A realisation of ethical concerns with smartphone personal health monitoring apps

The pervasiveness of smartphones has facilitated a new way in which owners of devices can monitor their health using applications (apps) that are installed on their smartphones. Smartphone personal health monitoring (SPHM) collects and stores health related data of the user either locally or in a third party storing mechanism. They are also capable of giving feedback to the user of the app in response to conditions are provided to the app therefore empowering the user to actively make decisions to adjust their lifestyle. Regardless of the benefits that this new innovative technology offers to its users, there are some ethical concerns to the user of SPHM apps. These ethical concerns are in some way connected to the features of SPHM apps. From a literature survey, this paper attempts to recognize ethical issues with personal health monitoring apps on smartphones, viewed in light of general ethics of ubiquitous computing. The paper argues that there are ethical concerns with the use of SPHM apps regardless of the benefits that the technology offers to users due to SPHM apps’ ubiquity leaving them open to known and emerging ethical concerns. The paper then propose a need further empirical research to validate the claim

PrivacyScore: Improving Privacy and Security via Crowd-Sourced Benchmarks of Websites

Website owners make conscious and unconscious decisions that affect their users, potentially exposing them to privacy and security risks in the process. In this paper we introduce PrivacyScore, an automated website scanning portal that allows anyone to benchmark security and privacy features of multiple websites. In contrast to existing projects, the checks implemented in PrivacyScore cover a wider range of potential privacy and security issues. Furthermore, users can control the ranking and analysis methodology. Therefore, PrivacyScore can also be used by data protection authorities to perform regularly scheduled compliance checks. In the long term we hope that the transparency resulting from the published benchmarks creates an incentive for website owners to improve their sites. The public availability of a first version of PrivacyScore was announced at the ENISA Annual Privacy Forum in June 2017.Comment: 14 pages, 4 figures. A german version of this paper discussing the legal aspects of this system is available at arXiv:1705.0888

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

Mind your step! : How profiling location reveals your identity - and how you prepare for it

Location-based services (LBS) are services that position your mobile phone to provide some context-based service for you. Some of these services – called ‘location tracking’ applications - need frequent updates of the current position to decide whether a service should be initiated. Thus, internet-based systems will continuously collect and process the location in relationship to a personal context of an identified customer. This paper will present the concept of location as part of a person’s identity. I will conceptualize location in information systems and relate it to concepts like privacy, geographical information systems and surveillance. The talk will present how the knowledge of a person's private life and identity can be enhanced with data mining technologies on location profiles and movement patterns. Finally, some first concepts about protecting location information

mHealth Research Applied to Regulated and Unregulated Behavioral Health Sciences

Behavioral scientists are developing new methods and frameworks that leverage mobile health technologies to optimize individual level behavior change. Pervasive sensors and mobile apps allow researchers to passively observe human behaviors “in the wild” 24/7 which supports delivery of personalized interventions in the real-world environment. This is all possible because these technologies contain an incredible array of sensors that allow applications to constantly record user location and can contextualize current environmental conditions through barometers, thermometers, and ambient light sensors and can also capture audio and video of the user and their surroundings through multiple integrated high-definition cameras and microphones. These tools are a game changer in behavioral health research and, not surprisingly, introduce new ethical, regulatory/legal and social implications described in this article

Implementing Ethics for a Mobile App Deployment

This paper discusses the ethical dimensions of a research project in which we deployed a personal tracking app on the Apple App Store and collected data from users with whom we had little or no direct contact. We describe the in-app functionality we created for supporting consent and withdrawal, our approach to privacy, our navigation of a formal ethical review, and navigation of the Apple approval process. We highlight two key issues for deployment-based research. Firstly, that it involves addressing multiple, sometimes conflicting ethical principles and guidelines. Secondly, that research ethics are not readily separable from design, but the two are enmeshed. As such, we argue that in-action and situational perspectives on research ethics are relevant to deployment-based research, even where the technology is relatively mundane. We also argue that it is desirable to produce and share relevant design knowledge and embed in-action and situational approaches in design activities

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Online behavioural tracking in Internet gambling research: ethical and methodological issues

In contrast to offline gambling, the use of online behavioural tracking presents an opportunity for researchers in the social sciences to examine the actual and real-time behaviour engaged in by gamblers. If gaming companies can use behavioural tracking to learn more about their clientele, there is no reason why researchers could not adopt the same practice in carrying out their research. After examining why the online medium is a good place to conduct research with online gamblers, the paper examines the (i) methodological issues in online gambling research, (ii) behavioural tracking tools in online gambling, (iii) the ethics of online data collection by the gambling industry, (iv) ethical issues in online behavioural tracking research, and (v) implications of online behavioural tracking for problem gambling screening criteria. In the main, the most salient problems that online researchers in the gambling studies field are likely to face concern ethical issues (informed consent, deception, public versus private spaces, lurking). Despite such ethical dilemmas, these are not insurmountable and can be remedied if careful thought and rationale is provided

Knowing Your Population: Privacy-Sensitive Mining of Massive Data

Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is controversial, in particular raising issues of privacy. However, our hypothesis is that privacy-sensitive uses are possible and often beneficial enough to warrant considerable research and development efforts. Our work contends that peoples behavior can yield patterns of both significant commercial, and research, value. For such purposes, methods and algorithms for mining telecommunication data to extract commonly used routes and locations, articulated through time-geographical constructs, are described in a case study within the area of transportation planning and analysis. From the outset, these were designed to balance the privacy of subscribers and the added value of mobility patterns derived from their mobile communication traffic and transactions data. Our work directly contrasts the current, commonly held notion that value can only be added to services by directly monitoring the behavior of individuals, such as in current attempts at location-based services. We position our work within relevant legal frameworks for privacy and data protection, and show that our methods comply with such requirements and also follow best-practice