Background Informed consent is one of the key principles of conducting research involving humans. When research participants give consent, they perform an act in which they utter, write or otherwise provide an authorisation to somebody to do something. This paper proposes a new understanding of the informed consent as a compositional act. This conceptualisation departs from a modular conceptualisation of informed consent procedures. Methods This paper is a conceptual analysis that explores what consent is and what it does or does (...) not do. It presents a framework that explores the basic elements of consent and breaks it down into its component parts. It analyses the consent act by first identifying its basic elements, namely: a) data subjects or legal representative that provides the authorisation of consent; b) a specific thing that is being consented to; and c) specific agent(s) to whom the consent is given. Results This paper presents a framework that explores the basic elements of consent and breaks it down into its component parts. It goes beyond only providing choices to potential research participants; it explains the rationale of those choices or consenting acts that are taking place when speaking or writing an authorisation to do something to somebody. Conclusions We argue that by clearly differentiating the goals, the procedures of implementation, and what is being done or undone when one consent, one can better face the challenges of contemporary data-intensive biomedical research, particularly regarding the retention and use of data. Conceptualising consent as a compositional act enhances more efficient communication and accountability and, therefore, could enable more trustworthy acts of consent in biomedical science. (shrink)

A great many important decisions we make in life depend on scientific information that we are not in a position to assess. So it seems we must defer to experts. By now there are a variety of criteria on offer by which non-experts can judge the trustworthiness of a scientist responsible for producing or promulgating this information. But science is, for the most part, a collective not an individual enterprise. This paper explores which of the criteria for judging the trustworthiness (...) of individual scientists can be amended for use in assessing the trustworthiness of scientific collectives. It also offers some new proposals specifically geared to assessing collective trustworthiness in science, notably, an analysis of where to apply the criteria (for example at the group or individual level) and additional criteria to assess group infrastructure and design. The paper ends with some practical suggestions for how to assist the non-expert in this task. (shrink)

Where does entitlement to trust come from? When we trust someone to φ, do we need to have reason to trust them to φ or do we start out entitled to trust them to φ by default? Reductivists think that entitlement to trust always “reduces to” or is explained by the reasons that agents have to trust others. In contrast, anti-reductivists think that, in a broad range of circumstances, we just have entitlement to trust. even if we don’t have positive (...) reasons to do so. In this paper, we argue for a version of anti-reductivism. Roughly, we argue that we have default entitlement to trust someone to φ so long as there is an operative norm that requires S to φ. At least in such circumstances (and absent defeaters), we don’t need any positive reasons to trust S to φ. (shrink)

Trust and trustworthiness are essential for good healthcare, especially in mental healthcare. New technologies, such as mobile health apps, can affect trust relationships. In mental health, some apps need the trust of their users for therapeutic efficacy and explicitly ask for it, for example, through an avatar. Suppose an artificial character in an app delivers healthcare. In that case, the following questions arise: Whom does the user direct their trust to? Whether and when can an avatar be considered trustworthy? Our (...) study aims to analyze different dimensions of trustworthiness in the context of mobile health app use. We integrate O'Neill's account of autonomy, trust, and trustworthiness into a model of trustworthiness as a relational concept with four relata: B is trustworthy with respect to A regarding the performance of Z because of C. Together with O'Neill's criteria of trustworthiness (honesty, competence, and reliability), this four-sided model is used to analyze different dimensions of trustworthiness in an exemplary case of mobile health app use. Our example focuses on an app that uses an avatar and is intended to treat sleep difficulties. The conceptual analysis shows that interpreting trust and trustworthiness in health app use is multi-layered and involves a net of interwoven universal obligations. At the same time, O'Neill's approach to autonomy, trust, and trustworthiness offers a normative account to structure and analyze these complex relations of trust and trustworthiness using mobile health apps. (shrink)

