Since anonymous agents can spread misinformation with impunity, many people advocate for greater accountability for internet speech. This paper provides a veritistic argument that accountability mechanisms can cause significant epistemic problems for internet encyclopedias and social media communities. I show that accountability mechanisms can undermine both the dissemination of true beliefs and the detection of error. Drawing on social psychology and behavioral economics, I suggest alternative mechanisms for increasing the trustworthiness of internet communication.

Although trustworthiness has been described as a source of competitive advantage, its value extends to organizational governance and wealth creation. We identify the importance of the commitment—compliance continuum in the decision to trust and note that trustworthiness is a subjective perception viewed through each person's mediating lens. That lens and each person's interpretation of the social contract impact one's commitment to cooperate. We suggest five propositions that integrate trustworthiness, governance, and wealth creation.

Beyond philosophy, discussions of trust and trustworthiness often concern collective entities such as corporations, states, and social groups. But much philosophical work takes trust in an individual person as paradigmatic, distinguishing such trust from mere reliance. This chapter explores the distinction between trustworthiness and mere reliability as it applies to collectives, arguing that the distinction does not have the same significance as it has in the individual case.

In the current philosophical literature on trustworthiness, two claims are very widely accepted, first that trustworthiness is a kind of reliability and secondly, that trustworthiness is not a virtue. Both claims are made, for instance, in Hawley's recent highly influential account of trustworthiness. I argue that both are mistaken. I develop and defend a new account of trustworthiness as responsibility, contrasting it with reliability and obligation accounts of trustworthiness. I argue that trustworthiness as (...) responsibility is very plausibly a kind of moral virtue. (shrink)

BackgroundDespite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often absent from discourse on the ethical design, development, and deployment of AI. This study explores the perspectives of birth parents and mothers on the introduction of AI-based cardiotocography (CTG) in the context of intrapartum care, focusing on issues pertaining to trust and trustworthiness.MethodsSeventeen semi-structured interviews were conducted with birth (...) parents and mothers based on a speculative case study. Interviewees were based in England and were pregnant and/or had given birth in the last two years. Thematic analysis was used to analyze transcribed interviews with the use of NVivo. Major recurring themes acted as the basis for identifying the values most important to this population group for evaluating the trustworthiness of AI.ResultsThree themes pertaining to the perceived trustworthiness of AI emerged from interviews: (1) trustworthy AI-developing institutions, (2) trustworthy data from which AI is built, and (3) trustworthy decisions made with the assistance of AI. We found that birth parents and mothers trusted public institutions over private companies to develop AI, that they evaluated the trustworthiness of data by how representative it is of all population groups, and that they perceived trustworthy decisions as being mediated by humans even when supported by AI.ConclusionsThe ethical values that underscore birth parents and mothers’ perceptions of trustworthy AI include fairness and reliability, as well as practices like patient-centered care, the promotion of publicly funded healthcare, holistic care, and personalized medicine. Ultimately, these are also the ethical values that people want to protect in the healthcare system. Therefore, trustworthy AI is best understood not as a list of design features but in relation to how it undermines or promotes the ethical values that matter most to its end users. An ethical commitment to these values when creating AI in healthcare contexts opens up new challenges and possibilities for the design and deployment of AI. (shrink)

In ‘Trustworthy Artificial Intelligence’, we develop a novel account of how it is that AI can be trustworthy and what it takes for an AI to be trustworthy. In this paper, we respond to a suite of recent comments on this account, due to J. Adam Carter, Dong-yong Choi, Rune Nyrup, and Fei Song. We would like to thank all four for their thoughtful engagement with our work, as well as the Asian Journal of Philosophy for publishing the symposium on (...) our paper. The game plan for the paper is as follows. We will first briefly rehearse the account and then respond to comments in turn. (shrink)

The approach of responsible research and innovation has been proposed to support the introduction of technologies that touch upon socially sensitive issues. RRI is intended to help designers and manufacturers of new technologies identify and accommodate public concerns when developing a new technology by engaging with a wide range of relevant actors in an interactive, transparent process. However what this approach amounts to exactly remains elusive as of yet, i.e. it is unclear what its contribution to the societal embedding of (...) new technologies should consists of exactly. The transition to a sustainable bio-economy that uses biomass as its main resource is a complicated trajectory involving many actors and touching upon societally sensitive issues such as the use of genetic modification. In this paper we pose the question in what way RRI can stimulate the development and diffusion of a sustainable bio-economy in The Netherlands and Europe. We claim that for the further development and diffusion of the bio-economy, trust among actors in the relevant value-chain is a prerequisite. RRI can play a pivotal part in the bio-economy by providing conditions for trustworthiness of actors and by enhancing trusting relationships. This can be achieved through instruments such as personal relationships, third person guarantors, institutions and the communication of values. From the application of RRI to the context of the bio-economy, lessons can be drawn for other socially intricate technological trajectories. (shrink)

