Through the exponential growth in digital devices and computational capabilities, big data technologies are putting pressure upon the boundaries of what can or cannot be considered acceptable from an ethical perspective. Much of the literature on ethical issues related to big data and big data technologies focuses on separate values such as privacy, human dignity, justice or autonomy. More holistic approaches, allowing a more comprehensive view and better balancing of values, usually focus on either a design-based approach, in which it (...) is tried to implement values into the design of new technologies, or an application-based approach, in which it is tried to address the ways in which new technologies are used. Some integrated approaches do exist, but typically are more general in nature. This offers a broad scope of application, but may not always be tailored to the specific nature of big data related ethical issues. In this paper we distil a comprehensive set of ethical values from existing design-based and application-based ethical approaches for new technologies and further focus these values to the context of emerging big data technologies. A total of four value lists were selected for this. The integrated list consists of a total of ten values: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity and environmental welfare. Together, this set of values provides a comprehensive and in-depth overview of the values that are to be taken into account for emerging big data technologies. (shrink)

This paper studies the construction of ethics in interactions between professionals in meetings, in relation to the rationing of resources. The research context is a supported housing unit targeted at clients with mental health and substance abuse problems. The service is provided for a municipality, which expects good progress of the clients. The research question is: how do the professionals produce implicit ethical justifications for setting limits to helping, even though the need for professional help is not called into question? (...) Five types of justification appear in the data covering 28 meetings. However, these types of justification do not solve the central ethical difficulty arising in the conversations. Limiting help would easily push people out of reach of all help. Thus, in spite of the talk about ethical justification, workers do not ultimately resort to limiting help in situations with no real alternatives for getting help. The ethical principle of following non-exclusionary practices is highly prioritized. (shrink)