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Search Results
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AI-Enhanced Journalism: How to Strengthen Its Role as an Epistemic and Evaluative Intermediary in Democracy
Journalism has two main functions in democracy: news coverage and the formation of public opinion. This essay develops a theoretical framework for the role of journalism as an epistemic and evaluative intermediary. This framework can be used to discuss the two-part question: how can AI improve the epistemic process of news production, and how can it strengthen the evaluative process of public opinion formation? Veristic social epistemology emphasizes the role of organized skepticism in the process of truth-seeking. One crucial weakness of AI is that it does not meet the necessary condition for collective scrutiny, namely, transparency regarding the process through which it generates truth claims. Consequently, AI can only support the human search for truth. Only a few studies have measured the epistemic quality of AI-generated content and its effects directly and systematically. With regard to public opinion formation, there is a theoretical gap that can be addressed using normative theories of democracy. Values can be derived from these theories, which can serve as yardsticks for democratic opinion formation. Empirical studies also paint a mixed picture. The risks include radicalization and confirmation bias. However, generative AI can also improve the quality of deliberation and enhance the communication skills of disadvantaged groups. The rapid development of AI models requires continuous monitoring and an experimental approach to understand the potential uses and limitations of AI in journalism and the democratic public sphere.
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Algorithmic Governmentality, Digital Sovereignty, and Agency Affordances: Extending the Possible Fields of Action
In today’s socio-technical constellations, our daily online and offline lives are increasingly governed by what can be termed algorithmic governmentality. Understood as the governing of the social based on the algorithmic processing of big data, algorithmic governmentality significantly limits human agency and individuals’ abilities to control data inputs and algorithmic outputs. An antidote and a solution to governance of this kind require assembling conditions for enabling digital sovereignty. Seen as a counter-conduct to governmentality, sovereignty concerns agency, control, autonomy, authority, self-reflection, and self-determination. Foregrounded on empirical research that relates specifically to platform algorithms, this article discusses the requirements for the digital sovereignty of individuals and the socio-technical conditions that should enable that sovereignty. By introducing and conceptualizing the notion of agency affordances, the article provides several illustrative examples of how this sovereignty can be inscribed through the technical and unfold via the societal.
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Editorial: Practicing Sovereignty – Interventions for Open Digital Futures
This issue is dedicated to the Weizenbaum Conference 2022, titled ‘Practicing Sovereignty: Interventions for Open Digital Futures.’ The Weizenbaum Institute’s annual gathering brought together researchers, networks, and collaborators to focus on the theme of ‘digital sovereignty.’ This term, hotly debated and used with varying connotations in fields such as research, activism, law, and policy-making, refers to competencies, duties, and rights in digital societies. The contributions compiled in this issue are based on papers presented at the 2022 conference. They explore notions of digital sovereignty in tension with topics such as AI deepfakes, algorithmic governmentality, ethics and datafication in the context of machine learning, and community-driven open-access publishing in academia.