Modern AI systems are man-made objects that leverage machine learning to support our lives across a myriad of contexts and applications. Despite extensive epistemological and ethical debates, their metaphysical foundations remain relatively under explored. The orthodox view simply suggests that AI systems, as artifacts, lack well-posed identity and persistence conditions—their metaphysical kinds are no real kinds. In this work, we challenge this perspective by introducing a theory of metaphysical identity of AI systems. We do so by characterizing their kinds and (...) introducing identity criteria—formal rules that answer the questions “When are two AI systems the same?” and “When does an AI system persist, despite change?” Building on Carrara and Vermaas’ account of fine-grained artifact kinds, we argue that AI trustworthiness provides a lens to understand AI system kinds and formalize the identity of these artifacts by relating their functional requirements to their physical make-ups. The identity criteria of AI systems are determined by their trustworthiness profiles—the collection of capabilities that the systems must uphold over time throughout their artifact histories, and their effectiveness in maintaining these capabilities. Our approach suggests that the identity and persistence of AI systems is sensitive to the socio-technical context of their design and utilization via their trustworthiness, providing a solid metaphysical foundation to the epistemological, ethical, and legal discussions about these artifacts. (shrink)

Organizational citizenship behaviors (OCBs) are essential for effective organizational functioning. Decisions by employees to engage in these important discretionary behaviors are based on how they make sense of the organizational context. Using fairness heuristic theory, we tested two important OCB predictors: manager trustworthiness and interactional justice. In the process, we control for the effects of dispositional factors (propensity to trust) and for system-based organizational fairness (procedural and distributive justice). Results, based on surveys collected from 120 employee–supervisor dyads, indicate that (...) manager trustworthiness explains variance in OCBs over and above the variance accounted for by interactional fairness. Implications for theory and practice are discussed. (shrink)

I present and defend an account of three-place trustworthiness according to which B is trustworthy with respect to A in domain of interaction D, if and only if she is competent with respect to that domain, and she would take the fact that A is counting on her, were A to do so in this domain, to be a compelling reason for acting as counted on. This is not the whole story of trustworthiness, however, for we want those (...) we can count on to identify themselves so that we can place our trust wisely. (shrink)

Using AI adequately is necessary for user companies to remain competitive. Studies show that nevertheless many companies are hesitant in this regard. In relation to the assumption that people’s ability to act is influenced by a lack of trust, particularly in the context of AI, we conducted a study as part of the TrustKI research project to analyze which factors are relevant to documenting trustworthiness in the context of AI. Our evaluation revealed that users demand holistic transparency; the provision (...) of relevant information on the AI solution and proof of technical expertise is not sufficient to build trust, but there is a demand from users for specific information about the respective company. Based on the generally recognized components, we were able to identify further dimensions to provide the required information even more precisely. Thus, the study allows us to propose a preliminary set of information requirements for AI providers. (shrink)

Generative AI agents (GenAIs) powered by Large-language models (LLMs) have emerged as prominent technological advancements. As these sophisticated systems permeate diverse sectors ranging from business to entertainment, their capability to handle moral queries becomes a focal point of exploration. This study investigates how users perceive Delphi, a GenAI trained to respond to moral queries (Jiang et al., 2025). Participants were instructed to interact with the agent, implemented either as a humanlike robot or a web client, to assess its moral competence (...) and trustworthiness. Both agents received high scores for moral competence and perceived morality, yet fell short by not offering justifications for their moral decisions. Despite being deemed trustworthy, participants were hesitant about relying on such systems in the future. This study offers an initial evaluation of an algorithm with moral competence in an embodied human-like interface, paving the way for the evolution of ethical robot advisors. (shrink)

Leaders in today's world face the challenge of earning the trust and commitment of organizational members if they expect to guide their companies to success in a highly competitive global context. In this article, we present empirical results indicating that when leadership behaviors are perceived as trustworthy through the observer's mediating lens, trust increases and leaders are more likely to be viewed as ethical stewards who honor a higher level of duties. This article contributes to the growing body of literature (...) about the importance of ethical stewardship in the trust relationship. (shrink)

