Panel Chair: Holger Zschenderlein
Abstracts
KARINA RODRIGUEZ ECHAVARRIA
Enhancing engagement with cultural heritage collections using 3D digital technologies
This paper will discuss the challenges and opportunities created by the availability of 3D technologies for enhancing the engagement of diverse audiences with cultural heritage collections. This includes research in the development of novel computational tools and workflows which involve technologies such as 3D digitisation, visual analysis, Virtual Reality (VR) and 3D printing of heritage artefacts. Using an interdisciplinary approach, these developments have been done in collaboration between heritage organisations, communities, artists and technical experts, including local institutions.
SIMONNE WEEKS
How can the Arts enhance public awareness of organ donation and transplantation amongst undergraduate students in the UK?
Organ shortage remains the main obstacle in transplant medicine. The number of patients on the UK’s active transplant list in February 2020 reached 6,138 and only 3,760 transplants were performed (1). This shortfall in treatment resources is especially significant in managing the UK’s current economic health and combating health inequalities (2). On 20 May 2020, the law adopted the opt-out system to help tackle the prolonged transplant list waiting times, especially amongst Black African, Black Caribbean and Asian recipients (3). Therefore, there is an urgent need to address this health inequality that is a direct result of the lack of awareness of the organ shortage amongst these groups by promoting organ donation and transplantation education in the university context.
It is widely reported that social networking is prevalent amongst undergraduate students and user-generated content can empower individuals to become involved in disseminating information and opinions about important health care issues through social media that speed up and enrich the communication process (4). In response to meet this gap in research, an interdisciplinary research group of nurses and biomedical scientists has formed to create opportunities for university students to co-design and co-deliver an educational public health event. The research team would welcome contributions from other creative practitioners, scientists and researchers to develop a creative and radical approach to this social and health inequality. Please see https://blogs.brighton.ac.uk/donorresearch/ for more information.
- NHS Blood and Transplant. Organ Donation and Transplantation Activity Report 2019/20. Available at: https://nhsbtdbe.blob.core.windows.net/umbraco-assets-corp/19220/activity-report-2019-2020.pdf [Accessed 01 Apr. 2021].
- Marmot M, Allen J, Goldblatt P, Boyce T, McNeish D, Grady M. Fair society, healthy lives. Strategic review of health inequalities in England post-2010. 2011 Nov 2.
- Rudge C, Johnson RJ, Fuggle SV, Forsythe JL. Renal transplantation in the United Kingdom for patients from ethnic minorities. Transplantation.
- D’Alessandro AM, Peltier JW, Dahl AJ. A large-scale qualitative study of the potential use of social media by university students to increase awareness and support for organ donation. Progress in Transplantation. 2012 Jun;22(2):183-91.
MARCUS WINTER
Public understanding of machine learning
![Image created by a generative adversarial network for the title of this talk: Hands-on machine learning.](https://blogs.brighton.ac.uk/collaborative/files/2021/06/WINTER-IMAGE.jpeg)
Artificial Intelligence (AI) and its subfield of Machine Learning (ML) play increasingly important roles in our lives, however, we typically experience them indirectly and often are not even aware of their workings behind the scenes. As a result, most people have only a vague understanding of the applications, capabilities and limitations of AI and ML. On a personal level, this leads to a loss of agency and control when dealing with “intelligent” systems. For society as a whole it leads to poorly informed public debates about AI and ML and the policies governing their use. This talk explores ways how people can take ownership on these technologies and learn about them through active experimentation. Considering recent developments in the field that allow for off-the-shelf, customisable, local machine learning on consumer-level hardware, it explores how non-experts can put these technologies to use and in the process develop a better understanding of them.
APURV CHAUHAN
Examining collective emotional response to COVID-19 pandemic in 19 countries
SARS-CoV-2 and the ensuing COVID-19 pandemic is the biggest public health crisis of this generation. Taking cognisance of the developing situation on the new virus, World Health Organisation (WHO) provided its first situation report on 21st of January 2020 and eventually declared it a pandemic on 11th of March 2020. Taking 21st of January as the day 1, this paper looks at collective emotions of anxiety and positive emotions in 19 countries during the first 120 days of the pandemic. A total of over 260 million words from over 105 million individual tweets were examined to develop a corpus of what people in 19 countries were saying about the pandemic on a daily basis between 21st of January and 18th of May 2020. Linguistic Inquiry and Word Count (LIWC) application was used to develop a time-series of anxiety and positive emotion levels and structural breaks in the series were estimated to detect dates when the series received exogeneous shocks. The results show that WHO’s declaration of the COVID-19 as a pandemic was the watershed moment resulting in a decline in anxiety in 14 countries and rise in positive emotions in 18 countries. In some countries, a similar shift in both emotions also coincided with individual governments announcing financial packages. Based on our results, we argue that WHO’s declaration of the situation as a pandemic reduced the uncertainty around the situation and contributed to reduction of systemic anxiety and increase in systemic positive emotions. This paper is the first to combine psychometric analysis of big-data with econometric methods.