New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage (...) in conceptual engineering (without naming it as such). We subsequently reflect on the case studies to find out how these illustrate conceptual engineering as an appropriate method to deal with pressing concerns in the philosophy of technology. We have two main goals. We first want to contribute to the literature on conceptual engineering by presenting concrete examples of conceptual engineering in the philosophy of technology. This is especially relevant, because the technologies that are designed based on the conceptual work done by philosophers of technology potentially have crucial moral and social implications. Secondly, we want to make explicit what choices are made when doing this conceptual work. Making explicit that some of the implicit assumptions are, in fact, debated in the literature allows for reflection on these questions. Ultimately, our hope is that conscious reflection leads to an improvement of the conceptual work done. (shrink)

This paper sets out an account of trust in AI as a relationship between clinicians, AI applications, and AI practitioners in which AI is given discretionary authority over medical questions by clinicians. Compared to other accounts in recent literature, this account more adequately explains the normative commitments created by practitioners when inviting clinicians’ trust in AI. To avoid committing to an account of trust in AI applications themselves, I sketch a reductive view on which discretionary authority is exercised by AI (...) practitioners through the vehicle of an AI application. I conclude with four critical questions based on the discretionary account to determine if trust in particular AI applications is sound, and a brief discussion of the possibility that the main roles of the physician could be replaced by AI. (shrink)

The potential capacity for robots to deceive has received considerable attention recently. Many papers explore the technical possibility for a robot to engage in deception for beneficial purposes (e.g., in education or health). In this short experimental paper, I focus on a more paradigmatic case: robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment that investigates the following three questions: (a) Are ordinary (...) people willing to ascribe deceptive intentions to artificial agents? (b) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (c) Do people blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than they presently receive. (shrink)

One of the main difficulties in assessing artificial intelligence (AI) is the tendency for people to anthropomorphise it. This becomes particularly problematic when we attach human moral activities to AI. For example, the European Commission’s High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI (HLEG AI Ethics guidelines for trustworthy AI, 2019, p. 35). Trust is one of the most important and defining activities in (...) human relationships, so proposing that AI should be trusted, is a very serious claim. This paper will show that AI cannot be something that has the capacity to be trusted according to the most prevalent definitions of trust because it does not possess emotive states or can be held responsible for their actions—requirements of the affective and normative accounts of trust. While AI meets all of the requirements of the rational account of trust, it will be shown that this is not actually a type of trust at all, but is instead, a form of reliance. Ultimately, even complex machines such as AI should not be viewed as trustworthy as this undermines the value of interpersonal trust, anthropomorphises AI, and diverts responsibility from those developing and using them. (shrink)

Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI’s progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since AI (...) systems can be relied on, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely on AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice. (shrink)

According to most accounts of trust, you can only trust other people (or groups of people). To trust is to think that another has goodwill, or something to that effect. I sketch a different form of trust: the unquestioning attitude. What it is to trust, in this sense, is to settle one’s mind about something, to stop questioning it. To trust is to rely on a resource while suspending deliberation over its reliability. Trust lowers the barrier of monitoring, challenging, checking, (...) and questioning. Trust sets up open pipelines between yourself and parts of the external world. Trust permits external resources to have a similar relationship to one as one’s internal cognitive faculties. This creates efficiency, but at the price of exquisite vulnerability. We must trust in this way because we are cognitively limited beings in a cognitively overwhelming world. Crucially, we can hold the unquestioning attitude towards objects and technologies. When I trust my climbing rope, I stop worrying about its reliability. When I trust my online calendaring system, I simply go to the events indicated, without question. But, one might worry, how could one ever hold such a normatively loaded attitude as trust towards mere objects? How could it ever make sense to feel betrayed by an object? Trust is our engine for expanding and outsourcing our agency — for binding external processes into our practical selves. Thus, we can be betrayed by our smartphones in the same way that we can be betrayed by our memory. When we trust, we try to make something a part of our agency, and we are betrayed when our part lets us down. To unquestioningly trust something is to let it in—to attempt to bring it inside one’s practical functioning. This suggests a new form of gullibility: agential gullibility, which occurs when agents too hastily and carelessly integrate external resources into their own agency. (shrink)