Why are people trustworthy? I argue for two theses. First, we cannot explain many socially important forms of trustworthiness solely in terms of the instrumentally rational seeking of one’s interests, in response to external sanctions or rewards. A richer psychology is required. So, second, possession of moral character is a plausible explanation of some socially important instances when people are trustworthy. I defend this conclusion against the influential account of trust as ‘encapsulated interest’, given by Russell Hardin, on which (...) most trustworthiness is explained by the interest of continuing relationship. (shrink)

Within medical ethics, there is widespread agreement that morally valid consent includes an understanding condition. Disagreement centers on what is meant by that understanding condition. Tom Dougherty proposed that this understanding condition should be divided into the two mutually exclusive categories of descriptive information and contextual information. Further, Dougherty argues that each type of information is necessary to satisfy the understanding condition. In contrast, I argue that when the deontic aspect of valid consent is in view, each type of information (...) can be sufficient to satisfy the understanding condition on its own. Moreover, by analyzing delegation, which is conceptually related to consent since both are morally transformative actions, I show that delegation often depends not on descriptive or contextual information but on trust. So, I argue that trustworthiness can also be a type of information that does the same work as descriptive and contextual information in satisfying the understanding condition for valid consent. (shrink)

In schools, trustworthiness is a foundational value taught to students through values education as well as the school activities, ethos and climate. A key determining factor for the establishment o...

In an unprecedented situation of uncertainty, the COVID-19 pandemic tested the public crisis communication capacity. Using focus group data, this study analyzes public reactions to COVID-19 policies in Scandinavia. In line with the “rally around the flag” hypothesis, trust in public health authorities remained high in all three Scandinavian countries throughout the COVID-19 pandemic. We asked how people assessed the trustworthiness of authorities, and how they discussed reasons for complying with regulations and recommendations. Our findings suggest that the (...) class='Hi'>trustworthiness of experts and leaders was continually negotiated, manufactured, and renegotiated, producing critical and conditional trust. Willingness to and reasons for complying with measures to curb the disease were expressed and justified by participants from Sweden, Norway, and Denmark, notwithstanding the national policies consisting of harsh regulations and mild pressure. (shrink)

We analyze the usage of computer simulation at the LHC and derive seven jointly necessary requirements for a simulation to be considered ’trustworthy’, such that it can be used as proxy for experiments. We show that these requirements can also be applied to systems without direct experimental access and discuss their validity for properties that have not yet been probed. While being necessary, these requirements are not sufficient. Such trustworthy simulations will be analyzed for the relative epistemic statuses of simulation (...) and material measurements, from which we argue that claims of their parity are unfounded. Instead, using credibility as a measure for epistemic status, and in view of the temporal and epistemic dependence of simulation on material measurements, we argue that the latter have a higher epistemic status than the former. We further argue that suggestions to qualify the epistemic status by ’defocussing’ on the material connection to the target system of either human or natural experiments are misleading. (shrink)

If educators are to educate they must be accorded some level of trust. Anthony Giddens claims that because trust is not easily created, it is now being replaced with ‘confidence’ because this latter disposition is much easier to give and is more convenient. It is argued in this paper that this shift from trust to confidence stifles education because emphasis is placed solely upon qualifications and competence, and is neglectful of disclosing one’s motives and desires—which are considered to be essential (...) elements for relationships and communities which depend upon trust. Therefore, educators ought to seek to become more trustworthy by going beyond evidence-based practices and codes of ethics, towards articulating a developed personal philosophy of education outlining the ultimate end-purposes to which they aspire. Through such a philosophy, educators identify their ultimate desires and commitments and this self-disclosure can make trust-giving more likely. Demonstrated evidence of achievements and qualifications encourage confidence and this has some value. In addition to these artefacts of evidence, it is argued here that educators must also articulate what they actually desire. This can be understood as John Dewey’s virtue of ‘genuine interest’ which he characterises as being wholehearted, persistent and impartial. For educators, this is often represented in our personal philosophy of education and because it is personal, it is also existential in the sense that it pertains to giving sense, meaning and purpose to all of our activities and way of life for which we are individually responsible and passionately committed to as professionals. As a consequence of being existential, our philosophy and our commitment to it has an intellectual and moral aspect and because it reaches to the very depths of our raison d’être, it pertains to our passion as described by Søren Kierkegaard. This paper shall draw upon Dewey’s notion of wholeheartedness and Kierkegaard’s notion of purity of heart, to make the case that if educators embrace these in their practices, we may become more trustworthy. (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)

