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This doctoral thesis examines the rise of Big Data as a complex sociotechnical phenomenon. How is it that the notion of Big Data could gain so much traction, becoming the subject of considerable hype and hope? Adopting a broadly interdisciplinary perspective, the article dissertation investigates the historical roots as well as contemporary causes of the recent push for data and numerical evidence. Furthermore, it critically analyses the epistemic decision making, and explores fictional accounts of algorithmic regulation that may trigger a more reflexive engagement with the potential pitfalls of Big Data-based technologies. The thesis objective is to contribute to a better understanding of the politics of people's trust in numbers, but also to point towards a more responsible and democracy-preserving governance of Big Data-driven innovation. What is ultimately argued is that Big Data should not be seen as a fad destined to fade, but as the current tagline for a process of computerization and datafication that will continue to shape and transform every aspect of our daily lives.

Ever since the outbreak of the COVID-19 pandemic, questions of whom or what to trust have become paramount. This article examines the public debates surrounding the initial development of the German Corona-Warn-App in 2020 as a case study to analyse such questions at the intersection of trust and trustworthiness in technology development, design and oversight. Providing some insights into the nature and dynamics of trust and trustworthiness, we argue that (a) trust is only desirable and justified if placed well, that is, if directed at those being trustworthy; that (b) trust and trustworthiness come in degrees and have both epistemic and moral components; and that (c) such a normatively demanding understanding of trust excludes technologies as proper objects of trust and requires that trust is directed at socio-technical assemblages consisting of both humans and artefacts. We conclude with some lessons learned from our case study, highlighting the epistemic and moral demands for trustworthy technology development as well as for public debates about such technologies, which ultimately requires attributing epistemic and moral duties to all actors involved.

With its promise to transform how we live, work, and think, Big Data has captured the imaginations of governments, businesses, and academia. However, the grand claims of Big Data advocates have been accompanied with concerns about potential detrimental implications for civil rights and liberties, leading to a climate of clash and mutual distrust between different stakeholders. Throughout the years, the interdisciplinary field of technology assessment (TA) has gained considerable experience in studying socio-technical controversies and as such is exceptionally well equipped to assess the premises and implications of Big Data practices. However, the relationship between Big Data as a socio- technical phenomenon and TA as a discipline assessing such phenomena is a peculiar one: Big Data may be the first topic TA deals with that is not only an object of inquiry, but also a major competitor, rivaling TA in several of its core functions, including the assessment of public views and visions, means and methods for exploring the future, and the provision of actionable knowledge and advice for political decision-making. Our paper explores this dual relationship between Big Data and TA before concluding with some considerations on how TA might contribute to more responsible data-based research and innovation.

Recently, there has been renewed interest in so-called evidence-based policy making. Enticed by the grand promises of Big Data, public officials seem increasingly inclined to experiment with more data-driven forms of governance. But while the rise of Big Data and related consequences has been a major issue of concern across different disciplines, attempts to develop a better understanding of the phenomenon's historical foundations have been rare. This short commentary addresses this gap by situating the current push for numerical evidence within a broader socio-political context, demonstrating how the epistemological claims of Big Data science intersect with specific forms of trust, truth, and objectivity. We conclude by arguing that regulators' faith in numbers can be attributed to a distinct political culture, a representative democracy undermined by pervasive public distrust and uncertainty.

Seit einiger Zeit gibt es wieder verstärktes Interesse an sogenannter evidenzbasierter Politikgestaltung. Angelockt durch die großen Versprechen von Big Data scheinen politische Entscheidungsträger zunehmend mit stärker auf digitalen Daten basierenden Regierungsformen experimentieren zu wollen. Doch obwohl das Aufkommen von Big Data und die damit verbundenen Gefahren von wissenschaftlicher Seite durchaus kritisch hinterfragt werden, gab es bislang nur wenige Versuche, ein besseres Verständnis für die historischen Kontexte und Grundlagen dieser Vorgänge zu entwickeln. Der hier vorliegende Kommentar befasst sich mit dieser Lücke, indem er das derzeitige Streben nach numerischen Beweisen in einen breiteren gesellschaftspolitischen Kontext einordnet und dadurch zeigt, wie die Erkenntnisversprechen von Big Data sich mit bestimmten Formen von Vertrauen, Wahrheit und Objektivität kreuzen. Wir argumentieren, dass das übersteigerte Vertrauen in zahlenbasierte Evidenz einer speziellen politischen Kultur zugeordnet werden kann, nämlich einer repräsentativen Demokratie, die von öffentlichem Misstrauen und großer Zukunftsunsicherheit gekennzeichnet ist.