The significance of big data for driving health research and improvements in patient care is well recognised. Along with these potential benefits, however, come significant challenges, including those concerning the sharing and linkage of health and social care records. Recently, there has been a shift in attention towards a paradigm of data sharing centred on the ‘trusted research environment’ (TRE). TREs are being widely adopted by the UK’s health data initiatives including Health Data Research UK (HDR UK),1 Our Future Health2 (...) and Genomics England.3 A recent review commissioned by the UK’s Department of Health and Social Care (hereafter referred to as the ‘Goldacre Review’) places TREs at the heart of its recommendations around the future of National Health Service (NHS) health data sharing for research, describing them as the ‘clear path forward’ to a health data system in which trust is ‘earned’ through ‘provable, credible steps to protect patient privacy, and by being transparent with everyone about everything that is done with their deepest medical secrets’.4 We argue that rather than building public trust, the TRE model actually reduces the need for trust in the use and sharing of patient health data. This is because trust is importantly connected to vulnerability and uncertainty; an essential part of trusting someone is accepting that one’s trust could be disappointed or betrayed. In attempting to provide assurances or guarantees of data privacy and security, TREs strive to remove this vulnerability, and so remove the need for trust. We do not see this as a problem and are broadly supportive of this kind of data sharing model because of the increased security and oversight it provides. However, having argued that TREs are not actually concerned with trust, we consider the importance of being precise about the words that we use …. (shrink)

A widespread assumption in debates about trust and trustworthiness is that the evaluative norms of principal interest on the trustor’s side of a cooperative exchange regulate trusting attitudes and performances whereas those on the trustee’s side regulate dispositions to respond to trust. The aim here will be to highlight some unnoticed problems with this asymmetrical picture – and in particular, how it elides certain key evaluative norms on both the trustor’s and trustee’s side the satisfaction of which are critical to (...) successful cooperative exchanges – and to show that a symmetrical, ‘achievement-first’ approach to theorising about trust and trustworthiness (and their relation to each other) has important advantages by comparison. The view I develop is guided by a structural analogy with practical reasoning. Just as practical reasoning is working as it should only when there is realisation (knowledge and action) of states (belief and intention) with reverse directions of fits (mind-to-world and world-to-mind), likewise, cooperation between trustor and trustee is functioning as it should only when there is an analogous kind of realisation on both sides of the cooperative exchange – viz., when the trustor ‘matches’ her achievement in trusting (an achievement in fitting reliance to reciprocity) with the trustee’s achievement in responding to trust (an achievement in fitting reciprocity to reliance). An upshot of viewing cooperation between trustor and trustee as exhibiting achievement-theoretic structure is that we will be better positioned to subsume trustworthiness (and its cognates on the trustee’s side), like trust, under a wider suite of evaluative norms that regulate attempts, dispositions, and achievements symmetrically on both sides of a cooperative exchange, with ‘matching achievements’ as the gold standard. (shrink)

The COVID-19 pandemic has both highlighted and exacerbated global health inequities, leading for calls for responses to COVID to promote social justice and ensure that no one is left behind. One key lesson to be learnt from the pandemic is the critical importance of decolonizing global health and global health research so that African countries are better placed to address pandemic challenges in contextually relevant ways. This paper argues that to be successful, programmes of decolonization in complex global health landscapes (...) require a complex three-dimensional approach. Drawing on the broader discourse of political decolonization that has been going on in the African context for over a century, we present a model for unpacking the complex task of decolonization. Our approach suggests a three-dimensional approach which encompasses hegemomic; epistemic; and commitmental elements. (shrink)

Purpose The purpose of this paper is to defend the notion of “trust in technology” against the philosophical view that this concept is misled and unsuitable for ethical evaluation. In contrast, it is shown that “trustworthy technology” addresses a critical societal need in the digital age as it is inclusive of IT-security risks not only from a technical but also from a public layperson perspective. Design/methodology/approach From an interdisciplinary perspective between philosophy andIT-security, the authors discuss a potential instantiation of a (...) “trustworthy information and communication technology ”: a solution for privacy respecting video surveillance. Here, strong data protection measures address grave concerns such as the threat of bulk biometric tracking of citizens. In a logical argument, however, the authors show that this technical notion of “trust” needs to be complemented by interlocking trust relations to justify public trust. Findings Based on this argument, the authors demonstrate that the philosophical position considering “trust in technology” to denote either “reliability” or “interpersonal trust” is too limited as it fails to address critical aspects of IT-security. In a broader, socio-technical sense, however, it is shown that several distinct accounts of trust – technical, interpersonal and institutional – should meaningfully interlock, to address concerns with ICTs. Originality/value This conceptual study demonstrates the potential of “trust in technology” for a more comprehensive evaluation of ICTs within the context of operation. Furthermore, it adds to the discussion of trust in IT-security by highlighting the layperson’s challenge of judging a technology’s trustworthiness. Vice versa, it contributes to Ethics of Technology by highlighting crucial IT-security needs. (shrink)

