Recently, there has been an upsurge of attention focused on bias and its impact on specialized artificial intelligence applications. Allegations of racism and sexism have permeated the conversation as stories surface about search engines delivering job postings for well-paying technical jobs to men and not women, or providing arrest mugshots when keywords such as “black teenagers” are entered. Learning algorithms are evolving; they are often created from parsing through large datasets of online information while having truth labels bestowed on them (...) by crowd-sourced masses. These specialized AI algorithms have been liberated from the minds of researchers and startups, and released onto the public. Yet intelligent though they may be, these algorithms maintain some of the same biases that permeate society. They find patterns within datasets that reflect implicit biases and, in so doing, emphasize and reinforce these biases as global truth. This paper describes specific examples of how bias has infused itself into current AI and robotic systems, and how it may affect the future design of such systems. More specifically, we draw attention to how bias may affect the functioning of a robot peacekeeper, a self-driving car, and a medical robot. We conclude with an overview of measures that could be taken to mitigate or halt bias from permeating robotic technology. (shrink)

Over the last decade, more U.S. taxpayers money has been spent trying to anticipate and address the bioethical issues raised by advances in human genetics than any other set of issues in the field. Does this make sense? Not everyone in bioethics thinks so. Some think there are more important topics, like issues of health care justice, that will be neglected if the field continues to follow the money to dwell on the moral challenges of a relatively small community of (...) research scientists. Others decry genetic exceptionalism as inappropriately singling out this scientific enterprise for criticism and regulation, when the same issues are faced even more acutely in other parts of the biomedical world. Human genetics is not accelerating as fast as pharmacology, for example, or as easy to abuse as virology, or as philosophically challenging as neurology. (shrink)

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...) of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: informed consent, privacy, ownership, epistemology and objectivity, and ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: the dangers of ignoring group-level ethical harms; the importance of epistemology in assessing the ethics of Big Data; the changing nature of fiduciary relationships that become increasingly data saturated; the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; future problems with ownership of intellectual property generated from analysis of aggregated datasets; and the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices. (shrink)

Empirical evidence suggests that while people hold the capacity to control their data in high regard, they increasingly experience a loss of control over their data in the online world. The capacity to exert control over the generation and flow of personal information is a fundamental premise to important values such as autonomy, privacy, and trust. In healthcare and clinical research this capacity is generally achieved indirectly, by agreeing to specific conditions of informational exposure. Such conditions can be openly stated (...) in informed consent documents or be implicit in the norms of confidentiality that govern the relationships of patients and healthcare professionals. However, with medicine becoming a data-intense enterprise, informed consent and medical confidentiality, as mechanisms of control, are put under pressure. In this paper we explore emerging models of informational control in data-intense healthcare and clinical research, which can compensate for the limitations of currently available instruments. More specifically, we discuss three approaches that hold promise in increasing individual control: the emergence of data portability rights as means to control data access, new mechanisms of informed consent as tools to control data use, and finally, new participatory governance schemes that allow individuals to control their data through direct involvement in data governance. We conclude by suggesting that, despite the impression that biomedical big data diminish individual control, the synergistic effect of new data management models can in fact improve it. (shrink)

Our society currently faces many complex and perplexing issues related to biotechnology, including the need to define the outer boundaries of genetic research on human beings and the need to protect individual and group rights to human tissue and the knowledge gained from the study of that tissue. Scientists have increasingly become interested in studying so-called “population isolates” to discover the nature and location of genes that are unique to particular groups. Indigenous peoples are often targeted by scientists because “the (...) relative isolation of the communities ensures minimal gene flow.” Such studies raise a number of issues related to privacy rights, property rights, informed consent, and group rights versus individual rights. These issues recently came to light in a case brought by the Havasupai Tribe and its members over the use of blood samples, handprints, and genealogy information initially taken by researchers at Arizona State University for a diabetes project. These materials were then allegedly used by researchers at ASU and other institutions for a multitude of unauthorized purposes, including research into the frequency of mental health disorders and the origin of human populations. Consequently, the affected members sued for damages under several legal theories. However, underlying all of these claims was the allegation that this unauthorized use of genetic resources and data not only injured the individuals who gave samples, but also caused a collective harm to the Havasupai Tribe and the cultural and spiritual beliefs of its members. (shrink)

