Trust

Trust in the scientific enterprise — in science as an institution — is arguably important to individuals’ and societies’ well-being. Although some measures of public trust in science exist, the recipients of that trust are often ambiguous between trusting individual scientists and the scientific community at large. We argue that more precision would be beneficial — specifically, targeting public trust of the scientific community at large — and describe the development and validation of such an instrument: the Scientific Community Trust (...) Index (SCTI). We show the results of initial field testing to establish instrument reliability and validity. We then demonstrate certain advantages of the SCTI against other measures of trust and deference, and present correlations between the SCTI and participant scores in two trust-in-science scenarios. Our results suggest that the SCTI is a useful and compact tool for measuring public trust in the scientific community. (shrink)

Corruption prevention can be more effective if it does not rely merely on legal enforcement. This theoretical review aimed to propose a hypothetical psychological model capable of explaining the behavior of corruption. Moral disengagement is a variable that is considered ontologically closest in “distance” to the variable of corruption behavior. Counterfeit self, implicit self-theory, ethical mindset and moral emotion are taken into account as the pivotal factors of the corruption behavior and its mechanism of moral disengagement. Counterfeit self along with (...) some moderating variables are regarded to “set” one’s future corrupt behavior based on his/her past/prior ethical or unethical behavior and moral emotions. This review discovered a conjectural-theoretical model of the corruption psychology. It can be used to design a social intervention and training for individuals to manage the mindset and emotion that can buffer counterfeit self effect. In addition, the users of these research findings are recommended to be aware of the surroundings that consist of groups of people with particular ethical mindset, moral emotion proneness and self-theory. (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)

Few recent developments in information technology have been as hyped as blockchain, the first implementation of which was the cryptocurrency Bitcoin. Such hype furnishes ample reason to be skeptical about the promise of blockchain implementations, but I contend that there’s something to the hype. In particular, I think that certain blockchain implementations, in the right material, social, and political conditions, constitute excellent bases for common knowledge. As a case study, I focus on trust in election outcomes, where the ledger records (...) not financial transactions but vote tallies. I argue that blockchain implementations could foster warranted trust in vote tallies and thereby trust in the democratic process. Finally, I argue that if the promise of blockchain implementations as democratic infrastructure is to be realized, then democracies first need to ensure that these material, social, and political conditions obtain. (shrink)

First, we explain the conception of trustworthiness that we employ. We model trustworthiness as a relation among a trustor, a trustee, and a field of trust defined and delimited by its scope. In addition, both potential trustors and potential trustees are modeled as being more or less reliable in signaling either their willingness to trust or their willingness to prove trustworthy in various fields in relation to various other agents. Second, following Alfano (forthcoming) we argue that the social scale of (...) a potential trust relationship partly determines both explanatory and normative aspects of the relation. Most of the philosophical literature focuses on dyadic trust between a pair of agents (Baier 1986, Jones 1996, Jones 2012, McGeer 2008, Pettit 1995), but there are also small communities of trust (Alfano forthcoming) and trust in large institutions (Potter 2002, Govier 1997, Townley & Garfield 2013, Hardin 2002). The mechanisms that induce people to extend their trust vary depending on the size of the community in question, and the ways in which trustworthiness can be established and trusting warranted vary with these mechanisms. Mechanisms that work in dyads and small communities are often unavailable in the context of trusting an institution or branch of government. Establishing trust on this larger social scale therefore requires new or modified mechanisms. In the third section of the paper, we recommend three policies that – we argue – tend to make institutions more trustworthy and to reliably signal that trustworthiness to the public. First, they should ensure that their decision-making processes are as open and transparent as possible. Second, they should make efforts to engage stakeholders in dialogue with decision-makers such as managers, members of the C-Suite, and highly-placed policy-makers. Third, they should foster diversity – gender, ethnicity, age, socioeconomic background, disability, etc. – in their workforce at all levels, but especially in management and positions of power. We conclude by discussing the warrant for distrust in institutions that do not adopt these policies, which we contend is especially pertinent for people who belong to groups that have historically faced (and in many cases still do face) oppression. (shrink)

