This paper presents LLooM, a probe designed to capture situated, temporal, and contradictory experiences with language technologies such as voice assistants, chatbots, and LLMs. The design of LLooM draws on work in probes, feminist HCI, and storytelling to invite participants to write stories about their encounters with language technologies on fabric strips and weave them into looms. Through a public, researcher-facilitated, and collective participant deployment with 56 participants, LLooM enabled participants to share diverse perspectives on language technologies. This methodological approach makes two contributions to probe design in HCI: enabling participants to reshape the methodological assumptions underlying research and allowing participants' visible contributions to become provocations that support collaborative meaning-making across diverse experiences.

AI-driven educational technologies (AI-EdTech) process extensive data, raising concerns about commercial exploitation of children's data and risks to their privacy, wellbeing, agency, and legal rights. The ‘fairness principle’ in data protection law requires fair data processing that meets children's expectations and avoids unexpected, detrimental, discriminatory, or misleading practices. However, children's own perspectives on what fairness means in AI-EdTech are underexplored in design. This study bridges the gap between law and design research to contextualize what fairness means through co-design workshops with 72 children (aged 10–12) and 4 teachers (N=76) in Scotland and Türkiye. We examine how children's perspectives can inform the operationalization of ‘fairness by design’ for AI-EdTech. Our contributions include: (1) an understanding of children's perspectives on how fairness manifests (or does not) in AI-EdTech and (2) recommendations for both design and legal communities to align AI-EdTech design and data practices with children's values and rights.

The way in which consumers engage with, utilise, or discard the technologies in their lives is constantly being reassessed and changed. This paper questions what role the emergent “right to repair” could play in resolving issues posed by the increasing ubiquity of the Internet of Things (IoT). The right gives consumers the ability and freedom to fix their devices, or to fair access to appropriate services that can carry out repair on their behalf. In this paper, firstly we establish the problem space surrounding consumer IoT – i.e., devices that are interconnected via the internet, enabling them to send and receive data. We reflect on hardware, software, and data components that pose legal and policy challenges for data protection, security, and sustainability. Through a literature review we then reflect on the current socio-legal developments that support or oppose changes in the consumer IoT market in regards to repair. We then highlight gaps in the existing literature that should inform future research trajectories in this area. This includes exploring disparities between environmental and consumer autonomy approaches, assessing consistency in regulatory developments, and market prioritisation. Finally, the paper concludes with a series of key insights and recommendations from our analysis including: recognition of the growing e-Waste problem and the inequalities it exacerbates and perpetuates; the need for identification and argumentation for different formulations of “repair” and how these may impact the implementation of a right going forward; the need for identification of the reasoning behind disparities in governmental approaches to the right to repair; and the need to practically translate better IoT design practices into reality.

Stunning advances in machine learning are heralding a new era in sensing, interpreting, simulating and stimulating human emotion. In the human sciences, research is increasingly highlighting the explanatory power of emotions, feelings, and other affective processes to predict how we think and behave. This is beginning to translate into an explosion of applications that can improve human wellbeing including methods to reduce stress and improve emotion regulation skills, techniques to support healthier social media use, pain monitoring in neonates, and decision-support tools that recognize emotional bias.

We present the design of the Memory Machine (MeMa), a technology probe that can store, contextualise, and document media to represent memories. We accumulate vast physical and digital possessions throughout our lives, making it difficult to distinguish value in amassed images, albums, videos, mementos, and music. One option we wanted to explore via MeMa was to frame personal memories as a gift, in turn providing a way to revisit, share, and collate personal archives. We deployed MeMa into participants’ homes and tasked them to create a digital gift involving an autobiographical memory. Through qualitative methods we uncovered the experience of twelve gift-givers. We found that the framing as a gift brought meaning to a collection of media, promoting reflection and emotional reminiscence in participants. Our contributions include design implications involving the relationship between emotions, technology, and gifting.

Sensor networks are increasingly commonplace in visions of smart cities and future healthcare systems, promising greater efficiency and increased wellbeing. However, the design of these technologies remains focused on specific users and fragmented by context, overlooking the diversity of needs, wants and values present when technologies, people, and lived realities interact within instrumented spaces. In this paper we present a workshop method – Sensing Care – that can help researchers, interdisciplinary design and development teams, and potentially affected users, to explore what it takes to design for living with sensor technologies that intersect and interact across private and public spaces, through speculative scenarios and role play. Drawing from three deployments of the workshop, we discuss how this approach supports the design of future care-oriented sensor networks, and helps designers understand what it means to live with complex technologies as people traverse diverse contexts.

Autonomous vehicles, one of the signature technologies of the rapid development of artificial intelligence, have brought about a rapid change in the relevant legal norms and legal mandates. This change makes it more challenging for manufacturers and designers of autonomous vehicles to ensure the legal compliance of their product designs in a more dynamic way. Therefore, rather than approaching the issue from the perspective of judges or the cars themselves, we propose a legal reasoning system applicable to the adjustment of autonomous vehicle design options from the designer’s perspective, building on a series of previous studies. Focusing on the circulation of autonomous vehicles between different countries, the system attempts to help designers accomplish the adjustment of design solutions between different legal systems instead of designing new prototypes.

