While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI’s beneficial outputs and concerns about the challenges of human–computer interaction in healthcare. To address these concerns, institutions have increasingly resorted to publishing AI guidelines for healthcare, aiming to align AI with ethical practices. However, guidelines as a form of written language can be analyzed to recognize the reciprocal links between its textual communication and underlying societal ideas. From this perspective, we conducted a (...) discourse analysis to understand how these guidelines construct, articulate, and frame ethics for AI in healthcare. We included eight guidelines and identified three prevalent and interwoven discourses: (1) AI is unavoidable and desirable; (2) AI needs to be guided with (some forms of) principles (3) trust in AI is instrumental and primary. These discourses signal an over-spillage of technical ideals to AI ethics, such as over-optimism and resulting hyper-criticism. This research provides insights into the underlying ideas present in AI guidelines and how guidelines influence the practice and alignment of AI with ethical, legal, and societal values expected to shape AI in healthcare. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and legal principles (...) consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

There is a problematic tradition of dualistic and reductionist thinking in artificial intelligence (AI) research, which is evident in AI storytelling and imaginations as well as in public debates about AI. Dualistic thinking is based on the assumption of a fixed reality and a hierarchy of power, and it simplifies the complex relationships between humans and machines. This commentary piece argues that we need to work against the grain of such logics and instead develop a thinking that acknowledges AI–human interconnectedness (...) and the complexity in such relations. To learn how to live better with AI in futures to come, the paper suggests an AI politics that turns to practices of serious attentiveness to help us re-imagine our machines and re-configure AI–human relations. (shrink)

Automated decision-making (ADM) systems can be worn in and on the body for various purposes, such as for tracking and managing chronic conditions. One case in point is do-it-yourself open-source artificial pancreas systems, through which users engage in what is referred to as “looping”; combining continuous glucose monitors and insulin pumps placed on the body with digital communication technologies to develop an ADM system for personal diabetes management. The idea behind these personalized systems is to delegate decision-making regarding insulin to (...) an algorithm that can make autonomous decisions. Based on interviews and photo diaries with Danish “loopers”, this paper highlights two interrelated narratives of how users have to care for the loop by _maintaining_ a stable communication circuit between body and ADM system, and by _modifying_ the loop through analysis and reflection. It shows how the human takes turns with the ADM system through practical doings and anticipation to safeguard continuous management of chronic disease. (shrink)

This study analyzes how ChatGPT portrays and describes itself, revealing misleading myths about AI technologies, specifically conversational agents based on large language models. This analysis allows for critical reflection on the potential harm these misconceptions may pose for public understanding of AI and related technologies. While previous research has explored AI discourses and representations more generally, few studies focus specifically on AI chatbots. To narrow this research gap, an experimental-qualitative investigation into auto-generated AI representations based on prompting was conducted. Over (...) the course of a month, ChatGPT (both in its GPT-4 and GPT-4o models) was prompted to “Draw an image of yourself,” “Represent yourself visually,” and “Envision yourself visually.” The resulting data (n = 50 images and 58 texts) was subjected to a critical exploratory visual semiotic analysis to identify recurring themes and tendencies in how ChatGPT is represented and characterized. Three themes emerged from the analysis: anthropomorphism, futuristic/futurism and (social)intelligence. Importantly, compared to broader AI imaginations, the findings emphasize ChatGPT as a friendly AI assistant. These results raise critical questions about trust in these systems, not only in terms of their capability to produce reliable information and handle personal data, but also in terms of human–computer relations. (shrink)

The current debate on artificial intelligence (AI) tends to associate AI imaginaries with the vision of a future technology capable of emulating or surpassing human intelligence. This article advocates for a more nuanced analysis of AI imaginaries, distinguishing “strong AI narratives,” i.e., narratives that envision futurable AI technologies that are virtually indistinguishable from humans, from "weak" AI narratives, i.e., narratives that discuss and make sense of the functioning and implications of existing AI technologies. Drawing on the academic literature on AI (...) narratives and imaginaries and examining examples drawn from the debate on Large Language Models and public policy, we underscore the critical role and interplay of weak and strong AI across public/private and fictional/non-fictional discourses. The resulting analytical framework aims to empower approaches that are more sensitive to the heterogeneity of AI narratives while also advocating normalising AI narratives, i.e., positioning weak AI narratives more firmly at the center stage of public debates about emerging technologies. (shrink)

