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.

Abstract: 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)

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)

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)

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)

This essay analyses the Confucian conception of xin, an attribute that broadly resembles what we would ordinarily call trustworthiness. More specifically, it provides an analysis of the psychology of someone who is xin and highlights a feature of the Confucian conception of trustworthiness: the trustworthy person has to ensure that there is a match between her self-presentation and the way she is. My goal is not to argue against any of the existing accounts of trustworthiness but to (...) draw on Confucian insights so as to shed light on features of trustworthiness that are overlooked in current discussions. I hope to show that the Confucian conception of trustworthiness puts more emphasis on the way a trustworthy person actively tries to make sure another’s dependency on her is not unwarranted than on how the trustworthy person responds to the one who gives trust. (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)

Cyberspace relies on information technologies to mediate relations between different people, across different communication networks and is reliant on the supporting technology. These interactions typically occur without physical proximity and those working depending on cybersystems must be able to trust the overall human–technical systems that support cyberspace. As such, detailed discussion of cybersecurity policy would be improved by including trust as a key value to help guide policy discussions. Moreover, effective cybersystems must have resilience designed into them. This paper argues (...) that trustworthy cybersystems are a key element to resilient systems, and thus are core to cybersecurity policy. The paper highlights the importance of trustworthiness for resilient cybersystems. The importance of trustworthiness is shown through a discussion of three events where trustworthiness was the target or casualty of cyberattacks: Stuxnet, hacking of communications and the Edward Snowden revelations. The impact of losing trust is highlighted, to underpin the argument that a resilient cybersystem ought to design in trustworthiness. The paper closes off by presenting a general set of policy implications arising from recognition of the interplay between trust, trustworthiness and resilience for effective cybersecurity. (shrink)

Trustworthiness is typically regarded as a desirable feature of national identification systems (NISs); but the variegated nature of the trustor communities associated with such systems makes it difficult to see how a single system could be equally trustworthy to all actual and potential trustors. This worry is accentuated by common theoretical accounts of trustworthiness. According to such accounts, trustworthiness is relativized to particular individuals and particular areas of activity, such that one can be trustworthy with regard to (...) some individuals in respect of certain matters, but not trustworthy with regard to all trustors in respect of every matter. The present article challenges this relativistic approach to trustworthiness by outlining a new account of trustworthiness, dubbed the expectation-oriented account. This account allows for the possibility of an absolutist (or one-place) approach to trustworthiness. Such an account, we suggest, is the approach that best supports the effort to develop NISs. To be trustworthy, we suggest, is to minimize the error associated with trustor expectations in situations of social dependency (commonly referred to as trust situations), and to be trustworthy in an absolute sense is to assign equal value to all expectation-related errors in all trust situations. In addition to outlining the features of the expectation-oriented account, we describe some of the implications of this account for the design, development, and management of trustworthy NISs. (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)

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)

Trust can be thought of as a three place relation: A trusts B to do X. Trustworthiness has two components: competence (does the trustee have the relevant skills, knowledge and abilities to do X?) and willingness (is the trustee intending or aiming to do X?). This chapter is about the willingness component, and the different motivations that a trustee may have for fulfilling trust. The standard assumption in economics is that agents are self-regarding, maximizing their own consumption of goods (...) and services. This is too restrictive. In particular, people may be concerned with the outcomes of others, and they may be concerned to follow ethical principles. I distinguish weak trustworthiness, which places no restrictions on B’s motivation for doing X, from strong trustworthiness, where the behaviour must have a particular non-selfish motivation, in finance the fiduciary commitment to promote the interests of the truster. I discuss why strong trustworthiness may be more efficient and also normatively preferable to weak. In finance, there is asymmetric information between buyer and seller, which creates a need for trustworthy assessment of products. It also creates an ambiguity about whether the relationship is one of buyer and seller, governed by caveat emptor, or a fiduciary relationship of advisor and client. This means that there are two possible reasons why trust may be breached: because the trustee didn’t realise that the truster framed the relationship as a fiduciary one, or because the trustee did realise but actively sought to take advantage of the trust. Correspondingly, there are two possible types of agent: normal people who are not always self-regarding and who are trust responsive (if they believe that they are being trusted then they are likely to fulfill that trust), and knaves, after Hume’s character who is always motivated by his own private interest. We can increase the trustworthiness of normal people by getting them to re-frame the situation as one of trust, so they will be strongly trustworthy (i.e. change of institutional culture), and by providing non-monetary incentives (the correct choice of incentive will depend on exactly what their non-selfish motivation is). Knaves need sanctions, which can make them weakly trustworthy. However, this is a delicate balance because sanctions can crowd out normative frames. We can also increase the trustworthiness of financiers by making finance less attractive to knaves; changing the mix of types in finance could help support the necessary cultural change. (shrink)