This paper investigates the foundational causes of hallucination in large language models (LLMs) and proposes a structural framework for achieving trustworthy AI systems. Rather than treating hallucination as an isolated technical failure, the study conceptualizes it as a breakdown of semantic reliability—specifically, disruptions in meaning stability, topological coherence, and resonance consistency across model layers. -/- To address this, we introduce the Layer-Knot Framework (LKF), which stabilizes semantic flow through inter-layer anchoring nodes that maintain coherence between intent and evidence. The framework (...) is operationalized through three quantitative indicators: Hallucination Rate (HR), Grounding Rate (GR), and Creativity Rate (CR). Together, these metrics capture the equilibrium between factual accuracy, evidential grounding, and generative diversity. -/- Experiments using TruthfulQA and a set of 2,000 domain-specific prompts show that LKF achieves a 50% reduction in HR, a 12% improvement in GR, and preserves CR stability. These findings demonstrate that reliability and creativity are not oppositional; when semantic integrity is structurally enforced, generative autonomy remains intact. -/- The study establishes that trustworthy LLMs are achieved not by restricting imagination but by aligning internal linguistic-semantic topologies. This reframes hallucination suppression as a process of semantic alignment, offering a principled foundation for next-generation high-reliability AI systems. (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)

We examine how trustworthy behaviour can be achieved in the financial sector. The task is to ensure that firms are motivated to pursue long-term interests of customers rather than pursuing short-term profits. Firms’ self-interested pursuit of reputation, combined with regulation, is often not sufficient to ensure that this happens. We argue that trustworthy behaviour requires that at least some actors show a concern for the wellbeing of clients, or a respect for imposed standards, and that the behaviour of these actors (...) is copied in such a way that it becomes a behavioural norm. We briefly suggest what such behavioural norms might need to be if trustworthy behaviour is to be achieved, and consider how they might be supported; we describe the research that is necessary in order to understand these norms in more detail. We argue that the norms of traders are different from the norms of those engaged in other activities, since they are inevitably self-interested, and we consider the risk that traders’ norms might undermine those of other actors. We analyse the task for governance in dealing with this problem, and the role which leadership by a corporate board and management might play in doing this. We describe the need for further research in to describe how this might be done. (shrink)

This paper examines how science advice can provide policy recommendations in a trustworthy manner. Despite their major political importance, expert recommendations are understudied in the philosophy of science and social epistemology. Matthew Bennett has recently developed a notion of what he calls recommendation trust, according to which well-placed trust in experts’ policy recommendations requires that recommendations are aligned with the interests of the trust-giver. While interest alignment might be central to some cases of public trust, this paper argues against the (...) significance of interest-alignment to meritorious public trust. First, political bodies and citizens can have a basic kind of well-placed recommendation trust in science advice based on an all-things-considered judgement regarding the possession of relevant competencies, responsible conduct, and a proper institutional design. Moreover, scientists’ policy recommendations can be seen as open-ended and as dynamic proposals that enable inter-institutional reasoning and political deliberation. Finally, by providing conditional recommendations, scientists can expand the scope of feasible policy options from which political bodies can choose, thus making the condition of interest alignment even less significant to the trustworthy provision of recommendations. (shrink)

When it comes to using patient data from the National Health Service (NHS) for research, we are often told that it is a matter of trust: we need to trust, we need to build trust, we need to restore trust. Various policy papers and reports articulate and develop these ideas and make very important contributions to public dialogue on the trustworthiness of our research institutions. But these documents and policies are apparently constructed with little sustained reflection on the nature (...) of trust and trustworthiness, and therefore are missing important features that matter for how we manage concerns related to trust. We suggest that what we mean by ‘trust’ and ‘trustworthiness’ matters and should affect the policies and guidance that govern data sharing in the NHS. We offer a number of initial, general reflections on the way in which some of these features might affect our approach to principles, policies and strategies that are related to sharing patient data for research. This paper is the outcome of a ‘public ethics’ coproduction activity which involved members of the public and two academic ethicists. Our task was to consider collectively the accounts of trust developed by philosophers as they applied in the context of the NHS and to coproduce an argumentative position relevant to this context. (shrink)

