Supporting users in understanding intelligent everyday systems

Intelligent systems have permeated many areas of daily life like communication, search, decision-making, and navigation, and thus present an important meeting point of people and artificial intelligence in practice. These intelligent everyday systems are in focus of this thesis. Intelligent everyday systems exhibit the characteristics of so-called complex systems as defined in cognitive science: They serve ill-defined user goals, change dynamically over time, and comprise a large number of interrelated variables whose dependencies are not transparent to users. Due to this complexity, intelligent everyday systems can violate established usability guidelines of user interface design like transparency, controllability and easy error correction. This may introduce uncertainty to interaction that users have to overcome in order to reach a goal. I introduce a perspective from cognitive science, where users do so through knowledge. The work presented in this thesis aims at assisting users in gaining this knowledge, or supporting users in understanding intelligent everyday systems, for example, through explanation, control, correction or feedback. To this end, the work included in this thesis makes three main contributions: First, I present a method for eliciting user need for support and informing adequate solutions through practical user problems with intelligent everyday systems in daily interaction. In a first phase, the presented method uses passive data collection to extract user problems with intelligent everyday systems through a combination of automated and manual analyses. In the second phase, these problems are then enriched and validated through active data collection to derive solutions for support. In addition, I report on the application of this method to uncover user problems with four popular commercial intelligent everyday systems (Facebook, Netflix, Google Maps and Google Assistant). Second, I introduce a conceptual framework for categorising and differentiating prevailing notionsin the field of how users should be supported in understanding intelligent systems related to what users seek to know, how they acquire knowledge, and what kind of knowledge they acquire. The presented framework can be used to make these notions explicit and thus introduces an overarching structure that abstracts from the field’s fractured terminological landscape. It aims at helping other researchers become aware of existing approaches and locate and reflect on their own work. Third, I present a number of case studies and arguments as an exploration of how users can be supported in the face of real-world challenges and trade-offs. My research reflects two possible perspectives to approach this question, a normative and a pragmatic one. As part of a critical reflection on the normative perspective, the work shows that explanations without information can similarly foster user trust in a system compared to real explanations, and discusses how user support can be exploited to deceive users. From the pragmatic perspective emerges a stage-based participatory design process that incorporates different stakeholder needs and a study assessing how support can be interwoven with users’ primary tasks. In summary, this thesis adopts a perspective on interaction with intelligent everyday systems, where understanding is a fundamental process towards reaching a user-set goal. On this basis, I introduce a research agenda for future work that incorporates the presented contributions and also includes challenges beyond the scope of this work, such as considering user empowerment. I hope that this agenda, along with the presented method, framework and design exploration, will help future work to shape interaction with intelligent everyday systems in a way that allows people to use them better, and to better ends and outcomes.Intelligente Systeme haben Einzug in viele Bereiche des täglichen Lebens wie Kommunikation, Informationssuche, Entscheidungsfindung, und Navigation erhalten und stellen damit einen wichtigen Berührungspunkt von Menschen und künstlicher Intelligenz in der Praxis dar. Solche intelligenten Alltagssysteme stehen im Fokus dieser Arbeit. Intelligente Alltagssysteme weisen die Charakteristika von sogenannten komplexen Systemen aus der Kognitionsforschung auf: Sie dienen unscharfen Nutzerzielen, verändern sich dynamisch über die Zeit, und beinhalten eine große Anzahl an miteinander verknüpften Variablen, deren Wechselbeziehungen für Nutzer nicht erkennbar sind. Auf Grund dieser Komplexität können intelligente Alltagssysteme bewährte Richtlinien zur Gestaltung von nutzerfreundlichen Benutzeroberflächen verletzen, beispielsweise Transparenz, Kontrollierbarkeit, und einfache Fehlerbehebung. Dies kann bei der Interaktion zu Unsicherheit führen, die Nutzer auf dem Weg zu einem Ziel überwinden müssen. Ich führe eine Perspektive aus der Kognitionsforschung ein, nach welcher Nutzer dies durch Wissen tun. Die hier präsentierten Arbeiten haben zum Ziel, Nutzern beim Erlangen dieses Wissens zu helfen, oder Nutzerverständnis von intelligenten Alltagssystemen zu unterstützen, beispielsweise durch Erklärung, Kontrolle, Korrektur oder Rückmeldung an das System. Hierzu leisten die vorgestellten Arbeiten hauptsächlich drei Beiträge: Ich präsentiere zunächst eine Methode, um das Nutzerbedürnis nach Unterstützung zu ermitteln und entsprechende Lösungen zu informieren. Die Methode identifiziert dazu praktische Nutzerprobleme mit intelligenten Alltagssystemen im täglichen Gebrauch. In einer ersten Phase werden diese Probleme auf Grund von passiver Datenerhebung unter Verwendung automatisierter und manueller Analysemethoden extrahiert. In der zweiten Phase werden die ermittelten Problemedurch aktive Datenerhebung angereichert und validiert, um Lösungen zur Unterstützung abzuleiten. Daneben berichte ich von der Anwendung dieser Methode, um Nutzerprobleme in vier verbreiteten kommerziellen intelligenten Alltagssystemen (Facebook, Netflix, Google Maps und Google Assistant) aufzudecken. Danach führe ich ein konzeptuelles Framework ein, mit dem im Feld vorherrschende Annahmen, wie Nutzerverständnis von intelligenten Alltagssystemen unterstützt werden sollte, klassifiziert und differenziert werden können. Diese Annahmen beziehen sich darauf, welches Wissen Nutzer erlangen wollen, wie sie dieses Wissen erlangen, und um welche Art von Wissen es sich handelt. Durch das Framework können die jeweiligen Annahmen explizit gemacht werden. Es schafft so eine übergreifende Struktur, die von der Fülle und Diversität der im Feld verwendeten Begrifflichkeiten abstrahiert. Das Framework kann anderen Forschern dabei helfen, sich über bestehende Ansätze bewusst zu werden, und ihre eigene Arbeit zu verorten und zu reflektieren. Zum Dritten bringe ich eine Reihe von Fallbeispielen und Argumenten an, die explorieren, wie Nutzer angesichts von Einschränkungen und Abwägungen in der Praxis unterstützt werden können. Meine Forschung spiegelt dabei zwei mögliche Sichtweisen auf diese Frage wider, eine normative und eine pragmatische. Im Zuge einer kritischen Betrachtung der normativen Sichtweise zeigt diese Arbeit, dass Erklärungen ohne Informationsgehalt in ähnlicher Weise Vertrauen in ein System hervorrufen können wie richtige Erklärungen. In diesem Zusammenhang wird weiterhin diskutiert, wie Unterstützung gezielt zur Täuschung von Nutzern missbraucht werden kann. Aus der pragmatischen Sichtweise geht in dieser Arbeit ein stufenförmiger partizipatorischer Designprozess hervor, der die verschiedenen Interessen in der Praxis Beteiligter berücksichtigt. Zudem wird in einer Studie untersucht, wie Unterstützung von Verständnis mit der Primäraufgabe von Nutzern verknüpft werden kann. Zusammenfassend nimmt diese Arbeit eine Perspektive auf Interaktion mit intelligenten Alltagssystemen ein, die Verstehen als grundlegenden Prozess auf dem Weg zu einem Nutzerziel begreift. Basierend darauf stelle ich eine Forschungsagenda vor, die die präsentierten Publikationen einschließt und zudem Herausforderungen über den Rahmen dieser Arbeit hinaus beinhaltet, wie beispielsweise die Einbeziehung von“Nutzer-Empowerment”. Ich hoffe, dass diese Agenda, die vorgestellte Methode, das Framework und die Erkenntnisse aus der Exploration möglicher Designansätze zukünftiger Forschung hilft, Interaktion mit intelligenten Systemen im Alltag zu gestalten – so, dass Nutzer sie besser und zu besseren Zwecken verwenden können