Can we engineer conceptual change? While a positive answer to this question would be exciting news for philosophy, there has been a growing number of pessimistic voices in the literature. This paper resists this trend. Its central aim is to argue not only that conceptual engineering is possible but also that it is not even distinctively hard. In order to achieve this, we will develop a novel approach to conceptual engineering that has two key components. First, it proposes a reorientation (...) of the conceptual engineering project away from fixing conceptual defects and towards bringing about conceptual innovation. Second, it offers a new account of when conceptual engineering is successful in terms of etiological functions. We then turn to the reasons that have motivated various forms of pessimism about conceptual engineering and show that, on our novel approach, none of them stands up to scrutiny. (shrink)

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

My claim in this article is that, contra what I take to be the orthodoxy in the wider literature, we do trust inanimate objects – per the example in the title, there are cases where people really do trust a ladder (to hold their weight, for instance), and, perhaps most importantly, that this poses a challenge to that orthodoxy. My argument consists of four parts. In Section 2 I introduce an alleged distinction between trust as mere reliance and trust as (...) a rich, morally loaded notion. In the course of doing so, I briefly sketch some models of trust. This will help us to get a handle on how some of the mainstream models of trust preclude or ignore the trusting of inanimate objects. In Section 3 I introduce cases designed to show that we have reason to think that we do trust inanimate objects. In Section 4 I consider an objection, and in Section 5 I discuss some consequences of this finding, before concluding in Section 6. (shrink)

Unlike conceptual analysis, conceptual engineering does not aim to identify the content that our current concepts do have, but the content which these concepts should have. For this method to show the results that its practitioners typically aim for, being able to change meanings seems to be a crucial presupposition. However, certain branches of semantic externalism raise doubts about whether this presupposition can be met. To the extent that meanings are determined by external factors such as causal histories or microphysical (...) structures, it seems that they cannot be changed intentionally. This paper gives an extended discussion of this ‘externalist challenge’. Pace Herman Cappelen’s recent take on this issue, it argues that the viability of conceptual engineering crucially depends on our ability to bring about meaning change. Furthermore, it argues that, contrary to first appearance, causal theories of reference do allow for a sufficient degree of meaning control. To this purpose, it argues that there is a sense of what is called ‘collective long-range control’, and that popular versions of the causal theory of reference imply that people have this kind of control over meanings. (shrink)

Trust should be able to explain cooperation, and its failure should help explain the emergence of cooperation-enabling institutions. This proposed methodological constraint on theorizing about trust, when satisfied, can then be used to differentiate theories of trust with some being able to explain cooperation more generally and effectively than others. Unrestricted views of trust, which take trust to be no more than the disposition to rely on others, fare well compared to restrictive views, which require the trusting person to have (...) some further attitude in addition to this disposition. The same methodological constraint also favours some restrictive views over others. (shrink)

This paper defends the view that trust is a moral attitude, by putting forward the Obligation-Ascription Thesis: If E trusts F to do X, this implies that E ascribes an obligation to F to do X. I explicate the idea of obligation-ascription in terms of requirement and the appropriateness of blame. Then, drawing a distinction between attitude and ground, I argue that this account of the attitude of trust is compatible with the possibility of amoral trust, that is, trust held (...) among amoral persons on the basis of amoral grounds. It is also compatible with trust adopted on purely predictive grounds. Then, defending the thesis against a challenge of motivational inefficacy, I argue that obligation-ascription can motivate people to act even in the absence of definite, mutually-known agreements. I end by explaining, briefly, the advantages of this sort of moral account of trust over a view based on reactive attitudes such as resentment. (shrink)

