Smart speakers are heralded to make everyday life more convenient in households around the world. These voice-activated devices have become part of intimate domestic contexts in which users interact with platforms.This chapter presents a dualstudy investigating the privacy perceptions of smart speaker users and non-users. Data collected in in-depth interviews and focus groups with Dutch users and non-users show that they make sense of privacy risks through imagined sociotechnical affordances. Imagined affordances emerge with the interplay between user expectations, technologies, and designer intentions. Affordances like controllability, assistance, conversation, linkability, recordability, and locatability are associated with privacy considerations. Viewing this observation in the light of privacy calculus theory, we provide insights into how users’ positive experiences of the control over and assistance in the home offered by smart speakers outweighs privacy concerns. On the contrary, non-users reject the devices because of fears that recordability and locatability would breach the privacy of their homes by tapping data to platform companies. Our findings emphasize the dynamic nature of privacy calculus considerations and how these interact with imagined affordances; establishing a contrast between rational and emotional responses relating to smart speaker use.Emotions play a pivotal role in adoption considerations whereby respondents balance fears of unknown malicious actors against trust in platform companies.This study paves the way for further research that examines how surveillance in the home is becoming increasingly normalized by smart technologies.
This matrix is generic. It is a tool for data stewards or other research supporters to assist researchers in taking appropriate measures for the safe use and protection of data about people in scientific research. It is a template that you can adjust to the context of your own institution, faculty and / or department by taking into consideration your setting’s own policies, guidelines, infrastructure and technical solutions. In this way you can more effectively determine the appropriate technical and organizational measures to protect the data based on the context of the research and the risks associated with the data.
Firms increasingly use social network sites to reach out to customers and proactively intervene with observed consumer messages. Despite intentions to enhance customer satisfaction by extending customer service, sometimes these interventions are received negatively by consumers. We draw on privacy regulation theory to theorize how proactive customer service interventions with consumer messages on social network sites may evoke feelings of privacy infringement. Subsequently we use privacy calculus theory to propose how these perceptions of privacy infringement, together with the perceived usefulness of the intervention, in turn drive customer satisfaction. In two experiments, we find that feelings of privacy infringement associated with proactive interventions may explain why only reactive interventions enhance customer satisfaction. Moreover, we find that customer satisfaction can be modeled through the calculus of the perceived usefulness and feelings of privacy infringement associated with an intervention. These findings contribute to a better understanding of the impact of privacy concerns on consumer behavior in the context of firm–consumer interactions on social network sites, extend the applicability of privacy calculus theory, and contribute to complaint and compliment management literature. To practitioners, our findings demonstrate that feelings of privacy are an element to consider when handling consumer messages on social media, but also that privacy concerns may be overcome if an intervention is perceived as useful enough.
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This project researches risk perceptions about data, technology, and digital transformation in society and how to build trust between organisations and users to ensure sustainable data ecologies. The aim is to understand the user role in a tech-driven environment and her perception of the resulting relationships with organisations that offer data-driven services/products. The discourse on digital transformation is productive but does not truly address the user’s attitudes and awareness (Kitchin 2014). Companies are not aware enough of the potential accidents and resulting loss of trust that undermine data ecologies and, consequently, forfeit their beneficial potential. Facebook’s Cambridge Analytica-situation, for instance, led to 42% of US adults deleting their accounts and the company losing billions. Social, political, and economic interactions are increasingly digitalised, which comes with hands-on benefits but also challenges privacy, individual well-being and a fair society. User awareness of organisational practices is of heightened importance, as vulnerabilities for users equal vulnerabilities for data ecologies. Without transparency and a new “social contract” for a digital society, problems are inevitable. Recurring scandals about data leaks and biased algorithms are just two examples that illustrate the urgency of this research. Properly informing users about an organisation’s data policies makes a crucial difference (Accenture 2018) and for them to develop sustainable business models, organisations need to understand what users expect and how to communicate with them. This research project tackles this issue head-on. First, a deeper understanding of users’ risk perception is needed to formulate concrete policy recommendations aiming to educate and build trust. Second, insights about users’ perceptions will inform guidelines. Through empirical research on framing in the data discourse, user types, and trends in organisational practice, the project develops concrete advice - for users and practitioners alike - on building sustainable relationships in a resilient digital society.
The goal of UPIN is to develop and evaluate a scalable distributed system that enables users to cryptographically verify and easily control the paths through which their data travels through an inter-domain network like the Internet, both in terms of router-to-router hops as well as in terms of router attributes (e.g., their location, operator, security level, and manufacturer). UPIN will thus provide the solution to a very relevant and current problem, namely that it is becoming increasingly opaque for users on the Internet who processes their data (e.g., in terms of service providers their data passes through as well as what jurisdictions apply) and that they have no control over how it is being routed. This is a risk for people’s privacy (e.g., a malicious network compromising a user’s data) as well as for their safety (e.g., an untrusted network disrupting a remote surgery). Motivating examples in which (sensitive) user data typically travels across the Internet without user awareness or control are: - Internet of Things for consumers: sensors such as sleep trackers and light switches that collect information about a user’s physical environment and send it across the Internet to remote services for analysis. - Medical records: health care providers requiring medical information (e.g., health records of patients or remote surgery telemetry) to travel between medical institutions according to specified agreements. - Intelligent transport systems: communication plays a crucial role in future autonomous transportation systems, for instance to avoid freight drones colliding or to ensure smooth passing of trucks through busy urban areas. The UPIN project is novel in three ways: 1. UPIN gives users the ability to control and verify the path that their data takes through the network all the way to the destination endpoint, both in terms of hops and attributes of routers traversed. UPIN accomplishes this by adding and improving remote attestation techniques for on-path routers to existing path verification mechanisms, and by adopting and further developing in-packet path selection directives for control. 2. We develop and simulate data and control plane protocols and router extensions to include the UPIN system in inter-domain networking systems such as IP (e.g., using BGP and segment routing) and emerging systems such as SCION and RINA. 3. We evaluate the scalability and performance of the UPIN system using a multi-site testbed of open programmable P4 routers, which is necessary because UPIN requires novel packet processing functions in the data plane. We validate the system using the earlier motivating examples as use cases. The impact we target is: - Increased trust from users (individuals and organizations) in network services because they are able to verify how their data travels through the network to the destination endpoint and because the UPIN APIs enable novel applications that use these network functions. - More empowered users because they are able to control how their data travels through inter-domain networks, which increases self-determination, both at the level of individual users as well as at the societal level.
