ELSI of New and Emerging Technologies

Two scientific domains that are crucial in “Biomedical Big Data”, computing and statistics, do not typically require “training in the responsible conduct of research” or research ethics. While “responsible conduct of research” (RCR) comprises interactions with subjects (human and non-human), it also involves interactions with other scientists, the scientific community, the public, and in some contexts, research funders. Historically, the development or emergence of disciplines and professions tend to involve a semi-simultaneous emergence of professional norms and/or codes of conduct. However, Biomedical Big Data is not emerging as a single discipline or profession, and engages practitioners from many diverse backgrounds. Moreover, the place of the data analyst or the computer scientist developing analytic algorithms seems to be too granular to be considered specifically within the activities that comprise “responsible research and innovation” (RRI). Current legal and policy-level considerations of Biomedical Big Data and RRI are implicitly assuming that scientists carrying out the research and achieving the innovations are exercising their scientific freedom – i.e., conducting research – responsibly. The assumption is that all scientists are trained to conduct research responsibly. In the United States, federal agencies funding research require that training in RCR be included – some of the time. Because the vast majority of research that was federally funded has not included Biomedical Big Data, RCR training paradigms have emerged over the past 20 years in US institutions that are not particularly relevant for Big Data. While it would be efficient to utilize such established, well-known, easily-documented RCR training programs, this chapter discusses how and why this is less likely to support the development of professional norms that are relevant for Biomedical Big Data. This chapter will describe an alternative approach that can support ongoing reflection on professional obligations, which can be used in a wide range of ethical, legal, and social implications (ELSI), including those that have not yet been identified. This may be the greatest strength of this alternative approach for preparing practitioners for Biomedical Big Data, because the ability to apply prior learning in ethics to previously unseen problems is especially critical in the current era of dynamic and massive data accumulation. To support the development of normative ethical practices among practitioners in Biomedical Big Data, this chapter reviews the guidelines for professional practice from three statistical associations (American Statistical Association; Royal Statistics Society; International Statistics Institute) and from the Association of Computing Machinery. These can be leveraged to ensure that, in their work with Biomedical Big Data, participants know and understand the ethical, legal, and social implications of that work. Formal integration of these (or other relevant) guidelines into the preparation for practice with data (big and small) can help in dealing with ethical challenges currently arising with Big Data in biomedical research; moreover, this integration can also help deal with challenges that have not yet arisen. These outcomes, which are consistent with recent calls for the institutionalization of reflection and reasoning around ELSI across scientific disciplines, in Europe, are only possible as long as the integration effort does not follow a currently-dominant paradigm for training in RCR.  Preparing scientists to engage competently in conversations around ethical issues in Biomedical Big Data requires purposeful, discipline-relevant, and developmental training that can come from, and support, a culture of ethical biomedical research and practice with Big Data.

Over the past 25 years, there has been growing recognition of the importance of studying the Ethical, Legal and Social Implications (ELSI) of genetic and genomic research. A large investment into ELSI research from the National Institutes of Health (NIH) Human Genomic Project budget in 1990 stimulated the growth of this emerging field; ELSI research has continued to develop and is starting to emerge as a field in its own right. The evolving subject matter of ELSI research continues to raise new research questions as well as prompt re-evaluation of earlier work and a growing number of scholars working in this area now identify themselves as ELSI scholars rather than with a particular discipline. Due to the international and interdisciplinary nature of ELSI research, scholars can often find themselves isolated from disciplinary or regionally situated support structures. We conducted a workshop with Early Career Researchers (ECRs) in Oxford, UK, and this paper discusses some of the par...

The Human Genome Project (HGP) has been hailed as an important milestone in the history of science, in the history of humanity even, and as a project whose completion would not only transform the practice of medicine, but change forever the course of human history as well. By setting up a flanking program devoted to anticipating and addressing the ethical, legal, and social implications of genomics, the HGP has had a substantial influence on the social sciences and humanities fields involved in studying contemporary science as well. In this article, the HGP is first of all placed in a historical perspective (as a key chapter in the history of the life sciences as such). As to the history of the HGP proper (1990–2003), three stages are
distinguished. Finally, the author assesses what the impact of the HGP has been, both for the life sciences as such and for the
society in a broader sense. Although biomedical benefits (in the form of new treatments, etc.) have been sparse (in comparison to the stellar expectations of the early years), the HGP did change the way we think about ourselves and our own history: Its ‘cultural’ relevance has been quite significant.