Faced with current urgent calls for more trust in experts, especially in high impact and politically sensitive domains, such as climate science and COVID-19, the complex and problematic nature of public trust in experts and the need for a more critical approach to the topic are easy to overlook. Scepticism – at least in its Humean mitigated form that encourages independent, questioning attitudes – can prove valuable to democratic governance, but stands in opposition to the cognitive dependency entailed by epistemic (...) trust. In this paper, we investigate the tension between the value of mitigated scepticism – understood as the exercise of reason-based doubt in a particular domain – and the need for trust in experts. We offer four arguments in favour of mitigated scepticism: the argument from loss of intellectual autonomy; the argument from democratic deficit; the argument from the normative failures of science; and the argument from past and current injustices. These arguments highlight the tension between the requirements for trust and justified scepticism about the role of experts. One solution, which we reject, is the idea that reliance, rather than trust, is sufficient for the purposes of accommodating experts in policy matters. The solution we endorse is to create a ‘climate of trust’, where questioning experts and expertise is welcomed, but the epistemic trust necessary for action upon information which the public cannot obtain first-hand is enabled and encouraged through structural, institutional, and justice-based measures. (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)

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

Friendship with the ancients is a set of imaginative exercises and engagements with the work of deceased authors that allows us to imagine them as friends. Authors from diverse cultures and times such as Mengzi, Niccolò Machiavelli, W.E.B Du Bois, and Clare Carlisle have engaged in it. The aim of this paper is to defend this practice, showing that friendship with the ancients is a species of philosophical friendship, which confers the unique benefits such friendships offer. It is conducive to (...) epistemic virtue, notably the related virtues of epistemic humility and of relational understanding. When we cultivate friendship with the ancients, we are not learning facts about them, but aim at understanding their views in their full scope in a way that a relationship between friends allows. (shrink)

In this paper, we locate a general rhetorical strategy employed in theoretical discourse wherein philosophers argue from the mere existence of internalized oppression to some kind of epistemic, moral, political, or cognitive deficiency of oppressed people. We argue that this strategy has harmful consequences for oppressed people, breaking down our analysis in terms of individual and structural harms within both epistemic and moral domains. These harms include attempting to undermine the self-trust of oppressed people, reinforcing unjust epistemic power hierarchies, undermining (...) the moral agency of oppressed people, and obscuring real issues of oppression. In light of these many harms, we conclude that there are pro tanto reasons not to employ this strategy, and instead offer a series of suggestions for those considering adopting such a rhetorical move. (shrink)

When philosophers consider factors compromising autonomy in consent, they often focus solely on the consent-giver’s agential capacities, overlooking the impact of the consent-receiver’s conduct on the consensual character of the activity. In this paper, I argue that valid consent requires justified trust in the consent-receiver to act only within the scope of consent. I call this the Trust Condition (TC), drawing on Katherine Hawley’s commitment account of trust. TC constitutes a belief that the consent-receiver is capable and willing to act (...) as we expect from them. If such trust is not warranted, I argue, consent lacks the appropriate normative grounds. After establishing TC, I explore its application in the sexual arena, asserting that due to the non-contractual dimensions of sexual activity — such as the dynamic nature of sexual desires and the absence of external factors effectively binding sexual partners to the terms of consent—trust is warranted in sexual consent by means of care. I define care as a special sensitivity and attention toward the partner’s will and discuss how this approach leads to safer intimate relationships in practice. (shrink)

