scholarly journals Design for data ethics: using service design approaches to operationalize ethical principles on four projects

2018 ◽  
Vol 376 (2128) ◽  
pp. 20170353 ◽  
Author(s):  
Cat Drew
Keyword(s):  
Data Science ◽  
Service Design ◽  
Initial Development ◽  
Social Good ◽  
Ethics Framework ◽  
Ethical Frameworks ◽  
Data Ethics ◽  
Use Of Data ◽  
Government Data ◽  
Guidance Needs

Ethical frameworks provide helpful guidance about what you should—and should not—do in relation to data projects. But they do not provide definitive yes/no answers about what an ethical data project is or is not. Indeed, research (Ipsos-MORI 2015 Public dialogue into the ethics of data science in government) conducted for the initial development of the Government's Data Ethics Framework shows that the public does not hold any clear red lines; rather, they make nuanced assessments based on a number of variables, including public good and privacy. Ethical frameworks provide a list of these variables to consider in shaping the form of the work. Some are now starting to provide more practical tools and guidance to reshape data projects and push it along those variables into a more ethical space. Alongside technical tools, service design approaches can help enhance the degree to which a data project is ethical, and provides a toolkit for data scientists, analysts and policymakers to take projects from ‘what should we do’ to ‘how can we do it’. This paper sets out the emergence of data science ethical frameworks within the context of the use of data for social good, and—with the recent release of the updated UK Government Data Ethics Framework—shows the recognition more practical guidance needs to be provided. The author then argues that service design approaches provide a helpful ‘wrap around’ for data projects, and draws on experience in using service design tools on four projects, as well as wider examples. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations’.

scholarly journals Data science ethics in government

2016 ◽  
Vol 374 (2083) ◽  
pp. 20160119 ◽  
Author(s):  
Cat Drew
Keyword(s):  
Data Science ◽  
New Technologies ◽  
Unintended Consequences ◽  
Ethical Framework ◽  
Social Good ◽  
Science Ethics ◽  
Policy Goals ◽  
Challenges And Opportunities ◽  
Government Data ◽  
The Government

Data science can offer huge opportunities for government. With the ability to process larger and more complex datasets than ever before, it can provide better insights for policymakers and make services more tailored and efficient. As with all new technologies, there is a risk that we do not take up its opportunities and miss out on its enormous potential. We want people to feel confident to innovate with data. So, over the past 18 months, the Government Data Science Partnership has taken an open, evidence-based and user-centred approach to creating an ethical framework. It is a practical document that brings all the legal guidance together in one place, and is written in the context of new data science capabilities. As part of its development, we ran a public dialogue on data science ethics, including deliberative workshops, an experimental conjoint survey and an online engagement tool. The research supported the principles set out in the framework as well as provided useful insight into how we need to communicate about data science. It found that people had a low awareness of the term ‘data science’, but that showing data science examples can increase broad support for government exploring innovative uses of data. But people's support is highly context driven. People consider acceptability on a case-by-case basis, first thinking about the overall policy goals and likely intended outcome, and then weighing up privacy and unintended consequences. The ethical framework is a crucial start, but it does not solve all the challenges it highlights, particularly as technology is creating new challenges and opportunities every day. Continued research is needed into data minimization and anonymization, robust data models, algorithmic accountability, and transparency and data security. It also has revealed the need to set out a renewed deal between the citizen and state on data, to maintain and solidify trust in how we use people's data for social good. This article is part of the themed issue ‘The ethical impact of data science’.

scholarly journals The opportunities and ethics of big data: practical priorities for a national Council of Data Ethics

2016 ◽  
Vol 374 (2083) ◽  
pp. 20160116 ◽  
Author(s):  
Olivia Varley-Winter ◽  
Hetan Shah
Keyword(s):  
Big Data ◽  
Data Science ◽  
Professional Competence ◽  
Data Access ◽  
National Council ◽  
Data Infrastructure ◽  
Ethical Frameworks ◽  
Data Ethics ◽  
Address Data ◽  
The Uk

