Future Everyday Interaction with the Autonomous Internet of Things

该项目旨在研究未来自主物联网（a -IoT）的交互机制和用户界面设计：一个超越当前大多数物联网形式的互联设备系统，将自主或自动化方面作为关键特征。新兴的A-IoT实例包括智能恒温器，它可以根据用户的存在和他们的日常生活来学习自主控制中央供暖系统，以及洗衣机，当洗涤剂用完时，它会订购洗涤剂。换句话说，这种a - iot可以主动响应感知到的环境变化，有效地代表用户做工作，并承诺更有效地利用资源（例如，使用更少的能源用于加热）或增加便利性（例如，始终有洗涤剂可用）。物联网产生的数据财富（或“洪水”）可能会继续增长，超出人类的能力，无法将其转化为可以采取行动的有意义的信息。因此，未来的交互系统需要越来越多地支持将大型复杂数据的细粒度决策授权给自主计算代理，允许用户根据他们的一般需求和舒适度做出明智的选择。自主物联网；数据和决策将在一定程度上由设备及其软件“主动”管理，利用机器学习技术和优化算法。然而，最近关于商业智能恒温器在现实世界中的接受度的研究强调了错误、系统操作的有限易读性以及用户过高的期望是如何引起挫败感的，并导致一些用户放弃了这项技术。我们自己之前的工作表明，由于缺乏对自主技术的所有权、意图和允许活动的问责制，人们不信任潜在的智能能源基础设施。这些结果表明，A-IoT系统的设计需要解决几个挑战才能负责任；包括，在系统方面，设计自主决策，以考虑到偶然人类行为的不确定性；在用户方面，需要使这些系统在日常生活中易于阅读和使用。事实上，在让系统的操作清晰可辨与不让人工智能算法的技术复杂性压倒用户之间，存在着一种内在的紧张关系。迄今为止，设计此类系统的方法相当稀少，并且不是特定于a - iot系统（跨越HCI， AI和Ubicomp），因此需要更集中的方法来确定a - iot系统实现的核心设计原则和方法。因此，我们的目标是在家庭日常环境中建立用户与a - iot系统交互的科学基础，旨在阐明以下研究问题：在日常环境中，用户愿意在多大程度上委托代理a - iot系统？如何设计与A-IoT系统的交互，以支持而不是阻碍用户的日常活动？智能代理管理此类A-IoT系统所必需的功能是什么？我们怎样才能设计这样的系统，让用户既能下放控制权，又能很容易地重新获得控制权？除非这些问题得到充分解决，否则A-IOT系统可能会让用户感到沮丧，从而导致时间和资源的大量浪费。因此，我们将通过技术组合来解决这些挑战，包括对现有实践的研究，新型a - iot原型的迭代开发及其野外评估。这种多学科的方法是由一个团队实现的，该团队汇集了人机交互、人工智能和设计人种学方面的国际领先研究人员。

This project seeks to investigate the design of interaction mechanisms and user interfaces for a future Autonomous Internet of Things (A-IoT): a system of interconnected devices that reaches beyond most current incarnations of the IoT to include aspects of autonomy or automation as a key feature. Nascent instantiations of the A-IoT range from smart thermostats that learn to autonomously control central heating systems based on the presence of users and their routine, to washing machines that order detergent for delivery when it runs out. In other words, this A-IoT can proactively respond to sensed environmental changes, effectively doing work on behalf of users, with the promise of a more efficient use of resources (e.g. to use less energy for heating) or increased convenience (e.g. to always have detergent available). The wealth (or "deluge") of data produced by the IoT is likely to keep growing beyond human capacity to turn it into meaningful information that can be acted on. Therefore, it will require future interactive systems to increasingly support the delegation of granular decision making over large and complex data to autonomous computational agents, allowing users to make informed choices about their general needs and comfort. In an Autonomous IoT; data and decisions will be, in part, 'actively' managed by the devices and their software, drawing upon machine learning techniques and optimization algorithms.However, recent studies examining the real-world acceptance of a commercial smart thermostat highlighted how errors, limited legibility of the system operation, and excessive user expectations caused frustration and led to some users abandoning the technology. Our own prior work revealed people distrust a potential smart energy infrastructure due to lack of accountability of the ownership, intent, and permitted activities of the autonomous technology. These results suggest that the design of A-IoT systems needs to address several challenges to be made accountable; including, on the system side, designing autonomous decision-making to take into account the uncertain nature of contingent human behaviour; and on the user side, the need to make these systems legible and usable in everyday life. Indeed there is an inherent tension between making a system's operation legible and not overwhelming users with the technical complexity of artificial intelligence algorithms. To date, the methodologies to design such systems are rather sparse and not specific to A-IoT systems (spanning HCI, AI, and Ubicomp) and hence a more focused approach is required to determine the core design principles and methods for the implementation of A-IoT systems.Our goal is thus to establish the scientific underpinnings of user interactions with A-IoT systems, in a domestic everyday context, with the aim of elucidate the following research questions: to what extent may users be willing to delegate agency to A-IoT systems in everyday contexts? How should interactions with A-IoT systems be engineered to support rather than hinder users' daily activities? What capabilities are essential for intelligent agents to manage such A-IoT systems? How can we design such systems so that they allow users to delegate control, yet easily regain it? Unless such questions are fully addressed, A-IOT systems are likely to frustrate users, resulting in significant waste of time and resources.Hence, we will address these challenges through a combination of techniques, including the study of existing practices, the iterative development of novel A-IoT prototypes and their evaluation in-the-wild. Such a multidisciplinary approach is made possible by a team that brings together internationally-leading researchers in human-computer interaction, artificial intelligence and design ethnography.