Are trust relationships involving humans and artificial agents possible? This controversial question has become a hotly debated topic in the emerging field of machine ethics. Employing a model of trust advanced by Buechner and Tavani :39–51, 2011), I argue that the “short answer” to this question is yes. However, I also argue that a more complete and nuanced answer will require us to articulate the various levels of trust that are also possible in environments comprising both human agents and AAs. (...) In defending this view, I show how James Moor’s model for distinguishing four levels of ethical agents in the context of machine ethics :18–21, 2006) can help us to develop a framework that differentiates four levels of trust. Via a series of hypothetical scenarios, I illustrate each level of trust involved in HA–AA relationships. Finally, I argue that these levels of trust reflect three key factors or variables: the level of autonomy of the individual AAs involved, the degree of risk/vulnerability on the part of the HAs who place their trust in the AAs, and the kind of interactions that occur between the HAs and AAs in the trust environments. (shrink)

We argue that the notion of trust, as it figures in an ethical context, can be illuminated by examining research in artificial intelligence on multi-agent systems in which commitment and trust are modeled. We begin with an analysis of a philosophical model of trust based on Richard Holton’s interpretation of P. F. Strawson’s writings on freedom and resentment, and we show why this account of trust is difficult to extend to artificial agents (AAs) as well as to other non-human entities. (...) We then examine Margaret Urban Walker’s notions of “default trust” and “default, diffuse trust” to see how these concepts can inform our analysis of trust in the context of AAs. In the final section, we show how ethicists can improve their understanding of important features in the trust relationship by examining data resulting from a classic experiment involving AAs. (shrink)

Among the various methods of deceit, lying is often thought to be a special affront on the grounds that it invites the victim’s trust. Such an explanation is incomplete without an account of the moral significance of trust. This article distinguishes two morally problematic relations to trust, betrayals and abuses, and, appealing to the idea that we should be grateful to be trusted, attempts to explain these wrongs as violations of distinct demands of gratitude for trust. Only the wrong of (...) abuse, not betrayal, is useful for distinguishing methods of deceit. Although lying commits an abuse of trust, it turns out that it is really the broader category of deceit by means of communication that is special in this way. -/- . (shrink)

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

Can we trust robots? Responding to the literature on trust and e-trust, this paper asks if the question of trust is applicable to robots, discusses different approaches to trust, and analyses some preconditions for trust. In the course of the paper a phenomenological-social approach to trust is articulated, which provides a way of thinking about trust that puts less emphasis on individual choice and control than the contractarian-individualist approach. In addition, the argument is made that while robots are neither human (...) nor mere tools, we have sufficient functional, agency-based, appearance-based, social-relational, and existential criteria left to evaluate trust in robots. It is also argued that such evaluations must be sensitive to cultural differences, which impact on how we interpret the criteria and how we think of trust in robots. Finally, it is suggested that when it comes to shaping conditions under which humans can trust robots, fine-tuning human expectations and robotic appearances is advisable. (shrink)

I argue to a conclusion I find at once surprising and intuitive: although many considerations show trust useful, valuable, important, or required, these are not the reasons for which one trusts a particular person to do a particular thing. The reasons for which one trusts a particular person on a particular occasion concern, not the value, importance, or necessity of trust itself, but rather the trustworthiness of the person in question in the matter at hand. In fact, I will suggest (...) that the degree to which you trust a particular person to do a particular thing will vary inversely with the degree to which you must rely, for the motivation or justification of your trusting response, on reasons that concern the importance, or value, or necessity of having such a response. (shrink)

Across the humanities and social sciences it has become commonplace for scholars to argue that categories once assumed to be “natural” are in fact “social” or, in the familiar lingo, “socially constructed”. Two common examples of such categories are race and gender, but there many others. One interpretation of this claim is that although it is typically thought that what unifies the instances of such categories is some set of natural or physical properties, instead their unity rests on social features (...) of the items in question. Social constructionists pursuing this strategy—and it is these social constructionists I will be focusing on in this paper—aim to “debunk” the ordinary assumption that the categories are natural, by revealing the more accurate social basis of the classification.2 To avoid confusion, and to resist some of the associations with the term ‘social construction’, I will sometimes use the term ‘socially founded’ for the categories that this sort of constructionist reveals as social rather than natural. (shrink)

