Year
2023
File Attachment
finalpaper_134_0502122959.pdf600.47 KB
Abstract
: The research community is exploring multiple potential applications of artificial intelligence
and its enabling technologies for international nuclear safeguards monitoring and verification. Based on
successful implementation in other domains or early safeguards development, some applications hold
significant promise. However, those benefits can only be realized if users place appropriate levels of
trust – that is, reliance in the system – when delegating tasking or accepting recommendations. Prior
work by members of this team has examined user trust in visual-based systems focused on model
performance, but voice user interfaces such as those in digital assistants pose unique opportunities.
While some safeguards challenges for voice user interfaces – noise in the operational environment, nonnative English speakers, etc. – have been addressed in other domains, there remain aspects of voice
user interfaces that are unique for trust in safeguards applications. In this work, we use human
performance testing to evaluate the factors that impact trust in voice user interfaces within the
safeguards context. Our aim is to provide actionable recommendations to the software development
community to optimize system performance of voice user interfaces for safeguards. In this paper, we
describe our task analysis and safeguards trust factors. We detail our experimental prioritization,
focusing on two safeguards tasks: seal checking and nuclear material measurement. We describe early
results and our experimental plans moving forward.