Identifying risk controls for future advanced brain-computer interfaces: A prospective risk assessment approach using work domain analysis

When tomorrow comes: A prospective risk assessment of a future artificial general intelligence-based uncrewed combat aerial vehicle system

There are concerns that Artificial General Intelligence (AGI) could pose an existential threat to humanity; however, as AGI does not yet exist it is difficult to prospectively identify risks and develop requisite controls. We applied the Work Domain Analysis Broken Nodes (WDA-BN) and Event Analysis of Systemic Teamwork-Broken Links (EAST-BL) methods to identify potential risks in a future 'envisioned world' AGI-based uncrewed combat aerial vehicle system. The findings suggest five main categories of risk in this context: sub-optimal performance risks, goal alignment risks, super-intelligence risks, over-control risks, and enfeeblement risks. Two of these categories, goal alignment risks and super-intelligence risks, have not previously been encountered or dealt with in conventional safety management systems. Whereas most of the identified sub-optimal performance risks can be managed through existing defence design lifecycle processes, we propose that work is required to develop controls to manage the other risks identified. These include controls on AGI developers, controls within the AGI itself, and broader sociotechnical system controls.

Eadem Sed Aliter. Validating an emergency department work domain analysis across three hospital configurations

Work Domain Analysis (WDA), the foundational phase in the Cognitive Work Analysis Framework (CWA), provides a platform for understanding and designing complex systems. Though it has been used extensively, there are few applications in healthcare, and model validation for different contexts is not always undertaken. The current study aimed to validate an Emergency Department (ED) WDA across three metropolitan hospitals that differ in the type and nature of services they provide, including the ED in which the original ED WDA was developed. A facilitated workshop was conducted at the first ED and interviews at two subsequent EDs to refine and validate the ED WDA. ED subject matter experts (SMEs) including nurses, doctors, administration, and allied health personnel provided feedback on the model. SME feedback resulted in modifications to the original ED WDA model including combining nodes to reduce duplication and amending five labels for clarity. The resulting WDA provides a valid representation of the EDs found in metropolitan districts within an Australian state and can be used by roles such as frontline ED clinicians, hospital managers, and policy developers to facilitate the design, testing, and sharing of solutions to local and shared problems. The findings also demonstrate the importance of validating WDA models across different contexts.