  The aviation literature gives relatively little guidance to practitioners
about the specifics of architecting systems for safety, particularly the impact
of architecture on allocating safety requirements, or the relative ease of
system assurance resulting from system or subsystem level architectural
choices. As an exemplar, this paper considers common architectural patterns
used within traditional aviation systems and explores their safety and safety
assurance implications when applied in the context of integrating artificial
intelligence (AI) and machine learning (ML) based functionality. Considering
safety as an architectural property, we discuss both the allocation of safety
requirements and the architectural trade-offs involved early in the design
lifecycle. This approach could be extended to other assured properties, similar
to safety, such as security. We conclude with a discussion of the safety
considerations that emerge in the context of candidate architectural patterns
that have been proposed in the recent literature for enabling autonomy
capabilities by integrating AI and ML. A recommendation is made for the
generation of a property-driven architectural pattern catalogue.