In recent years, there has been a growing public discourse regarding the influence AI will have on the future of work. Simultaneously, considerable critical attention has been given to the implications of AI on gender equality. Far from making precise predictions about the future, this discourse demonstrates that new technologies are instances for renegotiating the relation of gender and work. This paper examines how gender is addressed in news media discourse on AI and the future of work, focusing on Germany. (...) We approach this question from a perspective of feminist technology studies and discourse analysis, exploring a corpus of 178 articles from 2015 to 2021 from German newspapers and newsmagazines. The findings indicate that critical AI and gender knowledge circulates in public discourse in the form of specific discursive frames, thematizing algorithmic bias, automatization and enhancement, and gender stereotypes. As a result, we show that, first, the discourse takes up feminist and scholarly discourse on gender and discusses AI in a way that is informed by social constructivism and standpoint theories. Second, gender appears as a—to some extent intersectional—diversity category which is critical to AI, while at the same time omitting important perspectives. Third, it can be shown that there is a renegotiating of the ideal worker norm taking place, and finally, we argue that the gendered frame of the powerful men developer responsible for AI’s risk is a concept to be challenged. (shrink)

Modern democratic states are increasingly adopting new information and communication technologies to enhance the efficiency and quality of public administration, public policy and services. However, there is substantial variation in the extent to which countries are successful in pursuing such public digitalization. This paper zooms in on the role of social trust as a possible account for the observed empirical pattern in the range and scope of public digitalization across countries. Our argument is that high social trust makes it easier (...) to digitalize the public sector to the benefit of overall society. We develop a simple game-theoretical model that specifies this positive externality from a high-trust culture and provide empirical evidence that a higher level of social trust is associated with a higher level of public digitalization. Of course, high-trust countries cannot do without the rule of law and some institutionalized mechanisms of control and accountability. However, from our argument, it follows that one future challenge could be that control crowds out trust, so that the balance is no longer optimal. If such overcontrol occurs, public digitalization win–win situations between citizens and government can be undermined, even in high-trust countries. (shrink)

Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers—big tech, popular media, and authors of science fiction—represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and the (...) untold stories of the capabilities, issues, and everyday realities of the technology. One participant proposed a “story crisis” in which these narratives compete to shape the public discourse on AI. Our findings indicate that dominant narratives distract and mislead public understandings and conceptions of AI. This suggests a need to pay closer attention to missing AI narratives. It is not simply about telling new stories, it is about listening to existing stories and asking what is wanted from AI. We call for realistic, nuanced, and inclusive stories, working with and for diverse voices, which consider (1) story-teller; (2) genre, and (3) communicative purpose. Such stories can then inspire the next generation of thinkers, technologists, and storytellers. (shrink)

The promises and risks of Artificial Intelligence permeate current policy statements and have attracted much attention by AI governance research. However, most analyses focus exclusively on AI policy on the national and international level, overlooking existing federal governance structures. This is surprising because AI is connected to many policy areas, where the competences are already distributed between the national and subnational level, such as research or economic policy. Addressing this gap, this paper argues that more attention should be dedicated to (...) subnational efforts to shape AI and asks which themes are discussed in subnational AI policy documents with a case study of Germany’s 16 states. Our qualitative analysis of 34 AI policy documents issued on the subnational level demonstrates that subnational efforts focus on knowledge transfer between research and industry actors, the commercialization of AI, different economic identities of the German states, and the incorporation of ethical principles. Because federal states play an active role in AI policy, analysing AI as a policy issue on different levels of government is necessary and will contribute to a better understanding of the developments and implementations of AI strategies in different national contexts. (shrink)

Since the publication of ChatGPT and Dall-E, there has been heavy discussions on the possible dangers of generative artificial intelligence (AI) for society. These discussions question the extent to which the development of AI can be regulated by politics, law, and civic actors. An important arena for discourse on AI is the news media. The news media discursively construct AI as a technology that is more or less possible to regulate. There are various reasons for an assumed regulatability. Some voices (...) highlight the predominant capitalism of modern society as an ideology that enforces an uncontrolled development of AI. Others call on the rationality of civic society, which will push AI toward a development that serves humankind. Summarized, the discourse on AI floats between positions of technological and social determinism. The article conducts a discourse analysis on 113 articles from the German newspapers Süddeutsche Zeitung and Frankfurter Allgemeine Zeitung. The analysis shows how these center-left and center-right media frame the AI development in terms of social and technological determinism. As these newspapers reach out to a large audience, the article shows the kinds of perspectives on AI that confront civic society in Germany every day. News media can motivate or impede social action, as they frame the potential necessity of society and its members to intervene against certain developments. The article shows how the newspapers promote an understanding of AI, by which citizens will feel motivated to insist on a regulation of AI by politics and law. (shrink)