Der Erfolg von Maßnahmen zur Eindämmung der COVID-19-Pandemie ist abhängig vom Vertrauen der Öffentlichkeit in wissenschaftliche Experten. Zwar ist Vertrauen als Einstellung gegenüber Experten im Zusammenhang mit der Pandemie bereits viel Aufmerksamkeit zuteilgeworden, allerdings meist in Bezug auf das Vertrauen, das Laien Äußerungen wie Behauptungen und Mitteilungen entgegenbringen, die ihnen das Wissen der Experten zugänglich machen sollen. Dieser Aufsatz stellt dagegen eine andere Art der Äußerung in den Mittelpunkt: die Empfehlung. Im Zusammenhang mit der Pandemie haben Forderungen gegenüber der Politik (...) wissenschaftsbasiert zu verfahren zugenommen. Gleichzeitig sind Politikerinnen und Politiker aber nicht das Sprachrohr der Wissenschaft, sondern übernehmen Verantwortung für eine wissenschaftsbasierte Gesundheitspolitik, unter anderem indem sie Bürgerinnen und Bürgern bestimmte Handlungen empfehlen. Damit erhebt die Politik allerdings den Anspruch, dass Bürgerinnen nicht nur glauben sollten, was ihnen von den Experten gesagt wird, sondern auch, dass sie tun sollten, was von ihnen im Rahmen der Maßnahmen verlangt wird. Ziel dieses Aufsatzes ist es daher zu zeigen, dass Empfehlungen eine Konzeption von Vertrauen erfordert, die sich vom Vertrauen im Kontext von Mitteilungen und Behauptungen stark unterscheidet. Es geht nicht nur darum, diese Art von Vertrauen genauer zu spezifizieren, sondern auch darum zu erklären, unter welchen Voraussetzungen es vernünftig ist, wissenschaftsbasierten Empfehlungen der Politik mit Vertrauen zu begegnen. Dazu gehe ich folgendermaßen vor: In Abschnitt 1 analysiere ich zunächst den Sprechakt des Empfehlens. Das dadurch gewonnene Grundverständnis von empfehlenden Sprechakten untersuche ich dann im Kontext von Empfehlungen wissenschaftlicher Experten während der Covid-19-Pandemie (Abschnitt 2) und plädiere dann dafür, dass eine Analyse der an eine breite Öffentlichkeit gerichteten Empfehlungen am besten bei Äußerungen von Politikern ansetzen muss, die sich auf das kompetente Urteil wissenschaftlicher Expertinnen und Experten beziehen (Abschnitt 3). In Abschnitt 4 diskutiere ich dann die Gründe, die ein Hörer haben könnte, eine solche Empfehlung anzunehmen, bevor ich in den Abschnitten 5 und 6 die für Empfehlungen relevante Form des Vertrauens herausarbeite. Abschnitt 7 diskutiert die Auffassung, dass Vertrauen in wissenschaftsbasierte Empfehlungen nur durch die Anerkennung der Sprecherin im Sinne einer guten Ratgeberin als rationale Einstellung ausgewiesen werden kann, bevor ich abschließend argumentiere, dass diese Rationalitätsbedingungen im Kontext der COVID-19-Pandemie nur schwer einzulösen waren. (shrink)

This paper argues that the emotional cues exhibited by AI systems designed for social interaction may lead human users to hold misplaced trust in such AI systems, and this poses a substantial problem for human-AI relationships. It begins by discussing the communicative role of certain emotions relevant to perceived trustworthiness. Since displaying such emotions is a reliable indicator of trustworthiness in humans, we use such emotions to assess agents’ trustworthiness according to certain generalizations of folk psychology. Our tendency to engage (...) in anthropomorphism with artificial agents that display these communicative emotions may mislead us into trusting them, even when such trust is misplaced. This phenomenon is referred to as the Emotions-Trustworthiness Gap. This paper demonstrates this general concept with compassion and guilt. In both cases, we may be tempted to judge that AI systems' mere mimicking of relevant emotions constitutes evidence for their trustworthiness. However, most current AI systems are not trustworthy on any major view of trustworthy AI. Thus, the trust elicited from human users will be misplaced. This tendency of human users to hold misplaced trust in their AI companions leaves them vulnerable to serious harm. Several potential solutions to the Emotions-Trustworthiness Gap are discussed. (shrink)

Invitation to submit abstracts to the new special issue PHILOSOPHICAL PERSPECTIVES ON TRUST AND DISTRUST IN CONTEMPORARY SOCIETIES to be published by Sats. Northern European Journal of Philosophy in spring 2024.

Can AI developers be held epistemically responsible for the processing of their AI systems when these systems are epistemically opaque? And can explainable AI (XAI) provide public justificatory reasons for opaque AI systems’ outputs? Koskinen (2024) gives negative answers to both questions. Here, I respond to her and argue for affirmative answers. More generally, I suggest that when considering people’s uncertainty about the factors causally determining an opaque AI’s output, it might be worth keeping in mind that a degree of (...) uncertainty about conclusions is inevitable even in entirely human-based empirical science because in induction there’s always a risk of getting it wrong. Keeping this in mind may help appreciate that requiring full transparency from AI systems before epistemically trusting their outputs might be unusually (and potentially overly) demanding. (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)