Privacy by Design by Regulation: The Case Study of Ontario

This article presents the findings of a case study examining the role of the regulator in facilitating Privacy by Design (“PbD”) solutions. With the introduction of PbD into the new European Union General Data Protection Regulation, it is important to understand the conditions under which PbD can succeed and the role which regulators can play (if at all) in promoting such success. Two initiatives with similar technology are examined: first, a PbD success, the introduction of facial recognition technology into existing cameras in casinos in Ontario, and second, a PbD failure, the expanded deployment of cameras within the public transit system of Toronto. The findings are organized into three overarching themes: PbD-focused findings, leadership and organizational findings, and regulator-focused findings. The article argues that privacy continues to persist as an engineering problem despite PbD, that (related to that) there is growing recognition of privacy as an issue of organizational change and leadership, and consequently, that the role of the regulator must evolve if PbD is to become a meaningful regulatory tool, an evolution that carries with it both risks and opportunities for privacy.Not peer reviewe

Privacy by design by regulation: The case study of Ontario

This article presents the findings of a case study examining the role of the regulator in facilitating Privacy by Design (“PbD”) solutions. With the introduction of PbD into the new European Union General Data Protection Regulation, it is important to understand the conditions under which PbD can succeed and the role which regulators can play (if at all) in promoting such success. Two initiatives with similar technology are examined: first, a PbD success, the introduction of facial recognition technology into existing cameras in casinos in Ontario, and second, a PbD failure, the expanded deployment of cameras within the public transit system of Toronto. The findings are organized into three overarching themes: PbD-focused findings, leadership and organizational findings, and regulator-focused findings. The article argues that privacy continues to persist as an engineering problem despite PbD, that (related to that) there is growing recognition of privacy as an issue of organizational change and leadership, and consequently, that the role of the regulator must evolve if PbD is to become a meaningful regulatory tool, an evolution that carries with it both risks and opportunities for privacy.Not peer reviewe

