The stated aim of cryptocurrencies is to free the monetary system from the need to trust financial intermediaries, by relying on incentive design and technology. Many descriptive studies, however, have questioned cryptocurrencies’ delivery on the promise of trustlessness. This paper promotes a normative analysis of trust in cryptocurrencies by discussing (i) whether trust is in principle eliminable, and (ii) whether trustlessness is in itself a desirable goal. These issues are closely related, we argue, to the further issue of what kind (...) of institutions cryptocurrencies represent. We discuss the cognitive functions played by cryptocurrencies through the lens of the “extended mind” hypothesis in the philosophy of mind and hence conceive of cryptocurrencies as mind-extending institutions. As the models of institutional mind extension differ in the fiduciary bond they assume exists between individuals and institutional resources, we compare the reliance-based model of “scaffolding institutions” with the trust-based model of “cognitive institutions,” showing that the ineliminability and desirability of trust lead to seeing cryptocurrencies as instances of the latter. In the end, our discussion suggests that trust is a necessary component of cryptocurrencies’ cognitive functions and its promotion helps to perform such cognitive functions more effectively and sustainably. (shrink)

With focus on the development and use of artificial intelligence (AI) systems in the digital health context, we consider the following questions: How does the European Union (EU) seek to facilitate the development and uptake of trustworthy AI systems through the AI Act? What does trustworthiness and trust mean in the AI Act, and how are they linked to some of the ongoing discussions of these terms in bioethics, law, and philosophy? What are the normative components of trustworthiness? And how (...) do the requirements of the AI Act relate to these components? We first explain how the EU seeks to create an epistemic environment of trust through the AI Act to facilitate the development and uptake of trustworthy AI systems. The legislation establishes a governance regime that operates as a socio-epistemological infrastructure of trust which enables a performative framing of trust and trustworthiness. The degree of success that performative acts of trust and trustworthiness have achieved in realising the legislative goals may then be assessed in terms of statutorily defined proxies of trustworthiness. We show that to be trustworthy, these performative acts should be consistent with the ethical principles endorsed by the legislation; these principles are also manifested in at least four key features of the governance regime. However, specified proxies of trustworthiness are not expected to be adequate for applications of AI systems within a regulatory sandbox or in real-world testing. We explain why different proxies of trustworthiness for these applications may be regarded as ‘special’ trust domains and why the nature of trust should be understood as participatory. (shrink)