Overconfidence is typically damaging to one’s reputation as a trustworthy source of information. Previous research shows that the reputational cost associated with conveying a piece of false information is higher for confident than unconfident speakers. When judging speaker trustworthiness, individuals do not exclusively rely on past accuracy but consider the extent to which speakers expressed a degree of confidence that matched the accuracy of their claims (their “confidence-accuracy calibration”). The present study experimentally examines the interplay between confidence, accuracy and (...) a third factor, namely evidence, in the assessment of speaker trustworthiness. Experiment 1 probes the hypothesis that overconfidence does not backfire when a confident but inaccurate claim is justified: the trustworthiness of a confident speaker who turns out to be wrong is restored if the confidence expressed is based on strong evidence (good confidence-evidence calibration). Experiment 2 investigates the hypothesis that confidence can backfire if a confident and accurate claim is not justified: the trustworthiness of a confident speaker who turns out to be right is damaged if the confidence expressed is based on weak evidence (bad confidence-evidence calibration). Our results support both hypotheses and thus suggest that “confidence-evidence calibration” plays a crucial role in the assessment of speaker trustworthiness. (shrink)

Simion and Kelp defend a non-anthropocentric account of trustworthy AI, based on the idea that the obligations of AI systems should be sourced in purely functional norms. In this commentary, I highlight some pressing counterexamples to their account, involving AI systems that reliably fulfil their functions but are untrustworthy because those functions are antagonistic to the interests of the trustor. Instead, I outline an alternative account, based on the idea that AI systems should not be considered primarily as tools but (...) as technological participants in social practices. Specifically, I propose to source the obligations of an AI system in the norms that should govern the role it plays within the social practices it participates in, taking into account any changes to the social practices that its participation may bring about. This proposal is anthropocentric insofar as it ascribes obligations to AI systems that are similar to those of human participants in social practices, but only modestly so, as it does not require trustworthy AI to have contentious anthropomorphic capacities (e.g. for consciousness or moral responsibility). (shrink)

Simion and Kelp explain the trustworthiness of an AI based on that AI’s disposition to meet its obligations. Roughly speaking, according to Simion and Kelp, an AI is trustworthy regarding its task if and only if that AI is obliged to complete the task and its disposition to complete the task is strong enough. Furthermore, an AI is obliged to complete a task in the case where the task is the AI’s etiological function or design function. This account has (...) a strength in that it can provide a unificatory rationale for the trustworthy-making properties of AIs. According to this account, being explainable, being safe, and being transparent are the trustworthy-making properties of an AI because an AI can fulfill its etiological or design functions in the case where it is explainable, safe, and transparent. This paper shows that though Simion and Kelp’s account has a strength, this account is not satisfactory for two reasons. The first reason is that an AI’s trustworthiness is not determined just by the AI’s disposition to meet obligations, and the second reason is that it is difficult to explain how an AI’s etiological function and design function have to do with that AI’s obligations. To provide a full-fledged account, Simion and Kelp should dismiss these concerns. (shrink)

There is much to learn from Durán and Jongsma’s paper.1 One particularly important insight concerns the relationship between epistemology and ethics in medical artificial intelligence. In clinical environments, the task of AI systems is to provide risk estimates or diagnostic decisions, which then need to be weighed by physicians. Hence, while the implementation of AI systems might give rise to ethical issues—for example, overtreatment, defensive medicine or paternalism2—the issue that lies at the heart is an epistemic problem: how can physicians (...) know whether to trust decisions made by AI systems? In this manner, various studies examining the interaction of AI systems and physicians have shown that without being able to evaluate their trustworthiness, especially novice physicians become over-reliant on algorithmic support—and ultimately are led astray by incorrect decisions.3–5 This leads to a second insight from the paper, namely that even if some AI system happens to be opaque, it is still not built on the moon. To assess its trustworthiness, AI developers or physicians have different sorts of higher order evidence at hand. Most importantly, …. (shrink)

This paper investigates the trustworthiness of computation implemented in simulations in engineering, with a specific focus on equation-based simulations. Whereas opacity discussions in the computer simulation literature typically center on modeling opacity, we direct our attention to the grounds engineers should have for trusting that the computer indeed found an acceptable solution to a given model. This is a particularly sensitive issue in situations in which analytical or experimental methods are impossible or impractical. After critically reviewing alternative views found (...) in the literature, we propose a systematic approach for evaluating the accuracy of solutions obtained via computational methods, that involves quantifying residual errors and evaluating the model’s conditioning. We argue that, in equation-based simulations, ensuring that the residual is small enough and that the model is sufficiently well-conditioned provides a sufficient epistemic foundation for engineers to place their trust in the results obtained via computer simulations as much as they trust the models they use, thereby giving a conceptual basis for this much needed kind of conditional trust. (shrink)