This publication forms a basis for the interdisciplinary development of a certification system for artificial intelligence. In view of the rapid development of artificial intelligence with disruptive and lasting consequences for the economy, society, and everyday life, it highlights the resulting challenges that can be tackled only through interdisciplinary dialogue between IT, law, philosophy, and ethics. As a result of this interdisciplinary exchange, it also defines six AI-specific audit areas for trustworthy use of artificial intelligence. They comprise fairness, transparency, autonomy (...) and control, data protection as well as security and reliability while addressing ethical and legal requirements. The latter are further substantiated with the aim of operationalizability. (shrink)

We argue that, to be trustworthy, Computa- tional Intelligence (CI) has to do what it is entrusted to do for permissible reasons and to be able to give rationalizing explanations of its behavior which are accurate and gras- pable. We support this claim by drawing par- allels with trustworthy human persons, and we show what difference this makes in a hypo- thetical CI hiring system. Finally, we point out two challenges for trustworthy CI and sketch a mechanism which could be (...) used to gener- ate sufficiently accurate as well as graspable rationalizing explanations for CI behavior. (shrink)

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong (...) desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three diferent aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness. (shrink)

AI systems that demonstrate significant bias or lower than claimed accuracy, and resulting in individual and societal harms, continue to be reported. Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles. This paper focusses on the funding processes for AI research grants which we have identified as a gap in the current range of ethical AI solutions such as AI procurement guidelines, AI impact assessments and (...) AI audit frameworks. We highlight the responsibilities of funding bodies to ensure investment is channelled towards trustworthy and safe AI systems and provides case studies as to how other ethical funding principles are managed. We offer a first sight of two proposals for funding bodies to consider regarding procedures they can employ. The first proposal is for the inclusion of a Trustworthy AI Statement’ section in the grant application form and offers an example of the associated guidance. The second proposal outlines the wider management requirements of a funding body for the ethical review and monitoring of funded projects to ensure adherence to the proposed ethical strategies in the applicants Trustworthy AI Statement. The anticipated outcome for such proposals being employed would be to create a ‘stop and think’ section during the project planning and application procedure requiring applicants to implement the methods for the ethically aligned design of AI. In essence it asks funders to send the message “if you want the money, then build trustworthy AI!”. (shrink)

Algorithm engineering is sometimes portrayed as a new 21st century return of manipulative social engineering. Yet algorithms are necessary tools for individuals to navigate online platforms. Algorithms are like a sensory apparatus through which we perceive online platforms: this is also why individuals can be subtly but pervasively manipulated by biased algorithms. How can we better understand the nature of algorithm engineering and its proper function? In this chapter I argue that algorithm engineering can be best conceptualized as a type (...) of environmental engineering aimed at making the online environment more hospitable to human use, in particular by safeguarding the conditions that allow for trust. (shrink)

