Building privacy, trust and security into the evolving digital ecosystem is broadly recognized as a key societal challenge. Regulatory activities in the US, Europe and Japan are complemented by industry initiatives that seek to rebalance "the crisis in trust" occasioned by widespread personal data harvesting. All parties agree that key to this challenge are increased accountability and control. Accountability not only seeks to strengthen compliance but also make the emerging ecosystem more transparent to consumers, while control seeks to empower consumers and provide them with the means of actively exercising choice. This proposal will develop the underlying technology infrastructure required to deliver both accountability and control. Although personal data management is generally considered an intensely personal matter, it is also inherently social: it is impractical to withdraw from all online activity simply to protect one's privacy. The success of the modern Internet and the "free" services it supports largely rests on the ability for advertisers and analytics providers to make money with the result that approaches that remove or diminish advertising revenues have been doomed to failure. The many motivations and uses for systems enabling personal management of personal data point to a need for tools enabling individuals to take more explicit control over the collection and usage of their data and the information inferred from their online activities, while addressing the challenges of HDI. Working with partner organisations we have refined our vision of just such a tool, a Databox, an on-demand personal data aggregation and query point, control over which rests directly with the user. The Databox vision is of an open-source personal networked device augmented by cloud-hosted services that collates, curates, and mediates access to our personal data. The Databox will enable and, in some cases, may even host third party applications and services that process personal data. The Databox will form the heart of an individual's personal data processing ecosystem, providing a platform for managing secure access to these data and enabling authorised third parties to provide the owner with authenticated services while roaming outside the home environment.

Many decisions in today's world are made through a complex, dynamic process of interaction and communication between people and teams with different interests and priorities - so called "distributed decision-making" (DDM). For example, many businesses work across multiple geographically dispersed offices and timezones, with teams specialising in quite diverse areas. Each team may have its own goals and reward models, which do not necessarily coincide, and may be spread across multiple organisational units (e.g. different businesses or governments). Communication may happen via several different modalities with very different timescales and properties (e.g. email, instant messenger, and face-to-face meetings). Unfortunately, although many organisations have started to document these processes and even make records available (particularly governmental organisations e.g. https://data.gov.uk/), we have no way to automatically analyse these records. If we did, we could produce tools to automatically summarise decisions, trace who made them, and why and how they were made (and why other decisions weren't made). From a societal standpoint this would help make these processes more accountable and transparent. We'd also be able to identify collaborative failures, biases and other problems, and thus help improve decision-making in future. This project will develop these urgently required methods, using a combination of natural language processing and social network analysis. We will collate, annotate and publicly release the first multimodal dataset of real-world distributed decision-making. We will devise techniques to take natural language and semi-structured data to recognise the dialogue and interaction structures in decision making, and analyse those structures to produce summaries and evaluate the efficacy of the decision making process. We will then use the outputs to inform strategic interventions that can streamline and improve decision making. Our methods will be suitably generic to span several domains. However, the project will focus on one particular global organisation as its main use case: the Internet Engineering Task Force (IETF). This is an international forum responsible for producing Internet protocol standards - formal documents which specify the languages by which software and hardware "speak" across the Internet. To produce these documents, extensive international collaboration is performed - this spans several modalities including email discussions, collaborative document editing, face-to-face meetings and teleconferencing. Importantly, all of these modalities are documented via transparency reports ranging from public email archives to minutes from meetings. This project has partnered with the IETF to help model and streamline their decision making process. We will borrow from their experience, and employ our methods to extract decision making bottlenecks. We will devise tooling which will provide advice and proposed interventions to relevant parties within the IETF. Amongst many other things, we directly benefit the IETF, and the global Internet standards community, by helping them to uncover biases and help make important decision processes accountable.

Building privacy, trust and security into the evolving digital ecosystem is broadly recognized as a key societal challenge. Regulatory activities in the US, Europe and Japan are complemented by industry initiatives that seek to rebalance "the crisis in trust" occasioned by widespread personal data harvesting. All parties agree that key to this challenge are increased accountability and control. Accountability not only seeks to strengthen compliance but also make the emerging ecosystem more transparent to consumers, while control seeks to empower consumers and provide them with the means of actively exercising choice. This proposal will develop the underlying technology infrastructure required to deliver both accountability and control. Although personal data management is generally considered an intensely personal matter, it is also inherently social: it is impractical to withdraw from all online activity simply to protect one's privacy. The success of the modern Internet and the "free" services it supports largely rests on the ability for advertisers and analytics providers to make money with the result that approaches that remove or diminish advertising revenues have been doomed to failure. The many motivations and uses for systems enabling personal management of personal data point to a need for tools enabling individuals to take more explicit control over the collection and usage of their data and the information inferred from their online activities, while addressing the challenges of HDI. Working with partner organisations we have refined our vision of just such a tool, a Databox, an on-demand personal data aggregation and query point, control over which rests directly with the user. The Databox vision is of an open-source personal networked device augmented by cloud-hosted services that collates, curates, and mediates access to our personal data. The Databox will enable and, in some cases, may even host third party applications and services that process personal data. The Databox will form the heart of an individual's personal data processing ecosystem, providing a platform for managing secure access to these data and enabling authorised third parties to provide the owner with authenticated services while roaming outside the home environment.

