Pan: conversational agent for criminal investigations

We present an early prototype conversational agent (CA), called Pan, for retrieving information to support criminal investigations. Our approach tackles the issue of algorithmic transparency, which is critical in unpredictable, high risk, and high consequence domains. We present a novel method to flexibly model CA intentions and provide transparency of attributes that is underpinned with human recognition. We propose that Pan can be used for experimentation to probe analyst requirements and to evaluate the effectiveness of our explanation structure.

© 2020 Copyright held by the owner/author(s). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces Companion, http://dx.doi.org/10.1145/3379336.3381463