  Structured access is an emerging paradigm for the safe deployment of
artificial intelligence (AI). Instead of openly disseminating AI systems,
developers facilitate controlled, arm's length interactions with their AI
systems. The aim is to prevent dangerous AI capabilities from being widely
accessible, whilst preserving access to AI capabilities that can be used
safely. The developer must both restrict how the AI system can be used, and
prevent the user from circumventing these restrictions through modification or
reverse engineering of the AI system. Structured access is most effective when
implemented through cloud-based AI services, rather than disseminating AI
software that runs locally on users' hardware. Cloud-based interfaces provide
the AI developer greater scope for controlling how the AI system is used, and
for protecting against unauthorized modifications to the system's design. This
chapter expands the discussion of "publication norms" in the AI community,
which to date has focused on the question of how the informational content of
AI research projects should be disseminated (e.g., code and models). Although
this is an important question, there are limits to what can be achieved through
the control of information flows. Structured access views AI software not only
as information that can be shared but also as a tool with which users can have
arm's length interactions. There are early examples of structured access being
practiced by AI developers, but there is much room for further development,
both in the functionality of cloud-based interfaces and in the wider
institutional framework.