The increasing demand for transparency in AI has recently come under scrutiny. The question is often posted in terms of “epistemic double standards”, and whether the standards for transparency in AI ought to be higher than, or equivalent to, our standards for ordinary human reasoners. I agree that the push for increased transparency in AI deserves closer examination, and that comparing these standards to our standards of transparency for other opaque systems is an appropriate starting point. I suggest that a (...) more fruitful exploration of this question will involve a different comparison class. We routinely treat judgments made by highly trained experts in specialized fields as fair or well-grounded even though—by the nature of expert/layperson division of epistemic labor—an expert will not be able to provide an explanation of the reasoning behind these judgments that makes sense to most other people. Regardless, laypeople are thought to be acting reasonably—and ethically—in deferring to the judgments of experts that concern their areas of specialization. I suggest that we reframe our question regarding the appropriate standards of transparency in AI as one that asks when, why, and to what degree it would be ethical to accept opacity in AI. I argue that our epistemic relation to certain opaque AI technology may be relevantly similar to the layperson’s epistemic relation to the expert in certain respects, such that the successful expert/layperson division of epistemic labor can serve as a blueprint for the ethical use of opaque AI. (shrink)

Especially but not exclusively in the United States, there is a significant gulf between expert opinion and public opinion on a range of important political, social, and scientific issues. Large numbers of lay people hold views contrary to the expert consensus on topics such as climate change, vaccines, and economics. Much political commentary assumes that ordinary people should defer to experts more than they do, and this view is certainly lent force by the literally deadly effects of many denials of (...) established science. But there are complex philosophical issues here, concerning, among other things, (i) what an expert is; (ii) what kind of deference is called for; (iii) and when deference is called for. This entry gives an overview of these three issues and recent work on them. It then examines some potential collective and pragmatic disadvantages of deference, before concluding with reflections on what we can say to those who distrust experts. (shrink)

This introduction to the edited volume on "Testimonial Injustice and Trust" provides (a) a brief overview of the philosophical debate on the notion of ‘testimonial injustice’ and (b) a summary of the 18 chapters constituting this volume. The contributions are divided into four thematic sections. These are (I) Rethinking Testimonial Injustice, (II) Testimonial Injustice and the Question of Trust, (III) The Public Spheres of Testimonial Injustice, and (IV) Testimonial Injustice and Public Health. The contributions criticize, complement, or expand on Fricker’s (...) central case of testimonial injustice and the proposed virtue of testimonial justice, thereby contributing to its better understanding and extending its scope. Moreover, through the application of theories of epistemic injustice, and testimonial injustice in particular, to new real-world cases and contexts, they seek to render our theories and concepts more robust and valuable. (shrink)

ABSTRACT The testimonies of celebrities affect the lives of their many followers who pay attention to what they say. This gives celebrities a high degree of epistemic power, which has come under scrutiny during the COVID-19 pandemic. This paper investigates the duties that arise from this power. We argue that celebrities have a negative duty of testimonial justice not to undermine trust in authoritative sources by spreading misinformation or directing attention to untrustworthy sources. Moreover, celebrities have a general imperfect duty (...) to try to correct for an unjust distribution of attention by redirecting it to those who deserve it. During a pandemic this may become a perfect one, due to the harm that could be prevented if people follow the advice of experts. Relatedly, we argue that celebrities have an imperfect duty to promote behavior that will reduce the spread of a pandemic. We outline three ways they might do so: they might take on the position of a role model, they may act as a salience magnet or they can direct people’s attention towards others who have taken on these roles. (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)

This article evaluates an emerging element in popular debate and inquiry: DYOR. (Haven’t heard of the acronym? Then Do Your Own Research.) The slogan is flexible and versatile. It is used frequently on social media platforms about topics from medical science to financial investing to conspiracy theories. Using conceptual and empirical resources drawn from philosophy and psychology, we examine key questions about the slogan’s operation in human cognition and epistemic culture.