Can we decide to trust? Sometimes, yes. And when we do, we need not believe that our trust will be vindicated. This paper is motivated by the need to incorporate these facts into an account of trust. Trust involves reliance; and in addition it requires the taking of a reactive attitude to that reliance. I explain how the states involved here differ from belief. And I explore the limits of our ability to trust. I then turn to the idea of (...) trusting what others say. I suggest that we sometimes decide to trust people to be sincere and knowledgeable; and that having taken this attitude towards them, we come to believe what they say. I spell out some consequences that this has for an account of testimony, and for van Fraassen's decision theoretic principle of Reflection. (shrink)

Traditionally, theories of concepts in psychology assume that concepts are a single, uniform kind of mental representation. But no single kind of representation can explain all of the empirical data for which concepts are responsible. I argue that the assumption that concepts are uniformly the same kind of mental structure is responsible for these theories’ shortcomings, and outline a pluralist theory of concepts that rejects this assumption. On pluralism, concepts should be thought of as being constituted by multiple representational kinds, (...) with the particular kind of concept used on an occasion being determined by the context. I argue that endorsing pluralism does not lead to eliminativism about concepts as an object of scientific interest. (shrink)

Politicians and engineers are increasingly realizing that values are important in the development of technological artefacts. What is often overlooked is that different conceptualizations of these abstract values lead to different design-requirements. For example, designing social media platforms for deliberative democracy sets us up for technical work on completely different types of architectures and mechanisms than designing for so-called liquid or direct forms of democracy. Thinking about Democracy is not enough, we need to design for the proper conceptualization of these (...) values. As we see it, we cannot responsibly engineer and innovate and shape technology in accordance with our moral values without engaging in systematic and continuous conceptual engineering: This is not only an academic, or theoretical issue, it is also not simply an issue for public policy or politics, or regulators, it has become a central problem for engineering and the world of technology. In this paper, we present a framework for doing the necessary conceptual work in the context of requirement engineering. We draw on the literature on conceptual engineering to lay out a methodology to (1) assess different conceptions and (2) to develop new conceptions. Moreover, we integrate this methodology with extant approaches in the philosophy of technology which aim at designing technological artefacts ethically. In the final section we apply this integrated framework to freedom in the context of social media networks. (shrink)

With an increasing use of artificial intelligence (AI) systems, theorists have analyzed and argued for the promotion of trust in AI and trustworthy AI. Critics have objected that AI does not have the characteristics to be an appropriate subject for trust. However, this argumentation is open to counterarguments. Firstly, rejecting trust in AI denies the trust attitudes that some people experience. Secondly, we can trust other non‐human entities, such as animals and institutions, so why can we not trust AI systems? (...) Finally, human–AI trust is criticized based on a conception of human–human trust, which does not recognize the distinctiveness of the human–AI relationship. This article aims to refute these counterarguments based on the genealogical analyses of ‘trust’ and ‘trustworthiness’ of Karen Jones and Thomas Simpson, who show that trust and trustworthiness help to overcome vulnerabilities. This function of trust gives reason to use human–human trust as a standard. For this function, it is important that trustees are responsive to trust. While animals and institutions could be responsive, narrow AI systems are unable to be responsive to trust. Therefore, we should not apply trust to AI and instead direct our trust to those who can be responsive to and held responsible for our trust. (shrink)

This paper develops and defends a new account of therapeutic trust, its nature and its constitutive norms. Central to the view advanced is a distinction between two kinds of therapeutic trust – default therapeutic trust and overriding therapeutic trust – each which derives from a distinct kind of trusting competence. The new view is shown to have advantages over extant accounts of therapeutic trust, and its relation to standard (non-therapeutic) trust, as defended by Hieronymi, Frost-Arnold, and Jones.