The IoT represents a convergence of ubiquitous computing and communication technologies, with emerging uses that actuate in the real world. No longer do ubiquitous computing systems simply sense and respond digitally, now they physically interact with the world, ultimately becoming embodied and autonomous. At the same time, the game is changing from one of privacy, where it is often (contestably) cited that "users don't care", to one of user safety, where users (along with regulators, governments, and other stakeholders) certainly do care. Likewise, industry needs to become aware that this shift also changes the legal basis under which companies need to operate, from one of disparate and often weakly enforced privacy laws, to one of product liability. The current widely adopted approach in which cloud services underpin IoT devices has already raised major privacy issues. Importantly in an actuated future, untrammelled communications implicating a plethora of heterogeneous online services in their normal operation also brings with it resilience challenges. We must ensure the integrity of actuating systems, which will require greater local autonomy alongside increased situated accountability to users. This problem applies in many areas: industrial control, autonomous vehicles, and smart cities and buildings, including the intimate and shared context of the home. This research seeks to address the challenge in the context of the home, where the network infrastructure protection is minimal, providing little or no isolation between attached devices and the traffic they carry. Scant attention has been paid by the research community to home network security, and its acceptability and usability, from the viewpoint of ordinary citizens. This research is also deeply rooted in pragmatism and recognises the 'real world, real time' conditions that attach to the IoT: - that the cyber security solutions currently being defined for IoT systems will not deal with legacy issues and will never achieve 100% adoption; - that extant businesses limit the period of time for which they will provide software and security updates (if they even remain in business); - that cyber security is an arms race and threats will continue to emerge in future; - and that the public will never become network security experts.

The Horizon institute is a multidisciplinary centre of excellence for Digital Economy (DE) research. The core mission of Horizon has been to balance the opportunities arising from the capture, analysis and use of personal data with an awareness and understanding of human and social values. The focus on personal data in a wide range of contexts has required the development of a broad set of multidisciplinary competencies allowing us to build links from foundational algorithms and system to issues of society and policy. We follow a user-centred approach, undertaking research in the wild based on principles of open innovation. Horizon now encompasses over 50 researchers, spanning Computing, Engineering, Law, Psychology, Social Sciences, Business and the Humanities. It has grown a diverse network of over 200 external partners who are involved in ongoing collaborative research and impact with Horizon, ranging from major international corporations to SMEs, from a wide variety of sectors, alongside government and civil society groups. We have also established a CDT in the third wave of funding that will eventually deliver 150 PhDs. Our critical mass of researchers, partners, students and funding has already led to over 800 peer-reviewed publications, composed of: 277 journal articles, 51 books and book chapters, and 424 conference papers, in a total of 15 different disciplines. Over the years Horizon's focus has evolved from an emphasis on the collection and understanding of personal data to consider the user-centred design and development of data-driven products. This proposal builds on our established interdisciplinary competencies to deliver research and impact to ensure that future data-driven products can be both co-created and trusted by consumers. Core to our current vision is the idea that future products will be hybrids of both the digital and the physical. Physical products are increasingly augmented with digital capabilities, from data footprints that capture their provenance to software that enables them to adapt their behaviour. Conversely, digital products are ultimately physically experienced by people in some real-world context and increasingly adapt to both. This real-world context is social; hence the data is social and often implicates groups, not just individuals. We foresee that this blending of physical and digital will drive the merging of traditional goods, services and experiences into new forms of product. We also foresee that - just as today's social media services are co-created by consumers who provide content and data - so will be these new data-driven products. At the same time, we are also witnessing a crisis of trust concerning the commercial use of personal data that threatens to undermine this vision of data-driven products. Hence, it is vitally important to build trust with consumers and operate within an increasingly complex regulatory environment from the earliest stages of innovating future products. Our user-centred approach involves external partners and the public in "research-in-the-wild", grounding our fundamental research in real world challenges. Our delivery programme combines a bottom-up approach in which researchers are given the opportunity (and provided with the skills) to follow new impact opportunities in collaboration with partners as they arise (our Agile programme), with a top-down approach that strategically coordinates how these activities are targeted at wider communities (our Campaigns programme, with successive focus on Consumables, Co-production and Welfare), and reflective processes that allow us to draw out broader conclusions for the widest possible impact (our Cross-Cutting programme). Throughout we aim to continue to develop the capacity in our researchers, the wider DE research community and more broadly within society, to engage in responsible innovation using personal data within the Digital Economy.