Machine vision is one of the main applications of artificial intelligence. In China, the machine vision industry makes up more than a third of the national AI market, and technologies like face recognition, object tracking and automated driving play a central role in surveillance systems and social governance projects relying on the large-scale collection and processing of sensor data. Like other novel articulations of technology and society, machine vision is defined, developed and explained by different actors through the work of (...) imagination. In this article, we draw on the concept of sociotechnical imaginaries to understand how Chinese companies represent machine vision. Through a qualitative multimodal analysis of the corporate websites of leading industry players, we identify a cohesive sociotechnical imaginary of machine vision, and explain how four distinct visual registers contribute to its articulation. These four registers, which we call computational abstraction, human–machine coordination, smooth everyday, and dashboard realism, allow Chinese tech companies to articulate their global ambitions and competitiveness through narrow and opaque representations of machine vision technologies. (shrink)

Since the beginning of the current hype around Artificial Intelligence (AI), governments, research institutions, and the industry invited ethical, legal, and social sciences (ELS) scholars to research AI’s societal challenges from various disciplinary viewpoints and perspectives. This approach builds upon the tradition of supporting research on the societal aspects of emerging sciences and technologies, which started with the Ethical, Legal, and Social Implications (ELSI) Program in the Human Genome Project (HGP) in the early 1990s. However, although a diverse ELS research (...) community has formed since then, AI’s societal challenges came to be mostly understood under the narrow framing of ethics and disconnected from the insights and experiences of past ELS research. In this article, we make up for this gap and connect insights from past ELS researchers with current approaches to research the societal challenges of AI. We analyse and summarize the history of “ELS programs” (programs that emerged since the HGP to support ELS research in a given domain) as three distinct eras: a genomics era, a nano era, and an RRI era. Each of these eras comprises several achievements and challenges relevant to ELS programs in AI research, such as the setup of independent funding bodies, the engagement of the wider public in research practice, and the increasing importance of private actors. Based on these insights, we argue that AI research currently falls back on self-regulatory, less participatory, and industry-led approaches that trouble ELS programs’ past achievements and hinder opportunities to overcome the still-existing challenges. (shrink)

With technologies like machine learning and data analytics being deployed as privileged means to improve how contemporary bureaucracies work, many governments around the world have turned to artificial intelligence as a tool of statecraft. In that context, our paper uses Canada as a critical case to investigate the relationship between ideals of good government and good technology. We do so through not one, but two Trudeaus—celebrity Prime Minister Justin Trudeau (2015—…) and his equally famous father, former Prime Minister Pierre Elliott (...) Trudeau (1968–1979, 1980–1984). Both shared a similar interest in new ideas and practices of both intelligent government and artificial intelligence. Influenced by Marshall McLuhan and his media theory, Pierre Elliott Trudeau deployed new communication technologies to restore centralized control in an otherwise decentralized state. Partly successful, he left his son with an informationally inclined political legacy, which decades later animated Justin Trudeau's own turn toward Big Data and artificial intelligence. Compared with one another, these two visions for both government and artificial intelligence illustrate the broader tensions between cybernetic and neoliberal approaches to government, which inform how new technologies are conceived of, and adopted, as political ones. As this article argues, Canada offers a paradigmatic case for how artificial intelligence is as much shaped by theories of government as by investments and innovations in computing research, which together delimit the contours of intelligence by defining which technical systems, people, and organizations come to be recognized as its privileged bearers. (shrink)

China communicates strategic narratives about artificial intelligence in digital media productions to create a shared meaning about its actions and its image in the global race to develop AI. Building upon the literature in emotions and strategic narratives, this study seeks to clarify which emotions are discursively used in China’s international AI narratives, and their function and significance. Specifically, the study investigates emotion discourses in AI-focused videos disseminated on China’s international broadcasting. The analysis reveals that pride, hope and fear discourses (...) have multiple functions in China’s international AI narratives on CGTN. Hope is used to represent China as a key competitor in the global AI race, who is catching up to the US. China uses pride to showcase its advances in AI applications, to highlight its transformation of traditional industries, and to identity itself as equal to the US. Fear is used to frame US’s perception of China’s AI developments, to suggest their crisis of confidence, but also to refute the “China threat”. Additionally, the fear discourse is used to deliberate anticipated risks, particularly on job loss and data privacy. These emotion discourses forge China’s identity as a future global AI power. The paper then discusses how these findings contribute to key debates about Chinese discourse and media strategy. (shrink)