Biblio

Conversational agents (CAs), often referred to as chatbots, are being widely deployed within existing commercial frameworks and online service websites. As society moves further into incorporating data rich systems, like the internet of things (IoT), into daily life, it is expected that conversational agents will take on an increasingly important role to help users manage these complex systems. In this, the concept of personality is becoming increasingly important, as we seek for more human-friendly ways to interact with these CAs. In this work a conceptual framework is proposed that considers how existing standard psychological and persona models could be mapped to different kinds of CA functionality outside of strictly dialogue. As CAs become more diverse in their abilities, and more integrated with different kinds of systems, it is important to consider how function can be impacted by the design of agent personality, whether intentionally designed or not. Based on this framework, derived archetype classes of CAs are presented as starting points that can hopefully aid designers, developers, and the curious, into thinking about how to work toward better CA personality development.

The internet-of-things (IoT) consists of embedded devices and their networks of communication as they form decentralized frameworks of ubiquitous computing services. Within such decentralized systems the potential for malicious actors to impact the system is significant, with far-reaching consequences. Hence this work addresses the challenge of providing IoT systems engineers with a framework to elicit privacy and security design considerations, specifically for indoor adaptive smart environments. It introduces a new ambient intelligence indoor adaptive environment framework (CORE) which leverages multiple forms of data, and aims to elicit the privacy and security needs of this representative system. This contributes both a new adaptive IoT framework, but also an approach to systematically derive privacy and security design requirements via a combined and modified OCTAVE-Allegro and Privacy-by-Design methodology. This process also informs the future developments and evaluations of the CORE system, toward engineering more secure and private IoT systems.