Departing from the claim that AI needs to be trustworthy, we find that ethical advice from an AI-powered algorithm is trusted even when its users know nothing about its training data and when they learn information about it that warrants distrust. We conducted online experiments where the subjects took the role of decision-makers who received advice from an algorithm on how to deal with an ethical dilemma. We manipulated the information about the algorithm and studied its influence. Our findings suggest (...) that AI is overtrusted rather than distrusted. We suggest digital literacy as a potential remedy to ensure the responsible use of AI. (shrink)

There are two kinds of forgiveness that appear as radically different from one another: one presents forgiveness as essentially earned through remorseful apology; the other presents it as fundamentally non-earned—a gift. The first, which I label Moral Justice Forgiveness, adopts a stance of moral demand and conditionality; the second, which I label Gifted Forgiveness, adopts a stance of non-demand and un-conditionality. Each is real; yet how can two such different responses to wrongdoing be of one and the same kind? This (...) paper explains how, by showing that the basic role each plays in moral-social life is the same; and that one is conceptually and therefore historically prior to the other. The result is pluralism, with each kind of forgiveness represented as distinctive in both its psychology and its normativity; and yet an ordered pluralism—with Moral Justice Forgiveness revealed as the root kind, and Gifted Forgiveness a culturally contingent iteration. (shrink)

In his recent article ‘Limits of trust in medical AI,’ Hatherley argues that, if we believe that the motivations that are usually recognised as relevant for interpersonal trust have to be applied to interactions between humans and medical artificial intelligence, then these systems do not appear to be the appropriate objects of trust. In this response, we argue that it is possible to discuss trust in medical artificial intelligence (AI), if one refrains from simply assuming that trust describes human–human interactions. (...) To do so, we consider an account of trust that distinguishes trust from reliance in a way that is compatible with trusting non-human agents. In this account, to trust a medical AI is to rely on it with little monitoring and control of the elements that make it trustworthy. This attitude does not imply specific properties in the AI system that in fact only humans can have. This account of trust is applicable, in particular, to all cases where a physician relies on the medical AI predictions to support his or her decision making. (shrink)

Persuasive design draws on our basic psychological makeup to build products that make our engagement with them habitual. It uses variable rewards, creates Fear of Missing Out, and leverages social approval to incrementally increase and maintain user engagement. Social media and networking platforms, video games, and slot machines are all examples of persuasive technologies. Recent attention has focused on the dangers of PD: It can deceptively prod users into forming habits that help the company’s bottom line but not the user’s (...) wellbeing. But PD is not inherently immoral. We can take advantage of our psychological biases to make beneficial changes in ways that enhance our agency rather than limit it. Knowing that a tool is persuasively designed is a consideration in favor of using it when we are trying to break bad habits, such as smoking. How are we to conceptually distinguish between ethical and unethical uses of PD? In this paper, I argue that unethical uses of PD betray or erode our trust. Annette Baier offers a moral test for trust: If gaining knowledge about what other parties do with our trust in them would lead us to stop trusting, then that trusting relationship is immoral. I apply this test to the case of PD. Using trust as a litmus test for ferreting out unethical PD has several advantages, one of which is that it reveals how the harm of unethical PD extends beyond the individual to her wider social network. I close the paper by investigating these cascading effects. (shrink)

This paper provides a new analysis of e - trust , trust occurring in digital contexts, among the artificial agents of a distributed artificial system. The analysis endorses a non-psychological approach and rests on a Kantian regulative ideal of a rational agent, able to choose the best option for itself, given a specific scenario and a goal to achieve. The paper first introduces e-trust describing its relevance for the contemporary society and then presents a new theoretical analysis of this phenomenon. (...) The analysis first focuses on an agent’s trustworthiness , this one is presented as the necessary requirement for e-trust to occur. Then, a new definition of e-trust as a second-order-property of first-order relations is presented. It is shown that the second-order-property of e-trust has the effect of minimising an agent’s effort and commitment in the achievement of a given goal. On this basis, a method is provided for the objective assessment of the levels of e-trust occurring among the artificial agents of a distributed artificial system. (shrink)