Trust is valuable when placed in trustworthy agents and activities, but damaging or costly when placed in untrustworthy agents and activities. So it is puzzling that much contemporary work on trust – such as that based on polling evidence – studies generic attitudes of trust in types of agent, institution or activity in complete abstraction from any account of trustworthiness. Information about others’ generic attitudes of trust or mistrust that take no account of evidence whether those attitudes are well (...) or ill placed can offer little or no help for those who aim to place or refuse trust well. Information about attitudes is evidently useful to those who aim to influence those who hold them, which explains why polls about attitudes are popular with political parties, advertisers and other campaigning organisations. But where we aim not to influence others, but to place and refuse trust intelligently we must link trust to trustworthiness, and must focus on evidence of honesty, competence and r... (shrink)

The term ‘trustworthy AI’ has become one of the keywords in the academic and policy discussion of the social, ethical, and legal issues of artificial intelligence (AI), but it remains a contested notion and there are open debates about its meaning and how it is to be operationalized. For philosophers and ethicists, the debate has particularly revolved around the meaning of ‘trust’ and ‘trustworthiness’. However, since a thin and acultural understanding of trust and trustworthiness has been common in (...) the debate, the notion of trustworthy AI is at best ambiguous in a global and cross-cultural context, where trust and trustworthiness can be interpreted differently. A culturally-sensitive exploration of trust, trustworthiness, and trustworthy AI is, therefore, much needed to gain insights on what and how trustworthy AI can be conceptualised through the normative resources of other cultural traditions. This article attempts to offer a culturally sensitive exploration of trustworthy AI by drawing on recent analysis of trust and trustworthiness in Confucian philosophy. More specifically, I shall demonstrate how taking seriously the Confucian view of trust and trustworthiness in the context of AI provides us an alternative way to think about the ethics and governance of AI. (shrink)

Machine unlearning (MU) is often analyzed in terms of how it can facilitate the “right to be forgotten.” In this commentary, we show that MU can support the OECD’s five principles for trustworthy AI, which are influencing AI development and regulation worldwide. This makes it a promising tool to translate AI principles into practice. We also argue that the implementation of MU is not without ethical risks. To address these concerns and amplify the positive impact of MU, we offer policy (...) recommendations across six categories to encourage the research and uptake of this potentially highly influential new technology. (shrink)

I motivate and defend a new way of theorising about trust and trustworthiness – and their relationship to each other – by locating both within a broader picture that captures largely overlooked symmetries on both the trustor's and trustee's side of a cooperative exchange. The view defended here takes good cooperation as a theoretical starting point; on the view proposed, cooperation between trustor and trustee is working well when achievements in trust and in responding to trust are matched on (...) both sides of the trust exchange. In a bit more detail, 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). From this starting point, we can then appreciate symmetrical ways that the trustor and trustee can (respectively) fall short, by violating what are shown to be symmetrical evaluative norms – of success, competence and aptness – that regulate the attempts made by both trustor and trustee. The overall picture has important advantages over the received way of theorising about how trust stands to trustworthiness, and it clears the way – by identifying key questions that have been obscured – to making further progress. (shrink)

I argue that trustworthiness is an epistemic desideratum. It does not reduce to justified or reliable true belief, but figures in the reason why justified or reliable true beliefs are often valuable. Such beliefs can be precarious. If a belief's being justified requires that the evidence be just as we take it to be, then if we are off even by a little, the belief is unwarranted. Similarly for reliability. Although it satisfies the definition of knowledge, such a belief (...) is not trustworthy. We ought not use it as a basis for inference or action and ought not give others to believe it. The trustworthiness of a belief, I urge, depends on its being backed by reasons—considerations that other members of the appropriate epistemic community cannot reasonably reject. Trustworthiness is intersubjective. It both depends on and contributes to the evolving cognitive values of an epistemic community. (shrink)

This paper argues that trustworthiness is an epistemic virtue that promotes objectivity. I show that untrustworthy imposture can be an arrogant act of privilege that silences marginalized voices. But, as epistemologists of ignorance have shown, sometimes trickery and the betrayal of epistemic norms are important resistance strategies. This raises the question: when is betrayal of trust epistemically virtuous? After establishing that trust is central to objectivity, I argue for the following answer: a betrayal is epistemically vicious when it strengthens (...) or promotes oppressive, exclusive networks of trust, and a betrayal is epistemically virtuous when it expands trust networks to involve the oppressed. These criteria correctly account for both the epistemic vice of a recent case of Internet imposture and the epistemic virtue of resistant tricksters. (shrink)

Katherine Hawley investigates what trustworthiness means in our lives. We become untrustworthy when we break promises, miss deadlines, or give unreliable information. But we can't be sure about what we can commit to. Hawley examines the social obstacles to trustworthiness, and explores how we can steer between overcommitment and undercommitment.