A theme running through Katherine Hawley’s recent works on trust and trustworthiness is that thinking about the relations between these and Miranda Fricker’s notion of testimonial injustice offers a perspective from which we can see several limitations of Fricker’s own account of testimonial injustice. This paper clarifies the aspects of Fricker’s account that Hawley’s criticisms target, focusing on her objections to Fricker’s proposal that its primary harm involves a kind of epistemic objectification and her characterization of testimonial injustice in (...) terms of prejudicial credibility deficits. I also offer an assessment of the potency of Hawley’s objections, concluding that they do point to genuine limitations of Fricker’s account, but that we can appreciate Hawley’s points without adopting her trust-centric approach to testimonial injustice, or her specific commitment-based accounts of trust and trustworthiness. However, in the last section I examine the positive picture of testimonial injustice that emerges from Hawley’s discussion of unequally distributed obstacles to both being trustworthy and maintaining a reputation for trustworthy testimony in her recent book How To Be Trustworthy, considering how this picture contrasts with Fricker’s account and where it might have important affinities with other accounts in the literature. (shrink)

This paper proposes a formal account of AI trustworthiness, connecting both intrinsic and perceived trustworthiness in an operational schematization. We argue that trustworthiness extends beyond the inherent capabilities of an AI system to include significant influences from observers' perceptions, such as perceived transparency, agency locus, and human oversight. While the concept of perceived trustworthiness is discussed in the literature, few attempts have been made to connect it with the intrinsic trustworthiness of AI systems. Our analysis (...) introduces a novel schematization to quantify trustworthiness by assessing the discrepancies between expected and observed behaviors and how these affect perceived uncertainty and trust. The paper provides a formalization for measuring trustworthiness, taking into account both perceived and intrinsic characteristics. By detailing the factors that influence trust, this study aims to foster more ethical and widely accepted AI technologies, ensuring they meet both functional and ethical criteria. (shrink)

The aim of this paper is twofold: first, I provide a cluster of theories of truth in classical logic that is (internally) consistent with global reflection principles: the theories of positive truth (and falsity). After that, I analyse the _epistemic value_ of such theories. I do so employing the framework of cognitive projects introduced by Wright (Proc Aristot Soc 78:167–245, 2004), and employed—in the context of theories of truth—by Fischer et al. (Noûs 2019. https://doi.org/10.1111/nous.12292 ). In particular, I will argue (...) that theories of positive truth are _trustworthy_, analogously to the theories of full disquotational truth. Moreover, I argue that, for a given cognitive project, _if_ the acceptance of trustworthy theories is taken to be an _epistemic norm_ of cognitive project, then one has good reasons to accept theories of positive truth over other rival theories of truth in classical logic. On the other hand, the latter theories are deemed epistemically unacceptable. (shrink)

Following the publication of numerous ethical principles and guidelines, the concept of 'Trustworthy AI' has become widely used. However, several AI ethicists argue against using this concept, often backing their arguments with decades of conceptual analyses made by scholars who studied the concept of trust. In this paper, I describe the historical-philosophical roots of their objection and the premise that trust entails a human quality that technologies lack. Then, I review existing criticisms about 'Trustworthy AI' and the consequence of ignoring (...) these criticisms: if the concept of 'Trustworthy AI' is kept being used, we risk attributing responsibilities to agents who cannot be held responsible, and consequently, deteriorate social structures which regard accountability and liability. Nevertheless, despite suggestions to shift the paradigm from 'Trustworthy AI' to 'Reliable AI', I argue that, realistically, this concept will be kept being used. I end by arguing that, ultimately, AI ethics is also about power, social justice, and scholarly activism. Therefore, I propose that community-driven and social justice-oriented ethicists of AI and trust scholars further focus on (a) democratic aspects of trust formation; and (b) draw attention to critical social aspects highlighted by phenomena of distrust. This way, it will be possible to further reveal shifts in power relations, challenge unfair status quos, and suggest meaningful ways to keep the interests of citizens. (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)