A key debate in the epistemology of testimony concerns when it is reasonable to acquire belief through accepting what a speaker says. This debate has been largely understood as the debate over how much, or little, assessment and monitoring an audience must engage in. When it is understood in this way the debate simply ignores the relationship speaker and audience can have. Interlocutors rarely adopt the detached approach to communication implied by talk of assessment and monitoring. Audiences trust speakers to (...) be truthful and demonstrate certain reactive attitudes if they are not. Trust and the accompanying willingness to these reactive attitudes can then provide speakers with a reason to be trustworthy. So through ignoring interlocutors' engagement with the communicative process, the existing debate misses the possibility that it is an audience's trusting a speaker that makes it reasonable for the audience to accept what the speaker says. (shrink)

I consider Katherine Hawley's commitment account of interpersonal trustworthiness alongside her sceptical challenge regarding the value of philosophically modelling institutional trustworthiness as distinct from reliability. I argue, pace Hawley's challenge, that there would be significant diagnostic and explanatory loss if we were to content ourselves with ideas of institutional (un)reliability alone; and I offer an illustrative case where institutional unreliability is only the half of it, indicating that when it comes to certain kinds of institutional dysfunction, we do need philosophical (...) models of institutional ‘distrustworthiness’ if we are to achieve a proper diagnosis. (shrink)

The advent of intelligent artificial systems has sparked a dispute about the question of who is responsible when such a system causes a harmful outcome. This paper champions the idea that this dispute should be approached as a conceptual engineering problem. Towards this claim, the paper first argues that the dispute about the responsibility gap problem is in part a conceptual dispute about the content of responsibility and related concepts. The paper then argues that the way forward is to evaluate (...) the conceptual choices we have, in the light of a systematic understanding of why the concept is important in the first place—in short, the way forward is to engage in conceptual engineering. The paper then illustrates what approaching the responsibility gap problem as a conceptual engineering problem looks like. It outlines argumentative pathways out of the responsibility gap problem and relates these to existing contributions to the dispute. (shrink)

It is often taken for granted that monitoring stands in some kind of tension with trusting (e.g., Hieronymi 2008; Wanderer and Townsend 2013; Nguyen forthcoming; McMyler 2011, Castelfranchi and Falcone 2000; Frey 1993; Dasgupta 1988, Litzky et al. 2006) — especially three-place trust (i.e., A trusts B to X), but sometimes also two-place trust (i.e., A trusts B, see, e.g., Baier 1986). Using a case study involving relationship breakdown, repair, and formation, I will argue there are some ways in which (...) monitoring can be conducive to two-place trust, and to instances of three-place trust that are likely to be repeated over time—especially when previously established two-place trust has broken down. The result, I hope, is not any kind of abandoning of the important idea that monitoring can undermine trust, but an appreciation of where the conflict between monitoring and trust doesn’t lie – one from which future work will hopefully be better positioned to illuminate where exactly the conflict is. (shrink)

This paper explores the epistemology and moral psychology of “therapeutic trust,” in which one trusts with the aim of inspiring greater trust-responsiveness in the trusted. Theorists have appealed to alleged cases of rational therapeutic trust to show that trust can be adopted for broadly moral or practical reasons and to motivate accounts of trust that do not involve belief or confidence in someone’s trustworthiness. Some conclude from the cases that trust consists in having normative expectations and adopting vulnerabilities with respect (...) to the trusted; others that trust involves accepting that someone will prove trustworthy. Although there are, I argue, some genuine cases of rational therapeutic trust, some prominent examples confuse trusting with entrusting and are actually counterexamples to the adopted vulnerabilities and acceptance accounts they have been taken to support. An alternative account, which construes trust in terms of being confident enough to take salient risks on someone’s trustworthiness, makes better sense of therapeutic trust. (shrink)

I outline a number of parallels between trust and distrust, emphasising the significance of situations in which both trust and distrust would be an imposition upon the (dis)trustee. I develop an account of both trust and distrust in terms of commitment, and argue that this enables us to understand the nature of trustworthiness. Note that this article is available open access on the journal website.