What is it to know someone? Epistemologists rarely take up this question, though recent developments make such inquiry possible and desirable. This paper advances an account of how such interpersonal knowledge goes beyond mere propositional and qualitative knowledge about someone, giving a central place to second-personal treatment. It examines what such knowledge requires, and what makes it distinctive within epistemology as well as socially. It assesses its theoretic value for several issues in moral psychology, epistemic injustice, and philosophy of mind. (...) And it offers an account of the complex content in play if interpersonal knowledge is to be understood in terms of its mental states and their functions. (shrink)

Why comply with epistemic norms? In this paper, I argue that complying with epistemic norms, engaging in epistemically responsible conduct, and being epistemically trustworthy are constitutive elements of maintaining good epistemic relations with oneself and others. Good epistemic relations are in turn both instrumentally and finally valuable: they enable the kind of coordination and knowledge acquisition underpinning much of what we tend to associate with a flourishing human life; and just as good interpersonal relations with others can be good for (...) their own sake, standing in good epistemic relations is good for its own sake. On my account, we have reason to comply with epistemic norms because it is a way of respecting the final value of something that also tends to be an instrumentally valuable thing: good epistemic relations. Situating the account within the recent social turn in debates about epistemic instrumentalism, I argue that the dual‐value aspect of good epistemic relations can explain important anti‐instrumentalist intuitions, in a well‐motivated way, within a broadly instrumentalist framework. (shrink)

Whether we ought to trust the testimony of another person is often thought to primarily depend on features like their evidence, knowledge, or level of expertise. No doubt these are epistemically relevant features. However, a recent paper by Justin P. McBrayer (2024) convincingly argues that a testifier's interests may be more important than their expertise when it comes to how we should allocate our epistemic trust in them. Just think of the proverbial used car salesman. You should not trust what (...) he tells you, and realizing that he is an expert only seems to make things worse. In this reply, I consider McBrayer’s basic insight, constructively criticize his view, and tentatively explore further territory. (shrink)

Deepfakes are extremely realistic audio/video media. They are produced via a complex machine-learning process, one that centrally involves training an algorithm on hundreds or thousands of audio/video recordings of an object or person, S, with the aim of either creating entirely new audio/video media of S or else altering existing audio/video media of S. Deepfakes are widely predicted to have deleterious consequences (principally, moral and epistemic ones) for both individuals and various of our social practices and institutions. In this introduction (...) to the Topical Collection, I first survey existing philosophical research on deepfakes (Sects. 2 and 3). I then give an overview of the papers that comprise the Collection (Sect. 4). Finally, I conclude with remarks on a line of argument made in a number of papers in the Topical Collection: that deepfakes may cause their own demise (Sect. 5). (shrink)

What is epistemic self-trust? There is a tension in the way in which prominent accounts answer this question. Many construe epistemic trust in oneself as no more than reliance on our sub-personal cognitive faculties. Yet many accounts – often the same ones – construe epistemic trust in others as a normatively laden attitude directed at persons whom we expect to care about our epistemic needs. Is epistemic self-trust really so different from epistemic trust in others? I argue that it is (...) not. We certainly do rely on our cognitive faculties to achieve epistemic ends; but I argue that we also have the normatively rich sort of epistemic trust in ourselves. Moreover, there is a theoretical need for this normatively rich notion of epistemic self-trust: positing it yields the best account of how we secure important epistemic goods, including knowledge and recognition as knowers. I argue this by giving an account of epistemic trust in others and showing that it can be generalized to epistemic trust in oneself. (shrink)

We tend to think that philosophical progress, to the extent that it exists, is a good thing. I agree. Even so, it has some surprising unfortunate consequences for the rationality of philosophical belief.

In this chapter, I survey and assess various answers to two basic questions concerning experts: (1) What is an expert?; (2) How can laypeople identify the relevant experts? These questions are not mutually independent, since the epistemology and the metaphysics of experts should go hand in hand. On the basis of our platitudes about experts, I will argue that the prevailing accounts of experts such as truth-linked, knowledge-linked, understanding-linked or service-oriented accounts are inadequate. In contrast, I will defend an evidence-linked (...) account of expertise. In the second part of the chapter, I address the question of how laypeople can identify experts in this sense. Here, I will argue that agreement among experts plays a major role. I will outline how laypeople can follow this criterion without running into circularity. (shrink)

Deepfakes pose a multi-faceted threat to the acquisition of knowledge. It is widely hoped that technological solutions—in the form of artificially intelligent systems for detecting deepfakes—will help to address this threat. I argue that the prospects for purely technological solutions to the problem of deepfakes are dim. Especially given the evolving nature of the threat, technological solutions cannot be expected to prevent deception at the hands of deepfakes, or to preserve the authority of video footage. Moreover, the success of such (...) technologies depends on institutional trust that is in short supply. Finally, outsourcing the discrimination between the real and the fake to automated, largely opaque systems runs the risk of undermining epistemic autonomy. (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)

Epistemic Courage is a timely and thought-provoking exploration of the ethics of belief, which shows why epistemology is no mere academic abstraction - the question of what to believe couldn't be more urgent. Jonathan Ichikawa argues that a skeptical, negative bias about belief is connected to a conservative bias that reinforces the status quo.

