Human–Machine Boundary Management

Definition

Human–Machine Boundary Management examines clear control, responsibility and identity boundaries in integrated human–machine systems within the broader domain of therapeutic, assistive and elective technologies that extend cognitive, sensory or motor capability.

Why this matters

Failures concerning clear control, responsibility and identity boundaries in integrated human–machine systems can cause physical or psychological harm, loss of function, privacy invasion, identity compromise, exclusion, coercion or irreversible impact on human agency.

Research questions

Under which conditions can clear control, responsibility and identity boundaries in integrated human–machine systems be delivered, measured or protected reliably, and how do outcomes vary by person, device, duration, context and governance controls?

Hypotheses

A transparent, safety-bounded and person-centred approach to human–machine boundary management, combining validated measurement, informed consent, privacy and security controls, human oversight and longitudinal monitoring, will improve benefit–risk outcomes compared with opaque or technology-centred approaches.

Proposed methods

controlled performance testing; longitudinal outcome measurement; human-factors evaluation; equity analysis; dependency assessment; user interviews; ethics and policy review; expert and affected-user review; reproducibility testing; methods adapted specifically to Human–Machine Boundary Management

Stakeholders and beneficiaries

augmentation users; patients; clinicians; therapists; employers; insurers; manufacturers; disability advocates; regulators; carers