Psychiatric classification, as exemplified by the Diagnostic and Statistical Manual of Mental Disorders, is dealing with a lack of trust and credibility—in the scientific, but also in the public realm. Regarding the latter in particular, one possible remedial measure for this crisis in trust lies in an increased integration of patients into the DSM revision process. The DSM, as a manual for clinical practice, is forced to make decisions that exceed available data and involve value-judgments. Regarding such decisions, public epistemic (...) trustworthiness requires that these value-judgments should be representative of those of the affected public, and that the public has a reason to believe such a representation to be realized. Due to the long tradition of distrust in psychiatry, such a reason can in this case best be provided by an actual integration of patients into the decision-making process, rather than by their representation through scientific experts. (shrink)

I examine critically a received view of expert trustworthiness and the value-free ideal of science. According to this view, to be epistemically trustworthy in the eyes of citizens, scientific experts should aim to be as neutral as possible with respect to moral and social values when they provide research-based knowledge and advice to different publics. This view is thought to be feasible and desirable for both epistemic and moral/political reasons. I challenge this view by arguing against three recent attempts (...) to defend the legacy of the value-free ideal of science. An analysis of epistemic trustworthiness helps philosophers understand why moral and social values should guide scientific experts’ knowledge-sharing activities. It also helps understand which moral and social values are needed to build and maintain expert trustworthiness. However, it does not amount to a full-service account of the proper roles of non-epistemic values in science. The analysis offers merely a partial approach to the value management question. (shrink)

Situationists such as John Doris, Gilbert Harman, and Maria Merritt suppose that appeal to reliable behavioral dispositions can be dispensed with without radical revision to morality as we know it. This paper challenges this supposition, arguing that abandoning hope in reliable dispositions rules out genuine trust and forces us to suspend core reactive attitudes of gratitude and resentment, esteem and indignation. By examining situationism through the lens of trust we learn something about situationism (in particular, the radically revisionary moral implications (...) of its adoption) as well as something about trust (in particular, that the conditions necessary for genuine trust include a belief in a capacity for robust dispositions). (shrink)

Confucius’s teachings fall under four headings: “culture, moral conduct, doing one’s best, and being trustworthy in what one says” (7/25).1 Trust or, more precisely, being trustworthy, plays a central role in the Confucian ethic. This paper begins by examining the Confucian concept of trustworthiness. The second part of the paper discusses how the ideal of trustworthiness makes itself felt inbusiness practices within China. The paper concludes by raising and addressing several objections to the Confucian emphasis ontrustworthiness.

Establishing credibility and trustworthiness is essential in Economic Agent-Based Modeling (ABM), where clear epistemic standards cannot be defined a priori. In this paper, we first review the notions of trustworthiness and credibility in modeling. We then introduce a framework that emphasizes the modeler's epistemic responsibility to ensure coherence between modeling purposes, strategies and targets. We examine the challenges in assessing model reliability that arise from the interaction of conceptual, algorithmic and computational constituents, and we propose a meta-analytical approach (...) to enhance model consistency by conceptualizing agent-based simulations as iterated analogies. Our analysis outlines strategies for improving model accessibility and reliability while highlighting the modeler's role in preventing mistargeting and misuse. This research provides a normative basis for justifying the credibility of both idealized and targetless models by promoting transparency and consistency between model design and intended purposes. (shrink)

This paper proposes a novel way to understand trust in blockchain technology by analogy with trust placed in institutions. In support of the analysis, a detailed investigation of institutional trust is provided, which is then used as the basis for understanding the nature and ethical limits of blockchain trust. Two interrelated arguments are presented. First, given blockchains’ capacity for being institution-like entities by inviting expectations similar to those invited by traditional institutions, blockchain trust is argued to be best conceptualized as (...) a specialized form of trust in institutions. Keeping only the core functionality and certain normative ideas of institutions, this technology broadens our understanding of trust by removing the need for third parties while retaining the value of trust for the trustor. Second, the paper argues that blockchains’ decentralized nature and the implications and effects of this decentralization on trust issues are double-edged. With the erasure of central points, the systems simultaneously crowd out the pivotal role played by traditional institutions and a cadre of representatives in meeting their assigned obligations and securing the functional systems’ trustworthy performances. As such, blockchain is positioned as a technology containing both disruptive features that can be embedded with meaningful normative values and inherent ethical limits that pose a direct challenge to the actual trustworthiness of blockchain implementations. Such limits are proposed to be ameliorated by facilitating a shift of responsibility to the groups of people directly associated with the engendering of trust in the blockchain context. (shrink)