An epistemic agent A is a false epistemic authority for others iff they falsely believe A to be in a position to help them accomplish their epistemic ends. A major divide exists between what I call "epistemic quacks", who falsely believe themselves to be relevantly competent, and "epistemic charlatans", i.e., false authorities who believe or even know that they are incompetent. Both types of false authority do not cover what Lackey (2021) calls "predatory experts": experts who systematically misuse their social-epistemic (...) status as a cover for predatory behavior. Qua experts, predatory experts are competent and thus could (and maybe sometimes do) help their clients. But should we count them as genuine epistemic authorities? No, I argue, they are false epistemic authorities because, in addition to their practical and moral misconduct, such experts systematically deceive their clients, thereby thwarting the clients’ epistemic ends. (shrink)

I discuss an influential argument put forward by Hatherley in theJournal of Medical Ethics. Drawing on influential philosophical accounts of interpersonal trust, Hatherley claims that medical artificial intelligence is capable of being reliable, but not trustworthy. Furthermore, Hatherley argues that trust generates moral obligations on behalf of the trustee. For instance, when a patient trusts a clinician, it generates certain moral obligations on behalf of the clinician for her to do what she is entrusted to do. I make three objections (...) to Hatherley’s claims: (1) At least one philosophical account of interagent trust implies that medical AI is capable of being trustworthy. (2) Even if this account should ultimately be rejected, it does not matter much because what we care mostly about is that medical AI is reliable. (3) It is false that trust in itself generates moral obligations on behalf of the trustee. (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)

During the Covid-19 pandemic, a considerable amount of people seem to have been lured into believing in conspiracy theories. These people deliberately disregard expert advice by virologists and physicians concerning social behaviour that is aimed at reducing the number of new infections. Disregarding traditional experts and their advice is just one example of what, in the philosophy of science, is referred to as a crisis of expertise – the phenomenon whereby people seem to have lost their trust in traditional expert (...) advice and are looking for alternatives. In the following paper, the trend to use Internet technology as an epistemic alternative will be analysed in detail by investigating the question of whether the Internet really allows people to become epistemically more autonomous. The focus will be on the epistemic and moral vulnerability of people resorting to new media tools instead of relying on traditional expert opinion. It will be shown that some important presuppositions about the Internet and, in particular, social media tools as alternative ways to collect information and find emotional support in a group of like-minded people cannot be maintained. (shrink)

During the Covid-19 pandemic, a significant number of people has seemingly been lured in believing conspiracy theories. Many deliberately disregarded expert advices by virologists and physicians to reduce new infections. This turning away from traditional expert authorities exemplifies the »crisis of expertise« that has been discussed in the philosophy of science for some time, namely that many people seem to have lost their trust in the established authority of expert knowledge and are looking for epistemic alternatives, especially on the Internet (...) and in particular on social media. In this article, this digital cultural trend will be analysed. Will people actually becoming more epistemically autonomous as a result of this new tend? Attention is drawn to the epistemic and moral vulnerability of people who opt for new media as epistemic alternatives instead of relying on traditional expert opinion. It will be shown that some important presuppositions about the Internet and, especially, social media tools as alternative ways to gathering information and find moral support in a group of likeminded people do not hold. (shrink)

How is it that a speaker _S_ can at once make it obvious to an audience _A_ that she intends to communicate some proposition _p_, and yet at the same time retain plausible deniability with respect to this intention? The answer is that _S_ can bring it about that _A_ has a high justified credence that ‘_S_ intended _p_’ without putting _A_ in a position to know that ‘_S_ intended _p_’. In order to achieve this _S_ has to exploit a (...) sense in which communication can be lottery-like. After defending this view of deniability I argue that it compares favorably to a rival account recently developed by Dinges and Zakkou (Mind, https://doi.org/10.1093/mind/fzac056, 2023 ). (shrink)