Since the global financial crisis in 2008, corporations have faced a crisis of trust, with growing sentiment against ‘elites and ‘big business’ and a feeling that ‘something ought to be done’ to re-establish public regard for corporations. Trust and trustworthiness are deeply moral significant. They provide the ‘glue or lubricant’ that begets reciprocity, decreases risk, secures dignity and respect, and safeguards against the subordination of the powerless to the powerful. However, in deciding how to restore trust, it is difficult (...) to determine precisely what should be done, by whom, and who will bear the cost, especially if any action involves a risk to overall market efficiency and corporate profitability. The paper explores whether corporations have a moral duty to be trustworthy, to bear the cost of being so and thus contribute to resolving the current crisis of trust. It also considers where the state and other social actors have strong reason to protect and enforce such moral rights, while acknowledging that other actors have similar obligations to be trustworthy. It outlines five ‘salient factors’ that trigger specific rights to trustworthiness and a concomitant duty on corporations to be trustworthy: market power, subordination (threat and intimidation), the absence of choice, the need to preserve systemic trust, and corporate political power which might undermine a state’s legitimacy. Absent these factors and corporations do not have a general duty to be trustworthy, since a responsible actor in fair market conditions should be able to choose between the costs and benefits of dealing with generally trustworthy corporations. (shrink)

Philosophical accounts of trustworthiness typically define trustworthiness as an agent being reliable in virtue of a specific motivation such as goodwill. The underlying thought motivating this view is that to be trustworthy is to be more than merely reliable. If motivational accounts are correct, this is a problem for non-motivational accounts of trustworthiness, as motivations are not required for trustworthiness. In this paper, I defend the non-motivational approach to trustworthiness and show that the motivational approach (...) is inadequate. I do this by making a novel distinction between trusting-to and trusting-as relations. A trusting-to relation is a relation in which a trustor ‘X’ trusts the trustee ‘Y’ to do something. Trusting-as relations are an overlooked relation implicit in all trusting-to relations. They describe the social relationship that holds between X and Y. I will argue that trusting-as relations determine whether any specific motivations are required for trustworthiness trusting-to relations. Thus, I show that acknowledging trusting-as relations enables us to provide a satisfactory explanation of the motivation intuition without making specific motivations constitutive features of trust. -/- . (shrink)

Social epistemologists often operationalize the task of indirectly assessing experts’ trustworthiness to identifying whose beliefs are more reliably true on matters in an area of expertise. Not only does this neglect the philosophically rich space between belief formation and testimonial utterances, it also reduces trustworthiness to reliability. In ethics of trust, by contrast, explicitly relational views of trust include things like good will and responsiveness. One might think that relational aspects can be safely set aside for social epistemology (...) of trust in experts, that such considerations may be relevant for personal relationships but not for expert trustworthiness. Against these claims I argue for the social-epistemic relevance of relational aspects of trust in experts, and to that end I discuss three sorts of considerations – responsively positive, neutral, and negative factors – that can make a difference for expert trustworthiness. (shrink)

I reply to Piazza's objection to my reductio against phenomenal conservatism.

When people must either save a greater number of people from a smaller harm or a smaller number from a greater harm, do their choices reflect a reasonable moral outlook? We pursue this question with the help of an experiment. In our experiment, two-fifths of subjects employ a similarity heuristic. When alternatives appear dissimilar in terms of the number saved but similar in terms of the magnitude of harm prevented, this heuristic mandates saving the greater number. In our experiment, this (...) leads to choices that are inconsistent with all standard theories of justice. We argue that this demonstrates the untrustworthiness of distributive judgments in cases that elicit similarity-based choice. (shrink)

In this paper, I examine the ethics of e - trust and e - trustworthiness in the context of health care, looking at direct computer-patient interfaces (DCPIs), information systems that provide medical information, diagnosis, advice, consenting and/or treatment directly to patients without clinicians as intermediaries. Designers, manufacturers and deployers of such systems have an ethical obligation to provide evidence of their trustworthiness to users. My argument for this claim is based on evidentialism about trust and trustworthiness: the (...) idea that trust should be based on sound evidence of trustworthiness. Evidence of trustworthiness is a broader notion than one might suppose, including not just information about the risks and performance of the system, but also interactional and context-based information. I suggest some sources of evidence in this broader sense that make it plausible that designers, manufacturers and deployers of DCPIs can provide evidence to users that is cognitively simple, easy to communicate, yet rationally connected with actual trustworthiness. (shrink)

