Louise Bezuidenhout

In this chapter, we propose a non-traditional RCR training in data science that is grounded in a virtue theory framework. First, we delineate the approach in more theoretical detail by discussing how the goal of RCR training is to foster the cultivation of certain moral abilities. We specify the nature of these ‘abilities’: while the ideal is the cultivation of virtues, the limited space allowed by RCR modules can only facilitate the cultivation of superficial abilities or proto-virtues, which help students to familiarize themselves with moral and political issues in the data science environment. Third, we operationalize our approach by stressing that (proto-)virtue acquisition (like skill acquisition) occurs through the technical and social tasks of daily data science activities, where these repetitive tasks provide the opportunities to develop (proto-)virtue capacity and to support the development of ethically robust data systems. Finally, we discuss a concrete example of implementing this approach. In particular, we describe how this method is applied to teach data ethics to students participating in the CODATA-RDA Data Science Summer Schools.

Development-oriented funding schemes such as the UK Global Challenges Research Fund (GCRF) have opened up opportunities for collaborations between low-middle income countries (LMICs) and high-income country (HIC) researchers. In particular, funding for medical technology research has seen a rise in previously under-represented disciplines such as physics and engineering. These collaborations have considerable potential to advance healthcare in LMICs, yet can pose challenges experienced to researchers undertaking these collaborations. Key challenges include a lack of tradition of HIC/LMIC collaborations within participating departments, lack of experience with development agendas, designing contextually-appropriate technologies and ensuring long-term viability of research outputs. This paper reflects on these key challenges, using the experiences of the authors on the Open Laboratory Instrumentation (OLI) project as a focalizing lens. This project was a GCRF-funded collaboration between physicists in the UK and engineers in Tanzania to develop an open-source, 3D-printed, fully-automated laboratory microscope. The paper highlights key ethics lessons learnt.

Development-oriented funding schemes such as the UK Global Challenges Research Fund (GCRF) have opened up opportunities for collaborations between low-middle income countries (LMICs) and high-income country (HIC) researchers. In particular, funding for medical technology research has seen a rise in previously under-represented disciplines such as physics and engineering. These collaborations have considerable potential to advance healthcare in LMICs, yet can pose challenges experienced to researchers undertaking these collaborations. Key challenges include a lack of tradition of HIC/LMIC collaborations within participating departments, lack of experience with development agendas, designing contextually-appropriate technologies and ensuring long-term viability of research outputs. This paper reflects on these key challenges, using the experiences of the authors on the Open Laboratory Instrumentation (OLI) project as a focalizing lens. This project was a GCRF-funded collaboration between physicists in the UK and engineers in Tanzania to develop an open-source, 3D-printed, fully-automated laboratory microscope. The paper highlights key ethics lessons learnt.

Development-oriented funding schemes such as the UK Global Challenges Research Fund (GCRF) have opened up opportunities for collaborations between low-middle income countries (LMICs) and high-income country (HIC) researchers. In particular, funding for medical technology research has seen a rise in previously under-represented disciplines such as physics and engineering. These collaborations have considerable potential to advance healthcare in LMICs, yet can pose challenges experienced to researchers undertaking these collaborations. Key challenges include a lack of tradition of HIC/LMIC collaborations within participating departments, lack of experience with development agendas, designing contextually-appropriate technologies and ensuring long-term viability of research outputs. This paper reflects on these key challenges, using the experiences of the authors on the Open Laboratory Instrumentation (OLI) project as a focalizing lens. This project was a GCRF-funded collaboration between physicists in the UK and engineers in Tanzania to develop an open-source, 3D-printed, fully-automated laboratory microscope. The paper highlights key ethics lessons learnt.

In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students.