It has been argued that our currently most satisfactory social epistemology of science can’t account for science that is based on artificial intelligence (AI) because this social epistemology requires trust between scientists that can take full responsibility for the research tools they use, and scientists can’t take full responsibility for the AI tools they use since these systems are epistemically opaque. I think this argument overlooks that much AI-based science can be done without opaque models, and that agents can take (...) full responsibility for the systems they use even if these systems are opaque. Requiring that an agent fully understand how a system works is an untenably strong condition for that agent to take full responsibility for the system and risks absolving AI developers from responsibility for their products. AI-based science need not create trust-related social epistemological problems if we keep in mind that what makes both individual scientists and their use of AI systems trustworthy isn’t full transparency of the internal processing but their adherence to social and institutional norms that ensure that scientific claims can be trusted. (shrink)

Complex technology has become an essential aspect of everyday life. We rely on technology as part of basic infrastructure and repeatedly for tasks throughout the day. Yet, in many cases the relation surpasses mere reliance and evolves to trust in technology. A new, disruptive technology is blockchain. It claims to introduce trustless relationships among its users, aiming to eliminate the need for trust altogether—even being described as “the trust machine”. This paper presents a proposal to adjust the concept of trust (...) in blockchain applications with the tools provided by conceptual engineering. Its goal is to propose a concept of trust, that offers more than a halo term, devoid of the normative depth that the original, philosophical term actually carries. To evaluate possible concepts of trust in blockchain applications, five criteria are proposed: These criteria ensure that the conceptual relation indeed embodies trust, thereby being richer than mere reliance, and that the chosen concept highlights the active role of the trustor. While the concepts of trust in engineers and trust in algorithms have to be discarded, institutional trust emerges as a viable candidate, given some refinements. Ultimately, the concept of trust by normative expectations and attribution is suggested to capture the essence of trust in blockchain applications. (shrink)

This article investigates Public Understanding of Science (PUS) as an epistemic goal of science communication. It proposes to conceptualize PUS as a form of understanding and discusses what implications this has for science communication from a social epistemological perspective. Specifically, it is argued that 1) PUS can be conceptualized as an epistemic goal of science communication in a way that does not already imply the so-called deficit model, and 2) that interactive and dialogue- based forms of communication are also justified (...) for this goal from an epistemological perspective. (shrink)

The normative force of evidence can seem puzzling. It seems that having conclusive evidence for a proposition does not, by itself, make it true that one ought to believe the proposition. But spelling out the condition that evidence must meet in order to provide us with genuine normative reasons for belief seems to lead us into a dilemma: the condition either fails to explain the normative significance of epistemic reasons or it renders the content of epistemic norms practical. The first (...) aim of this paper is to spell out this challenge for the normativity of evidence. I argue that the challenge rests on a plausible assumption about the conceptual connection between normative reasons and blameworthiness. The second aim of the paper is to show how we can meet the challenge by spelling out a concept of epistemic blameworthiness. Drawing on recent accounts of doxastic responsibility and epistemic blame, I suggest that the normativity of evidence is revealed in our practice of suspending epistemic trust in response to impaired epistemic relationships. Recognizing suspension of trust as a form of epistemic blame allows us to make sense of a purely epistemic kind of normativity the existence of which has recently been called into doubt by certain versions of pragmatism and instrumentalism. (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)

When trust is broken, how should we determine who is at fault? Previous discus- sions of broken trust typically attribute the fault to trusters who place trust foolishly or trustees who act in an untrustworthy manner. These discussions take for granted the ability of the truster and trustee to communicate and understand the boundaries of what is being entrusted, that is, the domain of trust. However, the boundaries of entrusted domains are not always clear to either party which can result (...) in broken trust despite the best efforts of both truster and trustee. In this paper, I argue that deter- mining who to blame when trust is broken is a messy affair in which disagreements over fault regularly arise. I introduce three features of trust domains that take center stage in negotiations regarding who is at fault when trust is broken: scope, rigidity and ordering. (shrink)