Abstract: There are epistemic manipulators in the world. These people are actively attempting to sacrifice epistemic goods for personal gain. In doing so, manipulators have led many competent epistemic agents into believing contrarian theories that go against well-established knowledge. In this paper, I explore one mechanism by which manipulators get epistemic agents to believe contrarian theories. I do so by looking at a prominent empirical model of trustworthiness. This model identifies three major factors that epistemic agents look for when (...) trying to determine who is trustworthy. These are (i) ability, (ii) benevolence, and (iii) moral integrity. I then show how manipulators can manufacture the illusion that they possess these factors. This leads epistemic agents to view manipulators as trustworthy sources of information. Additionally, I argue that fact-checking will be an ineffective – or even harmful – practice when correcting the beliefs of epistemic agents who have been tricked by this illusion of epistemic trustworthiness. I suggest that in such cases we should use an alternative correction, which I call trust undercutting. (shrink)

In this paper we raise the question whether technological artifacts can properly speaking be trusted or said to be trustworthy. First, we set out some prevalent accounts of trust and trustworthiness and explain how they compare with the engineer’s notion of reliability. We distinguish between pure rational-choice accounts of trust, which do not differ in principle from mere judgments of reliability, and what we call “motivation-attributing” accounts of trust, which attribute specific motivations to trustworthy entities. Then we consider some (...) examples of technological entities that are, at first glance, best suited to serve as the objects of trust: intelligent systems that interact with users, and complex socio-technical systems. We conclude that the motivation-attributing concept of trustworthiness cannot be straightforwardly applied to these entities. Any applicable notion of trustworthy technology would have to depart significantly from the full-blown notion of trustworthiness associated with interpersonal trust. (shrink)

Many policies and ethical guidelines recommend developing “trustworthy AI”. We argue that developing morally trustworthy AI is not only unethical, as it promotes trust in an entity that cannot be trustworthy, but it is also unnecessary for optimal calibration. Instead, we show that reliability, exclusive of moral trust, entails the appropriate normative constraints that enable optimal calibration and mitigate the vulnerability that arises in high-stakes hybrid decision-making environments, without also demanding, as moral trust would, the anthropomorphization of AI and thus (...) epistemically dubious behavior. The normative demands of reliability for inter-agential action are argued to be met by an analogue to procedural metacognitive competence (i.e., the ability to evaluate the quality of one’s own informational states to regulate subsequent action). Drawing on recent empirical findings that suggest providing reliability scores (e.g., F1-scores) to human decision-makers improves calibration in the AI system, we argue that reliability scores provide a good index of competence and enable humans to determine how much they wish to rely on the system. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. (...) For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

The present study aimed to explore the effect of subliminal priming on team trust and the mechanism through the mediating role of perceived trustworthiness. A total of 144 participants were asked to complete a lexical decision task that was embedded with the “trust” or “suspicion” Chinese words as the subliminal stimuli. Then, they played a public good game and evaluated the perceived trustworthiness of the team. The results of the study showed that subliminal stimuli had a significant effect (...) on team trust [β = –0.99, 95% CI = (−1.64, −0.33)]. Perceived trustworthiness was found to have a significant mediating effect between the priming condition and team trust [β = −0.35, 95% CI = (−0.72, −0.02)]. The current study revealed the underlying mechanism through which subliminal priming techniques influence team trust and informed efforts by altering perceived trustworthiness. (shrink)