As AI products continue to evolve, increasingly legal problems are emerging for the engineers that design them. Current laws are often ambiguous, inconsistent or undefined when it comes to technologies that make use of AI. Engineers would benefit from decision support tools that provide engineer’s with legal advice and guidance on their design decisions. This research aims at exploring a new representation of legal ontology by importing argumentation theory and constructing a trustworthy legal decision system. While the ideas are generally applicable to AI products, our initial focus has been on Autonomous Vehicles (AVs).

This paper analyses the assumptions underpinning a range of emerging EU and UK smart home cybersecurity standards. We use internet of things (IoT) case studies (such as the Mirai Botnet affair) and the criminological concept of ‘routine activity theory’ to situate our critique. Our study shows that current cybersecurity standards mainly assume smart home environments are (and will continue to be) underpinned by cloud architectures. This is a shortcoming in the longevity of standards. This paper argues that edge computing approaches, such as personal information management systems , are emerging for the IoT and challenge the cloud focused assumptions of these standards. In edge computing, data can be stored in a decentralised manner, locally and analysed on the client using federated learning . This can have advantages for security, privacy and legal compliance, over centralised cloud-based approaches, particularly around cross border data flows and edge based security analytics . As a consequence, standards should start to reflect the increased interest in this trend to make them more aspirational and responsive for the long term; as ultimately, current IoT architectures are a choice, as opposed to inherent. Our paper unpacks the importance of the adoption of edge computing models which could enable better management of external cyber-criminality threats in smart homes. We also briefly discuss challenges of building smart homes that can accommodate the complex nature of everyday life in the home. In addition to technical aspects, the social and interactional complexities of the home mean internal threats can also emerge. As these human factors remain unresolved in current approaches to smart home cybersecurity, a user's security can be impacted by such technical design choices.

We explore how usage data captured from ideation cards can enable reflection on design. We deployed a deck of ideation cards on a Masters level module over two years, developing the means to capture the students' designs into a digital repository. We created two visualisations to reveal the relative co-occurrences of the cards as concept space and the relative proximity of designs (through cards used in common) as design space. We used these to elicit reflections from the perspectives of students, teachers and card designers. Our findings inspire ideas for extending the data-driven use of ideation cards throughout the design process; informing the redesign of cards, the rules for using them and their live connection to supporting materials and enabling stakeholders to reflect and recognise challenges and opportunities. We also identified the need, and potential ways, to capture a richer design rationale, including annotations, discarded cards and varying card interpretations.

Through sensors carried by people and sensors embedded in the environment, personal data is being processed to try to understand activity patterns and people's internal states in the context of human-building interaction. This data is used to actuate adaptive buildings to make them more comfortable, convenient, and accessible or information rich. In a series of envisioning workshops, we queried the future relationships between people, personal data and the built environment, when there are no technical limits to the availability of personal data to buildings. Our analysis of created designs and user experience fictions allows us to contribute a systematic exposition of the emerging design space for adaptive architecture that draws on personal data. This is being situated within the context of the new European information privacy legislation, the EU General Data Protection Regulation 2016. Drawing on the tension space analysis method, we conclude with the illustration of the tensions in the temporal, spatial, and inhabitation-related relationships of personal data and adaptive buildings, re-usable for the navigation of the emerging, complex issues by future designers.

Security incidents such as targeted distributed denial of service (DDoS) attacks on power grids and hacking of factory industrial control systems (ICS) are on the increase. This paper unpacks where emerging security risks lie for the industrial internet of things, drawing on both technical and regulatory perspectives. Legal changes are being ushered by the European Union (EU) Network and Information Security (NIS) Directive 2016 and the General Data Protection Regulation 2016 (GDPR) (both to be enforced from May 2018). We use the case study of the emergent smart energy supply chain to frame, scope out and consolidate the breadth of security concerns at play, and the regulatory responses. We argue the industrial IoT brings four security concerns to the fore, namely: appreciating the shift from offline to online infrastructure; managing temporal dimensions of security; addressing the implementation gap for best practice; and engaging with infrastructural complexity. Our goal is to surface risks and foster dialogue to avoid the emergence of an Internet of Insecure Industrial Things.

Bringing the new right to data portability (RTDP) from an abstract legal provision in Article 20 of the EU General Data Protection Regulation (GDPR) 2016 into practice requires a greater role for the IT design community. Simply put, the RTDP seeks to empower users by giving them greater control over their personal data, enabling them to both acquire their data and then move it around, for example to a different data controller. In this paper, we focus on how IT designers can use Privacy by Design (PbD) approaches to respond to these RTDP obligations. We are particularly interested in how the RTDP plays out for the technological context of the domestic Internet of things (IoT). By examining the legal, commercial and technical landscape around the RTDP, we can begin to unpack the practical roadblocks and opportunities ahead in implementing the right in practice.

The regulatory climate is in a process of change. Design, having been implicated for some time, is now explicitly linked to law. This paper recognises the heightened role of designers in the regulation of ambient interactive technologies. Taking account of incumbent legal requirements is difficult. Legal rules are convoluted, uncertain, and not geared towards operationalisable heuristics or development guidelines for system designers. Privacy and data protection are a particular moral, social and legal concern for technologies. This paper seeks to understand how to make emerging European data protection regulation more accessible to our community. Our approach develops and tests a series of data protection ideation cards with teams of designers. We find that, whilst wishing to protect users, regulation is viewed as a compliance issue. Subsequently we argue for the use of instruments, such as our cards, as a means to engage designers in leading a human-centered approach to regulation.