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- Item(De)constructing ethics for autonomous cars: A case study of Ethics Pen-Testing towards “AI for the Common Good”(2020) Berendt, BettinaRecently, many AI researchers and practitioners have embarked on research visions that involve doing AI for “Good”. This is part of a general drive towards infusing AI research and practice with ethical thinking. One frequent theme in current ethical guidelines is the requirement that AI be good for all, or: contribute to the Common Good. But what is the Common Good, and is it enough to want to be good? Via four lead questions, the concept of Ethics Pen-Testing (EPT) identifies challenges and pitfalls when determining, from an AI point of view, what the Common Good is and how it can be enhanced by AI. The current paper reports on a first evaluation of EPT. EPT is applicable to various artefacts that have ethical impact, including designs for or implementations of specific AI technology, and requirements engineering methods for eliciting which ethical settings to build into AI. The current study focused on the latter type of artefact. In four independent sessions, participants with close but varying involvements in “AI and ethics” were asked to deconstruct a method that has been proposed for eliciting ethical values and choices in autonomous car technology, an online experiment modelled on the Trolley Problem. The results suggest that EPT is well-suited to this task: the remarks made by participants lent themselves well to being structured by the four lead questions of EPT, in particular, regarding the question what the problem is and about which stakeholders define it. As part of the problem definition, the need became apparent for thorough technical domain knowledge in discussions of AI and ethics. Thus, participants questioned the framing and the presuppositions inherent in the experiment and the discourse on autonomous cars that underlies the experiment. They transitioned from discussing a specific AI artefact to discussing its role in wider socio-technical systems. Results also illustrate to what extent and how the requirements engineering method forces us to not only have a discussion about which values to “build into” AI systems, the substantive building blocks of the Common Good, but also about how we want to have this discussion at all. Thus, it forces us to become explicit about how we conceive of democracy and the constitutional state and the procedural building blocks of the Common Good.
- ItemVeiled conspiracism: Particularities and convergence in the styles and functions of conspiracy-related communication across digital platforms(2025) Buehling, Kilian; Zhang, Xixuan; Heft, AnnettDigital communication venues are essential infrastructures for anti-democratic actors to spread harmful content such as conspiracy theories. Capitalizing on platform affordances, they leverage conspiracy theories to mainstream their political views in broader public discourse. We compared the word choice, language style, and communicative function of conspiracy-related content to understand its platform-dependent differences and convergence. Our cases are the conspiracy theories of the New World Order and Great Replacement, which we analyzed on 4chan/pol/, Twitter, and seven alternative US news media longitudinally from 2011 to 2021. The conspiracy-related texts were comparatively analyzed using a multi-method approach of computational and quantitative text analyses. Our results show that conspiracy narrations are increasingly present in all venues. While language differs vastly between platforms, we observed a style convergence between Twitter and 4chan. The results show how more coded language veils the spread of racist and antisemitic content beyond the so-called dark platforms.
- ItemStochastic lies: How LLM-powered chatbots deal with Russian disinformation about the war in Ukraine(2024) Makhortykh, Mykola; Sydorova, Maryna; Baghumyan, A; Vziatysheva, Victoria; Kuznetsova, ElizavetaResearch on digital misinformation has turned its attention to large language models (LLMs) and their handling of sensitive political topics. Through an AI audit, we analyze how three LLM-powered chatbots (Perplexity, Google Bard, and Bing Chat) generate content in response to the prompts linked to common Russian disinformation narratives about the war in Ukraine. We find major differences between chatbots in the accuracy of outputs and the integration of statements debunking Russian disinformation claims related to prompts’ topics. Moreover, we show that chatbot outputs are subject to substantive variation, which can result in random user exposure to false information.
- ItemThe standard form under pressure? On the ecological reconfiguration of product presentation using the example of consumables(2024) Gajewski, Eltje; Schrör, SimonThis article provides a framework for analyzing valorizations and justifications for ecologically sustainable everyday products. By drawing on theoretical arguments from the French neo pragmatist approach of economics of conventions, especially the idea of enrichment, we develop a typology of valorizations that distinguishes between analytic and narrative presentations. A qualitative empirical analysis of green alternatives to standard consumables, such as coffee, textiles or hygiene products, is used to help explain the strategies by which sustainable products are placed and marketed. We state that sustainable product presentations use a range of established forms of valorization that also affects the justification of their often-higher prices. We conclude that the standard form of consumables comes under pressure while capitalist actors appear to incorporate the growing ecologic critique with a set of ecologic enrichments.
- ItemControl and Flexibility: The Use of Wearable Devices in Capital- and Labor-Intensive Work Processes(2024) Krzywdzinski, Martin; Evers, Maren; Gerber, ChristineThe use of wearables in the workplace allows for close monitoring of work processes and might also have consequences for work content and skill requirements. Past research has emphasized the detrimental effects of wearables, particularly those caused by the standardization of work and monitoring of workers. By contrast, this study asks under what conditions the implementation of wearables as part of digital assistance systems is beneficial for workers. Based on recent contributions in the field of labor process theory, this study analyzes the implementation of new technologies using the concepts of the regulatory regime, organizational first-order factors, and workplace second-order choices. The analysis is based on findings from 48 interviews with 83 interviewees in 16 German manufacturing workplaces along with making site visits. It examines the implementation of wearables and the impacts on work content, skills, working conditions, and employment. Besides showing how labor agency affects the implementation of new technologies, the particular contribution of this study lies in analyzing the differences in the implementation of wearables in capital- and labor-intensive organizations. While standardization of work and reduction of work content prevailed in labor-intensive processes, capital-intensive processes were most often characterized by the extension of skill requirements and the risk of work intensification.