OCE.8:11.2 - Source Contributions, Limits, and Currentness

Source line	Retained contribution	Use boundary and currentness
Current FPF A.15.8, A.2.2, E.23.CDI, C.38, and C.11	Configuration inputs and recovery probes; holder-specific capability and development; same-result comparison; and separately governed choice.	Use these patterns to qualify configuration, comparison, and choice; generate organization-specific candidates here and obtain local authority and realization evidence from their owners.
Naikar et al., distributed and joint human–AI design	Distributed teams, artifacts, networked technologies, communication, adaptation, and self-organization replace a dyadic human-versus-machine frame.	Treat the conceptual synthesis and illustrative application as design input; qualify the local allocation Method and institutional authority separately.
Waterson et al., function allocation for responsible AI	Interdependence, joint operation, decision and responsibility points, outcomes, authority, dynamic trust, failure, and recovery extend static allocation.	The evidence comes from an early framework and small experiments. Select local responsibility predicates, legal rules, and organization-design Methods for the actual setting.
Vaccaro, Almaatouq, and Malone, human–AI meta-analysis	Human-only, AI-only, and combined comparison remains visible when synergy matters; task type and the best solo alternative can reverse the answer.	The evidence covers heterogeneous experiments through June 2023. Test local comparative performance and obtain authority, safety, and provider conditions separately.
NASA, Objective Function Allocation Method	Several human, automation, and robotic allocations can be compared through task and performance trade spaces rather than stereotypes.	Qualify transfer from the completed deep-space project to the local organization, provider, authority, and affected-person conditions.
Lagomarsino et al., adaptive task planning and dynamic role allocation	Communication, skill transfer, adaptive planning, control, feedback, and reallocation matter when robotic roles change during Work.	Robotics algorithms, safety thresholds, and execution-time control remain with direct engineering and Operations Methods.
ISO 6385:2016 and ISO 10218-1/-2:2025	Human, social, technical, equipment, workspace, environment, skill, well-being, lifecycle, and current industrial-robot safety conditions belong in applicable comparisons.	Check which edition and requirements apply to the arrangement. Use the relevant requirements in the comparison, then qualify performers, capability, authority, and safe use for the actual arrangement.
NIST AI RMF 1.0 Core and human–AI interaction appendix	Explicit roles and oversight where applicable, third-party risk, deployment-representative evaluation, monitoring, incident response, recovery, override, and change management.	AI RMF 1.0 is voluntary and under revision in 2026. It supplies risk-management outcomes, not OCE authority, a universal human-in-the-loop rule, or provider adequacy.
Aksin and Masini, shared-service organization configurations	Shared-service configurations and their effectiveness are contingent rather than one universal best practice.	Qualify transfer from administrative and business services before choosing an internal, external, engineering, clinical, robotic, AI, or mixed arrangement.
Goth et al., shared-service administrative cost evidence	Objective cost-reduction evidence for administrative shared services is often weak or methodologically under-specified.	Require local evidence of cost gain, capability, provision, and arrangement adequacy before relying on the proposed shared service or outsourcing.

When a changed source or specialist result alters an assumption, obligation or comparison for this arrangement, reopen the affected result premise, candidate or OptionSet. Return a missing reusable arrangement move exposed by use to OCE.15.