Abstract
Much bioethical literature and policy guidances for big data analytics in biomedical research emphasize the importance of trust. It is essential that potential participants trust so they will allow their data to be used to further research. However, comparatively, little guidance is offered as to what trustworthy oversight mechanisms are, or how policy should support them, as data are collected, shared, and used. Generally, “trust” is not characterized well enough, or meaningfully enough, for the term to be systematically applied in policy development. Yet points made in the philosophical literature on trust can help. They allow us, not only to better distinguish the different ways the term “trust” may be interpreted, but also to better determine how different approaches to trust can align with policy and governance—in what ways they may relate to key bioethical concepts and related laws, and in what ways they can help to balance individual and group interests in data sharing. This article draws from the philosophical literature on trust to identify a relationship among consent, trust, and justice. Specifically, parallels are drawn between “character-trustworthiness” and “natural justice,” a set of widely held legal safeguards intended to ensure decision-makers follow a pattern of procedural fairness which protects the rights of the individual and thereby maintains public confidence in the decision-making process. Relevance to traditional bioethical principles, established laws, and consent procedures are addressed throughout. In conclusion, policy actions are suggested.
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Notes
Big data analytics (BDA) is a broad term. There are cases where new forms of data-enabled research in biomedicine concern new analytical capabilities which allow for an exponential increase in the volume of similar kinds of data. A paradigmatic example in genomics is genome-wide association studies (GWAS). And there are also cases where they concern analytic abilities in the “cross-matching” of multiple data types. Though, depending on the ethical legal considerations surrounding different kinds of data sets, the logistical and regulatory differences between them can be great; for simplicity’s sake, I use “BDA” to refer to both of these forms of data-enabled research.
Adherence to this priority helps ensure practices remain in accordance with the Universal Declaration of Human Rights (United Nations 1948) and related UNESCO Declarations on the human genome, human genetic data, and bioethics (UNESCO 1997, 2003, 2005), as well as with ethical duties, legal instruments, and official guidelines consistent with these, such as the recent Declaration of Taipei (World Medical Association 2016).
“Mission drift” is where consent conditions, the original parameters of an agreement to have one’s data collected and used, become decoupled from actual usage of the data.
The ethical considerations underlying different forms of consent is a source of great debate, yet that topic is beyond the scope of this article.
We see this desire to share personal data, for instance, among participants who seek to advance research on rare or undiagnosed diseases.
In addition to transparency, participation, and inclusion, protection of individuals is stressed. In language very similar to that found in UNESCO declarations on bioethics, the human genome, and genetic data, it also states, “Governance should be designed so the rights of individuals prevail over the interests of other stakeholders and science.”
The meanings of and distinctions between “trust,” “trusting,” and “trustworthiness” can vary in the philosophical literature, depending upon what theory is being applied. For the purposes of this article, “trust” is a relation between one who “trusts” and another person or entity who is “trustworthy.” The trust relation holds only where the former deems the latter to be trustworthy.
In the decades since it was introduced by Beauchamp and Childress, the influence of the four principles approach has steadily grown. But it is not without its critics. One point of contention is whether or not deliberation as to how to best balance them in any given context a rational or an intuitive process. Another is whether or not the principles are merely cultural constructs, susceptible to the same relativizing critiques as any other normative framework. The epistemic and metaethical status of the principles themselves is subject to debate.
For instance, the International Ethical Guidelines for Biomedical Research Involving Human Subjects Council for International Organizations of Medical Sciences.
For instance, beneficence applied in isolation from autonomy amounts to no more than a consequentialist approach. Potential participants in research have no say on the “good” being pursued in a type of research, as one does when considering whether or not to support a particular research mission statement (below). Attempting to isolate beneficence in this way stands opposed to the rights-based, deontological frameworks put in place by traditional bioethics and much related law (below), making it quite difficult to come to any agreement as to how the principle of justice should apply, let alone how justice should be administered in policy, practice, or law.
For instance, informed consent procedures may sometimes be in place to protect biobanks against potential litigation, rather than for the participant’s benefit.
“Dynamic consent,” in a general sense, refers to a consent process where individuals can give, revoke, or modify their permissions over time whenever their samples or data may be used in new research projects. It allows for different kinds of consent for different kinds of research. Here, the term also refers to a specific project in the field which is developing ICT interfaces of this type that satisfy regulatory requirements for consent (Kaye et al. 2015).
“By advancing scientific knowledge, the research community reciprocates and ‘pays back’ the participant’s volunteerism. A sense of community among participants can help bridge the gap between societal and individual rewards” (Erlich et al. 2014). However, their approach to dynamic consent prevents the model from being entirely based on these encapsulated interests.
For more on this last point, see the insightful analysis of risk by Jonathan Wolff (Wolff 2010).
For instance, one may have an interest in marketing cigarettes to children, while another may have an interest in protecting the health of his child, while that child might have an interest in learning to smoke.
See for example, the International Ethical Guidelines for Biomedical Research Involving Human Subjects Council for International Organizations of Medical Sciences.
It is worth noting that, while this can be quite a difficult process, it is not unlike what a typical ethics oversight committee routinely does when approving biomedical research proposals.
For instance, if one is to adjudicate over the interests involved in marketing cigarettes to children, the adjudicator should not have a financial interest in the selling of cigarettes and should instead be motivated by concern for the rights and well-being of all stakeholders.
This usage of “good” is in keeping with Aristotle’s, Mill’s, Kant’s, and Rawls’ initial uses, prior to the application of eudaimonic, utilitarian, and deontological constraints, respectively. Some may say this “economic” approach of reducing values to interests has little consequence for either rational or moral arguments, that it is no more than a method of “analytical book-keeping” (Simpson 2013). They would be right. And this is the intent. The point is to abstain from making any judgements about value systems at the individual level by divesting any one value system from a claim to moral absoluteness. Instead, moral judgments are to be made at the societal level by applying the constraints of natural justice. This is key to addressing issues of governance in that it ensures that both rational and normative arguments remain at the societal level, and can easily be distinguished from the individual level.
The claim is it is rational not to trust B when B has no interest in being trustworthy. It is not a claim that trust must be understood as being purely rationally-based. As noted above, trust may have many dimensions, rationality being only one. Baier, for instance, holds that trust is not something abstract and rationally determined so much as, following in the vein of David Hume, a result of the cultivation of relationships through virtuous character traits, such as sympathy or compassion. Perception of these may be better attributed to “emotional” rather than “rational” intelligence. Yet, here too, one can speak in terms of goodwill toward another’s interest, although in ways different than in rationalistic or contractarian frameworks. One would not say is it “not rational” to trust, rather one might say “trustworthiness is in doubt” (before a trust relation is established) or “trust is betrayed” (when a trust relation breaks down).
Such as in cases where there are in immediate dangers to public health and safety due to spread of infectious diseases and pandemics.
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Acknowledgments
This work was made possible by a Fellowship at Harris Manchester College, University of Oxford and the Center for Health, Law, and Emerging Technologies (HeLEX), Nuffield Department of Population Health, University of Oxford. My thanks go to Tom Simpson for sharing his unpublished essay discussed in this article, and to the reviewers of this article whose feedback helped to improve it substantially.
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The author is a member of the Global Alliance for Genomics and Health and has helped produce some of the policy documents and ICT tools highlighted in the article.
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Woolley, J.P. Trust and Justice in Big Data Analytics: Bringing the Philosophical Literature on Trust to Bear on the Ethics of Consent. Philos. Technol. 32, 111–134 (2019). https://doi.org/10.1007/s13347-017-0288-9
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DOI: https://doi.org/10.1007/s13347-017-0288-9