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While much of the scholarly work on ethics relating to academic authorship examines the fair distribution of authorship credit, none has yet examined situations where a researcher contributes significantly to the project, but whose contributions do not make it into the final manuscript. Such a scenario is commonplace in collaborative research settings in many disciplines and may occur for a number of reasons, such as excluding research in order to provide the paper with a clearer focus, tell a particular story, or exclude negative results that do not fit the hypothesis. Our concern in this paper is less about the reasons for including or excluding data from a paper and more about distributing credit in this type of scenario. In particular, we argue that the notion ‘substantial contribution’, which is part of the International Committee of Medical Journal Editors (ICMJE) authorship criteria, is ambiguous and that we should ask whether it concerns what ends up in the paper or what is a substantial contribution to the research process leading up to the paper. We then argue, based on the principles of fairness, due credit, and ensuring transparency and accountability in research, that the latter interpretation is more plausible from a research ethics point of view. We conclude that the ICMJE and other organizations interested in authorship and publication ethics should consider including guidance on authorship attribution in situations where researchers contribute significantly to the research process leading up to a specific paper, but where their contribution is finally omitted.

Even though public awareness about privacy risks in the Internet is increasing, in the evolution of the Internet to the Internet of Things (IoT) these risks are likely to become more relevant due to the large amount of data collected and processed by the “Things”. The business drivers for exploring ways to monetize such data are one of the challenges identified in this paper for the protection of Privacy in the IoT. Beyond the protection of privacy, this paper highlights the need for new approaches, which grant a more active role to the users of the IoT and which address other potential issues such as the Digital Divide or safety risks. A key facet in ethical design is the transparency of the technology and services in how that technology handles data, as well as providing choice for the user. This paper presents a new approach for users’ interaction with the IoT, which is based on the concept of Ethical Design implemented through a policy-based framework. In the proposed framework, users are provided with wider controls over personal data or the IoT services by selecting specific sets of policies, which can be tailored according to users’ capabilities and to the contexts where they operate. The potential deployment of the framework in a typical IoT context is described with the identification of the main stakeholders and the processes that should be put in place.

We argue that the recommendations made by the Institute of Medicine’s 2011 report, Chimpanzees in Biomedical and Behavioral Research: Assessing the Necessity, are methodologically and ethically confused. We argue that a proper understanding of evolution and complexity theory in terms of the science and ethics of using chimpanzees in biomedical research would have had led the committee to recommend not merely limiting but eliminating the use of chimpanzees in biomedical research. Specifically, we argue that a proper understanding of the difference between the gross level of examination of species and examinations on finer levels can shed light on important methodological and ethical inconsistencies leading to ignorance of potentially unethical practices and policies regarding the use of animals in scientific research.

A number of companies including Google and BMW are currently working on the development of autonomous cars. But if fully autonomous cars are going to drive on our roads, it must be decided who is to be held responsible in case of accidents. This involves not only legal questions, but also moral ones. The first question discussed is whether we should try to design the tort liability for car manufacturers in a way that will help along the development and improvement of autonomous vehicles. In particular, Patrick Lin’s concern that any security gain derived from the introduction of autonomous cars would constitute a trade-off in human lives will be addressed. The second question is whether it would be morally permissible to impose liability on the user based on a duty to pay attention to the road and traffic and to intervene when necessary to avoid accidents. Doubts about the moral legitimacy of such a scheme are based on the notion that it is a form of defamation if a person is held to blame for causing the death of another by his inattention if he never had a real chance to intervene. Therefore, the legitimacy of such an approach would depend on the user having an actual chance to do so. The last option discussed in this paper is a system in which a person using an autonomous vehicle has no duty (and possibly no way) of interfering, but is still held (financially, not criminally) responsible for possible accidents. Two ways of doing so are discussed, but only one is judged morally feasible.

This paper examines a constellation of ethical and editorial issues that have arisen since philosophers started to conduct, submit and publish empirical research. These issues encompass concerns over responsible authorship, fair treatment of human subjects, ethicality of experimental procedures, availability of data, unselective reporting and publishability of research findings. This study aims to assess whether the philosophical community has as yet successfully addressed such issues. To do so, the instructions for authors, submission process and published research papers of 29 main journals in philosophy have been considered and analyzed. In light of the evidence reported here, it is argued that the philosophical community has as yet failed to properly tackle such issues. The paper also delivers some recommendations for authors, reviewers and editors in the field.

Individual athletes, coaches and sports teams seek continuously for ways to improve performance and accomplishment in elite competition. New techniques of performance analysis are a crucial part of the drive for athletic perfection. This paper discusses the ethical importance of one aspect of the future potential of performance analysis in sport, combining the field of biomedicine, sports engineering and nanotechnology in the form of 'Nanobiosensors'. This innovative technology has the potential to revolutionise sport, enabling real time biological data to be collected from athletes that can be electronically distributed. Enabling precise real time performance analysis is not without ethical problems. Arguments concerning (1) data ownership and privacy; (2) data confidentiality; and (3) athlete welfare are presented alongside a discussion of the use of the Precautionary Principle in making ethical evaluations. We conclude, that although the future potential use of Nanobiosensors in sports analysis offers many potential benefits, there is also a fear that it could be abused at a sporting system level. Hence, it is essential for sporting bodies to consider the development of a robust ethically informed governance framework in advance of their proliferated use. ispartof: SCIENCE AND ENGINEERING ETHICS vol:23 issue:6 pages:1487-1505 ispartof: location:England status: published

The quality and authenticity of images is essential for data presentation, especially in the life sciences. Questionable images may often be a first indicator for questionable results, too. Therefore, a tool that uses mathematical methods to detect suspicious images in large image archives can be a helpful instrument to improve quality assurance in publications. As a first step towards a systematic screening tool, especially for journal editors and other staff members who are responsible for quality assurance, such as laboratory supervisors, we propose a basic classification of image manipulation. Based on this classification, we developed and explored some simple algorithms to detect copied areas in images. Using an artificial image and two examples of previously published modified images, we apply quantitative methods such as pixel-wise comparison, a nearest neighbor and a variance algorithm to detect copied-and-pasted areas or duplicated images. We show that our algorithms are able to detect some simple types of image alteration, such as copying and pasting background areas. The variance algorithm detects not only identical, but also very similar areas that differ only by brightness. Further types could, in principle, be implemented in a standardized scanning routine. We detected the copied areas in a proven case of image manipulation in Germany and showed the similarity of two images in a retracted paper from the Kato labs, which has been widely discussed on sites such as pubpeer and retraction watch.