Please provide an abstract or presentation Summary. (approx 300 words) * Artificial Intelligence (AI) is changing the way we work. The implementation of Intelligent Decision Support Systems (IDSS), where a machine ‘thinks’ for itself to generate responses to problems, will significantly impact workplaces across a range of industries. To date, there has been no attempt to synthesise workers’ perceptions of AI-driven approaches to decision support, which differ from alternative support systems in several critical ways (e.g., a capacity to learn from errors, a relatively low degree of transparency). Our research aims to better understand workers’ interactions with IDSS and how to ‘design out’ the reasons underlying wrongful rejection, which, in safety-critical situations, may save lives. This presentation focuses on recent findings from a systematic review of the empirical literature, as well as a survey of workers’ experiences, perceptions, and attitudes regarding current and prospective IDSS use. We address two research questions: 1) What is the general consensus from workers regarding the use of IDSS?; and, 2) What are the most important factors when deciding whether to accept advice from an IDSS? The survey data highlight a range of factors considered to be very important to the full exploitation of IDSS technology among a sample of largely prospective users (e.g., historical accuracy, decision risk and impact, ease of understanding, and accountability). Despite an abundance of evidence reporting workers’ aversion toward algorithm-based decision support systems, our review findings suggest that workers hold somewhat more positive views towards AI-driven systems. Critically, our review highlights a paucity of standardised assessments of workers’ interactions with the technology and signals a call to action for human factors and safety researchers. Taken together, these findings yield impressions that may mitigate the potential for safety risks stemming from invalid system rejection.