Virginia Portillo

Virginia Portillo
University of Nottingham | Notts · Horizon Digital Economy Research

PhD

About

33
Publications
1,823
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418
Citations
Introduction
My current research focuses on investigating young people and older adult's perceptions, experiences and ethical concerns regarding autonomous decision-making systems. I am particularly interested in embedding Responsible Innovation practice into research and to put forwards citizens' recommendations to guide the development of responsible design, co-creation and regulation of digital technologies. Skills: participatory research; co-creation; mixed-methods analysis; focus groups & policy impact.

Publications

Publications (33)
Preprint
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 show generally high acceptance, but little is known about the drivers and barriers to adoption of deploy...
Article
Full-text available
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 people to bring their opinions to the forefront while eliciting discussions. The results of the study...
Preprint
Full-text available
This paper describes the first stage of the ongoing development of two scales to measure online wellbeing and trust, based on the results of a series of workshops with younger and older adults. The first, the Online Wellbeing Scale includes subscales covering both psychological, or eudaimonic, wellbeing and subjective, or hedonic, wellbeing, as wel...
Article
Full-text available
Purpose The voices of children and young people have been largely neglected in discussions of the extent to which the internet takes into account their needs and concerns. This paper aims to highlight young people’s lived experiences of being online. Design/methodology/approach Results are drawn from the UnBias project’s youth led discussions, “Yo...
Article
Full-text available
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 limited. To explore users perceptions of algorithmic systems, we developed a prototype e-recruitment...
Article
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 show generally high acceptance, but little is known about the drivers and barriers to adoption of depl...
Preprint
Full-text available
BACKGROUND Algorithms rule the online environments and are essential for performing data processing, filtering, personalisation and other tasks. Research has shown that children and young people make up a significant proportion of Internet users, however little attention has been given to their experiences of algorithmically-mediated online platfor...
Article
Full-text available
The 5Rights Youth Juries are an educational intervention to promote digital literacy by engaging participants (i.e. jurors) in a deliberative discussion around their digital rights. The main objective of these jury-styled focus groups is to encourage children and young people to identify online concerns and solutions with a view to developing recom...
Article
Full-text available
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 impact of automated decision-making in our lives. Particularly problematic is the lack of transparency sur...
Conference Paper
Full-text available
The UnBias Youth Juries engage young people in discussion of issues that affect their online lives, especially in relation to algorithms, through the presentation of scenarios and prompts. Results from the first wave of juries, held in February 2017, produced valuable data about the concerns of young people and recommendations for improving their d...
Conference Paper
This paper explores the policy recommendations made by young people regarding algorithm fairness. It describes a piece of ongoing research developed to bring children and young people to the front line of the debate regarding children's digital rights. We employed the Youth Juries methodology which was designed to facilitate learning through discus...
Article
Notch signalling has been implicated in haematopoietic stem cell self-renewal. Although several studies have tested the effect of activating or inhibiting the Notch signalling pathway in stem cells, no study has yet determined the functional differences associated with expressing Notch1. The aims of this study were to characterise the expression of...
Article
Recent studies have highlighted the role of Notch signalling in the development of T cell acute lymphoblasic leukaemia (T-ALL). Over-expression of Notch3 and gain of function mutations in the Notch1 gene have been reported. The aims of this study were to determine the effect of Notch signalling on apoptosis in human T-ALL cell lines and to identify...
Data
PCR primer sequences. Sequences of PCR primers used to detect expression of known and novel Notch target genes.
Data
Gene expression following GSI treatment of T-ALL cell lines. 5 T-ALL cell lines (Jurkat, CEM, Molt4, HPB-ALL and SIL-ALL) were treated with DMSO or 10 uM GSI IX for 24 hrs and cDNA from these cells used for PCR analysis of Notch target genes. Fold change in gene expression (compared to DMSO-treated cells) was used to determine mean fold change in u...
Data
Affymetrix microarray analysis of Notch3-transduced Jurkat cells. Jurkat cells were transduced with GFP-alone, N1ΔE, or N3ΔE retrovirus and after 48 hrs, GFP+ cells were isolated by flow cytometry and total RNA extracted for Affymetrix array analysis. Data presented represents mean of 4 independent experiments. Graphical representation of microarra...
Data
ChIP-on-chip data from Margolin et al. PNAS 2009. Raw data from the Margolin et al. PNAS 2009 study was used to determine the ChIP-on-chip significance of Notch1 biding to the promoter regions of the genes identified in this study. p-values < 0.05 are shown in bold.
Data
Expression of novel Notch target genes in cell lines transduced with Notch. cDNA from GFP-alone pMX, N1ΔE, or N3ΔE-transduced T-ALL and non-T-ALL cell lines wwere used for PCR analysis of the 10 novel genes most upregulated by Notch1 based on microarray data in figure 1. Data represents fold change in gene expression from GFP-alone-transduced cells...
Data
Notch expression in T-ALL cells. (A) cDNA from parental Jurkat CEM and Molt4 cells was analysed for the expression of Notch homologues. Quantitative expression was determined using a standard made up of known numbers of copies of human genomic DNA. (B) Luciferase assay analysis of CSL-Luciferase reporter activity in HEK294T cells transfected with N...
Data
Upregulation of the GIMAP gene family by Notch. (A) cDNA from Jurkat cells transduced with GFP-alone, N1ΔE or N3ΔE retrovirus was used for real-time PCR analysis of GIMAP gene expression. GIMAP3 is a pseudogene. GIMAP8 was not expressed in Jurkat cells. * represents p < 0.05 vesus the GFP-alone-transduced sample. Data for GIMAP5 is shown in figure...
Article
Full-text available
Dysregulated Notch signalling is believed to play an important role in the development and maintenance of T cell leukaemia. At a cellular level, Notch signalling promotes proliferation and inhibits apoptosis of T cell acute lymphoblastic leukaemia (T-ALL) cells. In this study we aimed to identify novel transcriptional targets of Notch signalling in...
Article
The target site for the anthelmintic action of ivermectin is a family of nematode glutamate-gated chloride channel alpha subunits (GluClalpha) that bind the drug with high affinity and mediate its potent paralytic action. Whilst the action of ivermectin on the pharyngeal muscle of nematodes is relatively well understood, its effect on locomotor act...
Article
Most of the recent evidence suggests that the avermectin/milbemycin family of anthelmintics act via specific interactions with glutamate-gated chloride channels. These channels are encoded by a small family of genes in nematodes, though the composition of the gene family and the function of the individual members of the family may vary between spec...
Article
Glutamate-gated chloride channels (GluCl) are related to gamma-aminobutyric acid-A (GABA(A)) receptors and are the target sites for the avermectin/milbemycin (A/M) anthelmintics, drugs that cause paralysis of the somatic and pharyngeal muscles in nematodes. We have previously identified four GluCl subunits, HcGluClalpha, HcGluClbeta, HcGluClalpha3A...
Article
This work describes a new gene coding for a fatty acid binding protein (FABP) in the parasite Echinococcus granulosus, named EgFABP2. The complete gene structure, including the promoter sequence, is reported. The genomic coding domain organisation of the previously reported E. granulosus FABP gene (EgFABP1) has been also determined. The correspondi...
Article
Full-text available
Mutants of the yeast Saccharomyces cerevisiae defective in the RAD17 gene are sensitive to ultraviolet (UV) and γ radiation and manifest a defect in G2 arrest following radiation treatment. We have cloned the RAD17gene by complementation of the UV sensitivity of a rad17-1 mutant and identified an ORF of 1.2 kb encoding a predicted gene product of 4...