Nietzsche talks about trust [vertraue*] and mistrust [misstrau*] in all of his published and authorized works, from The Birth of Tragedy to Ecce Homo. He refers to trust in 90 passages and mistrust in 101 – approximately ten times as often as he refers to resentment/ressentiment. Yet the scholarly literature on Nietzsche and trust includes just a handful of publications. Worse still, I have been unable to find a single publication devoted to Nietzsche and mistrust. This chapter aims to fill (...) the gap in the secondary literature by using digital humanities methods to systematically investigate the functions of trust and mistrust in Nietzsche’s writings. I argue that Nietzsche offers three main insights into trust and an additional two into mistrust. When it comes to trust, in his free spirit works, he reflects on the development of interpersonal trust, with an eye to situations in which trust is or is not reciprocated. He also criticizes some of the heuristics people use to identify trustworthy partners, especially the notion that all and only people with stable character are trustworthy. And perhaps Nietzsche’s most interesting thoughts about trust relate to self-trust, which he thinks is often unjustifiably undermined. When it comes to mistrust, although he regards generalized mistrust as a sign of bad character, he also thinks that harnessing mistrust can be valuable in at least two domains. One is morality, where we are disposed to accept traditional pieties and would benefit from turning a suspicious eye towards these pieties. The other is science, which systematizes both trust and mistrust in pursuit of the truth. (shrink)

News about personal data breaches or data abusive practices, such as Cambridge Analytica, has questioned the trustworthiness of certain actors in the control of personal data. Innovations in the field of personal information management systems to address this issue have regained traction in recent years, also coinciding with the emergence of new decentralized technologies. However, only with ethically and legally responsible developments will the mistakes of the past be avoided. This contribution explores how current data management schemes are insufficient to (...) adequately safeguard data subjects, and in particular, it focuses on making these data flows transparent to provide an adequate level of accountability. To showcase this, and with the goal of enhancing transparency to foster trust, this paper investigates solutions for standardizing machine-readable policies to express personal data processing activities and their application to decentralized personal data stores as an example of ethical, legal, and technical responsible innovation in this field. (shrink)

When are we obligated to believe someone? To what extent are people authorities about their own experiences? What kind of harm might we enact when we doubt? Questions like these lie at the heart of many debates in social and feminist epistemology, and they’re the driving issue behind a key conceptual framework in these debates—gaslighting. But while the concept of gaslighting has provided fruitful insight, it's also proven somewhat difficult to adjudicate, and seems prone to over-application. In what follows, I (...) argue that Katherine Hawley's theory of trust can provide a useful alternative lens for looking at contested testimony. To do this, I focus on a particularly complex—but increasingly popular—application of gaslighting: the physician/patient relationship, and the idea of ‘medical gaslighting’. I argue that, even though patients can experience harm when they are disbelieved, there are nevertheless good reasons for physicians not to trust patients about at least some of their own narratives. (shrink)

If Annette Baier is right that ‘some degree of trust is … the very basis of morality” (Baier 2004, 180) , it is surprising that a philosopher so interested in moral psychology and interpersonal relationships such as Iris Murdoch does not explicitly discuss trust in her work. However, on closer inspection, Murdoch’s proposal of an ethics focused on realism, unselfing and attention crucially depends upon the possibility of trust – trust in reality, and in one’s own capacity for moral vision. (...) Connecting Murdoch's project with feminist philosophy and especially feminist epistemology, and drawing on the philosophy of trust developed by C. Thi Nguyen and Karen Jones, this chapter argues for a vision of 'trust in the world' implicit in Murdoch's work, where trust emerges not in the domain of personal relationships, but in our attitude towards reality, including moral reality, that is not perceived by us as merely something inert. (shrink)

In this paper, I distinguish three general approaches to public trust in science, which I call the individual approach, the semi-social approach, and the social approach, and critically examine their proposed solutions to what I call the problem of harmful distrust. I argue that, despite their differences, the individual and the semi-social approaches see the solution to the problem of harmful distrust as consisting primarily in trying to persuade individual citizens to trust science and that both approaches face two general (...) problems, which I call the problem of overidealizing science and the problem of overburdening citizens. I then argue that in order to avoid these problems we need to embrace a (thoroughly) social approach to public trust in science, which emphasizes the social dimensions of the reception, transmission, and uptake of scientific knowledge in society and the ways in which social forces influence both positively and negatively the trustworthiness of science. (shrink)