This article explores the potential for “trust in technology” to make a productive conceptual contribution to the ethical evaluation of technology, complementing the concepts of “acceptance” and “acceptability” already established in technology assessment. It shows that for digital technologies in particular, “trust” can better address aspects of security against attacks as it allows to integrate concepts of IT security. Furthermore, “trustworthy technology” allows for a better inclusion of lay perspectives, since rationally justified trust in the sense of risk expectations can (...) be mediated interpersonally by experts. Especially for the evaluation of digital technologies, “trust in technology” can thus bridge a conceptual gap between acceptance and acceptability. (shrink)

The COVID-19 pandemic has generated a range of responses from countries across the globe in managing and containing infections. Considerable research has highlighted the importance of trust in ethically and effectively managing infectious diseases in the population; however, considerations of reciprocal trust remain limited in debates on pandemic response. This paper aims to broaden the perspective of good ethical practices in managing an infectious disease outbreak by including the role of reciprocal trust. A synthesis of the approaches drawn from South (...) Korea and Taiwan reveals reciprocal trust as an important ethical response to the COVID-19 pandemic. Reciprocal trust offers the opportunity to reconcile the difficulties arising from restrictive measures for protecting population health and individual rights. (shrink)

Population-level biomedical research offers new opportunities to improve population health, but also raises new challenges to traditional systems of research governance and ethical oversight. Partly in response to these challenges, various models of public involvement in research are being introduced. Yet, the ways in which public involvement should meet governance challenges are not well understood. We conducted a qualitative study with 36 experts and stakeholders using the World Café method to identify key governance challenges and explore how public involvement can (...) meet these challenges. This brief report discusses four cross-cutting themes from the study: the need to move beyond individual consent; issues in benefit and data sharing; the challenge of delineating and understanding publics; and the goal of clarifying justifications for public involvement. The report aims to provide a starting point for making sense of the relationship between public involvement and the governance of population-level biomedical research, showing connections, potential solutions and issues arising at their intersection. We suggest that, in population-level biomedical research, there is a pressing need for a shift away from conventional governance frameworks focused on the individual and towards a focus on collectives, as well as to foreground ethical issues around social justice and develop ways to address cultural diversity, value pluralism and competing stakeholder interests. There are many unresolved questions around how this shift could be realised, but these unresolved questions should form the basis for developing justificatory accounts and frameworks for suitable collective models of public involvement in population-level biomedical research governance. (shrink)

Journal of Social Philosophy, EarlyView.

This paper proposes freedom as the condition of possibility for the construction of trust in human relationships. The methodology used is a review of the scientific literature of the most recent moral and political philosophy. As a result of the dialogue between different positions, it is discovered that freedom, despite being present in the act of trust, is forgotten in the discussion around trust, a forgetfulness that has as its main causes the assumption that trust is natural and the confusion (...) between the propensity to trust and the act of trusting. All this leads to proposing an approach of the act of trusting that starts from the freedom of the trustee and the trustor. (shrink)

This paper develops an account of trustworthy AI. Its central idea is that whether AIs are trustworthy is a matter of whether they live up to their function-based obligations. We argue that this account serves to advance the literature in a couple of important ways. First, it serves to provide a rationale for why a range of properties that are widely assumed in the scientific literature, as well as in policy, to be required of trustworthy AI, such as safety, justice, (...) and explainability, are properties (often) instantiated by trustworthy AI. Second, we connect the discussion on trustworthy AI in policy, industry, and the sciences with the philosophical discussion of trustworthiness. We argue that extant accounts of trustworthiness in the philosophy literature cannot make proper sense of trustworthy AI and that our account compares favourably with its competitors on this front. (shrink)