Trust is difficult to define. Instead of doing so, I propose that the best way to understand the concept is through a genealogical account. I show how a root notion of trust arises out of some basic features of what it is for humans to live socially, in which we rely on others to act cooperatively. I explore how this concept acquires resonances of hope and threat, and how we analogically apply this in related but different contexts. The genealogical account (...) explains both why the notion has such value for us and why it is difficult to define. (shrink)

Philosophy and Phenomenological Research, EarlyView.

Trust constitutes a fundamental strategy to deal with risks and uncertainty in complex societies. In line with the vast literature stressing the importance of trust in doctor–patient relationships, trust is therefore regularly suggested as a way of dealing with the risks of medical artificial intelligence (AI). Yet, this approach has come under charge from different angles. At least two lines of thought can be distinguished: (1) that trusting AI is conceptually confused, that is, that we cannot trust AI; and (2) (...) that it is also dangerous, that is, that we should not trust AI—particularly if the stakes are as high as they routinely are in medicine. In this paper, we aim to defend a notion of trust in the context of medical AI against both charges. To do so, we highlight the technically mediated intentions manifest in AI systems, rendering trust a conceptually plausible stance for dealing with them. Based on literature from human–robot interactions, psychology and sociology, we then propose a novel model to analyse notions of trust, distinguishing between three aspects: reliability, competence, and intentions. We discuss each aspect and make suggestions regarding how medical AI may become worthy of our trust. (shrink)

From the perspective of philosophy and political science it is often pointed out that trust is of central value for democracy. The paper critically examines this claim and argues that we should not overestimate the role of trust in democracy. In order to do that, I argue for a specific understanding of the notion of trust that appropriately accounts for the distinction between trust and mere reliance. In a second step, I argue that we have no reason to put this (...) kind of trust in our elected officials and representatives, but should instead focus on legislative and institutional ways to make sure that they are reliable in particular respects. After contrasting my suggestion with the position of Hardin, I point to two advantages of my account: The avoidance of political analysis through the lens of trust allows us to react more flexibly to unforeseen circumstances and resist populist attempts to emotionalize public debates; at the same time, diffusing the tension between trust and civic vigil... (shrink)

Philosophers and social scientists have focussed a great deal of attention on our human capacity to trust, but relatively little on the capacity to hope. This is a significant oversight, as hope and trust are importantly interconnected. This paper argues that, even though trust can and does feed our hopes, it is our empowering capacity to hope that significantly underwrites—and makes rational—our capacity to trust.

I provide an account of the cognitive attitude of trust that explains the role trust plays in the planning of rational agents. Many authors have dismissed choosing to trust as either impossible or irrational; however, this fails to account for the role of trust in practical reasoning. A can have therapeutic, coping, or corrective reasons to trust B to ${\phi}$ , even in the absence of evidence that B will ${\phi}$ . One can choose to engage in therapeutic trust to (...) inspire trustworthiness, coping trust to simplify one’s planning, or corrective trust to avoid doing a testimonial injustice. To accommodate such types of trust, without accepting doxastic voluntarism, requires an account of the cognitive attitude of trust broader than belief alone. I argue that trust involves taking the proposition that someone will do something as a premise in one’s practical reasoning, which can be a matter of believing or accepting the proposition. I defend this account against objections that it (i) provides insufficient rational constraints on trust, (ii) conflates trust and pretense of trust, and (iii) cannot account for the rationality of back-up planning. (shrink)