As artificial intelligence (AI) technologies become increasingly prominent in our daily lives, media coverage of the ethical considerations of these technologies has followed suit. Since previous research has shown that media coverage can drive public discourse about novel technologies, studying how the ethical issues of AI are portrayed in the media may lead to greater insight into the potential ramifications of this public discourse, particularly with regard to development and regulation of AI. This paper expands upon previous research by systematically analyzing and categorizing the media portrayal of the ethical issues of AI to better understand how media coverage of these issues may shape public debate about AI. Our results suggest that the media has a fairly realistic and practical focus in its coverage of the ethics of AI, but that the coverage is still shallow. A multifaceted approach to handling the social, ethical and policy issues of AI technology is needed, including inc...

Nos encontramos en una fase histórica clave: de un lado marcada por los potenciales que abren los nuevos desarrollos tecnocientíficos, y de otro por la amenaza de un colapso causado por la inminencia de las crisis socio-ecológica, energética y económica. El ritmo del desarrollo tecno-científico se ha acelerado enormemente. Sin embargo, a la vez que se ha incrementado el margen de lo posible, la capacidad para comprender y regular las tecnologías emergentes parece haber disminuido. Ante esta situación, es necesario tomar conciencia de que es la propia lógica de la modernización nos ha llevado a una situación que exige nuevas cotas de responsabilidad. Hacer al desafío que comportan las nuevas biotecnologías emergentes –en nuestro caso la biología sintética– exige una reflexión sobre las condiciones materiales, sociales y económicas que llevan a considerar “asumibles” los riesgos que estas novedades tecnocientíficas pueden implicar. Y eso implica cuestionar el propio modelo de investigación vigente.

The Adverse Outcome Pathway (AOP) concept is a knowledge assembly and communication tool to facilitate the transparent translation of mechanistic information into outcomes meaningful to the regulatory assessment of chemicals. The AOP framework and associated knowledgebases (KBs) have received significant attention and use in the regulatory toxicology community. However, it is increasingly apparent that the potential stakeholder community for the AOP concept and AOP KBs is broader than scientists and regulators directly involved in chemical safety assessment. In this paper we identify and describe those stakeholders who currently—or in the future—could benefit from the application of the AOP framework and knowledge to specific problems. We also summarize the challenges faced in implementing pathway-based approaches such as the AOP framework in biological sciences, and provide a series of recommendations to meet critical needs to ensure further progression of the framework as a useful, sustainable and dependable tool supporting assessments of both human health and the environment. Although the AOP concept has the potential to significantly impact the organization and interpretation of biological information in a variety of disciplines/applications, this promise can only be fully realized through the active engagement of, and input from multiple stakeholders, requiring multi-pronged substantive long-term planning and strategies.

The presence of experts holding patents and simultaneously providing policy advice on areas where they hold patents pose several normative questions. Through a comparative study of several IPCC reports, this article documents the scope of this phenomenon and discusses it with respect to a theory of conflict of interest. Seemingly, it is more likely to be patent-holders on issues of infrastructures, industry and transport rather than for single technologies as such. According to insights from studies on conflict of interest, there is an increased risk for bias. The article investigates the possible relations between patenting and conflicts of interest according to theoretical and empirical insights from the relation between science and society.

