Outputs (10)

Implementing responsible innovation: the role of the meso-level(s) between project and organisation (2024)
Journal Article
Stahl, B. C., Portillo, V., Wagner, H., Craigon, P., Darzentas, D., De Ossorno Garcia, S., …Webb, H. (2024). Implementing responsible innovation: the role of the meso-level(s) between project and organisation. Journal of Responsible Innovation, 11(1), Article 2370934. https://doi.org/10.1080/23299460.2024.2370934

Much of academic discussion of responsible innovation (RI) has focused on RI integration into research projects. In addition, significant attention has also been paid to RI structures and policies at the research policy and institutional level. This... Read More about Implementing responsible innovation: the role of the meso-level(s) between project and organisation.

Navigating the labyrinth of RI through a practical application — A case study in a cross-disciplinary research project (2023)
Journal Article
Zhao, J., Patel, M., Inglesant, P., Portillo, V., Webb, H., Dowthwaite, L., …Jirotka, M. (2023). Navigating the labyrinth of RI through a practical application — A case study in a cross-disciplinary research project. Journal of Responsible Technology, 15, Article 100064. https://doi.org/10.1016/j.jrt.2023.100064

Responsible Innovation (RI) aims to enable research and innovation to take a more systematic approach to anticipating potential risks and consequences of planned research/innovative outputs. The Anticipation, Reflection, Engagement and Action (AREA)... Read More about Navigating the labyrinth of RI through a practical application — A case study in a cross-disciplinary research project.

TrustScapes: A visualisation tool to capture stakeholders' concerns and recommendations about data protection, algorithmic bias, and online safety (2023)
Journal Article
Ito-Jaeger, S., Lane, G., Dowthwaite, L., Webb, H., Patel, M., Rawsthorne, M., …Perez Vallejos, E. (2023). TrustScapes: A visualisation tool to capture stakeholders' concerns and recommendations about data protection, algorithmic bias, and online safety. International Journal of Qualitative Methods, 22, 1-10. https://doi.org/10.1177/1609406923118696

This paper presents a new methodological approach, TrustScapes, an open access tool designed to identify and visualise stakeholders’ concerns and policy recommendations on data protection, algorithmic bias, and online safety for a fairer and more tru... Read More about TrustScapes: A visualisation tool to capture stakeholders' concerns and recommendations about data protection, algorithmic bias, and online safety.

TrustScapes: A Visualisation Tool to Capture Stakeholders’ Concerns and Recommendations About Data Protection, Algorithmic Bias, and Online Safety (2023)
Journal Article
Ito-Jaeger, S., Lane, G., Dowthwaite, L., Webb, H., Patel, M., Rawsthorne, M., …Perez Vallejos, E. (2023). TrustScapes: A Visualisation Tool to Capture Stakeholders’ Concerns and Recommendations About Data Protection, Algorithmic Bias, and Online Safety. International Journal of Qualitative Methods, 22, https://doi.org/10.1177/16094069231186965

This paper presents a new methodological approach, TrustScapes, an open access tool designed to identify and visualise stakeholders’ concerns and policy recommendations on data protection, algorithmic bias, and online safety for a fairer and more tru... Read More about TrustScapes: A Visualisation Tool to Capture Stakeholders’ Concerns and Recommendations About Data Protection, Algorithmic Bias, and Online Safety.

Assessing responsible innovation training (2023)
Journal Article
Stahl, B. C., Aicardi, C., Brooks, L., Craigon, P. J., Cunden, M., Burton, S. D., …Webb, H. (2023). Assessing responsible innovation training. Journal of Responsible Technology, 16, Article 100063. https://doi.org/10.1016/j.jrt.2023.100063

There is broad agreement that one important aspect of responsible innovation (RI) is to provide training on its principles and practices to current and future researchers and innovators, notably including doctoral students. Much less agreement can be... Read More about Assessing responsible innovation training.

Supporting Responsible Research and Innovation within a University-based digital research programme: reflections from the “hoRRIzon” project (2022)
Journal Article
Portillo, V., Craigon, P., Liz, D., Greenhalgh, C., & Pérez-Vallejos, E. (2022). Supporting Responsible Research and Innovation within a University-based digital research programme: reflections from the “hoRRIzon” project. Journal of Responsible Technology, 12, Article 100045. https://doi.org/10.1016/j.jrt.2022.100045

Integration of Responsible Research and Innovation (RRI) principles into a research project is key to ensure outputs are ethically acceptable and socially desirable. However, translating RRI principles into practice is challenging as there are no rec... Read More about Supporting Responsible Research and Innovation within a University-based digital research programme: reflections from the “hoRRIzon” project.

Understanding User Perceptions of Trustworthiness in E-Recruitment Systems (2021)
Journal Article
Ogunniye, G., Legastelois, B., Rovatsos, M., Dowthwaite, L., Portillo, V., Perez Vallejos, E., …Jirotka, M. (2021). Understanding User Perceptions of Trustworthiness in E-Recruitment Systems. IEEE Internet Computing, 25(6), 23-32. https://doi.org/10.1109/mic.2021.3115670

Algorithmic systems are increasingly deployed to make decisions that people used to make. Perceptions of these systems can significantly influence their adoption, yet, broadly speaking, users’ understanding of the internal working of these systems is... Read More about Understanding User Perceptions of Trustworthiness in E-Recruitment Systems.

Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study (2021)
Journal Article
Dowthwaite, L., Fischer, J., Perez Vallejos, E., Portillo, V., Nichele, E., Goulden, M., & McAuley, D. (2021). Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study. Journal of Medical Internet Research, 23(9), Article e29085. https://doi.org/10.2196/29085

Background: Digital contact tracing is employed to monitor and manage the spread of Covid-19. However, to be effective the system must be adopted by a substantial proportion of the population. Studies of (mostly hypothetical) contact tracing apps sho... Read More about Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study.

The impact of algorithmic decision-making processes on young people’s well-being (2021)
Journal Article
Perez Vallejos, E., Dowthwaite, L., Creswick, H., Portillo, V., Koene, A., Jirotka, M., …McAuley, D. (2021). The impact of algorithmic decision-making processes on young people’s well-being. Health Informatics Journal, 27(1), 1-21. https://doi.org/10.1177/1460458220972750

This study aims to capture the online experiences of young people when interacting with algorithm mediated systems and their impact on their well-being. We draw on qualitative (focus groups) and quantitative (survey) data from a total of 260 young pe... Read More about The impact of algorithmic decision-making processes on young people’s well-being.

“It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency (2019)
Journal Article
Webb, H., Patel, M., Rovatsos, M., Davoust, A., Ceppi, S., Koene, A., …Cano, M. (2019). “It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency. Journal of Information, Communication and Ethics in Society, 17(2), 210-228. https://doi.org/10.1108/jices-11-2018-0092

Purpose The purpose of this paper is to report on empirical work conducted to open up algorithmic interpretability and transparency. In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impac... Read More about “It would be pretty immoral to choose a random algorithm”: Opening up algorithmic interpretability and transparency.