Data science skills are rapidly becoming a necessity in modern science. In response to this need, institutions and organizations around the world are developing research data science curricula to teach the programming and computational skills that are needed to build and maintain data infrastructures and maximize the use of available data. To date, however, few of these courses have included an explicit ethics component, and developing such components can be challenging. This paper describes a novel approach to teaching data ethics on short courses developed for the CODATA-RDA Schools for Research Data Science. The ethics content of these schools is centred on the concept of open and responsible science citizenship that draws on virtue ethics to promote ethics of practice. Despite having little formal teaching time, this concept of citizenship is made central to the course by distributing ethics content across technical modules. Ethics instruction consists of a wide range of techniques, including stand-alone lectures, group discussions and mini-exercises linked to technical modules. This multi-level approach enables students to develop an understanding both of “responsible and open science citizenship”, and of how such responsibilities are implemented in daily research practices within their home environment. This approach successfully locates ethics within daily data science practice, and allows students to see how small actions build into larger ethical concerns. This emphasises that ethics are not something “removed from daily research” or the remit of data generators/end users, but rather are a vital concern for all data scientists.

ABSTRACTThere has considerable interest in bringing low/middle-income countries scientists into discussions on Open Data – both as contributors and users. The establishment of in situ data sharing practices within LMIC research institutions is vital for the development of an Open Data landscape in the Global South. Nonetheless, many LMICs have significant challenges – resource provision, research support and extra-laboratory infrastructures. These low-resourced environments shape data sharing activities, but are rarely examined within Open Data discourse. In particular, little attention is given to how these research environments shape scientists’ perceptions of data sharing incentives. This paper expands on these issues of incentivizing data sharing, using data from a quantitative survey disseminated to life scientists in 13 countries in sub-Saharan Africa. This interrogated not only perceptions of data sharing amongst LMIC scientists, but also how these are connected to the research environm...

BackgroundThe widespread sharing of biological and biomedical data is recognised as a key element in facilitating translation of scientific discoveries into novel clinical applications and services. At the same time, twenty-first century states are increasingly concerned that this data could also be used for purposes of bioterrorism. There is thus a tension between the desire to promote the sharing of data, as encapsulated by the Open Data movement, and the desire to prevent this data from ‘falling into the wrong hands’ as represented by ‘dual use’ policies. Both frameworks posit a moral duty for life sciences researchers with respect to how they should make their data available. However, Open data and dual use concerns are rarely discussed in concert and their implementation can present scientists with potentially conflicting ethical requirements.DiscussionBoth dual use and Open data policies frame scientific data and data dissemination in particular, though different, ways. As such they contain implicit models for how data is translated. Both approaches are limited by a focus on abstract conceptions of data and data sharing. This works to impede consensus-building between the two ethical frameworks. As an alternative, this paper proposes that an ethics of responsible management of scientific data should be based on a more nuanced understanding of the everyday data practices of life scientists. Responsibility for these ‘micromovements’ of data must consider the needs and duties of scientists as individuals and as collectively-organised groups.SummaryResearchers in the life sciences are faced with conflicting ethical responsibilities to share data as widely as possible, but prevent it being used for bioterrorist purposes. In order to reconcile the responsibilities posed by the Open Data and dual use frameworks, approaches should focus more on the everyday practices of laboratory scientists and less on abstract conceptions of data.

In recent years there have been major shifts in how the role of science—and scientists—are understood. The critical examination of scientific expertise within the field of Science and Technology Studies are increasingly eroding notions of the “otherness” of scientists. It would seem to suggest that anyone can be a scientist—when provided with the appropriate training and access to data. In contrast, however, ethnographic evidence from the scientific community tells a different story. Scientists are quick to recognize that not everyone can—or should—be a scientist. Appealing to notions such as “good hands” or “gut feelings”, scientists narrate a distinction between good and bad scientists that cannot be reduced to education, access, or opportunity. The key to good science requires scientists to express an intuitive feeling for their discipline, but also that individuals derive considerable personal satisfaction from their work. Discussing this personal joy in—and “fittingness” of—scientific occupations using the fields of STS, ethics and science policy is highly problematic. In this paper we turn to theology discourse to analyze the notion of “callings” as a means of understanding this issue. Callings highlight the identification and examination of individual talents to determine fit occupations for specific persons. Framing science as a calling represents a novel view of research that places the talents and dispositions of individuals and their relationship to the community at the center of flourishing practices.