As health systems around the world turn towards highly distributed, specialized and cooperative structures to increase quality and safety of care as well as efficiency and efficacy of delivery processes, there is a growing need for supporting communication and collaboration of all parties involved with advanced ICT solutions. The Electronic Health Record (EHR) provides the information platform which is maturing towards the eHealth core application. To meet the requirements for sustainable, semantically interoperable, and trustworthy EHR solutions, different standards and different (...) national strategies have been established. The workshop summarizes the requirements for such advanced EHR systems and their underlying architecture, presents different strategies and solutions advocated by corresponding protagonists, discusses pros and cons as well as harmonization and migration strategies for those approaches. It particularly highlights a turn towards ontology-driven architectures. (shrink)

The current study is conducted to examine the following research questions: 1) How are information trustworthiness, usefulness, and immersiveness associated with the general intention to try space tourism? 2) Does the uncertainty of information (proxied by information trustworthiness) moderate the associations between information usefulness, immersiveness, and the general intention to try space tourism?

In four experiments, we offer evidence that virtues are often judged as uniquely important for some business practices (e.g., hospital management and medical error investigation). Overall, actions done only from virtue (either by organizations or individuals) were judged to feel better, to be more praiseworthy, to be more morally right, and to be associated with more trustworthy leadership and greater personal life satisfaction compared to actions done only to produce the best consequences or to follow the correct moral rule. These (...) results accord with claims made by some virtue ethicists. The current data contribute to a small but growing body of literature emphasizing both empirical soundness and philosophical rigor in the scientific study of virtue. Results also offer some guidance concerning how businesses, employees, and executives are evaluated and perceived. Implications for theory and practice are discussed. (shrink)

The main thesis of this paper is that when we trust the results of scientific research, that trust is inevitably directed at least in part at collective bodies rather than at single researchers, and that accordingly, reasonable assessments of epistemic trustworthiness in science must attend to these collective bodies. In order to support this claim, I start by invoking the collaborative nature of most of today’s scientific research. I argue that the trustworthiness of a collaborative research group does (...) not supervene on the trustworthiness of its individual members and point out some specific problems for the assessment of epistemic trustworthiness that arise from the specific nature of today’s collaborative research. Next, I argue that the social diffusion of trustworthiness goes even further; we always also need an assessment of the trustworthiness of the respective research community as a whole. Communities, I claim, play an essential role in the epistemic quality management of science. To see why this role is indispensible, we have to appreciate the full complexity of determining what is desirable in a method of inquiry. The relevant features of a method include three different dimensions: the reliability of positive results, the reliability of negative results, and the method’s power. Every methodological choice involves a trade-off between these three dimensions. The right balance between them (the “distribution of inductive risks”, or DIR) depends on value judgments about the costs of false results and the benefits of correct ones. Conventional methodological standards of research communities impose constraints on admissible DIR and thereby harmonize the implicit value judgments. Trusting that the research community has set the limitations on DIR in a suitable way is thus always part of placing our trust in a scientific result. (shrink)

AI is revolutionizing everyone’s life, and it is crucial that it does so in the right way. AI’s profound and far-reaching potential for transformation concerns the engineering of systems that have some degree of autonomous agency. This is epochal and requires establishing a new, ethical balance between human and artificial autonomy.

Societies need markets, so just as trustworthy professionals are needed in fields such as healthcare, law and education, modern societies need trustworthy market managers, including corporate officers and directors. But in its screening of candidates, U.S. corporate business has lagged behind fields such as medicine and law, which in the nineteenth century addressed their need for screening by upgrading professional education and establishing licensing of individual practitioners. Corporate business, by contrast, has been too tolerant of problematic executives, particularly executives of (...) a type shown by recent research in psychology to exhibit a set of personality traits including below average concern about bad effects of their actions on other people. Over-representation of this problematic type has cost corporate business the trust and respect it could earn by resting fully on a time-honored alternative foundation already espoused by many trustworthy teachers and practitioners of business. Society needs these trustworthy people of business to work together to establish screening of candidates for high level corporate positions by upgrading MBA education and establishing licensing for these positions. For reasons again based on current findings in psychology, screening candidates for the MBA could be significantly strengthened by requiring historical studies, particularly history of the corporate legal structure in the U.S. and history of the MBA itself. Upgrading the MBA and establishing correlated licensing could open the way toward corrections in the legal form of the corporation to bring it into line with hospitals, law courts and universities as places where responsible professionals pursue their callings on behalf of society. (shrink)