Definition of the problem This article critically addresses the conceptualization of trust in the ethical discussion on artificial intelligence (AI) in the specific context of social robots in care. First, we attempt to define in which respect we can speak of ‘social’ robots and how their ‘social affordances’ affect the human propensity to trust in human–robot interaction. Against this background, we examine the use of the concept of ‘trust’ and ‘trustworthiness’ with respect to the guidelines and recommendations of the High-Level (...) Expert Group on AI of the European Union. Arguments Trust is analyzed as a multidimensional concept and phenomenon that must be primarily understood as departing from trusting as a human functioning and capability. To trust is an essential part of the human basic capability to form relations with others. We further want to discuss the concept of _responsivity _which has been established in phenomenological research as a foundational structure of the relation between the self and the other. We argue that trust and trusting as a capability is fundamentally _responsive_ and needs responsive others to be realized. An understanding of _responsivity_ is thus crucial to conceptualize trusting in the ethical framework of human flourishing. We apply a phenomenological–anthropological analysis to explore the link between certain qualities of social robots that construct responsiveness and thereby simulate responsivity and the human propensity to trust. Conclusion Against this background, we want to critically ask whether the concept of trustworthiness in social human–robot interaction could be misguided because of the limited ethical demands that the constructed responsiveness of social robots is able to answer to. (shrink)

Background Biobanks are a key aspect of healthcare research; they enable access to a wide range of heterogenous samples and data, as well as saving individual researchers time and funds on the collection, storage and/or curation of such resources. However, biobanks are also associated with impacts associated with a depletion of natural resources (energy, water etc.) production of toxic chemicals during manufacturing of laboratory equipment, and effects on biodiversity. We wanted to better understand the biobanking sector in the UK as (...) a first step to assessing the environmental impacts of UK biobanking. Methods We explored the sample storage infrastructure and environmental sustainability practices at a number of UK biobanks through a mixed methods quantitative and qualitative approach, including information gathering on an online platform, and eight in-depth interviews. Results Environmental sustainability was deprioritised behind biobanks’ financial sustainability practices. Nevertheless, both often aligned in practice. However, there was a tendency towards underutilisation of stored samples, the avoidance of centralisation, and providing accessibility to biosamples, and this conflicted with valuing sustainability goals. This related to notions of individualised and competitive biobanking culture. Furthermore, the study raised how value attachments to biosamples overshadows needs for both financial and environmental sustainability concerns. Conclusions We need to move away from individualised and competitive biobanking cultures towards a realisation that the health of the publics and patients should be first and foremost. We need to ensure the use of biosamples, ahead of their storage (‘smart attachments’), align with environmental sustainability goals and participants’ donation wishes for biosample use. (shrink)

In responding to my critics, James Childress, Tom Beauchamp, Soren Holm, and Ruth Macklin, I reprise my arguments for medical ethics being an uncommon morality. I also elaborate on points that required further clarification. I explain the role of trust and trustworthiness in the creation of a profession. I also describe my views on the relationship of the medical profession to the society in which medicine is practiced. Finally, I defend my claim that medical ethics “is constructed by medical professionals (...) for medical professionals” by describing the profession’s unique vantage point for regulating and policing the profession’s uncommon powers and privileges. (shrink)

The Covid‐19 pandemic highlighted the need to examine public trust in the U.S. Food and Drug Administration (FDA) vaccine approval process and the role of political influence in the FDA's decisions. Ensuring that the FDA is itself trustworthy is important for justifying public trust in its actions, like vaccine approvals, thereby promoting public health. We propose five conditions of trustworthiness that the FDA should meet when it reviews vaccines, even during emergencies: consistency with rules, proper expert or political decision‐makers, proper (...) decision‐making and noninterference, connection to public preference, and transparency of both reasons and procedures. The five conditions provide a road map of procedural and substantive requirements, which the FDA has variably implemented, focused on ensuring appropriate influence of political interests. While being a trustworthy agency cannot guarantee the public's trust, implementing these conditions builds a groundwork for public trust. (shrink)

