To enhance trustworthiness of AI systems, a number of solutions have been proposed to document how such systems are built and used. A key facet of realizing trust in AI is how to make such systems accountable - a challenging task, not least due to the lack of an agreed definition of accountability and differing perspectives on what information should be recorded and how it should be used (e.g., to inform audit). Information originates across the life cycle stages of an AI system and from a variety of sources (individuals, organizations, systems), raising numerous challenges around collection, management, and audit. In our previous work, we argued that semantic Knowledge Graphs (KGs) are ideally suited to address those challenges and we presented an approach utilizing KGs to aid in the tasks of modelling, recording, viewing, and auditing accountability information related to the design stage of AI system development. Moreover, as KGs store data in a structured format understandable by both humans and machines, we argued that this approach provides new opportunities for building intelligent applications that facilitate and automate such tasks. In this paper, we expand our earlier work by reporting additional detailed requirements for knowledge representation and capture in the context of AI accountability; these extend the scope of our work beyond the design stage, to also include system implementation. Furthermore, we present the RAInS ontology which has been extended to satisfy these requirements. We evaluate our approach against three popular baseline frameworks, namely, Datasheets, Model Cards, and FactSheets, by comparing the range of information that can be captured by our KGs against these three frameworks. We demonstrate that our approach subsumes and extends the capabilities of the baseline frameworks and discuss how KGs can be used to integrate and enhance accountability information collection processes.

Social media influence materialises in the physical world by shaping our urban environment and changing the modality we experience. This under-explored outcome still lacks the conceptual tools to build a discourse around it. We present a case study that showcases how urban planning and development are influenced by social media and a first framework addressing the interrelation between social media, urban design, and the experience of the urban environment. This short contribution provides concepts for critically analysing the physical implications of social media-based ubiquitous hypertext systems.

Background: Healthy lifestyle interventions have a positive impact on multiple disease trajectories, including cancer-related outcomes. Specifically, appropriate habitual physical activity, adequate sleep, and a regular wholesome diet are of paramount importance for the wellness and supportive care of survivors of cancer. Mobile health (mHealth) apps have the potential to support novel tailored lifestyle interventions. Objective: This observational pilot study aims to assess the feasibility of mHealth multidimensional longitudinal monitoring in survivors of cancer. The primary objective is to test the compliance (user engagement) with the monitoring solution. Secondary objectives include recording clinically relevant subjective and objective measures collected through the digital solution. Methods: This is a monocentric pilot study taking place in Bangor, Wales, United Kingdom. We plan to enroll up to 100 adult survivors of cancer not receiving toxic anticancer treatment, who will provide self-reported behavioral data recorded via a dedicated app and validated questionnaires and objective data automatically collected by a paired smartwatch over 16 weeks. The participants will continue with their normal routine surveillance care for their cancer. The primary end point is feasibility (eg, mHealth monitoring acceptability). Composite secondary end points include clinically relevant patient-reported outcome measures (eg, the Edmonton Symptom Assessment System score) and objective physiological measures (eg, step counts). This trial received a favorable ethical review in May 2023 (Integrated Research Application System 301068). Results: This study is part of an array of pilots within a European Union funded project, entitled “GATEKEEPER,” conducted at different sites across Europe and covering various chronic diseases. Study accrual is anticipated to commence in January 2024 and continue until June 2024. It is hypothesized that mHealth monitoring will be feasible in survivors of cancer; specifically, at least 50% (50/100) of the participants will engage with the app at least once a week in 8 of the 16 study weeks. Conclusions: In a population with potentially complex clinical needs, this pilot study will test the feasibility of multidimensional remote monitoring of patient-reported outcomes and physiological parameters. Satisfactory compliance with the use of the app and smartwatch, whether confirmed or infirmed through this study, will be propaedeutic to the development of innovative mHealth interventions in survivors of cancer. International Registered Report Identifier (IRRID): PRR1-10.2196/52957

Digital applications for supporting health management often fail to achieve large-scale adoption. Costs related to purchasing, maintaining, and using medical or sensor devices, such as smartwatches, currently hinder uptake and sustained engagement, particularly in the prevention and monitoring of lifelong conditions. As an alternative, smartphone-based passive monitoring could provide a viable strategy for lifelong use, removing hardware-related costs and exploiting the synergies between mobile health (mHealth) and ambient assisted living (AAL). However, smartphone sensor toolkits are not designed for diagnostic purposes, and their quality varies depending on the model, maker, and generation. This narrative overview of recent reviews (narrative meta-review) on the current state of smartphone-based passive monitoring highlights the strengths, weaknesses, opportunities, and threats (SWOT analysis) of this approach, which pervasively encompasses digital health, mHealth, and AAL. The results are then consolidated into a newly defined concept of a mobile biomarker, that is, a general model of medical indices for diagnostic tasks that can be computed using smartphone sensors and capabilities.