| Abstrakt: |
Real-world events like the COVID-19 pandemic and wildfires in Australia, Europe, and America remind us that the demands of complex operational settings are met by multiple, distributed teams interwoven with a large array of artefacts and networked technologies, including automation. Yet, current models of human-automation interaction, including those intended for human-machine teaming or collaboration, tend to be dyadic in nature, assuming individual humans interacting with individual machines. Given the opportunities and challenges of emerging artificial intelligence (AI) technologies, and the growing interest of many organisations in utilising these technologies in complex operations, we suggest turning to contemporary perspectives of sociotechnical systems for a way forward. We show how ideas of distributed cognition, joint cognitive systems, and self-organisation lead to specific concepts for designing human-AI systems, and propose that design frameworks informed by contemporary views of complex work performance are needed. We discuss cognitive work analysis as an example. Emerging developments in AI will pose challenges for the design of human-machine systems. Contemporary perspectives of sociotechnical systems, namely distributed cognition, joint cognitive systems, and self-organisation, have design implications that are unaccommodated by traditional methods. Cognitive work analysis may provide a way forward. Abbreviation: AI: Artificial intelligence. [ABSTRACT FROM AUTHOR] |