When forecasting events, multiple types of uncertainty are often inherently present in the modeling process. Various uncertainty typologies exist, and each type of uncertainty has different implications a scientist might want to convey. In this work, we focus on one type of distinction betweendirect quantitative uncertaintyandindirect qualitative uncertainty. Direct quantitative uncertainty describes uncertainty about facts, numbers, and hypotheses that can be communicated in absolute quantitative forms such as probability distributions or confidence intervals. Indirect qualitative uncertainty describes the quality of knowledge (...) concerning how effectively facts, numbers, or hypotheses represent reality, such as evidence confidence scales proposed by the Intergovernmental Panel on Climate Change. A large body of research demonstrates that both experts and novices have difficulty reasoning with quantitative uncertainty, and visualizations of uncertainty can help with such traditionally challenging concepts. However, the question of if, and how, people may reason with multiple types of uncertainty associated with a forecast remains largely unexplored. In this series of studies, we seek to understand if individuals can integrate indirect uncertainty about how “good” a model is (operationalized as a qualitative expression of forecaster confidence) with quantified uncertainty in a prediction (operationalized as a quantile dotplot visualization of a predicted distribution). Our first study results suggest that participants utilize both direct quantitative uncertainty and indirect qualitative uncertainty when conveyed as quantile dotplots and forecaster confidence. In manipulations where forecasters were less sure about their prediction, participants made more conservative judgments. In our second study, we varied the amount of quantified uncertainty (in the form of the SD of the visualized distributions) to examine how participants’ decisions changed under different combinations of quantified uncertainty (variance) and qualitative uncertainty (low, medium, and high forecaster confidence). The second study results suggest that participants updated their judgments in the direction predicted by both qualitative confidence information (e.g., becoming more conservative when the forecaster confidence is low) and quantitative uncertainty (e.g., becoming more conservative when the variance is increased). Based on the findings from both experiments, we recommend that forecasters present qualitative expressions of model confidence whenever possible alongside quantified uncertainty. (shrink)

BackgroundAs the use of AI becomes more pervasive, and computerised systems are used in clinical decision-making, the role of trust in, and the trustworthiness of, AI tools will need to be addressed. Using the case of computational phenotyping to support the diagnosis of rare disease in dysmorphology, this paper explores under what conditions we could place trust in medical AI tools, which employ machine learning.MethodsSemi-structured qualitative interviews with stakeholders who design and/or work with computational phenotyping systems. The method of constant (...) comparison was used to analyse the interview data.ResultsInterviewees emphasized the importance of establishing trust in the use of CP technology in identifying rare diseases. Trust was formulated in two interrelated ways in these data. First, interviewees talked about the importance of using CP tools within the context of a trust relationship; arguing that patients will need to trust clinicians who use AI tools and that clinicians will need to trust AI developers, if they are to adopt this technology. Second, they described a need to establish trust in the technology itself, or in the knowledge it provides—epistemic trust. Interviewees suggested CP tools used for the diagnosis of rare diseases might be perceived as more trustworthy if the user is able to vouchsafe for the technology’s reliability and accuracy and the person using/developing them is trusted.ConclusionThis study suggests we need to take deliberate and meticulous steps to design reliable or confidence-worthy AI systems for use in healthcare. In addition, we need to devise reliable or confidence-worthy processes that would give rise to reliable systems; these could take the form of RCTs and/or systems of accountability transparency and responsibility that would signify the epistemic trustworthiness of these tools. words 294. (shrink)

It is widely acknowledged that trust plays an important role for the acceptability of data sharing practices in research and healthcare, and for the adoption of new health technologies such as AI. Yet there is reported distrust in this domain. Although in the UK, the NHS is one of the most trusted public institutions, public trust does not appear to accompany its data sharing practices for research and innovation, specifically with the private sector, that have been introduced in recent years. (...) In this paper, we examine the question of, what is it about sharing NHS data for research and innovation with for-profit companies that challenges public trust? To address this question, we draw from political theory to provide an account of public trust that helps better understand the relationship between the public and the NHS within a democratic context, as well as, the kind of obligations and expectations that govern this relationship. Then we examine whether the way in which the NHS is managing patient data and its collaboration with the private sector fit under this trust-based relationship. We argue that the datafication of healthcare and the broader ‘health and wealth’ agenda adopted by consecutive UK governments represent a major shift in the institutional character of the NHS, which brings into question the meaning of public good the NHS is expected to provide, challenging public trust. We conclude by suggesting that to address the problem of public trust, a theoretical and empirical examination of the benefits but also the costs associated with this shift needs to take place, as well as an open conversation at public level to determine what values should be promoted by a public institution like the NHS. (shrink)

