A Platform for Responsive Conversational Agents to Enhance Engagement and Disclosure (PRoCEED)

随着用户越来越期待快速、可靠和准确的信息，个人与技术互动的方式正在迅速发展。为了提供能够满足这些期望的系统，企业和政府部门都转向会话代理（或聊天机器人）。这些会话代理能够与用户交互和参与，回答用户的查询，甚至根据需要提供建议和指导。本研究考虑了如何优化该技术以提供更有效的通信方法，同时也关注用户与会话代理之间的隐含信任。作为本研究的一部分，我们将调查敏感信息的性质以及信息的上下文如何在其感知敏感性中发挥作用。这将通过一系列实验来实现，以更好地了解公众对个人信息的看法，以及这些看法与信息分类的关系。为了充分理解会话代理的使用，必须正确理解个人敏感信息的性质及其感知的可信度。我们将研究对话代理的人性、个性和外表的不同方面如何影响个体对该代理的感知和信任。我们将重点讨论在三个关键领域使用会话代理：医疗保健、国防和安全以及技术。之所以选择这三个领域，是因为它们都是会话代理的重要用户，都处理潜在的敏感信息和个人信息，同时也是重要的公共支出领域。我们的研究将了解如何优化人与计算机之间的这些交互，以提供定制的会话代理，以满足个人的期望和需求。这反过来又会增加对这些数字服务的信任和信心。

The way in which individuals interact with technology is rapidly evolving, as users increasingly expect fast, reliable and accurate information. In order to deliver systems capable of meeting these expectation both businesses and government departments alike are turning to conversational agents (or chatbots). These conversational agents are capable of interacting and engaging with users, answering user queries and even providing advice and guidance as required. This research considers how this technology can be optimised to provide a more effective method of communication, while also focusing on the implicit trust that a user has with a conversational agent. As part of this research we will investigate the nature of sensitive information and how the context of the information can play a role in its perceived sensitivity. This will be achieved using a range of experiments to better understand the public's perceptions of personal information, and how those perceptions relate to the classification of the information. In order to fully understand the use of conversational agents it is essential to properly understand the nature of personal, sensitive information and also their perceived trustworthiness. We will examine how different facets of a conversational agent's humanity, personality and appearance can be used to affect an individual's perceptions and trust in that agent. We will focus on the use of conversational agents across three key sectors: healthcare, defence and security and technology. These three areas have been selected as they are significant users of conversational agents and all deal with potentially sensitive and personal information, as well as being areas of significant public spending. Our research will understand how these interactions between humans and computers can be optimised to deliver a bespoke conversational agent tailored to meet the expectations and needs of the individual. This in turn will increase the trust and confidence in these digital services.