This chapter explores properties that bind individuals, knowledge, and communities, together. Section ‎‎1 introduces Hardwig’s argument from trust in others’ testimonies as entailing that trust is the glue ‎that binds individuals into communities. Section 2 asks “what grounds trust?” by exploring assessment ‎of collaborators’ explanatory responsiveness, formal indicators such as affiliation and credibility, ‎appreciation of peers’ tacit knowledge, game-theoretical considerations, and the role moral character ‎of peers, social biases, and social values play in grounding trust. Section 3 deals with establishing (...) ‎reliability standards for formation and breaching of trust. Different epistemic considerations and their ‎underpinning of inductive risks are examined through various communication routes within a ‎discipline, between disciplines, and to the public. Section 4 examines whether a collective entity can ‎be trusted over and above trust that is given to its individual members. Section 5 deals with the roles ‎technological artifacts play in distributed research and collective knowledge. It presents the common ‎view in which genuine trust cannot, in principle, be accorded to artifacts, so as an opposite view. We ‎show that what counts as a genuine object of trust is relevant to debates about the boundaries of ‎collective agency and as a criterion for extended cognitive systems.‎. (shrink)

One prominent argument for pragmatic encroachment (PE) is that PE is entailed by a combination of a principle that states that knowledge warrants proper practical reasoning, and judgments that it is more difficult to reason well when the stakes go up. I argue here that this argument is unsuccessful. One problem is that empirical tests concerning knowledge judgments in high-stakes situations only sometimes exhibit the result predicted by PE. I argue here that those judgments that appear to support PE are (...) better interpreted not as judgments that the epistemic demands for knowing increase as one’s practical situation becomes more demanding, but instead as judgments reflecting a different kind of normative epistemic evaluation, namely whether one is acting in an epistemically responsible way. The general idea is that when someone treats a proposition as a reason for acting we can evaluate them epistemically both in terms of whether they know that proposition, as well as in terms of whether they are acting on their knowledge in the right kind of way. My charge against the PE proponent, then, is that she is interpreting judgments that are indicative of whether we are adhering to certain normative epistemic requirements generally as being indicative of whether we have knowledge specifically. There are, however, normative epistemic requirements that make demands of us that are indicative of something other than our possession of knowledge. (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)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said to embody (...) certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can (...) give testimony. In section 3, I identify three assumptions underlying the view that rejects conversational AIs – AI-based technologies that converse, as testifiers: conversational AIs (1) lack intentions, (2) cannot be normatively assessed, and (3) cannot constitute an object in trust relations, while humans can. In section 4, I propose the concept ‘AI-testimony’ for analyzing outputs of conversational AIs, suggesting three conditions for technologies to deliver AI-testimony: (1) content is propositional, (2) generated and delivered with no other human directly involved, (3) the output is perceived as phenomenologically similar to that of a human. I conclude that this concept overcomes the limitations of the anthropocentric concept of testimony, opening future directions of research without associating conversational AIs with human-like agency. (shrink)

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

Technologies can have profound effects on social moral systems. Is there any way to systematically investigate and anticipate these potential effects? This paper aims to contribute to this emerging field on inquiry through a case study method. It focuses on two core human values—truth and trust—describes their structural properties and conceptualisations, and then considers various mechanisms through which technology is changing and can change our perspective on those values. In brief, the paper argues that technology is transforming these values by (...) changing the costs/benefits of accessing them; allowing us to substitute those values for other, closely-related ones; increasing their perceived scarcity/abundance; and disrupting traditional value-gatekeepers. This has implications for how we study other, technologically-mediated, value changes. (shrink)

There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important goal of explanation is to acquire or maintain the users’ trust. In this paper, I investigate the relation between explanation and trust in the context of computing science. (...) This analysis draws on literature study and concept analysis, using elements from system theory as well as actor-network theory. I apply the conceptual framework to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main focus is on expert systems (AI) and electronic voting systems (security). Finally, I discuss consequences of the analysis for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities. (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)

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)

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)

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artifi-cial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative theories, such as Kantianism or utilitarianism, (...) that reason-responsive people can be persuaded by. This proposal can play a normative role and it is also a more promising avenue towards moral enhancement. It is more promising because such a system can be designed to take advantage of the sometimes undue trust that people put in automated technologies. We could therefore expect a well-designed moral reasoner system to be able to persuade people that may not be persuaded by similar arguments from other people. So, all things considered, there is hope in artificial intelli-gence for moral enhancement, but not in artificial intelligence that relies solely on ambient intelligence technologies. (shrink)

The role that trust plays in blockchain-based systems is understood and portrayed in various manners. The blockchain technology is said to enable and establish trust as well as to redirect it, to substitute for it, and to make it obsolete. Furthermore, there is disagreement on whom or what users have to trust when using the blockchain technology: code, math, algorithms, and machines, or still human actors. This paper hypothesizes that the divergences of the depictions largely rest on implicitly adhering to (...) different accounts of trust. Thus, the goal of this paper is to outline how the current lack of a shared understanding of the term “trust” leads to diverging interpretations of the blockchain technology’s core features. Furthermore, it shows how this lack of common understanding obstructs scholars from referring to one another meaningfully in the discourse on blockchain technology. To do so, this paper outlines the most prominent depictions of the setup of relevant trust relationships within blockchain-based systems and traces their roots to different underlying assumptions on the nature of trust. (shrink)

This paper discusses the epistemology of the Internet of Things [IoT] by focusing on the topic of trust. It presents various frameworks of trust, and argues that the ethical framework of trust is what constitutes our responsibility to reveal desired norms and standards and embed them in other frameworks of trust. The first section briefly presents the IoT and scrutinizes the scarce philosophical work that has been done on this subject so far. The second section suggests that the field of (...) epistemology is not sufficiently capable of dealing with technologies, and presents a possible solution to this problem. It is argued that knowledge is not only social phenomena, but also a technological one, and that in order to address epistemological issues in technology, we need to carefully depart from traditional epistemic analysis and form a new approach that is technological (termed here Techno-Epistemology). The third and fourth sections engage in an epistemic analysis of trust by dividing it in to various frameworks. The last section argues that these various frameworks of trust can be understood to form a trustworthy large-scale socio-technological system, emphasizing the place of ethical trust as constituting our commitment to give proper accounts for all of the other frameworks. (shrink)

In this panel, we explore the future of value sensitive design (VSD). The stakes are high. Many in public and private sectors and in civil society are gradually realizing that taking our values seriously implies that we have to ensure that values effectively inform the design of technology which, in turn, shapes people’s lives. Value sensitive design offers a highly developed set of theory, tools, and methods to systematically do so.