The genetic revolution is well underway, with genetic research and knowledge expanding at an exponential rate. Much of the new genetics research is focused on population groups, and proponents of “population genomics” argue that such studies are necessary since genetic “variation” among human populations holds the most promise for technological innovations that can improve human health and lead to increased understanding of the origin of human populations. Population genomic research thus targets specific groups to discover variation that could lead to (...) knowledge about genetic disorders, possible cures, and the origin and migration patterns of distinctive peoples. Research on genetic differences among groups or populations, however, raises many pressing ethical and legal questions. For example, focus on biological differences of racial and ethnic groups has in the past lead to assumptions about superiority and inferiority between groups, and in practice resulted in stigmatization and discrimination. Consequently, attention on groups should raise legal and moral red flags and compel us to move cautiously in this area. Pragmatically, targeting population groups as the object of study requires the determination of the nature and scope of “population groups” for purposes of genetics research. (shrink)

The United States’ ambitious Precision Medicine Initiative proposes to accelerate exponentially the adoption of precision medicine, an approach to health care that tailors disease diagnosis, treatment, and prevention to individual variability in genes, environment, and lifestyle. It aims to achieve this by creating a cohort of volunteers for precision medicine research, accelerating biomedical research innovation, and adopting policies geared toward patients’ empowerment. As strategies to implement the PMI are formulated, critical consideration of the initiative's ethical and sociopolitical dimensions is needed. (...) Drawing on scholarship of nationalism and democracy, we discuss the PMI's construction of what we term “genomic citizenship”; the possible normative obligations arising therefrom; and the ethical, legal, and social challenges that will ensue. Although the PMI is a work in progress, discussion of the existing and emerging issues can facilitate the development of policies, structures, and procedures that can maximize the initiative's ability to produce equitable and socially sensitive outcomes. Our analysis can also be applied to other population-based, precision medicine research programs. (shrink)

ABSTRACT Genetics research, like research in sociology and anthropology, creates risks for groups from which research subjects are drawn. This paper considers what sort of protection for groups from the risks of genetics research should be provided and by whom. The paper categorizes harms by distinguishing process‐related from outcome‐related harms and by distinguishing two kinds of group harms. It argues that calls for community engagement are justified with respect to some kinds of harms, but not with respect to others; and (...) it cautions that community engagement may itself be harmful. (shrink)

Vulnerability is one of the least examined concepts in research ethics. Vulnerability was linked in the Belmont Report to questions of justice in the selection of subjects. Regulations and policy documents regarding the ethical conduct of research have focused on vulnerability in terms of limitations of the capacity to provide informed consent. Other interpretations of vulnerability have emphasized unequal power relationships between politically and economically disadvantaged groups and investigators or sponsors. So many groups are now considered to be vulnerable in (...) the context of research, particularly international research, that the concept has lost force. In addition, classifying groups as vulnerable not only stereotypes them, but also may not reliably protect many individuals from harm. Certain individuals require ongoing protections of the kind already established in law and regulation, but attention must also be focused on characteristics of the research protocol and environment that present ethical challenges. (shrink)

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are (...) discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission—aiding infection control measures and policies—emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: automation and algorithmic reliance impacting freedom of choice, big data analytics complexity impacting informed consent, reliance on profiling impacting individual and group identities and justice/fair access and increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement. (shrink)

: This essay distinguishes between two kinds of group harms: harms to individuals in virtue of their membership in groups and harms to "structured" groups that have a continuing existence, an organization, and interests of their own. Genetic research creates risks of causing both kinds of group harms, and engagement with the groups at risk can help to mitigate those harms. The two kinds of group harms call for different kinds of group engagement.

