HACWD was developed through research into how humans actually work alongside autonomous systems in high-consequence environments. Not how they are supposed to work. How they do.
In mining, energy, and defence, AI and automation are deployed at scale. But work; the design of roles, decisions, authority, and accountability, is rarely redesigned to match. The result is a class of latent risk that technical audits do not find: humans who are accountable for decisions they cannot see, operating systems they cannot always override, in organisations that have no structured way to measure any of it.
HACWD addresses that gap. It provides the framework for designing work, decision authority, governance, and capability in organisations where intelligent systems are part of how work gets done.
The methodology operates across four dimensions:
Work design and role clarity — how work is structured and whether roles reflect actual decision-making responsibilities in an AI-enabled environment.
Human factors and capability — the cognitive, skill, and psychosocial conditions that determine whether operators can exercise effective judgement.
Decision authority and governance — who owns decisions, how automated outputs are treated, and whether accountability is clear when systems fail.
Technology integration — whether intelligent systems were designed around human authority or in spite of it.
