Ori Freiman

• Central banks are exploring, developing and implementing a new form of money: central bank digital currency (CBDC). In short, it is a digital version of a country’s currency issued by its central bank. • While significant research has focused on the economic and technological aspects, the governance perspective has not received enough consideration. This paper focuses on the topics of programmability and surveillance — from a governance perspective. • Two concepts of programmability are discussed: programmable payments that automatically transfer funds based on predetermined conditions; and programmable money that refers to restrictions on usage. These new technological options can support social policies; however, they also raise questions about the authorities’ influence and control, and how to ensure there is no abuse of power. • Regarding surveillance, privacy is considered the most significant challenge in CBDC design. Meeting anti-money laundering (AML)/combatting the financing of terrorism (CFT) requirements while offering cash-like anonymity seems incompatible. Authorities’ access to citizens’ data could lead to state-level surveillance, threatening civil liberties and human rights. Even if safeguards are put in place, CBDC infrastructure could be changed and initial safeguards overridden, rendering this risk a time-consistency problem. • This paper also discusses whether CBDC is needed and suggests that if it is, then legal protection for cash should be considered. Issues of centrality, pace and public involvement are compared with another new technology — artificial intelligence (AI). • Eleven policy recommendations are suggested on privacy and data rights, accessibility, public participation and oversight, prohibiting programmable money, legislation protecting cash and more. Ultimately, democratic institutions uphold trust in CBDCs.

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.

This paper examines the trust relations involved in Israel’s COVID-19 vaccination campaign, focusing on vaccine hesitancy and the concept of ‘trust’. The first section offers a conceptual analysis of ‘trust’. Instead of analyzing trust in the vaccination campaign as a whole, a few objects of trust are identified and examined. In section two, the Israeli vaccination campaign is presented, and the focus is placed on vaccine hesitancy. In section three, different trust relations are examined: public trust in the Israeli government and health institutions, interpersonal trust in healthcare professionals and experts, trust in the pharmaceutical companies that make the COVID-19 vaccine, the US FDA, and trust in the new vaccine and the new technology. Through this complexity of trust relations, I argue that it is impossible to completely separate the trust that the vaccine is safe and effective from social aspects of mistrust. Additionally, practices of silencing and censoring the concerns of vaccine hesitaters – both experts and among the public, are pointed out. I contend that these cases further minimize vaccine hesitaters' trust in vaccine-related entities. In contrast, in section four, I suggest the ‘trust-based approach’: since vaccine hesitancy is not solely the result of knowledge deficiency but also a lack of trust relations, any campaign that addresses vaccine hesitancy should also focus on trust. The advantages of this approach are spelled out. For governments, a discussion based on trust is, ultimately, the best democratic way to encourage hesitaters to take the plunge and get vaccinated.

Speaking with conversational AIs, technologies whose interfaces enable human-like interaction based on natural language, has become a common phenomenon. During these interactions, people form their beliefs due to the say-so of conversational AIs. In this paper, I consider, and then reject, the concepts of testimony-based beliefs and instrument-based beliefs as suitable for analysis of beliefs acquired from these technologies. I argue that the concept of instrument-based beliefs acknowledges the non-human agency of the source of the belief. However, the analysis focuses on perceiving signs and indicators rather than content expressed in natural language. At the same time, the concept of testimony-based beliefs does refer to natural language propositions, but there is an underlying assumption that the agency of the testifier is human. To fill the lacuna of analyzing belief acquisition from conversational AIs, I suggest a third concept: technology-based beliefs. It acknowledges the non-human agency-status of the originator of the belief. Concurrently, the focus of analysis is on the propositional content that forms the belief. Filling the lacuna enables analysis that considers epistemic, ethical, and social issues of conversational AIs without excluding propositional content or compromising accepted assumptions about the agency of technologies.

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

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.‎

During the last few decades, the proliferation of interest in conspiracy theories became a widespread phenomenon in our culture, and also in academia. In this piece, I review a new book on the topic of conspiracy theory theory (that is-the theory of conspiracy theories) Taking Conspiracy Theories Seriously, edited by M R. X. Dentith. To contextualize the review, I first turn to the '90s, to see what sparked current interest in conspiracy theories within the field of analytic philosophy. I then critically asses the current limitations of social epistemology, as a field. Among other things, I show how accepted assumptions in social epistemology cause cross-disciplinary disagreements with other social sciences, present the dilemma of trivializing whistle-blowers, and discuss few neglected roles technologies play in belief formation.

There is an existing debate regarding the view that technological instruments, devices, or machines can assert ‎or testify. A standard view in epistemology is that only humans can testify. However, the notion of quasi-‎testimony acknowledges that technological devices can assert or testify under some conditions, without ‎denying that humans and machines are not the same. Indeed, there are four relevant differences between ‎humans and instruments. First, unlike humans, machine assertion is not imaginative or playful. Second, ‎machine assertion is prescripted and context restricted. As such, computers currently cannot easily switch ‎contexts or make meaningful relevant assertions in contexts for which they were not programmed. Third, ‎while both humans and computers make errors, they do so in different ways. Computers are very sensitive to ‎small errors in input, which may cause them to make big errors in output. Moreover, automatic error control ‎is based on finding irregularities in data without trying to establish whether they make sense. Fourth, ‎testimony is produced by a human with moral worth, while quasi-testimony is not. Ultimately, the notion of ‎quasi-testimony can serve as a bridge between different philosophical fields that deal with instruments and ‎testimony as sources of knowledge, allowing them to converse and agree on a shared description of reality, ‎while maintaining their distinct conceptions and ontological commitments about knowledge, humans, and ‎nonhumans.‎

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.