Exploring Security, Privacy, and Reliability Strategies to Enable the Adoption of IoT

The Internet of things (IoT) is a technology that will enable machine-to-machine communication and eventually set the stage for self-driving cars, smart cities, and remote care for patients. However, some barriers that organizations face prevent them from the adoption of IoT. The purpose of this qualitative exploratory case study was to explore strategies that organization information technology (IT) leaders use for security, privacy, and reliability to enable the adoption of IoT devices. The study population included organization IT leaders who had knowledge or perceptions of security, privacy, and reliability strategies to adopt IoT at an organization in the eastern region of the United States. The diffusion of innovations theory, developed by Rogers, was used as the conceptual framework for the study. The data collection process included interviews with organization IT leaders (n = 8) and company documents and procedures (n = 15). Coding from the interviews and member checking were triangulated with company documents to produce major themes. Through methodological triangulation, 4 major themes emerged during my analysis: securing IoT devices is critical for IoT adoption, separating private and confidential data from analytical data, focusing on customer satisfaction goes beyond reliability, and using IoT to retrofit products. The findings from this study may benefit organization IT leaders by enhancing their security, privacy, and reliability practices and better protect their organization\u27s data. Improved data security practices may contribute to social change by reducing risk in security and privacy vulnerabilities while also contributing to new knowledge and insights that may lead to new discoveries such as a cure for a disease

What regulators can do to advance privacy through design

The perception that privacy is losing an arms race with technology is a constant source of public anxiety, and regulatory action. Many privacy and data protection laws directly respond to advances in technology-from cameras, to large databases, to the Internet, to cellular, to sensors. The paradigm plays out over and over again: technology erodes privacy, regulations are passed to protect it. Bringing privacy concerns into the design of products and standards is a significant new regulatory approach. It reflects growing recognition of the substantial role that technical systems play in supporting and shaping societal values. Regulators must adopt strategies that encourage designers to engage with multiple, context-dependent concepts of privacy. There are some indications this will happen, but ensuring it does is essential to the success of the privacy by design effort. Third, the success of this regulatory initiative turns on new privacy professionals

What regulators can do to advance privacy through design

The perception that privacy is losing an arms race with technology is a constant source of public anxiety, and regulatory action. Many privacy and data protection laws directly respond to advances in technology-from cameras, to large databases, to the Internet, to cellular, to sensors. The paradigm plays out over and over again: technology erodes privacy, regulations are passed to protect it. Bringing privacy concerns into the design of products and standards is a significant new regulatory approach. It reflects growing recognition of the substantial role that technical systems play in supporting and shaping societal values. Regulators must adopt strategies that encourage designers to engage with multiple, context-dependent concepts of privacy. There are some indications this will happen, but ensuring it does is essential to the success of the privacy by design effort. Third, the success of this regulatory initiative turns on new privacy professionals

What regulators can do to advance privacy through design

The perception that privacy is losing an arms race with technology is a constant source of public anxiety, and regulatory action. Many privacy and data protection laws directly respond to advances in technology-from cameras, to large databases, to the Internet, to cellular, to sensors. The paradigm plays out over and over again: technology erodes privacy, regulations are passed to protect it. Bringing privacy concerns into the design of products and standards is a significant new regulatory approach. It reflects growing recognition of the substantial role that technical systems play in supporting and shaping societal values. Regulators must adopt strategies that encourage designers to engage with multiple, context-dependent concepts of privacy. There are some indications this will happen, but ensuring it does is essential to the success of the privacy by design effort. Third, the success of this regulatory initiative turns on new privacy professionals

From Dataveillance to Data Economy: Firm View on Data Protection

The increasing availability of electronic records and the expanded reliance on online communications and services have made available a huge amount of data about people’s behaviours, characteristics, and preferences. Advancements in data processing technology, known as big data, offer opportunities to increase organisational efficiency and competitiveness. Analytically sophisticated companies excel in their ability to extract value from the analysis of digital data. However, in order to exploit the potential economic benefits produced by big data and analytics, issues of data privacy and information security need to be addressed. In Europe, organisations processing personal data are being required to implement basic data protection principles, which are considered difficult to implement in big data environments. Little is known in the privacy studies literature about how companies manage the trade-off between data usage and data protection. This study contributes to explore the corporate data privacy environment, by focusing on the interrelationship between the data protection legal regime, the application of big data analytics to achieve corporate objectives, and the creation of an organisational privacy culture. It also draws insights from surveillance studies, particularly the idea of dataveillance, to identify potential limitations of the current legal privacy regime. The findings from the analysis of survey data show that big data and data protection support each other, but also that some frictions can emerge around data collection and data fusion. The demand for the integration of different data sources poses challenges to the implementation of data protection principles. However, this study finds no evidence that data protection laws prevent data gathering. Implications relevant for the debate on the reform of European data protection law are also drawn from these findings