  In order to develop trustworthy healthcare artificial intelligence (AI)
prospective and ergonomics studies that consider the complexity and reality of
real-world applications of AI systems are needed. To achieve this, technology
developers and deploying organisations need to form collaborative partnerships.
This entails access to healthcare data, which frequently might also include
potentially identifiable data such as audio recordings of calls made to an
ambulance service call centre. Information Governance (IG) processes have been
put in place to govern the use of personal confidential data. However,
navigating IG processes in the formative stages of AI development and
pre-deployment can be challenging, because the legal basis for data sharing is
explicit only for the purpose of delivering patient care, i.e., once a system
is put into service. In this paper we describe our experiences of managing IG
for the assurance of healthcare AI, using the example of an
out-of-hospital-cardiac-arrest recognition software within the context of the
Welsh Ambulance Service. We frame IG as a socio-technical process. IG processes
for the development of trustworthy healthcare AI rely on information governance
work, which entails dialogue, negotiation, and trade-offs around the legal
basis for data sharing, data requirements and data control. Information
governance work should start early in the design life cycle and will likely
continue throughout. This includes a focus on establishing and building
relationships, as well as a focus on organisational readiness deeper
understanding of both AI technologies as well as their safety assurance
requirements.
