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)

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)

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)

Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence. According to an article in The New York Times, the course on artificial intelligence is (...) “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom. Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®. (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)

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (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)

Maps the future of phenomenological thought, accounting for how technology expands our means of experiencing the world.

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)

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 summary of the philosophical literature on trust.

Trust is one of the big buzzwords in debates about the shaping of society, democracy, and emerging technologies. For example, one prominent idea put forward by the High‐Level Expert Group on Artificial Intelligence appointed by the European Commission is that artificial intelligence should be trustworthy. In this essay, we explore the notion of trust and argue that both proponents and critics of trustworthy AI have flawed pictures of the nature of trust. We develop an approach to understanding trust in AI (...) that does not conceive of trust merely as an accelerator for societal acceptance of AI technologies. Instead, we argue, trust is granted through leaps of faith. For this reason, trust remains precarious, fragile, and resistant to promotion through formulaic approaches. We also highlight the significance of distrust in societal deliberation, as it is relevant to trust in various and intricate ways. Among the fruitful aspects of distrust is that it enables individuals to forgo technology if desired, to constrain its power, and to exercise meaningful human control. (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)

The power of new medical technologies, the cultural authority of physicians, and the gendered power dynamics of many patient-physician relationships can all inhibit women's reproductive freedom. Often these factors interfere with women's ability to trust themselves to choose and act in ways that are consistent with their own goals and values. In this book Carolyn McLeod introduces to the reproductive ethics literature the idea that in reproductive health care women's self-trust can be undermined in ways that threaten their autonomy. Understanding (...) the importance of self-trust for autonomy, McLeod argues, is crucial to understanding the limits on women's reproductive freedom. -/- McLeod brings feminist insights in philosophical moral psychology to reproductive ethics, and to health-care ethics more broadly. She identifies the social environments in which self-trust is formed and encouraged. She also shows how women's experiences of reproductive health care can enrich our understanding of self-trust and autonomy as philosophical concepts. The book's theoretical components are grounded in women's concrete experiences. The cases discussed, which involve miscarriage, infertility treatment, and prenatal diagnosis, show that what many women feel toward themselves in reproductive contexts is analogous to what we feel toward others when we trust or distrust them. -/- McLeod also discusses what health-care providers can do to minimize the barriers to women's self-trust in reproductive health care, and why they have a duty to do so as part of their larger duty to respect patient autonomy. (shrink)

In this paper I argue that even if one accepts non-cognitivism about trust, the view that trust is not a species of and does not require belief, one should reject voluntarism about trust, the view that we can trust directly at will. There is good reason to think that we cannot trust directly at will, in the way that we can act, and this is so regardless of whether trust requires belief.

Real engines of the artificial intelligence revolution, machine learning models, and algorithms are embedded nowadays in many services and products around us. As a society, we argue it is now necessary to transition into a phronetic paradigm focused on the ethical dilemmas stemming from the conception and application of AIs to define actionable recommendations as well as normative solutions. However, both academic research and society-driven initiatives are still quite far from clearly defining a solid program of study and intervention. In (...) this contribution, we will focus on selected ethical investigations around AI by proposing an incremental model of trust that can be applied to both human-human and human-AI interactions. Starting with a quick overview of the existing accounts of trust, with special attention to Taddeo’s concept of “e-trust,” we will discuss all the components of the proposed model and the reasons to trust in human-AI interactions in an example of relevance for business organizations. We end this contribution with an analysis of the epistemic and pragmatic reasons of trust in human-AI interactions and with a discussion of kinds of normativity in trustworthiness of AIs. (shrink)