Generative artificial intelligence (GenAI) raises ethical and social challenges that can be examined according to a normative and an epistemological approach. The normative approach, increasingly adopted by European institutions, identifies the pros and cons of technological advancement. The main pros concern technological innovation, economic development and the achievement of social goals and values. The disadvantages mainly concern cases of abuse, use or underuse of Gen AI. The epistemological approach investigates the specific way in which Gen AI produces information, knowledge, and a representation of reality that differs from that of human beings. To fully realise the impact of Gen AI, our paper contends that both these approaches should be pursued: an identification of the risks and opportunities of Gen AI also depends on considering how this form of AI works from an epistemological viewpoint and our ability to interact with it. Our analysis compares the epistemology of Gen AI with that of law, to highlight four problematic issues in terms of: (i) qualification; (ii) reliability; (iii) pluralism and novelty; (iv) technological dependence. The epistemological analysis of these issues leads to a better framing of the social and ethical aspects resulting from the use, abuse or underuse of Gen AI.

The only surviving student transcript of any of Kant’s course lectures on political philosophy, the Feyerabend lecture notes of 1784, provide Kant’s criticisms of Natural Law theory as well as a statement of Kant’s own developing theory at a time when he published very little on the topic. This introduction describes the nature of the course lecture and gives an overview of the contributions that follow.

This chapter addresses the interplay of invisibility, status, and power in UX writing. My aim in the chapter is twofold. First, I am interested in how UX writers understand and negotiate the (in)visibility of language in their own work. Tracing the semiotic ideologies of these professional language workers, I discuss how UX writers operationalize a discursive ideal of invisible writing in order to establish the value of their linguistic work vis-à-vis their colleagues, who typically privilege other modes of meaning making. Second, I examine how UX writers make sense of the linguistic and cultural-political consequences of this invisibility. In this regard, I suggest that the ideal of an invisible interface is a central media ideology that not only structures the work of UX writers but ultimately determines how ordinary users can(not) communicate with and through digital media. I conclude by linking my case study to broader discussions of invisibility in cultural studies of technology, arguing that communication with and through digital media is shaped not only by users’ perspectives but also by the semiotic and media ideologies of its producers.

This chapter introduces methods for generating and documenting paradata before and during data creation practices and processes (i.e. prospective and in-situ approaches, respectively). It introduces formal metadata-based paradata documentation using standards and controlled vocabularies to contribute to paradata consistency and interoperability. Narrative descriptions and recordings are advantageous for providing contextual richness and detailed documentation of data generation processes. Logging methods, including log files and blockchain technology, allow for automatic paradata generation and for maintaining the integrity of the record. Data management plans and registered reports are examples of measures to prospectively generate potential paradata on forthcoming activities. Finally, facilitative workflow-based approaches are introduced for step-by-step modelling of practices and processes. Rather than suggesting that a single approach to generating and documenting paradata will suffice, we encourage users to consider a selective combination of approaches, facilitated by adequate institutional resources, technical and subject expertise, to enhance the understanding, transparency, reproducibility and credibility of paradata describing practices and processes.

The AI Act contains some specific provisions dealing with the possible use of artificial intelligence for discriminatory purposes or in discriminatory ways, in the context of the European Union. The AI Act also regulates generative AI models. However, these two respective sets of rules have little in common: provisions concerning non-discrimination tend not to cover generative AI, and generative AI rules tend not to cover discrimination. Based on this analysis, the Chapter considers what is currently the Eu legal framework on discriminatory output of generative AI models, and concludes that those expressions that are already prohibited by anti-discrimination law certainly remain prohibited after the approval of the AI Act, while discriminatory content that is not covered by Eu non-discrimination legislation will remain lawful. For the moment, the AI Act has not brought any particularly relevant innovation on this specific matter, but the picture might change in the future.

During the 1930s and early 1940s, numerous groups in Uruguay coalesced to oppose fascism. This chapter examines the antifascist efforts organized by ethnic societies, labor unions, women’s groups, Afro-Uruguayans, students, intellectuals, and artists, among others. The emergent antifascist movements in Uruguay served as nodes in the broader transnational struggle for democracy and against totalitarianism. While some Uruguayans traveled to Spain to directly take part in the Spanish Civil War, others sought to marshal support at home to combat the influence of European fascism. The ideological struggles in Europe were also pressing at home, as President Gabriel Terra initiated a dictatorship in the 1930s that revealed his supporters’ fascist leanings. Likewise, an engrained sense of national exceptionalism tied to Uruguay’s decades-long democratic tradition, augmented the need to resist Terra’s dictatorship (1933–38) and later to repudiate any remnants of its legacy.