Most scientists recognize the importance of sharing data online in an open fashion. Nonetheless, many studies have documented the concerns that accompany data sharing activities, including loss of credit or IP, misuse and the time needed to curate interoperable data. To this end, discussions around data sharing often identify incentives that could potentially ameliorate these disincentivising concerns. Nonetheless, current Open Data discussions often rely on evidence‐based studies to identify the disincentives to overcome. This results in highly specific and directed interventions. In contrast, this paper offers a different interpretation of these concerns. To do so, it makes use of the Thomas Theorem which suggests that: “If men define situations as real, they are real in their consequences”. Using empirical evidence from sub‐Saharan African (bio)chemistry laboratories, this paper illustrates how individual perceptions of research environments – whether associated with evidence or not – are highly influential in shaping data sharing practices. It concludes with the suggestion that discussion on incentivising data sharing amongst scientific communities need to take a broader set of concerns into account and offer a more creative approach to ameliorating environmental disincentives.

The life sciences are increasingly being called on to produce “socially robust” knowledge that honors the social contract between science and society. This has resulted in the emergence of a number of “broad social issues” that reflect the ethical tensions in these social contracts. These issues are framed in a variety of ways around the world, evidenced by differences in regulations addressing them. It is important to question whether these variations are simply regulatory variations or in fact reflect a contextual approach to ethics that brings into question the existence of a system of “global scientific ethics”. Nonetheless, within ethics education for scientists these broad social issues are often presented using this scheme of global ethics due to legacies of science ethics pedagogy. This paper suggests this may present barriers to fostering international discourse between communities of scientists, and may cause difficulties in harmonizing (and transporting) national regulations for the governance of these issues. Reinterpreting these variations according to how the content of ethical principles is attributed by communities is proposed as crucial for developing a robust international discourse. To illustrate this, the paper offers some empirical fieldwork data that considers how the concept of dual-use (as a broad social issue) was discussed within African and UK laboratories. Demonstrating that African scientists reshaped the concept of dual-use according to their own research environmental pressures and ascribed alternative content to the principles that underpin it, suggests that the limitations of a “global scientific ethics” system for these issues cannot be ignored

The concept of dual-use encapsulates the potential for well-intentioned, beneficial scientific research to also be misused by a third party for malicious ends. The concept of dual-use challenges scientists to look beyond the immediate outcomes of their research and to develop an awareness of possible future (mis)uses of scientific research. Since 2001 much attention has been paid to the possible need to regulate the dual-use potential of the life sciences. Regulation initiatives fall under two broad categories—those that develop the ethical education of scientists and foster an awareness and responsibility of dual-use issues, and those which assess the regulation of information being generated by current research. Both types of initiatives are premised on a cautious, risk-adverse philosophy which advocates careful examination of all future endpoints of research endeavors. This caution advocated within initiatives such as pre-publication review of journal articles contrasts to the obligation to share underpinning data sharing discussions. As the dual-use debate has yet to make a significant impact on data sharing discussions (and vice versa) it is possible that these two areas of knowledge control may present areas of ethical conflict for scientists, and thus need to be more closely examined. This paper examines the tension between the obligation to share exemplified by data sharing principles and the concerns raised by the risk-cautious culture of the dual-use debates. The paper concludes by reflecting on the issues of responsibility as raised by dual-use as relating to data sharing, such as the chain of custody for shared data