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Projects

Project (1)
Project
UnBias: Emancipating Users Against Algorithmic Biases for a Trusted Digital Economy In an age of ubiquitous data collecting, analysis and processing, how can citizens judge the trustworthiness and fairness of systems that heavily rely on algorithms? News feeds, search engine results and product recommendations increasingly use personalization algorithms to help us cut through the mountains of available information and find those bits that are most relevant, but how can we know if the information we get really is the best match for our interests? There is no such thing as a neutral algorithm. As anyone who has ever created something knows, even something as simple as a meal, the act of creating inevitably involves choices that will affect the properties of the final product. Despite this truism recommendations and selections made by algorithms are commonly presented to consumers as if they are inherently free from (human) bias and ‘fair’ because the decisions are ‘based on data’. During the recent controversy about possible political bias in Facebook’s Trending Topics for instance the focus was almost exclusively on the role of the human editors even though 95% or more of the news selection process is done by algorithms. Human judgements however are ultimately also based on data. If there is anything that makes an algorithm based system more trustworthy than a human based one, surely it cannot simply be the use of data alone but rather comes down to audit-ability. An algorithm is a piece of code that can be inspected and analysed. All elements that go into the decision making process can in principle be revealed. If we know the equation we can follow the chain of logic that leads from the inputs to the output. Moreover, all the inputs that are used in the process are in principle identifiable. Clearly this trustworthiness can only be given to subjects of the algorithm’s decision making if there is transparency. This reasoning is at the heart of legal protections such as Principle 6 of the Data Protection Act: “The right of subject access allows an individual access to information about the reasoning behind any decisions taken by automated means”. The reality of the user experience however is often far removed from such transparency. When using online services users are generally given next-to-no information about the algorithms, or even the data that is used. They are instead expected to blindly trust the service provider. In part this is due to commercial interests for whom the algorithms are key intellectual property. Increasingly however the complexity of the algorithms, which can include many hundreds of parameters and possibly incorporate machine-learning elements, can make it very challenging even for the designers of the systems to transparently understand why a specific conclusion might have been reached. Furthermore, in order for transparency to be meaningful it must provide interpretable understanding of the decision process, not pages upon pages of code or equations that would only be accessible to a handful or experts. Transparency at the level of code would be so opaque for most users as to make the current lack of understandability of Terms & Conditions documents pale in comparison. Starting in September 2016 the EPSRC funded project “UnBias: Emancipating Users Against Algorithmic Biases for a Trusted Digital Economy” will look at all of the issues above in much greater detail. A large part of this work will include user group studies to understand the concerns and perspectives of citizens. UnBias aims to provide policy recommendations, ethical guidelines and a ‘fairness toolkit’ co-produced with young people and other stakeholders that will include educational materials and resources to support youth understanding about online environments as well as raise awareness among online providers about the concerns and rights of young internet users. The project is relevant for young people as well as society as a whole to ensure trust and transparency are not missing from the internet. The results will be widely disseminated to a variety of audiences ranging from academic peer-review journals to community groups of interest such as secondary schools and youth clubs. Project team: - Prof. Derek McAuley, University of Nottingham - Prof. Tom Rodden, University of Nottingham - Dr. Ansgar Koene, University of Nottingham - Dr. Elvira Perez Vallejos, University of Nottingham - Monica Cano Gomez, University of Nottingham - Liz Dowthwaite, University of Nottingham - Virginia Portillo, University of Nottingham - Prof. Marina Jirotka, University of Oxford - Dr. Helena Webb, University of Oxford - Menisha Patel, University of Oxford - Dr. Michael Rovatsos, University of Edinburgh - Sofia Ceppi, University of Edinburgh