In this article, we explore questions about the culture of trustworthy artificial intelligence (AI) through the lens of ecosystems. We draw on the European Commission’s Guidelines for Trustworthy AI and its philosophical underpinnings. Based on the latter, the trustworthiness of an AI ecosystem can be conceived of as being grounded by both the so-called rational-choice and motivation-attributing accounts—i.e., trusting is rational because solution providers deliver expected services reliably, while trust also involves resigning control by attributing one’s motivation, and hence, (...) goals, onto another entity. Our research question is: What aspects contribute to a responsible AI ecosystem that can promote justifiable trustworthiness in a healthcare environment? We argue that especially within devising governance and support aspects of a medical AI ecosystem, considering the so-called motivation-attributing account of trust provides fruitful pointers. There can and should be specific ways and governance structures supporting and nurturing trustworthiness beyond mere reliability. After compiling a list of preliminary requirements for this, we describe the emergence of one particular medical AI ecosystem and assess its compliance with and future ways of improving its functioning as a responsible AI ecosystem that promotes trustworthiness. (shrink)

Previous literature has demonstrated the important role that trust plays in developing and maintaining well-functioning societies. However, if we are to learn how to increase levels of trust in society, we must first understand why people choose to trust others. One potential answer to this is that people view trust as normative: there is a social norm for trusting that imposes punishment for noncompliance. To test this, we report data from a survey with salient rewards to elicit people’s attitudes regarding (...) the punishment of distrusting behavior in a trust game. Our results show that people do not behave as though trust is a norm. Our participants expected that most people would not punish untrusting investors, regardless of whether the potential trustee was a stranger or a friend. In contrast, our participants behaved as though being trustworthy is a norm. Most participants believed that most people would punish someone who failed to reciprocate a stranger’s or a friend’s trust. We conclude that, while we were able to reproduce previous results establishing that there is a norm of reciprocity, we found no evidence for a corresponding norm of trust, even among friends. (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 (...) class='Hi'>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)

Achieving trustworthy AI is increasingly considered an essential desideratum to integrate AI systems into sensitive societal fields, such as criminal justice, finance, medicine, and healthcare, among others. For this reason, it is important to spell out clearly its characteristics, merits, and shortcomings. This article is the first survey in the specialized literature that maps out the philosophical landscape surrounding trust and trustworthiness in AI. To achieve our goals, we proceed as follows. We start by discussing philosophical positions on trust (...) and trustworthiness, focusing on interpersonal accounts of trust. This allows us to explain why trust, in its most general terms, is to be understood as reliance plus some “extra factor”. We then turn to the first part of the definition provided, i.e., reliance, and analyze two opposing approaches to establishing AI systems’ reliability. On the one hand, we consider transparency and, on the other, computational reliabilism. Subsequently, we focus on debates revolving around the “extra factor”. To this end, we consider viewpoints that most actively resist the possibility and desirability of trusting AI systems before turning to the analysis of the most prominent advocates of it. Finally, we take up the main conclusions of the previous sections and briefly point at issues that remain open and need further attention. (shrink)

With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets (...) and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. (shrink)

Patient data is used to drive an ecosystem of advanced digital tools in health care, like predictive models or artificial intelligence‐based decision support. Patients themselves, however, receive little information about these technologies or how they affect their care. This raises important questions about patient trust and continued engagement in a health care system that extracts their data but does not treat them as key stakeholders. This essay explores these tensions and provides steps forward for health systems as they design advanced (...) health information‐technology (IT) policies and practices. It centers patients, their concerns, and the ways they perceive trustworthiness to reframe advanced health IT in service of patient interests. (shrink)

What is it to trust someone? What is it for someone to be trustworthy? These are the two main questions that this paper addresses. There are various situations that can be described as ones of trust, but this paper considers the issue of trust between individuals. In it, I suggest that trust is distinct from reliance or cases where someone asks for something on the expectation that it will be done due to the different attitude taken by the trustor. I (...) argue that the trustor takes Holton’s ‘participant stance’ and this distinguishes trust from reliance. I argue that trustworthiness is different from reliability and that an account of trustworthiness cannot be successful whilst ignoring the point that aligning trustworthiness with reliability removes the virtue from being trustworthy. On the question of what it is distinguishes trustworthiness from reliability, I argue that the distinction is in the opportunity for the trustee to act against the wishes of the trustor and the trustee’s consideration of the value of the trust that has been placed in them by the trustor. (shrink)