ABSTRACT Soft regulatory measures are often promoted as an alternative for existing regulatory regimes for nanotechnologies. The call for new regulatory approaches stems from several challenges that traditional approaches have difficulties dealing with. These challenges relate to general problems of governability, tensions between public interests, but also (and maybe particularly) to almost complete lack of certainty about the implications of nanotechnologies. At the same time, the field of nanotechnology can be characterized by a high level of diversity. In this paper, we discuss and compare two models for framing public policy in relation to technology regulation: the first is a deliberative model based on foresight knowledge and the second the wide reflective equilibrium model, developed by political philosopher John Rawls. In both models, the aim is to find consensus on (a framework for) policy measures and regulation. On the basis of a critical discussion of the strengths and weaknesses of both models, some tentative conclusions are drawn for effective policy making and implementation based on soft law.

Digital phenotyping represents an avenue of consideration in patients' self-management. This scoping review aims to explore the trends in the body of literature on ethical, legal, and social challenges relevant to the implementation of digital phenotyping technologies in healthcare. The study followed the PRISMA-ScR methodology (Tricco et al. in Ann Int Med 169(7):467–473, 2018. https://doi.org/10.7326/M18-0850). The review systematically identified relevant literature, characterised the discussed technology, explored its impacts and the proposed solutions to identified challenges. Overall, the literature, perhaps unsurprisingly, concentrates on technical rather than ethical, legal, and social perspectives, which limits understanding of the more complex cultural and social factors in which digital phenotyping technologies are embedded. ELS issues mostly concern privacy, security, consent, lack of regulation, and issues of adoptability, and seldom expand to more complex ethical i...

Over the past 25 years, there has been growing recognition of the importance of studying the Ethical, Legal and Social Implications (ELSI) of genetic and genomic research. A large investment into ELSI research from the National Institutes of Health (NIH) Human Genomic Project budget in 1990 stimulated the growth of this emerging field; ELSI research has continued to develop and is starting to emerge as a field in its own right. The evolving subject matter of ELSI research continues to raise new research questions as well as prompt re-evaluation of earlier work and a growing number of scholars working in this area now identify themselves as ELSI scholars rather than with a particular discipline. Due to the international and interdisciplinary nature of ELSI research, scholars can often find themselves isolated from disciplinary or regionally situated support structures. We conducted a workshop with Early Career Researchers (ECRs) in Oxford, UK, and this paper discusses some of the par...

Here you will find several talks that uniquely blend genomic science with Social Determinants of Health Theory. HEALTH IS CONTEXTUAL! And in the current context, we cannot honestly and ethically sample Indigenous populations without highlighting that there is NO TECHNOLOGICAL FIX for Structural Racism and Inherent Bias. Likely the "commons" of genomic information will be co-opted into Intellectual Property by any number of Corporations that would preclude any significant change to the Amerindigenous Health Disparity that exists today.

As artificial intelligence (AI) technologies become increasingly prominent in our daily lives, media coverage of the ethical considerations of these technologies has followed suit. Since previous research has shown that media coverage can drive public discourse about novel technologies, studying how the ethical issues of AI are portrayed in the media may lead to greater insight into the potential ramifications of this public discourse, particularly with regard to development and regulation of AI. This paper expands upon previous research by systematically analyzing and categorizing the media portrayal of the ethical issues of AI to better understand how media coverage of these issues may shape public debate about AI. Our results suggest that the media has a fairly realistic and practical focus in its coverage of the ethics of AI, but that the coverage is still shallow. A multifaceted approach to handling the social, ethical and policy issues of AI technology is needed, including inc...

Soft regulatory measures are often promoted as an alternative for existing regulatory regimes for nanotechnologies. The call for new regulatory approaches stems from several challenges that traditional approaches have difficulties dealing with. These challenges relate to general problems of governability, tensions between public interests, but also (and maybe particularly) to almost complete lack of certainty about the implications of nanotechnologies. At the same time, the field of nanotechnology can be characterized by a high level of diversity. In this paper, we discuss and compare two models for framing public policy in relation to technology regulation: the first is a deliberative model based on foresight knowledge and the second the wide reflective equilibrium model, developed by political philosopher John Rawls. In both models, the aim is to find consensus on (a framework for) policy measures and regulation. On the basis of a critical discussion of the strengths and weaknesses of both models, some tentative conclusions are drawn for effective policy making and implementation based on soft law.