Artificially intelligent machines are different in kind from all previous machines and tools. While many are used for relatively benign purposes, the types of artificially intelligent machines that we should care about, the ones that are worth focusing on, are the machines that purport to replace humans entirely and thereby engage in what Brian Cantwell Smith calls “judgment.” As impressive as artificially intelligent machines are, their abilities are still derived from humans and as such lack the sort of normative commitments (...) that humans have. So while artificially intelligent machines possess a great capacity for “reckoning,” to use Smith’s terminology, i.e., a calculative prowess of extraordinary utility and importance, they still lack the kind of considered human judgment that accompanies the ethical commitment and responsible action we humans must ultimately aspire toward. But there is a perfect technological storm brewing. Artificially intelligent machines are analogous to a perfect storm in that such machines involve the convergence of a number of factors that threaten our ability to behave ethically and maintain meaningful human control over the outcomes of processes involving artificial intelligence. I argue that the storm in the context of artificially intelligent machines makes us vulnerable to moral complacency. That is, this perfect technological storm is capable of lulling people into a state in which they abdicate responsibility for decision-making and behaviour precipitated by the use of artificially intelligent machines, a state that I am calling “moral complacency.” I focus on three salient problems that converge to make us especially vulnerable to becoming morally complacent and losing meaningful human control. The first problem is that of transparency/opacity. The second problem is that of overtrust in machines, often referred to as the automation bias. The third problem is that of ascribing responsibility. I examine each of these problems and how together they threaten to render us morally complacent. (shrink)

With focus on the development and use of artificial intelligence (AI) systems in the digital health context, we consider the following questions: How does the European Union (EU) seek to facilitate the development and uptake of trustworthy AI systems through the AI Act? What does trustworthiness and trust mean in the AI Act, and how are they linked to some of the ongoing discussions of these terms in bioethics, law, and philosophy? What are the normative components of trustworthiness? And how (...) do the requirements of the AI Act relate to these components? We first explain how the EU seeks to create an epistemic environment of trust through the AI Act to facilitate the development and uptake of trustworthy AI systems. The legislation establishes a governance regime that operates as a socio-epistemological infrastructure of trust which enables a performative framing of trust and trustworthiness. The degree of success that performative acts of trust and trustworthiness have achieved in realising the legislative goals may then be assessed in terms of statutorily defined proxies of trustworthiness. We show that to be trustworthy, these performative acts should be consistent with the ethical principles endorsed by the legislation; these principles are also manifested in at least four key features of the governance regime. However, specified proxies of trustworthiness are not expected to be adequate for applications of AI systems within a regulatory sandbox or in real-world testing. We explain why different proxies of trustworthiness for these applications may be regarded as ‘special’ trust domains and why the nature of trust should be understood as participatory. (shrink)

Problem Self-tracking—and of course also health-related self-tracking—has an influence on those who use it. This influence can (but does not necessarily have to) pose a threat to the autonomy of people tracking themselves. Argumentation Self-tracking can easily come into conflict with one of the three conditions for autonomy defined by Beauchamp, Faden, and Childress: voluntariness. Based on a distinction between different forms of manipulative influence—mildly controlling and substantially controlling—I will argue that health-related self-tracking often has a mildly controlling influence but (...) that it can also turn into a substantially controlling manipulative influence and even become coercive. Conclusion Substantially manipulative self-tracking and self-tracking that involves coercion is a violation of the condition of voluntariness set for autonomy. This risk of violating autonomy must be taken into account when assessing health-related self-tracking. (shrink)

This article describes and analyzes the design and functioning of the Statistical Ethics System (SETE) in Colombia’s National Statistical Office. It presents the methodology and general process of planning and implementation of the System, supported by a conceptual analysis of the requirements for an ethical functioning of official statistics. The general objective of the article is to make a practical contribution to the understanding of conceptual and practical features that ought to be considered in the implementation of an ethical system (...) in the operation of the public sector, particularly in the area of the production of official statistics. The text is divided into five parts. In the first part, we make a general introduction to the ethical value of official statistics. In the second and third parts, we make a presentation and analysis of the principles and risks that were selected as the basic ethical framework for the production of official statistics at the National Administrative Department of Statistics (DANE). The fourth section presents the conceptual and practical bases of how SETE operates. The fifth section we present some concluding remarks. (shrink)