A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...) should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation. (shrink)

By adopting social exchange theory and the affect-infusion-model, the hypothesis is made that emotional intelligence (EI) will have an impact on three perceptions of trustworthiness – ability, integrity and benevolence – at the beginning of a relationship. It was also hypothesized that additional information would gradually displace EI in forming the above perceptions. The results reveal that EI initially does not contribute to any of the perceptions of trustworthiness. As more information is revealed EI has an impact on (...) the perception of benevolence, but not on the perceptions of ability and integrity. This impact was observed to be negative when the nature of the information was negative. On the other hand, information alone was shown to have a significant impact on the perceptions of ability and integrity, but not on the perception of benevolence. Theoretical and practical implications of the findings are addressed. (shrink)

Trust is a core feature of the physician-patient relationship, and risk is central to trust. Patients take risks when they trust their providers to care for them effectively and appropriately. Not all patients take these risks: some medical relationships are marked by mistrust and suspicion. Empirical evidence suggests that some patients and families of color in the United States may be more likely to mistrust their providers and to be suspicious of specific medical practices and institutions. Given both historical and (...) ongoing oppression and injustice in American medical institutions, such mistrust can be apt. Yet it can also frustrate patient care, leading to family and provider distress. In this paper, I propose one way that providers might work to reestablish trust by taking risks in signaling their own trustworthiness. This interpersonal step is not meant to replace efforts to remedy systemic injustice, but is an immediate measure for addressing mistrust in occurrent cases. (shrink)

Abstract:Trust is important for a variety of social relationships. Trust facilitates trade, which increases prosperity and induces us to interact with people of different backgrounds on terms that benefit all parties. Trade promotes trustworthiness, which enables us to form meaningful as well as mutually beneficial relationships. In what follows, I argue that when we erect institutions that enhance trust and reward people who are worthy of trust, we create the conditions for a certain kind of moral progress.

Trust is commonly defined as a metaphysically-hybrid notion involving an attitude and an action. The action component of trust is defined as a special form of reliance in which the trustor has: (1) heightened expectations of their trustee; and (2) a disposition to justifiably feel betrayed if their trust is broken. The first aim of this paper is to reject the view that trust is a form of reliance. -/- The second aim of this paper is to develop and defend (...) a non-reliance-based variation of Katherine Hawley’s commitment trust account. Roughly, on my variant account, if X trusts Y to ϕ, then X has a belief with the following counterfactual as its content: ‘if I were to rely on Y to keep a commitment to ϕ, then I believe that Y would keep that commitment to ϕ.’ I defend this account against the objection that non-reliance accounts cannot explain the intuition that trust involves heightened expectations, and that it elicits justified betrayal when broken. I also respond to the argument that such accounts can’t provide adequate explanations of therapeutic trust, which is taken to be a counterexample of belief trust insofar as it describes instances where trustors trust trustees despite not believing that they are trustworthy. (shrink)

Recent AI ethics has focused on applying abstract principles downward to practice. This paper moves in the other direction. Ethical insights are generated from the lived experiences of AI-designers working on tangible human problems, and then cycled upward to influence theoretical debates surrounding these questions: 1) Should AI as trustworthy be sought through explainability, or accurate performance? 2) Should AI be considered trustworthy at all, or is reliability a preferable aim? 3) Should AI ethics be oriented toward establishing protections for (...) users, or toward catalyzing innovation? Specific answers are less significant than the larger demonstration that AI ethics is currently unbalanced toward theoretical principles, and will benefit from increased exposure to grounded practices and dilemmas. (shrink)