In order to generate the gains that can come from analysing and linking big datasets, data holders need to consider the ethical frameworks, principles and applications that help to maintain public trust. In the USA, the National Science Foundation helped to set up a Council for Big Data, Ethics and Society, of which there is no equivalent in the UK. In November 2015, the Royal Statistical Society convened a workshop of 28 participants from government, academia and the private sector, and discussed the practical priorities that might be assisted by a new Council of Data Ethics in the UK. This article draws together the views from that meeting. Priorities for policy-makers and others include seeking a public mandate and informing the terms of the social contract for use of data; building professional competence and due diligence on data protection; appointment of champions who are competent to address public concerns; and transparency, across all dimensions. For government data, further priorities include improvements to data access, and development of data infrastructure. In conclusion, we support the establishment of a national Data Ethics Council, alongside wider and deeper engagement of the public to address data ethics dilemmas. This article is part of the themed issue ‘The ethical impact of data science’.

scholarly journals Mathematical Issues in Data Science and Applications for Health care

2019 ◽  
Author(s):  
Sitti Zuhaerah Thalhah ◽  
Mohammad Tohir ◽  
Phong Thanh Nguyen ◽  
K. Shankar ◽  
Robbi Rahim
Keyword(s):  
Data Analytics ◽  
Data Science ◽  
Predictive Analytics ◽  
Big Data Analytics ◽  
Decision Models ◽  
Computational Techniques ◽  
Healthcare Applications ◽  
Use Of Data ◽  
Source Data ◽  
Military Applications

For development in military applications, industrial and government the predictive analytics and decision models have long been cornerstones. In modern healthcare system technologies and big data analytics and modeling of multi-source data system play an increasingly important role. Into mathematical models in these domains various problems arising that can be formulated, by using computational techniques, sophisticated optimization and decision analysis it can be analyzed. This paper studies the use of data science in healthcare applications and the mathematical issues in data science.

scholarly journals Book Review: Data Feminism

2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Shannon O'Reilly
Keyword(s):  
Data Science ◽  
Racial Profiling ◽  
Race And Gender ◽  
Data Ethics ◽  
Political Commentary ◽  
Intersectional Analysis ◽  
Visual Approach ◽  
And Gender

This book review critiques Lauren F. Klein and Catherine D'lgnazio's Data Feminism (2020). Klein and D'lgnazio take a visual approach to provide a synopsis—underpinned by social and political commentary—that explores the avenues through which data science and data ethics shape how contemporary technologies exploit injustices related to race and gender. Klein and D'lgnazio offer examples of this exploitation, such as the discriminatory surveillance apparatus that relies on racial profiling tactics. These examples are emboldened by the use of contemporary data strategies that—on the surface—strive to achieve a more equitable and ‘neutral’ hierarchal society. This review examines the text’s visual approach to demonstrating institutional inequities and the authors’ acknowledgement of their own privilege, specifically the role they play in upholding the oppressive systems they seek to dismantle through collaboration and intersectional analysis.

Technological Innovations Through Digital Service Design in Hospital Districts

2021 ◽  
Vol 12 (2) ◽  
pp. 48-62
Author(s):  
Sanna Ryynänen ◽  
Riitta Uusisalmi
Keyword(s):  
Technological Innovation ◽  
Diffusion Of Innovation ◽  
Narrative Analysis ◽  
Service Innovation ◽  
Service Design ◽  
Technological Innovations ◽  
Diffusion Of Innovation Theory ◽  
Initial Development ◽  
Digital Service ◽  
Adoption Of Innovation

The aim of the study is to describe and increase understanding about digital service design in creating technological innovations in Finnish hospital districts. The data was collected via an open questionnaire during March-August 2019 and analyzed using a combined thematic and narrative analysis. Three distinct themes arose from the research narratives: cooperation, development, and cost. First, the importance of cooperation in the early stages of the service design process, when new technological innovation ideas are developed, was emphasized. Second, the possibilities of digitalization and need for new innovations were taken into account in the development theme. Third, costs define the utilization of an innovation and guide its initial development. If savings and costs are in balance, technological innovations will move forward. Moreover, the findings show that technological innovations in hospital districts progress in a certain pattern, and the utilization of innovations come from the need and pressure to evolve. Keywords Adoption of Innovation, Deployment of Innovation, Digital Service Design, Rogers's Diffusion of Innovation Theory, Service Design, Service Innovation, Specialized Medical Care

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