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: (only) code, math, algorithms, and machines, or still (also) 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.

The emergence and increasing prevalence of Artificial Intelligence (AI) systems in a growing number of application areas brings about opportunities but also risks for individuals and society as a whole. To minimize the risks associated with AI systems and to mitigate potential harm caused by them, recent policy papers and regulatory proposals discuss obliging developers, deployers, and operators of these systems to avoid certain types of use and features in their design. However, most AI systems are complex socio-technical systems in which control over the system is extensively distributed. In many cases, a multitude of different actors is involved in the purpose setting, data management and data preparation, model development, as well as deployment, use, and refinement of such systems. Therefore, determining sensible addressees for the respective obligations is all but trivial. This article discusses two frameworks for assigning obligations that have been proposed in the European Commission’s whitepaper On Artificial Intelligence—A European approach to excellence and trust and the proposal for the Artificial Intelligence Act respectively. The focus is on whether the frameworks adequately account for the complex constellations of actors that are present in many AI systems and how the various tasks in the process of developing, deploying, and using AI systems, in which threats can arise, are distributed among these actors.

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This article argues that the emergence of AI systems and AI regulation showcases developments that have significant implications for computer ethics and make it necessary to reexamine some key assumptions of the discipline. Focusing on design- and policy-oriented computer ethics, the article investigates new challenges and opportunities that occur in this context. The main challenges concern how an AI system’s technical, social, political, and economic features can hinder a successful application of computer ethics. Yet, the article demonstrates that features of AI systems that potentially interfere with successfully applying some approaches to computer ethics are (often) only contingent, and that computer ethics can influence them. Furthermore, it shows how computer ethics can make use of how power manifests in an AI system’s technical, social, political, and economic features to achieve its goals. Lastly, the article outlines new interdependencies between policy- and design-oriented computer ethics, manifesting as either conflicts or synergies.

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