Why do we trust TV news? What reasons might support a recipient’s assessment of the trustworthiness of this kind of information? This paper presents a veritistic analysis of the epistemic practice of news production and communication. The topic is approached by discussing a detailed case study, namely the characteristics of the most popular German news programme, called the ‘Tagesschau’. It will be shown that a veritistic analysis can indeed provide a recipient with relevant reasons to consider when pondering on (...) the trustworthiness of sources of information. Moreover, it will turn out that these reasons are part of what recipients might gather from media literacy. (shrink)

The increasing use of artificial intelligence (AI) systems in our daily life through various applications, services, and products explains the significance of trust/distrust in AI from a user perspective. AI-driven systems have significantly diffused into various fields of our lives, serving as beneficial tools used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust/distrust in AI plays the role of a regulator and could significantly (...) control the level of this diffusion, as trust can increase, and distrust may reduce the rate of adoption of AI. Recently, varieties of studies have paid attention to the variant dimension of trust/distrust in AI, and its relevant considerations. In this systematic literature review, after conceptualization of trust in the current AI literature review, we will investigate trust in different types of human-Machine interaction, and its impact on technology acceptance in different domains. In addition to that, we propose a taxonomy of technical (i.e., safety, accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and mixed) trustworthiness metrics, and some trustworthy measurements. Moreover, we examine some major trust-breakers in AI (e.g., autonomy and dignity threat), and trust makers; and propose some future directions and probable solutions for the transition to a trustworthy AI. (shrink)

Public discourse implicitly appeals to what we call the “Traumatic Untrustworthiness Argument” (TUA). To motivate, articulate, and assess the TUA, we appeal to Hawley’s (2019) commitment account of trust and trustworthiness. On Hawley’s account, being trustworthy consists in the successful avoidance of unfulfilled commitments and involves three components: the actual avoidance of unfulfilled commitments, sincerity in one’s taking on elective commitments, and competence in fulfilling commitments one has incurred. In contexts of testimony, what’s at issue is the speaker’s competence (...) and sincere intention to speak truthfully. The TUA targets trauma victims’ competence rather than their sincerity. According to the TUA, empirical evidence shows that trauma undermines victims’ trustworthiness with regard to speaking truthfully about their trauma by undermining their competence to remember the relevant event. We argue that what the evidence shows is rather that remembering traumatic events involves a distinct “mode of manifesting” the competence to remember particular events from the personal past. Trauma victims are competent to speak truthfully about their trauma and ought to be trusted at least with regard to the central details of the event. By suggesting otherwise, the TUA threatens an insidious form of epistemic injustice which Hawley’s account helps us locate. (shrink)

This research explores how a person with whom information has been shared and, importantly, an artificial intelligence (AI) system used to deduce information from the shared data contribute to making the disclosure context private. The study posits that private contexts are constituted by the interactions of individuals in the social context of intersubjectivity based on trust. Hence, to make the context private, the person who is the trustee (i.e., with whom information has been shared) must fulfil trust norms. According to (...) the commitment account of trustworthiness, a person is trustworthy only if they satisfy the norm of competence. It is argued that a person using an AI system to answer a question is competent only if they are ex post justified in believing what has been delivered by the AI system. A person’s belief is justified in the doxastic sense only if the AI system is accurate. This feature of AI’s performance affects a person’s competence and, as a result, trustworthiness. The effect of AI on trust as an essential component of making the context private, and thus on privacy, means an AI system also impacts privacy. Therefore, a private context is constituted when the individual with whom the information is shared fulfils the competence norm and the AI system used for analysing the information is sufficiently accurate to adhere to this norm. The result of this research emphasises the significance of the relationship between individuals involved in information-sharing and how an AI system used for analysing that information impacts the relationship regarding making the context private, as well as how it impacts privacy. The findings of this research have significant implications for improving or ameliorating privacy regulations in light of trust. (shrink)