In Things We Trust? Towards trustability in the Internet of Things

This essay discusses the main privacy, security and trustability issues with the Internet of Things

Sensible Privacy: How We Can Protect Domestic Violence Survivors Without Facilitating Misuse

Privacy is a concept with real life ties and implications. Privacy infringement has the potential to lead to serious consequences for the stakeholders involved, hence researchers and organisations have developed various privacy enhancing techniques and tools. However, there is no solution that fits all, and there are instances where privacy solutions could be misused, for example to hide nefarious activities. Therefore, it is important to provide suitable measures and to make necessary design tradeoffs in order to avoid such misuse. This short paper aims to make a case for the need of careful consideration when designing a privacy solution, such that the design effectively addresses the user requirements while at the same time minimises the risk of inadvertently assisting potential offenders. In other words, this paper strives to promote “sensible privacy” design, which deals with the complex challenges in balancing privacy, usability and accountability. We illustrate this idea through a case study involving the design of privacy solutions for domestic violence survivors. This is the main contribution of the paper. The case study presents specific user requirements and operating conditions, which coupled with the attacker model, provide a complex yet interesting scenario to explore. One example of our solutions is described in detail to demonstrate the feasibility of our approach

"The dearest of our possessions": applying Floridi's information privacy concept in models of information behavior and information literacy

This conceptual paper argues for the value of an approach to privacy in the digital information environment informed by Luciano Floridi's philosophy of information and information ethics. This approach involves achieving informational privacy, through the features of anonymity and obscurity, through an optimal balance of ontological frictions. This approach may be used to modify models for information behavior and for information literacy, giving them a fuller and more effective coverage of privacy issues in the infosphere. For information behavior, the Information Seeking and Communication Model, and the Information Grounds conception, are most appropriate for this purpose. For information literacy, the metaliteracy model, using a modification a privacy literacy framework, is most suitable

A qualitative study of stakeholders' perspectives on the social network service environment

Over two billion people are using the Internet at present, assisted by the mediating activities of software agents which deal with the diversity and complexity of information. There are, however, ethical issues due to the monitoring-and-surveillance, data mining and autonomous nature of software agents. Considering the context, this study aims to comprehend stakeholders' perspectives on the social network service environment in order to identify the main considerations for the design of software agents in social network services in the near future. Twenty-one stakeholders, belonging to three key stakeholder groups, were recruited using a purposive sampling strategy for unstandardised semi-structured e-mail interviews. The interview data were analysed using a qualitative content analysis method. It was possible to identify three main considerations for the design of software agents in social network services, which were classified into the following categories: comprehensive understanding of users' perception of privacy, user type recognition algorithms for software agent development and existing software agents enhancement

Implementing GDPR in the Charity Sector: A Case Study

Due to their organisational characteristics, many charities are poorly prepared for the General Data Protection Regulation (GDPR). We present an exemplar process for implementing GDPR and the DPIA Data Wheel, a DPIA framework devised as part of the case study, that accounts for these characteristics. We validate this process and framework by conducting a GDPR implementation with a charity that works with vulnerable adults. This charity processes both special category (sensitive) and personally identifiable data. This GDPR implementation was conducted and devised for the charity sector, but can be equally applied in any organisation that needs to implement GDPR or conduct DPIAs

Saving lives in road traffic—ethical aspects

Aim: This article aims at giving an overview of five ethical problem areas relating to traffic safety, thereby providing a general framework for analysing traffic safety from an ethical perspective and encouraging further discussion concerning problems, policies and technology in this area. Subjects and methods: The problems presented in the article are criminalisation, paternalism, privacy, justice and responsibility, and the reasons for choosing these are the following. First, they are all important areas in moral philosophy. Second, they are fairly general and it should be possible to categorise more specific problems under these headings. Ethical aspects of road traffic have not received the philosophical attention they deserve. Every year, more than 1 million people die globally in traffic accidents, and 20 to 50 million people are injured. Ninety per cent of the road traffic fatalities occur in low- and middle-income countries, where it is a growing problem. Politics, economics, culture and technology affect the number of fatalities and injuries, and the measures used to combat deaths in traffic as well as the role of road traffic should be ethically scrutinised. The topics are analysed and discussed from a moral-philosophical perspective, and the discussion includes both theory and applications. Results and conclusion: The author concludes with some thoughts on how the ethical discussion can be included in the public debate on how to save lives in road traffic. People in industrialised societies are so used to road traffic that it is almost seen as part of nature. Consequently, we do not acknowledge that we can introduce change and that we can affect the role we have given road traffic and cars. By acknowledging the ethical aspects of road traffic and illuminating the way the choices society makes are ethically charged, it becomes clear that there are alternative ways to design the road traffic system. The most important general conclusion is that discussion concerning these alternative ways of designing the system should be encouraged

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined

Applying Contextual integrity to Open Data Publishing

Open data publishing by both corporate and public bodies has increased significantly in recent years and this type of data could soon be developing into a real commodity. However, not all organisations pay sufficient heed to privacy as part of the decision-making process around open data publication, leaving both the organisation and the users whose data they handle vulnerable to privacy breaches. We present a case study in which we applied contextual integrity in practice, working with a UK local authority using real data. This illustrated how privacy can be incorporated into the decision-making process prior to publication taking place. Our results illustrate the application of Nissenbaum's Contextual Integrity Framework (CI) to the open data domain, and shows that CI is usable in practice

The Psychology of Privacy in the Digital Age

Privacy is a psychological topic suffering from historical neglect – a neglect that is increasingly consequential in an era of social media connectedness, mass surveillance and the permanence of our electronic footprint. Despite fundamental changes in the privacy landscape, social and personality psychology journals remains largely unrepresented in debates on the future of privacy. By contrast, in disciplines like computer science and media and communication studies, engaging directly with socio- technical developments, interest in privacy has grown considerably. In our review of this interdisciplinary literature we suggest four domains of interest to psychologists. These are: sensitivity to individual differences in privacy disposition; a claim that privacy is fundamentally based in social interactions; a claim that privacy is inherently contextual; and a suggestion that privacy is as much about psychological groups as it is about individuals. Moreover, we propose a framework to enable progression to more integrative models of the psychology of privacy in the digital age, and in particular suggest that a group and social relations based approach to privacy is needed

Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

Background: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. Objective: We propose a matrix for setting different standards, which is responsive to context and public expectations. Methods: The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. Results: The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. Conclusions: The matrix offers a tool with context-specific standards for anonymization in data researc