators to fully understand what is happening when acting as passive automation monitors. In this sense, active cognitive engagement with a task can improve understanding and retention of critical information. The concept of SA has been extensively studied in various operational contexts, including military settings, transportation, sport, healthcare and medicine, process control, and emergency services. There are three theoretical models of SA: individual, team and system (Stanton et al., 2017). At the individual level, the most widely used definition of SA is given by Endsley (Salmon et al., 2008). Situation awareness describes the individual's ability to "be aware of what is happening around you and understand what that information means to you now and in the future" (Endsley, 2016). Endsley's definition can be broken down into three levels of awareness. Level 1 refers to the individual's perception of the relevant environmental elements' status, attributes, and dynamics. For instance, an operator needs data on a machine's status, and a car driver needs to know the positions of other vehicles. Level 2 includes understanding the significance of those elements and integrating them with relevant goals to comprehend the situation. For example, a power plant operator must combine various data elements to determine how well the system is functioning. Level 3 denotes the ability to project future actions from environmental characteristics. A review of the impacts of automation on the mining industry identified issues related to workload, cognitive load, communication, overreliance, acceptance of automation, trust, and mental well-being
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