In July 2000, the Seminole Nation of Oklahoma passed a resolution that would effectively expel a significant portion of its tribal members. The resolution amended the Nation's constitution by changing its membership criteria. Previously, potential members needed to show descent from an enrollee of the 1906 Dawes Rolls, the official American Indian tribal rolls established by the Dawes Commission to facilitate the allotment of reservation land. The amended constitution requires possession of one-eighth Seminole Indian blood, a requirement that a significant (...) portion of the tribe's membership cannot fulfill. The members of the Nation who fail to meet this new membership criterion all have one thing in common: they are black.Descendents of former slaves who came to live among the Seminole Indians of Florida in the seventeenth and eighteenth centuries, the black Seminoles have been officially recognized by the U.S. government as members of the Seminole Nation of Oklahoma since 1866. (shrink)

Strategies for protecting historically disadvantaged groups have been extensively debated in the context of genetic variation research, making this a useful starting point in examining the protection of social groups from harm resulting from biomedical research. We analyze research practices developed in response to concerns about the involvement of indigenous communities in studies of genetic variation and consider their potential application in other contexts. We highlight several conceptual ambiguities and practical challenges associated with the protection of group interests and argue (...) that protectionist strategies developed in the context of genetic research will not be easily adapted to other types of research in which social groups are placed at risk. We suggest that it is this set of conceptual and practical issues that philosophers, ethicists, and others should focus on in their efforts to protect identifiable social groups from harm resulting from biomedical research. (shrink)

Expectations are high around the world that more research on human genomic variation will improve the utility of “precision medicine” and help address population health disparities through “precision public health”. In large measure, these expectations rest on the premise that researchers will be able to share human DNA samples and genomic data freely and widely across the international scientific community. The human genomics community pioneered polices of early deposit of genomic research data into open databases to facilitate the exchange and (...) use of data during the mapping and sequencing of the human genome in the 1990s, and the success of those policies has made a... (shrink)

Meaningful participant engagement has been identified as a key contributor to the success of efforts to share data via a “Medical Information Commons”. We present findings from expert stakeholder interviews aimed at understanding barriers to engagement and the appropriate role of MIC participants. Although most interviewees supported engagement, they distinguished between individual versus collective forms. They also noted challenges including representation and perceived inefficiency, prompting reflection on political aspects of engagement and efficiency concerns.

Global health research partnerships are increasingly taking the form of consortia of institutions from high-income countries and low- and middle-income countries that undertake programs of research. These partnerships differ from collaborations that carry out single projects in the multiplicity of their goals, scope of their activities, and nature of their management. Although such consortia typically aim to reduce health disparities between and within countries, what is required for them to do so has not been clearly defined. This article takes a (...) conceptual approach to explore how the governance of transnational global health research consortia should be structured to advance health equity. To do so, it applies an account called shared health governance to derive procedural and substantive guidance. A checklist based on this guidance is proposed to assist research consortia determine where their governance practices strongly promote equity and where they may fall short. (shrink)

Paul Appelbaum and colleagues propose four models of informed consent to research that deploys whole genome sequencing and may generate incidental findings. They base their analysis on empirical data that suggests that research participants want to be offered incidental findings and on a normative consensus that researchers incur a duty to offer them. Their models will contribute to the heated policy debate about return of incidental findings. But in my view, they do not ask the foundational question, In the context (...) of genome sequencing, how much work can consent be asked to do? (shrink)

Although scientific and commercial excitement about genomic biobanks has subsided since the biotech bust in 2000, they continue to fascinate life scientists, bioethicists, and politicians alike. Indeed, these assemblages of personal health information, human DNA, and heterogeneous capital have become and remain important events in the ethics and politics of the life sciences. For starters, they continue to reveal and produce the central scientific, technological, and economic paradigms so ascendant in biology today: genome, infotech, and market. Biobanks also illustrate what (...) might be called the new distributive politics of biomedical research. Within those politics, the commodification of persons – or at the very least, of their informational representations – has challenged the ontological, ethical, and political underpinnings of the social contract between researchers and their human research subjects. In brief, biobanks are unsettling relations between genes, tissue, medical records, and persons. But it is also clear that these relations are increasingly being restructured by new rights of control, access, exclusion, and use known as “property,” both material and intellectual. (shrink)