Without trust there is no credible human health research (HHR). This article accepts this truism and addresses a crucial question that arises: how can trust continually be promoted in an ever-changing and uncertain HHR environment? The article analyses long-standing mechanisms that are designed to elicit trust—such as consent, anonymization, and transparency—and argues that these are best understood as trust represented by proxies of trustworthiness, i.e., regulatory attempts to convey the trustworthiness of the HHR system and/or its actors. Often, such proxies (...) are assumed to operate as markers that trust exists or, at least, has not been lost. But, since trust can neither be “built” nor “secured,” this is a precarious assumption. Worryingly, there is no existing theoretical account of how to understand and evaluate these proxies of trustworthiness as part of a trusted HHR ecosystem. To remedy this, the paper argues for a radical reimagining of trust and trustworthiness as performative acts that ought to be understood in relation to each other and by reference to the common values at stake. It is shown that proxies of trustworthiness are the operational tools used to perform trustworthiness. It advocates for a values-based approach to understanding the relationship between trust and trustworthiness. This establishes a strong basis for an evaluative framework for proxies of trustworthiness, i.e., to determine how to perform trustworthiness well. Five common proxies in HHR are scrutinized from a values perspective. The contribution is to provide a far-reaching normative and practical framework by which existing and future proxies of trustworthiness can be identified, assessed, maintained, or replaced in rapidly changing HHR regulatory ecosystems where trust itself is crucial to the success of the entire HHR enterprise. (shrink)

This paper examines the conditions of trustworthy science advice mechanisms, in which scientists have a mandated role to inform public policymaking. Based on the literature on epistemic trust and public trust in science, we argue that possession of relevant expertise, justified moral and political considerations, as well as proper institutional design are conditions for trustworthy science advice. In order to assess these conditions further, we explore the case of temporary advisory committees in Norway. These committees exemplify a de facto trusted (...) and seemingly well-functioning science advice mechanism. Still, this mechanism turns out to poorly realize some central conditions of trustworthy science advice. From this we draw three lessons. Firstly, it remains crucial to distinguish between well-placed and de facto trust. Secondly, some conditions of trustworthy science advice seem more significant than others and there are thresholds for realizing each condition. Thirdly, not only does the institutional design and organization of science advice matter more than often recognized; the trust and trustworthiness of the broader social and political context and institutional environment make a difference as well. (shrink)

AbstractSimion and Kelp offer a prima facie very promising account of trustworthy AI. One benefit of the account is that it elegantly explains trustworthiness in the case of cancer diagnostic AIs, which involve the acquisition by the AI of a representational etiological function. In this brief note, I offer some reasons to think that their account cannot be extended — at least not straightforwardly — beyond such cases (i.e., to cases of AIs with non-representational etiological functions) without incurring the unwanted (...) cost of overpredicting untrustworthiness. (shrink)

Genome editing is revolutionising the field of genetics, which includes novel applications to food animals. Responsible research and innovation has been advocated as a way of ensuring that a wider-range of stakeholders and publics are able to engage with new and emerging technologies to inform decision making from their perspectives and values. We posit that genome editing is now proceeding at such a fast rate, and in so many different directions, such as to overwhelm attempts to achieving a more reflective (...) pace. An alternative location for reflection is during the much slower process of taking products from the lab to market. We suggest emphasising Responsible Innovation, putting the ‘I’ back into RRI, and encouraging companies to embrace an RRI approach. We review some previous attempts at developing industry-relevant frameworks for RRI. We then describe two examples of genome editing in livestock; hornless cattle and disease resistant pigs, and reflect on the sorts of questions that could be considered in these two genome editing examples. This paper seeks to take forward the discussion on RRI by extending it to bringing products to market in the context of genome edited livestock. (shrink)

BackgroundLarge-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their (...) participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal.MethodsWe conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data.ResultsThe decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants.ConclusionsOur findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures. (shrink)

Expert-informed public policy often depends on a degree of public trust in the relevant expert authorities. But if lay citizens are not themselves authorities on the relevant area of expertise, how can they make good judgements about the trustworthiness of those who claim such authority? I argue that the answer to this question depends on the kind of trust under consideration. Specifically, I maintain that a distinction between epistemic trust and recommendation trust has consequences for novices judging the trustworthiness of (...) experts. I argue for this by identifying the unique difficulties that emerge when a novice is asked not just to believe expert testimony, but to follow expert recommendations. I outline criteria for novice judgements of expert trustworthiness that have been proposed by Elizabeth Anderson and show that novel problems emerge for her criteria when we shift focus from epistemic trust to recommendation trust. More is needed when we are asked not just to believe the experts but to act as they recommend, because novices looking for trustworthy expert recommendations need to establish whether the recommended course of action supports what is important to them and accords with their values. (shrink)