Studies of science are increasingly drawing attention to the highly communal nature of research. Ethics, sociology, philosophy, and anthropology of science all emphasize the key role that collaborative actions play in the generation of scientific knowledge. Nonetheless, despite the increasing interest in these communal aspects of scientific research, studies on the relationships underpinning communality are commonly focused on the how the individual interacts with their peers and contributes to the epistemic activities of science. In contrast, there is little literature that broadens out the scope of this analysis to consider the multidimensional nature of these research relationships. In particular, little is said about how scientists mediate their social interactions with peers during daily laboratory research. Less, indeed, is said about the tradition of ‘learning through example’ that characterizes most in situ laboratory training.All of these relational activities are of critical importance in sustaining and perpetuating the practice of science. It therefore becomes important to ask how we understand these relational activities directed towards building and sustaining relationships in different loci for the primary purpose of strengthening the practice of research and sustaining the traditions of scientific research. Moreover, it is vital to consider how discussions on responsibility may be cached out for individual scientists.This article employs a virtue ethics approach to consider these issues. It begins by sketching out the plethora of different relationships present in daily laboratory practice using existing ethnographic studies. It then uses virtue ethics to identify specific responsibilities that individual scientists have in cultivating and safeguarding the development of these relationships. It concludes by suggesting ways in which these issues may be taken up in teaching responsible conduct to scientists.

Responsibility within life science research is a highly scrutinised field. Increasingly, scientists are presented with a range of duties and expectations regarding their conduct within the research setting. In many cases, these duties are presented deontologically, forgoing extensive discussion on how these are practically implemented into the minutiae of daily research practices. This de-contextualized duty has proven problematic when it comes to practical issues of compliance, however it is not often considered as a fundamental aspect of building ethics discourse. This paper examines this issue in detail, particularly focusing on how differences in the contrasts between the ideal and real physical research environments cause conceptual problems for scientists and retard ethical engagement. Such issues are particularly pertinent in low- and middle-income countries. This paper combines theoretical and empirical analyses using the concept of “dual-use” as a focalizing topic. The data show that the research environment acts as an intimate component in the interpretation and implementation of ethical actions

In recent months months the hashtag #overlyhonestmethods has steadily been gaining popularity. Posts under this hashtag—presumably by scientists—detail aspects of daily scientific research that differ considerably from the idealized interpretation of scientific experimentation as standardized, objective and reproducible. Over and above its entertainment value, the popularity of this hashtag raises two important points for those who study both science and scientists. Firstly, the posts highlight that the generation of data through experimentation is often far less standardized than is commonly assumed. Secondly, the popularity of the hashtag together with its relatively blasé reception by the scientific community reveal that the actions reported in the tweets are far from shocking and indeed may be considered just “part of scientific research”. Such observations give considerable pause for thought, and suggest that current conceptions of data might be limited by failing to recognize this “inherent variability” within the actions of generation—and thus within data themselves. Is it possible, we must ask, that epistemic virtues such as standardization, consistency, reportability and reproducibility need to be reevaluated? Such considerations are, of course, of particular importance to data sharing discussions and the Open Data movement. This paper suggests that the notion of a “moral professionalism” for data generation and sharing needs to be considered in more detail if the inherent variability of data are to be addressed in any meaningful manner

A linguistic barrier between healthcare professional and patient is a challenging experience for both parties. In many cases, the absence of formally trained medical interpreters necessitates that an informal interpreter, drawn from the immediate environment, be used to facilitate communication. While the presence of an interpreter in a medical interview raises many questions about the effectiveness of the communication between healthcare professional and patient, it also gives rise to new speculations revolving on patient rights, medical ethics and patient privacy. In this article we examine the concept of communication competency in medical interviews, as well as translation theory, and link these theories to Western medical ethics in order to identify potential areas in which informal interpretation could impact on the patient

The dual-use issue is often framed as a series of paralyzing ‘dilemmas’ facing the scientific community as well as institutions which support innovation. While this conceptualization of the dual-use issue can be useful in certain contexts its usefulness is more limited when reflecting on the governance and politics of the dual-use issue. Within this paper, key shortcomings of the dilemma framing are outlined. It is argued that many of the issues raised in the most recent debates about ‘dual-use’ bird flu research remain unresolved. This includes questions about the trajectories of certain lines of research, as well as broader trends in the practice and governance of science. This leads to difficult questions about current approaches to the dual-use issue within the US, as well as internationally